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PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_qq_unf | def plot_qq_unf(fignum, D, title, subplot=False, degrees=True):
"""
plots data against a uniform distribution in 0=>360.
Parameters
_________
fignum : matplotlib figure number
D : data
title : title for plot
subplot : if True, make this number one of two subplots
degrees : if True, assume that these are degrees
Return
Mu : Mu statistic (Fisher et al., 1987)
Mu_crit : critical value of Mu for uniform distribution
Effect
______
makes a Quantile Quantile plot of data
"""
if subplot == True:
plt.subplot(1, 2, fignum)
else:
plt.figure(num=fignum)
X, Y, dpos, dneg = [], [], 0., 0.
if degrees:
D = (np.array(D)) % 360
X = D/D.max()
X = np.sort(X)
n = float(len(D))
i = np.arange(0, len(D))
Y = (i-0.5)/n
ds = (i/n)-X
dpos = ds.max()
dneg = ds.min()
plt.plot(Y, X, 'ro')
v = dneg + dpos # kuiper's v
# Mu of fisher et al. equation 5.16
Mu = v * (np.sqrt(n) - 0.567 + (old_div(1.623, (np.sqrt(n)))))
plt.axis([0, 1., 0., 1.])
bounds = plt.axis()
notestr = 'N: ' + '%i' % (n)
plt.text(.1 * bounds[1], .9 * bounds[3], notestr)
notestr = 'Mu: ' + '%7.3f' % (Mu)
plt.text(.1 * bounds[1], .8 * bounds[3], notestr)
if Mu > 1.347:
notestr = "Non-uniform (99%)"
elif Mu < 1.207:
notestr = "Uniform (95%)"
elif Mu > 1.207:
notestr = "Uniform (99%)"
plt.text(.1 * bounds[1], .7 * bounds[3], notestr)
plt.text(.1 * bounds[1], .7 * bounds[3], notestr)
plt.title(title)
plt.xlabel('Uniform Quantile')
plt.ylabel('Data Quantile')
return Mu, 1.207 | python | def plot_qq_unf(fignum, D, title, subplot=False, degrees=True):
"""
plots data against a uniform distribution in 0=>360.
Parameters
_________
fignum : matplotlib figure number
D : data
title : title for plot
subplot : if True, make this number one of two subplots
degrees : if True, assume that these are degrees
Return
Mu : Mu statistic (Fisher et al., 1987)
Mu_crit : critical value of Mu for uniform distribution
Effect
______
makes a Quantile Quantile plot of data
"""
if subplot == True:
plt.subplot(1, 2, fignum)
else:
plt.figure(num=fignum)
X, Y, dpos, dneg = [], [], 0., 0.
if degrees:
D = (np.array(D)) % 360
X = D/D.max()
X = np.sort(X)
n = float(len(D))
i = np.arange(0, len(D))
Y = (i-0.5)/n
ds = (i/n)-X
dpos = ds.max()
dneg = ds.min()
plt.plot(Y, X, 'ro')
v = dneg + dpos # kuiper's v
# Mu of fisher et al. equation 5.16
Mu = v * (np.sqrt(n) - 0.567 + (old_div(1.623, (np.sqrt(n)))))
plt.axis([0, 1., 0., 1.])
bounds = plt.axis()
notestr = 'N: ' + '%i' % (n)
plt.text(.1 * bounds[1], .9 * bounds[3], notestr)
notestr = 'Mu: ' + '%7.3f' % (Mu)
plt.text(.1 * bounds[1], .8 * bounds[3], notestr)
if Mu > 1.347:
notestr = "Non-uniform (99%)"
elif Mu < 1.207:
notestr = "Uniform (95%)"
elif Mu > 1.207:
notestr = "Uniform (99%)"
plt.text(.1 * bounds[1], .7 * bounds[3], notestr)
plt.text(.1 * bounds[1], .7 * bounds[3], notestr)
plt.title(title)
plt.xlabel('Uniform Quantile')
plt.ylabel('Data Quantile')
return Mu, 1.207 | plots data against a uniform distribution in 0=>360.
Parameters
_________
fignum : matplotlib figure number
D : data
title : title for plot
subplot : if True, make this number one of two subplots
degrees : if True, assume that these are degrees
Return
Mu : Mu statistic (Fisher et al., 1987)
Mu_crit : critical value of Mu for uniform distribution
Effect
______
makes a Quantile Quantile plot of data | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L362-L417 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_qq_exp | def plot_qq_exp(fignum, I, title, subplot=False):
"""
plots data against an exponential distribution in 0=>90.
Parameters
_________
fignum : matplotlib figure number
I : data
title : plot title
subplot : boolean, if True plot as subplot with 1 row, two columns with fignum the plot number
"""
if subplot == True:
plt.subplot(1, 2, fignum)
else:
plt.figure(num=fignum)
X, Y, dpos, dneg = [], [], 0., 0.
rad = old_div(np.pi, 180.)
xsum = 0
for i in I:
theta = (90. - i) * rad
X.append(1. - np.cos(theta))
xsum += X[-1]
X.sort()
n = float(len(X))
kappa = old_div((n - 1.), xsum)
for i in range(len(X)):
p = old_div((float(i) - 0.5), n)
Y.append(-np.log(1. - p))
f = 1. - np.exp(-kappa * X[i])
ds = old_div(float(i), n) - f
if dpos < ds:
dpos = ds
ds = f - old_div((float(i) - 1.), n)
if dneg < ds:
dneg = ds
if dneg > dpos:
ds = dneg
else:
ds = dpos
Me = (ds - (old_div(0.2, n))) * (np.sqrt(n) + 0.26 +
(old_div(0.5, (np.sqrt(n))))) # Eq. 5.15 from Fisher et al. (1987)
plt.plot(Y, X, 'ro')
bounds = plt.axis()
plt.axis([0, bounds[1], 0., bounds[3]])
notestr = 'N: ' + '%i' % (n)
plt.text(.1 * bounds[1], .9 * bounds[3], notestr)
notestr = 'Me: ' + '%7.3f' % (Me)
plt.text(.1 * bounds[1], .8 * bounds[3], notestr)
if Me > 1.094:
notestr = "Not Exponential"
else:
notestr = "Exponential (95%)"
plt.text(.1 * bounds[1], .7 * bounds[3], notestr)
plt.title(title)
plt.xlabel('Exponential Quantile')
plt.ylabel('Data Quantile')
return Me, 1.094 | python | def plot_qq_exp(fignum, I, title, subplot=False):
"""
plots data against an exponential distribution in 0=>90.
Parameters
_________
fignum : matplotlib figure number
I : data
title : plot title
subplot : boolean, if True plot as subplot with 1 row, two columns with fignum the plot number
"""
if subplot == True:
plt.subplot(1, 2, fignum)
else:
plt.figure(num=fignum)
X, Y, dpos, dneg = [], [], 0., 0.
rad = old_div(np.pi, 180.)
xsum = 0
for i in I:
theta = (90. - i) * rad
X.append(1. - np.cos(theta))
xsum += X[-1]
X.sort()
n = float(len(X))
kappa = old_div((n - 1.), xsum)
for i in range(len(X)):
p = old_div((float(i) - 0.5), n)
Y.append(-np.log(1. - p))
f = 1. - np.exp(-kappa * X[i])
ds = old_div(float(i), n) - f
if dpos < ds:
dpos = ds
ds = f - old_div((float(i) - 1.), n)
if dneg < ds:
dneg = ds
if dneg > dpos:
ds = dneg
else:
ds = dpos
Me = (ds - (old_div(0.2, n))) * (np.sqrt(n) + 0.26 +
(old_div(0.5, (np.sqrt(n))))) # Eq. 5.15 from Fisher et al. (1987)
plt.plot(Y, X, 'ro')
bounds = plt.axis()
plt.axis([0, bounds[1], 0., bounds[3]])
notestr = 'N: ' + '%i' % (n)
plt.text(.1 * bounds[1], .9 * bounds[3], notestr)
notestr = 'Me: ' + '%7.3f' % (Me)
plt.text(.1 * bounds[1], .8 * bounds[3], notestr)
if Me > 1.094:
notestr = "Not Exponential"
else:
notestr = "Exponential (95%)"
plt.text(.1 * bounds[1], .7 * bounds[3], notestr)
plt.title(title)
plt.xlabel('Exponential Quantile')
plt.ylabel('Data Quantile')
return Me, 1.094 | plots data against an exponential distribution in 0=>90.
Parameters
_________
fignum : matplotlib figure number
I : data
title : plot title
subplot : boolean, if True plot as subplot with 1 row, two columns with fignum the plot number | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L420-L477 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_di | def plot_di(fignum, DIblock):
global globals
"""
plots directions on equal area net
Parameters
_________
fignum : matplotlib figure number
DIblock : nested list of dec, inc pairs
"""
X_down, X_up, Y_down, Y_up = [], [], [], [] # initialize some variables
plt.figure(num=fignum)
#
# plot the data - separate upper and lower hemispheres
#
for rec in DIblock:
Up, Down = 0, 0
XY = pmag.dimap(rec[0], rec[1])
if rec[1] >= 0:
X_down.append(XY[0])
Y_down.append(XY[1])
else:
X_up.append(XY[0])
Y_up.append(XY[1])
#
if len(X_down) > 0:
# plt.scatter(X_down,Y_down,marker='s',c='r')
plt.scatter(X_down, Y_down, marker='o', c='blue')
if globals != 0:
globals.DIlist = X_down
globals.DIlisty = Y_down
if len(X_up) > 0:
# plt.scatter(X_up,Y_up,marker='s',facecolor='none',edgecolor='black')
plt.scatter(X_up, Y_up, marker='o',
facecolor='white', edgecolor='blue')
if globals != 0:
globals.DIlist = X_up
globals.DIlisty = Y_up | python | def plot_di(fignum, DIblock):
global globals
"""
plots directions on equal area net
Parameters
_________
fignum : matplotlib figure number
DIblock : nested list of dec, inc pairs
"""
X_down, X_up, Y_down, Y_up = [], [], [], [] # initialize some variables
plt.figure(num=fignum)
#
# plot the data - separate upper and lower hemispheres
#
for rec in DIblock:
Up, Down = 0, 0
XY = pmag.dimap(rec[0], rec[1])
if rec[1] >= 0:
X_down.append(XY[0])
Y_down.append(XY[1])
else:
X_up.append(XY[0])
Y_up.append(XY[1])
#
if len(X_down) > 0:
# plt.scatter(X_down,Y_down,marker='s',c='r')
plt.scatter(X_down, Y_down, marker='o', c='blue')
if globals != 0:
globals.DIlist = X_down
globals.DIlisty = Y_down
if len(X_up) > 0:
# plt.scatter(X_up,Y_up,marker='s',facecolor='none',edgecolor='black')
plt.scatter(X_up, Y_up, marker='o',
facecolor='white', edgecolor='blue')
if globals != 0:
globals.DIlist = X_up
globals.DIlisty = Y_up | plots directions on equal area net
Parameters
_________
fignum : matplotlib figure number
DIblock : nested list of dec, inc pairs | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L541-L577 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_di_sym | def plot_di_sym(fignum, DIblock, sym):
global globals
"""
plots directions on equal area net
Parameters
_________
fignum : matplotlib figure number
DIblock : nested list of dec, inc pairs
sym : set matplotlib symbol (e.g., 'bo' for blue circles)
"""
X_down, X_up, Y_down, Y_up = [], [], [], [] # initialize some variables
plt.figure(num=fignum)
#
# plot the data - separate upper and lower hemispheres
#
for rec in DIblock:
Up, Down = 0, 0
XY = pmag.dimap(rec[0], rec[1])
if rec[1] >= 0:
X_down.append(XY[0])
Y_down.append(XY[1])
else:
X_up.append(XY[0])
Y_up.append(XY[1])
#
if 'size' not in list(sym.keys()):
size = 50
else:
size = sym['size']
if 'edgecolor' not in list(sym.keys()):
sym['edgecolor'] = 'k'
if len(X_down) > 0:
plt.scatter(X_down, Y_down, marker=sym['lower'][0],
c=sym['lower'][1], s=size, edgecolor=sym['edgecolor'])
if globals != 0:
globals.DIlist = X_down
globals.DIlisty = Y_down
if len(X_up) > 0:
plt.scatter(X_up, Y_up, marker=sym['upper'][0],
c=sym['upper'][1], s=size, edgecolor=sym['edgecolor'])
if globals != 0:
globals.DIlist = X_up
globals.DIlisty = Y_up | python | def plot_di_sym(fignum, DIblock, sym):
global globals
"""
plots directions on equal area net
Parameters
_________
fignum : matplotlib figure number
DIblock : nested list of dec, inc pairs
sym : set matplotlib symbol (e.g., 'bo' for blue circles)
"""
X_down, X_up, Y_down, Y_up = [], [], [], [] # initialize some variables
plt.figure(num=fignum)
#
# plot the data - separate upper and lower hemispheres
#
for rec in DIblock:
Up, Down = 0, 0
XY = pmag.dimap(rec[0], rec[1])
if rec[1] >= 0:
X_down.append(XY[0])
Y_down.append(XY[1])
else:
X_up.append(XY[0])
Y_up.append(XY[1])
#
if 'size' not in list(sym.keys()):
size = 50
else:
size = sym['size']
if 'edgecolor' not in list(sym.keys()):
sym['edgecolor'] = 'k'
if len(X_down) > 0:
plt.scatter(X_down, Y_down, marker=sym['lower'][0],
c=sym['lower'][1], s=size, edgecolor=sym['edgecolor'])
if globals != 0:
globals.DIlist = X_down
globals.DIlisty = Y_down
if len(X_up) > 0:
plt.scatter(X_up, Y_up, marker=sym['upper'][0],
c=sym['upper'][1], s=size, edgecolor=sym['edgecolor'])
if globals != 0:
globals.DIlist = X_up
globals.DIlisty = Y_up | plots directions on equal area net
Parameters
_________
fignum : matplotlib figure number
DIblock : nested list of dec, inc pairs
sym : set matplotlib symbol (e.g., 'bo' for blue circles) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L580-L622 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_circ | def plot_circ(fignum, pole, ang, col):
"""
function to put a small circle on an equal area projection plot, fig,fignum
Parameters
__________
fignum : matplotlib figure number
pole : dec,inc of center of circle
ang : angle of circle
col :
"""
plt.figure(num=fignum)
D_c, I_c = pmag.circ(pole[0], pole[1], ang)
X_c_up, Y_c_up = [], []
X_c_d, Y_c_d = [], []
for k in range(len(D_c)):
XY = pmag.dimap(D_c[k], I_c[k])
if I_c[k] < 0:
X_c_up.append(XY[0])
Y_c_up.append(XY[1])
else:
X_c_d.append(XY[0])
Y_c_d.append(XY[1])
plt.plot(X_c_d, Y_c_d, col + '.', ms=5)
plt.plot(X_c_up, Y_c_up, 'c.', ms=2) | python | def plot_circ(fignum, pole, ang, col):
"""
function to put a small circle on an equal area projection plot, fig,fignum
Parameters
__________
fignum : matplotlib figure number
pole : dec,inc of center of circle
ang : angle of circle
col :
"""
plt.figure(num=fignum)
D_c, I_c = pmag.circ(pole[0], pole[1], ang)
X_c_up, Y_c_up = [], []
X_c_d, Y_c_d = [], []
for k in range(len(D_c)):
XY = pmag.dimap(D_c[k], I_c[k])
if I_c[k] < 0:
X_c_up.append(XY[0])
Y_c_up.append(XY[1])
else:
X_c_d.append(XY[0])
Y_c_d.append(XY[1])
plt.plot(X_c_d, Y_c_d, col + '.', ms=5)
plt.plot(X_c_up, Y_c_up, 'c.', ms=2) | function to put a small circle on an equal area projection plot, fig,fignum
Parameters
__________
fignum : matplotlib figure number
pole : dec,inc of center of circle
ang : angle of circle
col : | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L625-L648 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_zij | def plot_zij(fignum, datablock, angle, s, norm=True):
"""
function to make Zijderveld diagrams
Parameters
__________
fignum : matplotlib figure number
datablock : nested list of [step, dec, inc, M (Am2), type, quality]
where type is a string, either 'ZI' or 'IZ' for IZZI experiments
angle : desired rotation in the horizontal plane (0 puts X on X axis)
s : specimen name
norm : if True, normalize to initial magnetization = unity
Effects
_______
makes a zijderveld plot
"""
global globals
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
amin, amax = 0., -100.
if norm == 0:
fact = 1.
else:
fact = (1./datablock[0][3]) # normalize to NRM=1
# convert datablock to DataFrame data with dec,inc, int
data = pd.DataFrame(datablock)
if len(data.columns) == 5:
data.columns = ['treat', 'dec', 'inc', 'int', 'quality']
if len(data.columns) == 6:
data.columns = ['treat', 'dec', 'inc', 'int', 'type', 'quality']
elif len(data.columns) == 7:
data.columns = ['treat', 'dec', 'inc', 'int', 'type', 'quality', 'y']
#print (len(data.columns))
data['int'] = data['int']*fact # normalize
data['dec'] = (data['dec']-angle) % 360 # adjust X axis angle
gdata = data[data['quality'].str.contains('g')]
bdata = data[data['quality'].str.contains('b')]
forVDS = gdata[['dec', 'inc', 'int']].values
gXYZ = pd.DataFrame(pmag.dir2cart(forVDS))
gXYZ.columns = ['X', 'Y', 'Z']
amax = np.maximum(gXYZ.X.max(), gXYZ.Z.max())
amin = np.minimum(gXYZ.X.min(), gXYZ.Z.min())
if amin > 0:
amin = 0
bXYZ = pmag.dir2cart(bdata[['dec', 'inc', 'int']].values).transpose()
# plotting stuff
if angle != 0:
tempstr = "\n Declination rotated by: " + str(angle) + '\n'
if globals != 0:
globals.text.insert(globals.END, tempstr)
globals.Zlist = gXYZ['x'].tolist()
globals.Zlisty = gXYZ['y'].tolist()
globals.Zlistz = gXYZ['z'].tolist()
if len(bXYZ) > 0:
plt.scatter(bXYZ[0], bXYZ[1], marker='d', c='y', s=30)
plt.scatter(bXYZ[0], bXYZ[2], marker='d', c='y', s=30)
plt.plot(gXYZ['X'], gXYZ['Y'], 'ro')
plt.plot(gXYZ['X'], gXYZ['Z'], 'ws', markeredgecolor='blue')
plt.plot(gXYZ['X'], gXYZ['Y'], 'r-')
plt.plot(gXYZ['X'], gXYZ['Z'], 'b-')
for k in range(len(gXYZ)):
plt.annotate(str(k), (gXYZ['X'][k], gXYZ['Z']
[k]), ha='left', va='bottom')
if amin > 0 and amax >0:amin=0 # complete the line
if amin < 0 and amax <0:amax=0 # complete the line
xline = [amin, amax]
# yline=[-amax,-amin]
yline = [amax, amin]
zline = [0, 0]
plt.plot(xline, zline, 'k-')
plt.plot(zline, xline, 'k-')
if angle != 0:
xlab = "X: rotated to Dec = " + '%7.1f' % (angle)
if angle == 0:
xlab = "X: rotated to Dec = " + '%7.1f' % (angle)
plt.xlabel(xlab)
plt.ylabel("Circles: Y; Squares: Z")
tstring = s + ': NRM = ' + '%9.2e' % (datablock[0][3])
plt.axis([amin, amax, amax, amin])
plt.axis("equal")
plt.title(tstring) | python | def plot_zij(fignum, datablock, angle, s, norm=True):
"""
function to make Zijderveld diagrams
Parameters
__________
fignum : matplotlib figure number
datablock : nested list of [step, dec, inc, M (Am2), type, quality]
where type is a string, either 'ZI' or 'IZ' for IZZI experiments
angle : desired rotation in the horizontal plane (0 puts X on X axis)
s : specimen name
norm : if True, normalize to initial magnetization = unity
Effects
_______
makes a zijderveld plot
"""
global globals
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
amin, amax = 0., -100.
if norm == 0:
fact = 1.
else:
fact = (1./datablock[0][3]) # normalize to NRM=1
# convert datablock to DataFrame data with dec,inc, int
data = pd.DataFrame(datablock)
if len(data.columns) == 5:
data.columns = ['treat', 'dec', 'inc', 'int', 'quality']
if len(data.columns) == 6:
data.columns = ['treat', 'dec', 'inc', 'int', 'type', 'quality']
elif len(data.columns) == 7:
data.columns = ['treat', 'dec', 'inc', 'int', 'type', 'quality', 'y']
#print (len(data.columns))
data['int'] = data['int']*fact # normalize
data['dec'] = (data['dec']-angle) % 360 # adjust X axis angle
gdata = data[data['quality'].str.contains('g')]
bdata = data[data['quality'].str.contains('b')]
forVDS = gdata[['dec', 'inc', 'int']].values
gXYZ = pd.DataFrame(pmag.dir2cart(forVDS))
gXYZ.columns = ['X', 'Y', 'Z']
amax = np.maximum(gXYZ.X.max(), gXYZ.Z.max())
amin = np.minimum(gXYZ.X.min(), gXYZ.Z.min())
if amin > 0:
amin = 0
bXYZ = pmag.dir2cart(bdata[['dec', 'inc', 'int']].values).transpose()
# plotting stuff
if angle != 0:
tempstr = "\n Declination rotated by: " + str(angle) + '\n'
if globals != 0:
globals.text.insert(globals.END, tempstr)
globals.Zlist = gXYZ['x'].tolist()
globals.Zlisty = gXYZ['y'].tolist()
globals.Zlistz = gXYZ['z'].tolist()
if len(bXYZ) > 0:
plt.scatter(bXYZ[0], bXYZ[1], marker='d', c='y', s=30)
plt.scatter(bXYZ[0], bXYZ[2], marker='d', c='y', s=30)
plt.plot(gXYZ['X'], gXYZ['Y'], 'ro')
plt.plot(gXYZ['X'], gXYZ['Z'], 'ws', markeredgecolor='blue')
plt.plot(gXYZ['X'], gXYZ['Y'], 'r-')
plt.plot(gXYZ['X'], gXYZ['Z'], 'b-')
for k in range(len(gXYZ)):
plt.annotate(str(k), (gXYZ['X'][k], gXYZ['Z']
[k]), ha='left', va='bottom')
if amin > 0 and amax >0:amin=0 # complete the line
if amin < 0 and amax <0:amax=0 # complete the line
xline = [amin, amax]
# yline=[-amax,-amin]
yline = [amax, amin]
zline = [0, 0]
plt.plot(xline, zline, 'k-')
plt.plot(zline, xline, 'k-')
if angle != 0:
xlab = "X: rotated to Dec = " + '%7.1f' % (angle)
if angle == 0:
xlab = "X: rotated to Dec = " + '%7.1f' % (angle)
plt.xlabel(xlab)
plt.ylabel("Circles: Y; Squares: Z")
tstring = s + ': NRM = ' + '%9.2e' % (datablock[0][3])
plt.axis([amin, amax, amax, amin])
plt.axis("equal")
plt.title(tstring) | function to make Zijderveld diagrams
Parameters
__________
fignum : matplotlib figure number
datablock : nested list of [step, dec, inc, M (Am2), type, quality]
where type is a string, either 'ZI' or 'IZ' for IZZI experiments
angle : desired rotation in the horizontal plane (0 puts X on X axis)
s : specimen name
norm : if True, normalize to initial magnetization = unity
Effects
_______
makes a zijderveld plot | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L654-L738 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_mag | def plot_mag(fignum, datablock, s, num, units, norm):
"""
plots magnetization against (de)magnetizing temperature or field
Parameters
_________________
fignum : matplotlib figure number for plotting
datablock : nested list of [step, 0, 0, magnetization, 1,quality]
s : string for title
num : matplotlib figure number, can set to 1
units : [T,K,U] for tesla, kelvin or arbitrary
norm : [True,False] if True, normalize
Effects
______
plots figure
"""
global globals, graphmenu
Ints = []
for plotrec in datablock:
Ints.append(plotrec[3])
Ints.sort()
plt.figure(num=fignum)
T, M, Tv, recnum = [], [], [], 0
Mex, Tex, Vdif = [], [], []
recbak = []
for rec in datablock:
if rec[5] == 'g':
if units == "T":
T.append(rec[0] * 1e3)
Tv.append(rec[0] * 1e3)
if recnum > 0:
Tv.append(rec[0] * 1e3)
elif units == "U":
T.append(rec[0])
Tv.append(rec[0])
if recnum > 0:
Tv.append(rec[0])
elif units == "K":
T.append(rec[0] - 273)
Tv.append(rec[0] - 273)
if recnum > 0:
Tv.append(rec[0] - 273)
elif "T" in units and "K" in units:
if rec[0] < 1.:
T.append(rec[0] * 1e3)
Tv.append(rec[0] * 1e3)
else:
T.append(rec[0] - 273)
Tv.append(rec[0] - 273)
if recnum > 0:
Tv.append(rec[0] - 273)
else:
T.append(rec[0])
Tv.append(rec[0])
if recnum > 0:
Tv.append(rec[0])
if norm:
M.append(old_div(rec[3], Ints[-1]))
else:
M.append(rec[3])
if recnum > 0 and len(rec) > 0 and len(recbak) > 0:
v = []
if recbak[0] != rec[0]:
V0 = pmag.dir2cart([recbak[1], recbak[2], recbak[3]])
V1 = pmag.dir2cart([rec[1], rec[2], rec[3]])
for el in range(3):
v.append(abs(V1[el] - V0[el]))
vdir = pmag.cart2dir(v)
# append vector difference
Vdif.append(old_div(vdir[2], Ints[-1]))
Vdif.append(old_div(vdir[2], Ints[-1]))
recbak = []
for el in rec:
recbak.append(el)
delta = .005 * M[0]
if num == 1:
if recnum % 2 == 0:
plt.text(T[-1] + delta, M[-1],
(' ' + str(recnum)), fontsize=9)
recnum += 1
else:
if rec[0] < 200:
Tex.append(rec[0] * 1e3)
if rec[0] >= 200:
Tex.append(rec[0] - 273)
Mex.append(old_div(rec[3], Ints[-1]))
recnum += 1
if globals != 0:
globals.MTlist = T
globals.MTlisty = M
if len(Mex) > 0 and len(Tex) > 0:
plt.scatter(Tex, Mex, marker='d', color='k')
if len(Vdif) > 0:
Vdif.append(old_div(vdir[2], Ints[-1]))
Vdif.append(0)
if Tv:
Tv.append(Tv[-1])
plt.plot(T, M)
plt.plot(T, M, 'ro')
if len(Tv) == len(Vdif) and norm:
plt.plot(Tv, Vdif, 'g-')
if units == "T":
plt.xlabel("Step (mT)")
elif units == "K":
plt.xlabel("Step (C)")
elif units == "J":
plt.xlabel("Step (J)")
else:
plt.xlabel("Step [mT,C]")
if norm == 1:
plt.ylabel("Fractional Magnetization")
if norm == 0:
plt.ylabel("Magnetization")
plt.axvline(0, color='k')
plt.axhline(0, color='k')
tstring = s
plt.title(tstring)
plt.draw() | python | def plot_mag(fignum, datablock, s, num, units, norm):
"""
plots magnetization against (de)magnetizing temperature or field
Parameters
_________________
fignum : matplotlib figure number for plotting
datablock : nested list of [step, 0, 0, magnetization, 1,quality]
s : string for title
num : matplotlib figure number, can set to 1
units : [T,K,U] for tesla, kelvin or arbitrary
norm : [True,False] if True, normalize
Effects
______
plots figure
"""
global globals, graphmenu
Ints = []
for plotrec in datablock:
Ints.append(plotrec[3])
Ints.sort()
plt.figure(num=fignum)
T, M, Tv, recnum = [], [], [], 0
Mex, Tex, Vdif = [], [], []
recbak = []
for rec in datablock:
if rec[5] == 'g':
if units == "T":
T.append(rec[0] * 1e3)
Tv.append(rec[0] * 1e3)
if recnum > 0:
Tv.append(rec[0] * 1e3)
elif units == "U":
T.append(rec[0])
Tv.append(rec[0])
if recnum > 0:
Tv.append(rec[0])
elif units == "K":
T.append(rec[0] - 273)
Tv.append(rec[0] - 273)
if recnum > 0:
Tv.append(rec[0] - 273)
elif "T" in units and "K" in units:
if rec[0] < 1.:
T.append(rec[0] * 1e3)
Tv.append(rec[0] * 1e3)
else:
T.append(rec[0] - 273)
Tv.append(rec[0] - 273)
if recnum > 0:
Tv.append(rec[0] - 273)
else:
T.append(rec[0])
Tv.append(rec[0])
if recnum > 0:
Tv.append(rec[0])
if norm:
M.append(old_div(rec[3], Ints[-1]))
else:
M.append(rec[3])
if recnum > 0 and len(rec) > 0 and len(recbak) > 0:
v = []
if recbak[0] != rec[0]:
V0 = pmag.dir2cart([recbak[1], recbak[2], recbak[3]])
V1 = pmag.dir2cart([rec[1], rec[2], rec[3]])
for el in range(3):
v.append(abs(V1[el] - V0[el]))
vdir = pmag.cart2dir(v)
# append vector difference
Vdif.append(old_div(vdir[2], Ints[-1]))
Vdif.append(old_div(vdir[2], Ints[-1]))
recbak = []
for el in rec:
recbak.append(el)
delta = .005 * M[0]
if num == 1:
if recnum % 2 == 0:
plt.text(T[-1] + delta, M[-1],
(' ' + str(recnum)), fontsize=9)
recnum += 1
else:
if rec[0] < 200:
Tex.append(rec[0] * 1e3)
if rec[0] >= 200:
Tex.append(rec[0] - 273)
Mex.append(old_div(rec[3], Ints[-1]))
recnum += 1
if globals != 0:
globals.MTlist = T
globals.MTlisty = M
if len(Mex) > 0 and len(Tex) > 0:
plt.scatter(Tex, Mex, marker='d', color='k')
if len(Vdif) > 0:
Vdif.append(old_div(vdir[2], Ints[-1]))
Vdif.append(0)
if Tv:
Tv.append(Tv[-1])
plt.plot(T, M)
plt.plot(T, M, 'ro')
if len(Tv) == len(Vdif) and norm:
plt.plot(Tv, Vdif, 'g-')
if units == "T":
plt.xlabel("Step (mT)")
elif units == "K":
plt.xlabel("Step (C)")
elif units == "J":
plt.xlabel("Step (J)")
else:
plt.xlabel("Step [mT,C]")
if norm == 1:
plt.ylabel("Fractional Magnetization")
if norm == 0:
plt.ylabel("Magnetization")
plt.axvline(0, color='k')
plt.axhline(0, color='k')
tstring = s
plt.title(tstring)
plt.draw() | plots magnetization against (de)magnetizing temperature or field
Parameters
_________________
fignum : matplotlib figure number for plotting
datablock : nested list of [step, 0, 0, magnetization, 1,quality]
s : string for title
num : matplotlib figure number, can set to 1
units : [T,K,U] for tesla, kelvin or arbitrary
norm : [True,False] if True, normalize
Effects
______
plots figure | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L743-L861 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_zed | def plot_zed(ZED, datablock, angle, s, units):
"""
function to make equal area plot and zijderveld plot
Parameters
_________
ZED : dictionary with keys for plots
eqarea : figure number for equal area projection
zijd : figure number for zijderveld plot
demag : figure number for magnetization against demag step
datablock : nested list of [step, dec, inc, M (Am2), quality]
step : units assumed in SI
M : units assumed Am2
quality : [g,b], good or bad measurement; if bad will be marked as such
angle : angle for X axis in horizontal plane, if 0, x will be 0 declination
s : specimen name
units : SI units ['K','T','U'] for kelvin, tesla or undefined
Effects
_______
calls plotting functions for equal area, zijderveld and demag figures
"""
for fignum in list(ZED.keys()):
fig = plt.figure(num=ZED[fignum])
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
DIbad, DIgood = [], []
for rec in datablock:
if cb.is_null(rec[1],zero_as_null=False):
print('-W- You are missing a declination for specimen', s, ', skipping this row')
continue
if cb.is_null(rec[2],zero_as_null=False):
print('-W- You are missing an inclination for specimen', s, ', skipping this row')
continue
if rec[5] == 'b':
DIbad.append((rec[1], rec[2]))
else:
DIgood.append((rec[1], rec[2]))
badsym = {'lower': ['+', 'g'], 'upper': ['x', 'c']}
if len(DIgood) > 0:
plot_eq(ZED['eqarea'], DIgood, s)
if len(DIbad) > 0:
plot_di_sym(ZED['eqarea'], DIbad, badsym)
elif len(DIbad) > 0:
plot_eq_sym(ZED['eqarea'], DIbad, s, badsym)
AngleX, AngleY = [], []
XY = pmag.dimap(angle, 90.)
AngleX.append(XY[0])
AngleY.append(XY[1])
XY = pmag.dimap(angle, 0.)
AngleX.append(XY[0])
AngleY.append(XY[1])
plt.figure(num=ZED['eqarea'])
# Draw a line for Zijderveld horizontal axis
plt.plot(AngleX, AngleY, 'r-')
if AngleX[-1] == 0:
AngleX[-1] = 0.01
plt.text(AngleX[-1] + (old_div(AngleX[-1], abs(AngleX[-1]))) * .1,
AngleY[-1] + (old_div(AngleY[-1], abs(AngleY[-1]))) * .1, 'X')
norm = 1
#if units=="U": norm=0
# if there are NO good points, don't try to plot
if DIgood:
plot_mag(ZED['demag'], datablock, s, 1, units, norm)
plot_zij(ZED['zijd'], datablock, angle, s, norm)
else:
ZED.pop('demag')
ZED.pop('zijd')
return ZED | python | def plot_zed(ZED, datablock, angle, s, units):
"""
function to make equal area plot and zijderveld plot
Parameters
_________
ZED : dictionary with keys for plots
eqarea : figure number for equal area projection
zijd : figure number for zijderveld plot
demag : figure number for magnetization against demag step
datablock : nested list of [step, dec, inc, M (Am2), quality]
step : units assumed in SI
M : units assumed Am2
quality : [g,b], good or bad measurement; if bad will be marked as such
angle : angle for X axis in horizontal plane, if 0, x will be 0 declination
s : specimen name
units : SI units ['K','T','U'] for kelvin, tesla or undefined
Effects
_______
calls plotting functions for equal area, zijderveld and demag figures
"""
for fignum in list(ZED.keys()):
fig = plt.figure(num=ZED[fignum])
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
DIbad, DIgood = [], []
for rec in datablock:
if cb.is_null(rec[1],zero_as_null=False):
print('-W- You are missing a declination for specimen', s, ', skipping this row')
continue
if cb.is_null(rec[2],zero_as_null=False):
print('-W- You are missing an inclination for specimen', s, ', skipping this row')
continue
if rec[5] == 'b':
DIbad.append((rec[1], rec[2]))
else:
DIgood.append((rec[1], rec[2]))
badsym = {'lower': ['+', 'g'], 'upper': ['x', 'c']}
if len(DIgood) > 0:
plot_eq(ZED['eqarea'], DIgood, s)
if len(DIbad) > 0:
plot_di_sym(ZED['eqarea'], DIbad, badsym)
elif len(DIbad) > 0:
plot_eq_sym(ZED['eqarea'], DIbad, s, badsym)
AngleX, AngleY = [], []
XY = pmag.dimap(angle, 90.)
AngleX.append(XY[0])
AngleY.append(XY[1])
XY = pmag.dimap(angle, 0.)
AngleX.append(XY[0])
AngleY.append(XY[1])
plt.figure(num=ZED['eqarea'])
# Draw a line for Zijderveld horizontal axis
plt.plot(AngleX, AngleY, 'r-')
if AngleX[-1] == 0:
AngleX[-1] = 0.01
plt.text(AngleX[-1] + (old_div(AngleX[-1], abs(AngleX[-1]))) * .1,
AngleY[-1] + (old_div(AngleY[-1], abs(AngleY[-1]))) * .1, 'X')
norm = 1
#if units=="U": norm=0
# if there are NO good points, don't try to plot
if DIgood:
plot_mag(ZED['demag'], datablock, s, 1, units, norm)
plot_zij(ZED['zijd'], datablock, angle, s, norm)
else:
ZED.pop('demag')
ZED.pop('zijd')
return ZED | function to make equal area plot and zijderveld plot
Parameters
_________
ZED : dictionary with keys for plots
eqarea : figure number for equal area projection
zijd : figure number for zijderveld plot
demag : figure number for magnetization against demag step
datablock : nested list of [step, dec, inc, M (Am2), quality]
step : units assumed in SI
M : units assumed Am2
quality : [g,b], good or bad measurement; if bad will be marked as such
angle : angle for X axis in horizontal plane, if 0, x will be 0 declination
s : specimen name
units : SI units ['K','T','U'] for kelvin, tesla or undefined
Effects
_______
calls plotting functions for equal area, zijderveld and demag figures | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L867-L937 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_dir | def plot_dir(ZED, pars, datablock, angle):
"""
function to put the great circle on the equal area projection
and plot start and end points of calculation
DEPRECATED (used in zeq_magic)
"""
#
# find start and end points from datablock
#
if pars["calculation_type"] == 'DE-FM':
x, y = [], []
plt.figure(num=ZED['eqarea'])
XY = pmag.dimap(pars["specimen_dec"], pars["specimen_inc"])
x.append(XY[0])
y.append(XY[1])
plt.scatter(x, y, marker='^', s=80, c='r')
plt.show()
return
StartDir, EndDir = [0, 0, 1.], [0, 0, 1.]
for rec in datablock:
if rec[0] == pars["measurement_step_min"]:
StartDir[0] = rec[1]
StartDir[1] = rec[2]
if pars["specimen_direction_type"] == 'l':
StartDir[2] = rec[3]/datablock[0][3]
if rec[0] == pars["measurement_step_max"]:
EndDir[0] = rec[1]
EndDir[1] = rec[2]
if pars["specimen_direction_type"] == 'l':
EndDir[2] = rec[3]/datablock[0][3]
#
# put them on the plots
#
x, y, z, pole = [], [], [], []
if pars["calculation_type"] != 'DE-BFP':
plt.figure(num=ZED['eqarea'])
XY = pmag.dimap(pars["specimen_dec"], pars["specimen_inc"])
x.append(XY[0])
y.append(XY[1])
plt.scatter(x, y, marker='d', s=80, c='b')
x, y, z = [], [], []
StartDir[0] = StartDir[0] - angle
EndDir[0] = EndDir[0] - angle
XYZs = pmag.dir2cart(StartDir)
x.append(XYZs[0])
y.append(XYZs[1])
z.append(XYZs[2])
XYZe = pmag.dir2cart(EndDir)
x.append(XYZe[0])
y.append(XYZe[1])
z.append(XYZe[2])
plt.figure(num=ZED['zijd'])
plt.scatter(x, y, marker='d', s=80, c='g')
plt.scatter(x, z, marker='d', s=80, c='g')
plt.scatter(x, y, marker='o', c='r', s=20)
plt.scatter(x, z, marker='s', c='w', s=20)
#
# put on best fit line
# new way (from Jeff Gee's favorite website http://GET THIS):
# P1=pmag.dir2cart([(pars["specimen_dec"]-angle),pars["specimen_inc"],1.]) # princ comp.
# P2=pmag.dir2cart([(pars["specimen_dec"]-angle-180.),-pars["specimen_inc"],1.]) # antipode of princ comp.
# P21,Ps,Pe,Xs,Xe=[],[],[],[],[]
# for i in range(3):
# P21.append(P2[i]-P1[i])
# Ps.append(XYZs[i]-P1[i])
# Pe.append(XYZe[i]-P1[i])
# norm=pmag.cart2dir(P21)[2]
# us=(Ps[0]*P21[0]+Ps[1]*P21[1]+Ps[2]*P21[2])/(norm**2)
# ue=(Pe[0]*P21[0]+Pe[1]*P21[1]+Pe[2]*P21[2])/(norm**2)
# px,py,pz=[],[],[]
# for i in range(3):
# Xs.append(P1[i]+us*(P2[i]-P1[i]))
# Xe.append(P1[i]+ue*(P2[i]-P1[i]))
# old way:
cm = pars["center_of_mass"]
if cm != [0., 0., 0.]:
cm = np.array(pars["center_of_mass"])/datablock[0][3]
cmDir = pmag.cart2dir(cm)
cmDir[0] = cmDir[0] - angle
cm = pmag.dir2cart(cmDir)
diff = []
for i in range(3):
diff.append(XYZe[i] - XYZs[i])
R = np.sqrt(diff[0]**2 + diff[1]**2 + diff[2]**2)
P = pmag.dir2cart(
((pars["specimen_dec"] - angle), pars["specimen_inc"], R/2.5))
px, py, pz = [], [], []
px.append((cm[0] + P[0]))
py.append((cm[1] + P[1]))
pz.append((cm[2] + P[2]))
px.append((cm[0] - P[0]))
py.append((cm[1] - P[1]))
pz.append((cm[2] - P[2]))
plt.plot(px, py, 'g', linewidth=2)
plt.plot(px, pz, 'g', linewidth=2)
plt.axis("equal")
else:
plt.figure(num=ZED['eqarea'])
XY = pmag.dimap(StartDir[0], StartDir[1])
x.append(XY[0])
y.append(XY[1])
XY = pmag.dimap(EndDir[0], EndDir[1])
x.append(XY[0])
y.append(XY[1])
plt.scatter(x, y, marker='d', s=80, c='b')
pole.append(pars["specimen_dec"])
pole.append(pars["specimen_inc"])
plot_circ(ZED['eqarea'], pole, 90., 'g')
plt.xlim((-1., 1.))
plt.ylim((-1., 1.))
plt.axis("equal") | python | def plot_dir(ZED, pars, datablock, angle):
"""
function to put the great circle on the equal area projection
and plot start and end points of calculation
DEPRECATED (used in zeq_magic)
"""
#
# find start and end points from datablock
#
if pars["calculation_type"] == 'DE-FM':
x, y = [], []
plt.figure(num=ZED['eqarea'])
XY = pmag.dimap(pars["specimen_dec"], pars["specimen_inc"])
x.append(XY[0])
y.append(XY[1])
plt.scatter(x, y, marker='^', s=80, c='r')
plt.show()
return
StartDir, EndDir = [0, 0, 1.], [0, 0, 1.]
for rec in datablock:
if rec[0] == pars["measurement_step_min"]:
StartDir[0] = rec[1]
StartDir[1] = rec[2]
if pars["specimen_direction_type"] == 'l':
StartDir[2] = rec[3]/datablock[0][3]
if rec[0] == pars["measurement_step_max"]:
EndDir[0] = rec[1]
EndDir[1] = rec[2]
if pars["specimen_direction_type"] == 'l':
EndDir[2] = rec[3]/datablock[0][3]
#
# put them on the plots
#
x, y, z, pole = [], [], [], []
if pars["calculation_type"] != 'DE-BFP':
plt.figure(num=ZED['eqarea'])
XY = pmag.dimap(pars["specimen_dec"], pars["specimen_inc"])
x.append(XY[0])
y.append(XY[1])
plt.scatter(x, y, marker='d', s=80, c='b')
x, y, z = [], [], []
StartDir[0] = StartDir[0] - angle
EndDir[0] = EndDir[0] - angle
XYZs = pmag.dir2cart(StartDir)
x.append(XYZs[0])
y.append(XYZs[1])
z.append(XYZs[2])
XYZe = pmag.dir2cart(EndDir)
x.append(XYZe[0])
y.append(XYZe[1])
z.append(XYZe[2])
plt.figure(num=ZED['zijd'])
plt.scatter(x, y, marker='d', s=80, c='g')
plt.scatter(x, z, marker='d', s=80, c='g')
plt.scatter(x, y, marker='o', c='r', s=20)
plt.scatter(x, z, marker='s', c='w', s=20)
#
# put on best fit line
# new way (from Jeff Gee's favorite website http://GET THIS):
# P1=pmag.dir2cart([(pars["specimen_dec"]-angle),pars["specimen_inc"],1.]) # princ comp.
# P2=pmag.dir2cart([(pars["specimen_dec"]-angle-180.),-pars["specimen_inc"],1.]) # antipode of princ comp.
# P21,Ps,Pe,Xs,Xe=[],[],[],[],[]
# for i in range(3):
# P21.append(P2[i]-P1[i])
# Ps.append(XYZs[i]-P1[i])
# Pe.append(XYZe[i]-P1[i])
# norm=pmag.cart2dir(P21)[2]
# us=(Ps[0]*P21[0]+Ps[1]*P21[1]+Ps[2]*P21[2])/(norm**2)
# ue=(Pe[0]*P21[0]+Pe[1]*P21[1]+Pe[2]*P21[2])/(norm**2)
# px,py,pz=[],[],[]
# for i in range(3):
# Xs.append(P1[i]+us*(P2[i]-P1[i]))
# Xe.append(P1[i]+ue*(P2[i]-P1[i]))
# old way:
cm = pars["center_of_mass"]
if cm != [0., 0., 0.]:
cm = np.array(pars["center_of_mass"])/datablock[0][3]
cmDir = pmag.cart2dir(cm)
cmDir[0] = cmDir[0] - angle
cm = pmag.dir2cart(cmDir)
diff = []
for i in range(3):
diff.append(XYZe[i] - XYZs[i])
R = np.sqrt(diff[0]**2 + diff[1]**2 + diff[2]**2)
P = pmag.dir2cart(
((pars["specimen_dec"] - angle), pars["specimen_inc"], R/2.5))
px, py, pz = [], [], []
px.append((cm[0] + P[0]))
py.append((cm[1] + P[1]))
pz.append((cm[2] + P[2]))
px.append((cm[0] - P[0]))
py.append((cm[1] - P[1]))
pz.append((cm[2] - P[2]))
plt.plot(px, py, 'g', linewidth=2)
plt.plot(px, pz, 'g', linewidth=2)
plt.axis("equal")
else:
plt.figure(num=ZED['eqarea'])
XY = pmag.dimap(StartDir[0], StartDir[1])
x.append(XY[0])
y.append(XY[1])
XY = pmag.dimap(EndDir[0], EndDir[1])
x.append(XY[0])
y.append(XY[1])
plt.scatter(x, y, marker='d', s=80, c='b')
pole.append(pars["specimen_dec"])
pole.append(pars["specimen_inc"])
plot_circ(ZED['eqarea'], pole, 90., 'g')
plt.xlim((-1., 1.))
plt.ylim((-1., 1.))
plt.axis("equal") | function to put the great circle on the equal area projection
and plot start and end points of calculation
DEPRECATED (used in zeq_magic) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L940-L1053 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_arai | def plot_arai(fignum, indata, s, units):
"""
makes Arai plots for Thellier-Thellier type experiments
Parameters
__________
fignum : figure number of matplotlib plot object
indata : nested list of data for Arai plots:
the araiblock of data prepared by pmag.sortarai()
s : specimen name
units : [K, J, ""] (kelvin, joules, unknown)
Effects
_______
makes the Arai plot
"""
global globals
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
x, y, x_zi, y_zi, x_iz, y_iz, xptrm, yptrm, xptrmt, yptrmt = [
], [], [], [], [], [], [], [], [], []
xzptrm, yzptrm = [], [] # zero field ptrm checks
zptrm_check = []
first_Z, first_I, ptrm_check, ptrm_tail, zptrm_check = indata[
0], indata[1], indata[2], indata[3], indata[4]
if len(indata) > 6:
if len(indata[-1]) > 1:
s = s + ":PERP" # there are Delta checks, must be a LP-PI-M-S perp experiment
recnum, yes, Nptrm, Nptrmt, diffcum = 0, 0, 0, 0, 0
# plot the NRM-pTRM data
forVDS = []
for zrec in first_Z:
forVDS.append([zrec[1], zrec[2], old_div(zrec[3], first_Z[0][3])])
ZI = zrec[4]
if zrec[0] == '0':
irec = ['0', 0, 0, 0]
if zrec[0] == '273' and units == 'K':
irec = ['273', 0, 0, 0]
else:
for irec in first_I:
if irec[0] == zrec[0]:
break
# save the NRM data used for calculation in Vi
x.append(old_div(irec[3], first_Z[0][3]))
y.append(old_div(zrec[3], first_Z[0][3]))
if ZI == 1:
x_zi.append(old_div(irec[3], first_Z[0][3]))
y_zi.append(old_div(zrec[3], first_Z[0][3]))
else:
x_iz.append(old_div(irec[3], first_Z[0][3]))
y_iz.append(old_div(zrec[3], first_Z[0][3]))
plt.text(x[-1], y[-1], (' ' + str(recnum)), fontsize=9)
recnum += 1
# now deal with ptrm checks.
if len(ptrm_check) != 0:
for prec in ptrm_check:
step = prec[0]
for zrec in first_Z:
if zrec[0] == step:
break
xptrm.append(old_div(prec[3], first_Z[0][3]))
yptrm.append(old_div(zrec[3], first_Z[0][3]))
# now deal with zptrm checks.
if len(zptrm_check) != 0:
for prec in zptrm_check:
step = prec[0]
for zrec in first_Z:
if zrec[0] == step:
break
xzptrm.append(old_div(prec[3], first_Z[0][3]))
yzptrm.append(old_div(zrec[3], first_Z[0][3]))
# and the pTRM tails
if len(ptrm_tail) != 0:
for trec in ptrm_tail:
step = trec[0]
for irec in first_I:
if irec[0] == step:
break
xptrmt.append(old_div(irec[3], first_Z[0][3]))
yptrmt.append((old_div(trec[3], first_Z[0][3])))
# now plot stuff
if len(x) == 0:
print("Can't do nuttin for ya")
return
try:
if len(x_zi) > 0:
plt.scatter(x_zi, y_zi, marker='o', c='r',
edgecolors="none") # zero field-infield
if len(x_iz) > 0:
plt.scatter(x_iz, y_iz, marker='s', c='b',
faceted="True") # infield-zerofield
except:
if len(x_zi) > 0:
plt.scatter(x_zi, y_zi, marker='o', c='r') # zero field-infield
if len(x_iz) > 0:
plt.scatter(x_iz, y_iz, marker='s', c='b') # infield-zerofield
plt.plot(x, y, 'r')
if globals != 0:
globals.MTlist = x
globals.MTlisty = y
if len(xptrm) > 0:
plt.scatter(xptrm, yptrm, marker='^', c='g', s=80)
if len(xzptrm) > 0:
plt.scatter(xzptrm, yzptrm, marker='v', c='c', s=80)
if len(xptrmt) > 0:
plt.scatter(xptrmt, yptrmt, marker='s', c='b', s=80)
try:
plt.axhline(0, color='k')
plt.axvline(0, color='k')
except:
pass
plt.xlabel("pTRM gained")
plt.ylabel("NRM remaining")
tstring = s + ': NRM = ' + '%9.2e' % (first_Z[0][3])
plt.title(tstring)
# put on VDS
vds = pmag.dovds(forVDS)
plt.axhline(vds, color='b')
plt.text(1., vds - .1, ('VDS '), fontsize=9) | python | def plot_arai(fignum, indata, s, units):
"""
makes Arai plots for Thellier-Thellier type experiments
Parameters
__________
fignum : figure number of matplotlib plot object
indata : nested list of data for Arai plots:
the araiblock of data prepared by pmag.sortarai()
s : specimen name
units : [K, J, ""] (kelvin, joules, unknown)
Effects
_______
makes the Arai plot
"""
global globals
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
x, y, x_zi, y_zi, x_iz, y_iz, xptrm, yptrm, xptrmt, yptrmt = [
], [], [], [], [], [], [], [], [], []
xzptrm, yzptrm = [], [] # zero field ptrm checks
zptrm_check = []
first_Z, first_I, ptrm_check, ptrm_tail, zptrm_check = indata[
0], indata[1], indata[2], indata[3], indata[4]
if len(indata) > 6:
if len(indata[-1]) > 1:
s = s + ":PERP" # there are Delta checks, must be a LP-PI-M-S perp experiment
recnum, yes, Nptrm, Nptrmt, diffcum = 0, 0, 0, 0, 0
# plot the NRM-pTRM data
forVDS = []
for zrec in first_Z:
forVDS.append([zrec[1], zrec[2], old_div(zrec[3], first_Z[0][3])])
ZI = zrec[4]
if zrec[0] == '0':
irec = ['0', 0, 0, 0]
if zrec[0] == '273' and units == 'K':
irec = ['273', 0, 0, 0]
else:
for irec in first_I:
if irec[0] == zrec[0]:
break
# save the NRM data used for calculation in Vi
x.append(old_div(irec[3], first_Z[0][3]))
y.append(old_div(zrec[3], first_Z[0][3]))
if ZI == 1:
x_zi.append(old_div(irec[3], first_Z[0][3]))
y_zi.append(old_div(zrec[3], first_Z[0][3]))
else:
x_iz.append(old_div(irec[3], first_Z[0][3]))
y_iz.append(old_div(zrec[3], first_Z[0][3]))
plt.text(x[-1], y[-1], (' ' + str(recnum)), fontsize=9)
recnum += 1
# now deal with ptrm checks.
if len(ptrm_check) != 0:
for prec in ptrm_check:
step = prec[0]
for zrec in first_Z:
if zrec[0] == step:
break
xptrm.append(old_div(prec[3], first_Z[0][3]))
yptrm.append(old_div(zrec[3], first_Z[0][3]))
# now deal with zptrm checks.
if len(zptrm_check) != 0:
for prec in zptrm_check:
step = prec[0]
for zrec in first_Z:
if zrec[0] == step:
break
xzptrm.append(old_div(prec[3], first_Z[0][3]))
yzptrm.append(old_div(zrec[3], first_Z[0][3]))
# and the pTRM tails
if len(ptrm_tail) != 0:
for trec in ptrm_tail:
step = trec[0]
for irec in first_I:
if irec[0] == step:
break
xptrmt.append(old_div(irec[3], first_Z[0][3]))
yptrmt.append((old_div(trec[3], first_Z[0][3])))
# now plot stuff
if len(x) == 0:
print("Can't do nuttin for ya")
return
try:
if len(x_zi) > 0:
plt.scatter(x_zi, y_zi, marker='o', c='r',
edgecolors="none") # zero field-infield
if len(x_iz) > 0:
plt.scatter(x_iz, y_iz, marker='s', c='b',
faceted="True") # infield-zerofield
except:
if len(x_zi) > 0:
plt.scatter(x_zi, y_zi, marker='o', c='r') # zero field-infield
if len(x_iz) > 0:
plt.scatter(x_iz, y_iz, marker='s', c='b') # infield-zerofield
plt.plot(x, y, 'r')
if globals != 0:
globals.MTlist = x
globals.MTlisty = y
if len(xptrm) > 0:
plt.scatter(xptrm, yptrm, marker='^', c='g', s=80)
if len(xzptrm) > 0:
plt.scatter(xzptrm, yzptrm, marker='v', c='c', s=80)
if len(xptrmt) > 0:
plt.scatter(xptrmt, yptrmt, marker='s', c='b', s=80)
try:
plt.axhline(0, color='k')
plt.axvline(0, color='k')
except:
pass
plt.xlabel("pTRM gained")
plt.ylabel("NRM remaining")
tstring = s + ': NRM = ' + '%9.2e' % (first_Z[0][3])
plt.title(tstring)
# put on VDS
vds = pmag.dovds(forVDS)
plt.axhline(vds, color='b')
plt.text(1., vds - .1, ('VDS '), fontsize=9) | makes Arai plots for Thellier-Thellier type experiments
Parameters
__________
fignum : figure number of matplotlib plot object
indata : nested list of data for Arai plots:
the araiblock of data prepared by pmag.sortarai()
s : specimen name
units : [K, J, ""] (kelvin, joules, unknown)
Effects
_______
makes the Arai plot | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1057-L1176 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_np | def plot_np(fignum, indata, s, units):
"""
makes plot of de(re)magnetization data for Thellier-Thellier type experiment
Parameters
__________
fignum : matplotlib figure number
indata : araiblock from, e.g., pmag.sortarai()
s : specimen name
units : [K, J, ""] (kelvin, joules, unknown)
Effect
_______
Makes a plot
"""
global globals
first_Z, first_I, ptrm_check, ptrm_tail = indata[0], indata[1], indata[2], indata[3]
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
X, Y, recnum = [], [], 0
#
for rec in first_Z:
if units == "K":
if rec[0] != 0:
X.append(rec[0] - 273.)
else:
X.append(rec[0])
if (units == "J") or (not units) or (units == "T"):
X.append(rec[0])
Y.append(old_div(rec[3], first_Z[0][3]))
delta = .02 * Y[0]
if recnum % 2 == 0:
plt.text(X[-1] - delta, Y[-1] + delta,
(' ' + str(recnum)), fontsize=9)
recnum += 1
plt.plot(X, Y)
plt.scatter(X, Y, marker='o', color='b')
X, Y = [], []
for rec in first_I:
if units == "K":
if rec[0] != 0:
X.append(rec[0] - 273)
else:
X.append(rec[0])
if (units == "J") or (not units) or (units == "T"):
X.append(rec[0])
Y.append(old_div(rec[3], first_Z[0][3]))
if globals != 0:
globals.DIlist = X
globals.DIlisty = Y
plt.plot(X, Y)
plt.scatter(X, Y, marker='s', color='r')
plt.ylabel("Circles: NRM; Squares: pTRM")
if units == "K":
plt.xlabel("Temperature (C)")
elif units == "J":
plt.xlabel("Microwave Energy (J)")
else:
plt.xlabel("")
title = s + ": NRM = " + '%9.2e' % (first_Z[0][3])
plt.title(title)
plt.axhline(y=0, xmin=0, xmax=1, color='k')
plt.axvline(x=0, ymin=0, ymax=1, color='k') | python | def plot_np(fignum, indata, s, units):
"""
makes plot of de(re)magnetization data for Thellier-Thellier type experiment
Parameters
__________
fignum : matplotlib figure number
indata : araiblock from, e.g., pmag.sortarai()
s : specimen name
units : [K, J, ""] (kelvin, joules, unknown)
Effect
_______
Makes a plot
"""
global globals
first_Z, first_I, ptrm_check, ptrm_tail = indata[0], indata[1], indata[2], indata[3]
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
X, Y, recnum = [], [], 0
#
for rec in first_Z:
if units == "K":
if rec[0] != 0:
X.append(rec[0] - 273.)
else:
X.append(rec[0])
if (units == "J") or (not units) or (units == "T"):
X.append(rec[0])
Y.append(old_div(rec[3], first_Z[0][3]))
delta = .02 * Y[0]
if recnum % 2 == 0:
plt.text(X[-1] - delta, Y[-1] + delta,
(' ' + str(recnum)), fontsize=9)
recnum += 1
plt.plot(X, Y)
plt.scatter(X, Y, marker='o', color='b')
X, Y = [], []
for rec in first_I:
if units == "K":
if rec[0] != 0:
X.append(rec[0] - 273)
else:
X.append(rec[0])
if (units == "J") or (not units) or (units == "T"):
X.append(rec[0])
Y.append(old_div(rec[3], first_Z[0][3]))
if globals != 0:
globals.DIlist = X
globals.DIlisty = Y
plt.plot(X, Y)
plt.scatter(X, Y, marker='s', color='r')
plt.ylabel("Circles: NRM; Squares: pTRM")
if units == "K":
plt.xlabel("Temperature (C)")
elif units == "J":
plt.xlabel("Microwave Energy (J)")
else:
plt.xlabel("")
title = s + ": NRM = " + '%9.2e' % (first_Z[0][3])
plt.title(title)
plt.axhline(y=0, xmin=0, xmax=1, color='k')
plt.axvline(x=0, ymin=0, ymax=1, color='k') | makes plot of de(re)magnetization data for Thellier-Thellier type experiment
Parameters
__________
fignum : matplotlib figure number
indata : araiblock from, e.g., pmag.sortarai()
s : specimen name
units : [K, J, ""] (kelvin, joules, unknown)
Effect
_______
Makes a plot | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1183-L1247 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_arai_zij | def plot_arai_zij(ZED, araiblock, zijdblock, s, units):
"""
calls the four plotting programs for Thellier-Thellier experiments
Parameters
__________
ZED : dictionary with plotting figure keys:
deremag : figure for de (re) magnezation plots
arai : figure for the Arai diagram
eqarea : equal area projection of data, color coded by
red circles: ZI steps
blue squares: IZ steps
yellow triangles : pTRM steps
zijd : Zijderveld diagram color coded by ZI, IZ steps
deremag : demagnetization and remagnetization versus temperature
araiblock : nested list of required data from Arai plots
zijdblock : nested list of required data for Zijderveld plots
s : specimen name
units : units for the arai and zijderveld plots
Effects
________
Makes four plots from the data by calling
plot_arai : Arai plots
plot_teq : equal area projection for Thellier data
plotZ : Zijderveld diagram
plot_np : de (re) magnetization diagram
"""
angle = zijdblock[0][1]
norm = 1
if units == "U":
norm = 0
plot_arai(ZED['arai'], araiblock, s, units)
plot_teq(ZED['eqarea'], araiblock, s, "")
plot_zij(ZED['zijd'], zijdblock, angle, s, norm)
plot_np(ZED['deremag'], araiblock, s, units)
return ZED | python | def plot_arai_zij(ZED, araiblock, zijdblock, s, units):
"""
calls the four plotting programs for Thellier-Thellier experiments
Parameters
__________
ZED : dictionary with plotting figure keys:
deremag : figure for de (re) magnezation plots
arai : figure for the Arai diagram
eqarea : equal area projection of data, color coded by
red circles: ZI steps
blue squares: IZ steps
yellow triangles : pTRM steps
zijd : Zijderveld diagram color coded by ZI, IZ steps
deremag : demagnetization and remagnetization versus temperature
araiblock : nested list of required data from Arai plots
zijdblock : nested list of required data for Zijderveld plots
s : specimen name
units : units for the arai and zijderveld plots
Effects
________
Makes four plots from the data by calling
plot_arai : Arai plots
plot_teq : equal area projection for Thellier data
plotZ : Zijderveld diagram
plot_np : de (re) magnetization diagram
"""
angle = zijdblock[0][1]
norm = 1
if units == "U":
norm = 0
plot_arai(ZED['arai'], araiblock, s, units)
plot_teq(ZED['eqarea'], araiblock, s, "")
plot_zij(ZED['zijd'], zijdblock, angle, s, norm)
plot_np(ZED['deremag'], araiblock, s, units)
return ZED | calls the four plotting programs for Thellier-Thellier experiments
Parameters
__________
ZED : dictionary with plotting figure keys:
deremag : figure for de (re) magnezation plots
arai : figure for the Arai diagram
eqarea : equal area projection of data, color coded by
red circles: ZI steps
blue squares: IZ steps
yellow triangles : pTRM steps
zijd : Zijderveld diagram color coded by ZI, IZ steps
deremag : demagnetization and remagnetization versus temperature
araiblock : nested list of required data from Arai plots
zijdblock : nested list of required data for Zijderveld plots
s : specimen name
units : units for the arai and zijderveld plots
Effects
________
Makes four plots from the data by calling
plot_arai : Arai plots
plot_teq : equal area projection for Thellier data
plotZ : Zijderveld diagram
plot_np : de (re) magnetization diagram | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1250-L1286 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_b | def plot_b(Figs, araiblock, zijdblock, pars):
"""
deprecated (used in thellier_magic/microwave_magic)
"""
angle = zijdblock[0][1]
plotblock = []
Dir, zx, zy, zz, ax, ay = [], [], [], [], [], []
zstart, zend = 0, len(zijdblock)
first_Z, first_I = araiblock[0], araiblock[1]
for rec in zijdblock:
if rec[0] == pars["measurement_step_min"]:
Dir.append((rec[1] - angle, rec[2],
old_div(rec[3], zijdblock[0][3])))
if rec[0] == pars["measurement_step_max"]:
Dir.append((rec[1] - angle, rec[2],
old_div(rec[3], zijdblock[0][3])))
for drec in Dir:
cart = pmag.dir2cart(drec)
zx.append(cart[0])
# zy.append(-cart[1])
# zz.append(-cart[2])
zy.append(cart[1])
zz.append(cart[2])
if len(zx) > 0:
plt.figure(num=Figs['zijd'])
plt.scatter(zx, zy, marker='d', s=100, c='y')
plt.scatter(zx, zz, marker='d', s=100, c='y')
plt.axis("equal")
ax.append(old_div(first_I[0][3], first_Z[0][3]))
ax.append(old_div(first_I[-1][3], first_Z[0][3]))
ay.append(old_div(first_Z[0][3], first_Z[0][3]))
ay.append(old_div(first_Z[-1][3], first_Z[0][3]))
for k in range(len(first_Z)):
if first_Z[k][0] == pars["measurement_step_min"]:
ay[0] = (old_div(first_Z[k][3], first_Z[0][3]))
if first_Z[k][0] == pars["measurement_step_max"]:
ay[1] = (old_div(first_Z[k][3], first_Z[0][3]))
if first_I[k][0] == pars["measurement_step_min"]:
ax[0] = (old_div(first_I[k][3], first_Z[0][3]))
if first_I[k][0] == pars["measurement_step_max"]:
ax[1] = (old_div(first_I[k][3], first_Z[0][3]))
new_Z, new_I = [], []
for zrec in first_Z:
if zrec[0] >= pars['measurement_step_min'] and zrec[0] <= pars['measurement_step_max']:
new_Z.append(zrec)
for irec in first_I:
if irec[0] >= pars['measurement_step_min'] and irec[0] <= pars['measurement_step_max']:
new_I.append(irec)
newblock = [new_Z, new_I]
plot_teq(Figs['eqarea'], newblock, "", pars)
plt.figure(num=Figs['arai'])
plt.scatter(ax, ay, marker='d', s=100, c='y')
#
# find midpoint between two endpoints
#
sy = []
sy.append((pars["specimen_b"] * ax[0] +
old_div(pars["specimen_ytot"], first_Z[0][3])))
sy.append((pars["specimen_b"] * ax[1] +
old_div(pars["specimen_ytot"], first_Z[0][3])))
plt.plot(ax, sy, 'g', linewidth=2)
bounds = plt.axis()
if pars['specimen_grade'] != '':
notestr = 'Grade: ' + pars["specimen_grade"]
plt.text(.7 * bounds[1], .9 * bounds[3], notestr)
notestr = 'B: ' + '%6.2f' % (pars["specimen_int"] * 1e6) + ' uT'
plt.text(.7 * bounds[1], .8 * bounds[3], notestr) | python | def plot_b(Figs, araiblock, zijdblock, pars):
"""
deprecated (used in thellier_magic/microwave_magic)
"""
angle = zijdblock[0][1]
plotblock = []
Dir, zx, zy, zz, ax, ay = [], [], [], [], [], []
zstart, zend = 0, len(zijdblock)
first_Z, first_I = araiblock[0], araiblock[1]
for rec in zijdblock:
if rec[0] == pars["measurement_step_min"]:
Dir.append((rec[1] - angle, rec[2],
old_div(rec[3], zijdblock[0][3])))
if rec[0] == pars["measurement_step_max"]:
Dir.append((rec[1] - angle, rec[2],
old_div(rec[3], zijdblock[0][3])))
for drec in Dir:
cart = pmag.dir2cart(drec)
zx.append(cart[0])
# zy.append(-cart[1])
# zz.append(-cart[2])
zy.append(cart[1])
zz.append(cart[2])
if len(zx) > 0:
plt.figure(num=Figs['zijd'])
plt.scatter(zx, zy, marker='d', s=100, c='y')
plt.scatter(zx, zz, marker='d', s=100, c='y')
plt.axis("equal")
ax.append(old_div(first_I[0][3], first_Z[0][3]))
ax.append(old_div(first_I[-1][3], first_Z[0][3]))
ay.append(old_div(first_Z[0][3], first_Z[0][3]))
ay.append(old_div(first_Z[-1][3], first_Z[0][3]))
for k in range(len(first_Z)):
if first_Z[k][0] == pars["measurement_step_min"]:
ay[0] = (old_div(first_Z[k][3], first_Z[0][3]))
if first_Z[k][0] == pars["measurement_step_max"]:
ay[1] = (old_div(first_Z[k][3], first_Z[0][3]))
if first_I[k][0] == pars["measurement_step_min"]:
ax[0] = (old_div(first_I[k][3], first_Z[0][3]))
if first_I[k][0] == pars["measurement_step_max"]:
ax[1] = (old_div(first_I[k][3], first_Z[0][3]))
new_Z, new_I = [], []
for zrec in first_Z:
if zrec[0] >= pars['measurement_step_min'] and zrec[0] <= pars['measurement_step_max']:
new_Z.append(zrec)
for irec in first_I:
if irec[0] >= pars['measurement_step_min'] and irec[0] <= pars['measurement_step_max']:
new_I.append(irec)
newblock = [new_Z, new_I]
plot_teq(Figs['eqarea'], newblock, "", pars)
plt.figure(num=Figs['arai'])
plt.scatter(ax, ay, marker='d', s=100, c='y')
#
# find midpoint between two endpoints
#
sy = []
sy.append((pars["specimen_b"] * ax[0] +
old_div(pars["specimen_ytot"], first_Z[0][3])))
sy.append((pars["specimen_b"] * ax[1] +
old_div(pars["specimen_ytot"], first_Z[0][3])))
plt.plot(ax, sy, 'g', linewidth=2)
bounds = plt.axis()
if pars['specimen_grade'] != '':
notestr = 'Grade: ' + pars["specimen_grade"]
plt.text(.7 * bounds[1], .9 * bounds[3], notestr)
notestr = 'B: ' + '%6.2f' % (pars["specimen_int"] * 1e6) + ' uT'
plt.text(.7 * bounds[1], .8 * bounds[3], notestr) | deprecated (used in thellier_magic/microwave_magic) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1289-L1355 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_slnp | def plot_slnp(fignum, SiteRec, datablock, key):
"""
plots lines and planes on a great circle with alpha 95 and mean
deprecated (used in pmagplotlib)
"""
# make the stereonet
plt.figure(num=fignum)
plot_net(fignum)
s = SiteRec['er_site_name']
#
# plot on the data
#
coord = SiteRec['site_tilt_correction']
title = ''
if coord == '-1':
title = s + ": specimen coordinates"
if coord == '0':
title = s + ": geographic coordinates"
if coord == '100':
title = s + ": tilt corrected coordinates"
DIblock, GCblock = [], []
for plotrec in datablock:
if plotrec[key + '_direction_type'] == 'p': # direction is pole to plane
GCblock.append(
(float(plotrec[key + "_dec"]), float(plotrec[key + "_inc"])))
else: # assume direction is a directed line
DIblock.append(
(float(plotrec[key + "_dec"]), float(plotrec[key + "_inc"])))
if len(DIblock) > 0:
plot_di(fignum, DIblock) # plot directed lines
if len(GCblock) > 0:
for pole in GCblock:
plot_circ(fignum, pole, 90., 'g') # plot directed lines
#
# put on the mean direction
#
x, y = [], []
XY = pmag.dimap(float(SiteRec["site_dec"]), float(SiteRec["site_inc"]))
x.append(XY[0])
y.append(XY[1])
plt.scatter(x, y, marker='d', s=80, c='g')
plt.title(title)
#
# get the alpha95
#
Xcirc, Ycirc = [], []
Da95, Ia95 = pmag.circ(float(SiteRec["site_dec"]), float(
SiteRec["site_inc"]), float(SiteRec["site_alpha95"]))
for k in range(len(Da95)):
XY = pmag.dimap(Da95[k], Ia95[k])
Xcirc.append(XY[0])
Ycirc.append(XY[1])
plt.plot(Xcirc, Ycirc, 'g') | python | def plot_slnp(fignum, SiteRec, datablock, key):
"""
plots lines and planes on a great circle with alpha 95 and mean
deprecated (used in pmagplotlib)
"""
# make the stereonet
plt.figure(num=fignum)
plot_net(fignum)
s = SiteRec['er_site_name']
#
# plot on the data
#
coord = SiteRec['site_tilt_correction']
title = ''
if coord == '-1':
title = s + ": specimen coordinates"
if coord == '0':
title = s + ": geographic coordinates"
if coord == '100':
title = s + ": tilt corrected coordinates"
DIblock, GCblock = [], []
for plotrec in datablock:
if plotrec[key + '_direction_type'] == 'p': # direction is pole to plane
GCblock.append(
(float(plotrec[key + "_dec"]), float(plotrec[key + "_inc"])))
else: # assume direction is a directed line
DIblock.append(
(float(plotrec[key + "_dec"]), float(plotrec[key + "_inc"])))
if len(DIblock) > 0:
plot_di(fignum, DIblock) # plot directed lines
if len(GCblock) > 0:
for pole in GCblock:
plot_circ(fignum, pole, 90., 'g') # plot directed lines
#
# put on the mean direction
#
x, y = [], []
XY = pmag.dimap(float(SiteRec["site_dec"]), float(SiteRec["site_inc"]))
x.append(XY[0])
y.append(XY[1])
plt.scatter(x, y, marker='d', s=80, c='g')
plt.title(title)
#
# get the alpha95
#
Xcirc, Ycirc = [], []
Da95, Ia95 = pmag.circ(float(SiteRec["site_dec"]), float(
SiteRec["site_inc"]), float(SiteRec["site_alpha95"]))
for k in range(len(Da95)):
XY = pmag.dimap(Da95[k], Ia95[k])
Xcirc.append(XY[0])
Ycirc.append(XY[1])
plt.plot(Xcirc, Ycirc, 'g') | plots lines and planes on a great circle with alpha 95 and mean
deprecated (used in pmagplotlib) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1358-L1410 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_lnp | def plot_lnp(fignum, s, datablock, fpars, direction_type_key):
"""
plots lines and planes on a great circle with alpha 95 and mean
Parameters
_________
fignum : number of plt.figure() object
datablock : nested list of dictionaries with keys in 3.0 or 2.5 format
3.0 keys: dir_dec, dir_inc, dir_tilt_correction = [-1,0,100], direction_type_key =['p','l']
2.5 keys: dec, inc, tilt_correction = [-1,0,100],direction_type_key =['p','l']
fpars : Fisher parameters calculated by, e.g., pmag.dolnp() or pmag.dolnp3_0()
direction_type_key : key for dictionary direction_type ('specimen_direction_type')
Effects
_______
plots the site level figure
"""
# make the stereonet
plot_net(fignum)
#
# plot on the data
#
dec_key, inc_key, tilt_key = 'dec', 'inc', 'tilt_correction'
if 'dir_dec' in datablock[0].keys(): # this is data model 3.0
dec_key, inc_key, tilt_key = 'dir_dec', 'dir_inc', 'dir_tilt_correction'
coord = datablock[0][tilt_key]
title = s
if coord == '-1':
title = title + ": specimen coordinates"
if coord == '0':
title = title + ": geographic coordinates"
if coord == '100':
title = title + ": tilt corrected coordinates"
DIblock, GCblock = [], []
for plotrec in datablock:
if plotrec[direction_type_key] == 'p': # direction is pole to plane
GCblock.append((float(plotrec[dec_key]), float(plotrec[inc_key])))
else: # assume direction is a directed line
DIblock.append((float(plotrec[dec_key]), float(plotrec[inc_key])))
if len(DIblock) > 0:
plot_di(fignum, DIblock) # plot directed lines
if len(GCblock) > 0:
for pole in GCblock:
plot_circ(fignum, pole, 90., 'g') # plot directed lines
#
# put on the mean direction
#
x, y = [], []
XY = pmag.dimap(float(fpars["dec"]), float(fpars["inc"]))
x.append(XY[0])
y.append(XY[1])
plt.figure(num=fignum)
plt.scatter(x, y, marker='d', s=80, c='g')
plt.title(title)
#
# get the alpha95
#
Xcirc, Ycirc = [], []
Da95, Ia95 = pmag.circ(float(fpars["dec"]), float(
fpars["inc"]), float(fpars["alpha95"]))
for k in range(len(Da95)):
XY = pmag.dimap(Da95[k], Ia95[k])
Xcirc.append(XY[0])
Ycirc.append(XY[1])
plt.plot(Xcirc, Ycirc, 'g') | python | def plot_lnp(fignum, s, datablock, fpars, direction_type_key):
"""
plots lines and planes on a great circle with alpha 95 and mean
Parameters
_________
fignum : number of plt.figure() object
datablock : nested list of dictionaries with keys in 3.0 or 2.5 format
3.0 keys: dir_dec, dir_inc, dir_tilt_correction = [-1,0,100], direction_type_key =['p','l']
2.5 keys: dec, inc, tilt_correction = [-1,0,100],direction_type_key =['p','l']
fpars : Fisher parameters calculated by, e.g., pmag.dolnp() or pmag.dolnp3_0()
direction_type_key : key for dictionary direction_type ('specimen_direction_type')
Effects
_______
plots the site level figure
"""
# make the stereonet
plot_net(fignum)
#
# plot on the data
#
dec_key, inc_key, tilt_key = 'dec', 'inc', 'tilt_correction'
if 'dir_dec' in datablock[0].keys(): # this is data model 3.0
dec_key, inc_key, tilt_key = 'dir_dec', 'dir_inc', 'dir_tilt_correction'
coord = datablock[0][tilt_key]
title = s
if coord == '-1':
title = title + ": specimen coordinates"
if coord == '0':
title = title + ": geographic coordinates"
if coord == '100':
title = title + ": tilt corrected coordinates"
DIblock, GCblock = [], []
for plotrec in datablock:
if plotrec[direction_type_key] == 'p': # direction is pole to plane
GCblock.append((float(plotrec[dec_key]), float(plotrec[inc_key])))
else: # assume direction is a directed line
DIblock.append((float(plotrec[dec_key]), float(plotrec[inc_key])))
if len(DIblock) > 0:
plot_di(fignum, DIblock) # plot directed lines
if len(GCblock) > 0:
for pole in GCblock:
plot_circ(fignum, pole, 90., 'g') # plot directed lines
#
# put on the mean direction
#
x, y = [], []
XY = pmag.dimap(float(fpars["dec"]), float(fpars["inc"]))
x.append(XY[0])
y.append(XY[1])
plt.figure(num=fignum)
plt.scatter(x, y, marker='d', s=80, c='g')
plt.title(title)
#
# get the alpha95
#
Xcirc, Ycirc = [], []
Da95, Ia95 = pmag.circ(float(fpars["dec"]), float(
fpars["inc"]), float(fpars["alpha95"]))
for k in range(len(Da95)):
XY = pmag.dimap(Da95[k], Ia95[k])
Xcirc.append(XY[0])
Ycirc.append(XY[1])
plt.plot(Xcirc, Ycirc, 'g') | plots lines and planes on a great circle with alpha 95 and mean
Parameters
_________
fignum : number of plt.figure() object
datablock : nested list of dictionaries with keys in 3.0 or 2.5 format
3.0 keys: dir_dec, dir_inc, dir_tilt_correction = [-1,0,100], direction_type_key =['p','l']
2.5 keys: dec, inc, tilt_correction = [-1,0,100],direction_type_key =['p','l']
fpars : Fisher parameters calculated by, e.g., pmag.dolnp() or pmag.dolnp3_0()
direction_type_key : key for dictionary direction_type ('specimen_direction_type')
Effects
_______
plots the site level figure | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1413-L1476 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_eq | def plot_eq(fignum, DIblock, s):
"""
plots directions on eqarea projection
Parameters
__________
fignum : matplotlib figure number
DIblock : nested list of dec/inc pairs
s : specimen name
"""
# make the stereonet
plt.figure(num=fignum)
if len(DIblock) < 1:
return
# plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plot_net(fignum)
#
# put on the directions
#
plot_di(fignum, DIblock) # plot directions
plt.axis("equal")
plt.text(-1.1, 1.15, s)
plt.draw() | python | def plot_eq(fignum, DIblock, s):
"""
plots directions on eqarea projection
Parameters
__________
fignum : matplotlib figure number
DIblock : nested list of dec/inc pairs
s : specimen name
"""
# make the stereonet
plt.figure(num=fignum)
if len(DIblock) < 1:
return
# plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plot_net(fignum)
#
# put on the directions
#
plot_di(fignum, DIblock) # plot directions
plt.axis("equal")
plt.text(-1.1, 1.15, s)
plt.draw() | plots directions on eqarea projection
Parameters
__________
fignum : matplotlib figure number
DIblock : nested list of dec/inc pairs
s : specimen name | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1479-L1502 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_eq_sym | def plot_eq_sym(fignum, DIblock, s, sym):
"""
plots directions with specified symbol
Parameters
__________
fignum : matplotlib figure number
DIblock : nested list of dec/inc pairs
s : specimen name
sym : matplotlib symbol (e.g., 'bo' for blue circle)
"""
# make the stereonet
plt.figure(num=fignum)
if len(DIblock) < 1:
return
# plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plot_net(fignum)
#
# put on the directions
#
plot_di_sym(fignum, DIblock, sym) # plot directions with symbols in sym
plt.axis("equal")
plt.text(-1.1, 1.15, s) | python | def plot_eq_sym(fignum, DIblock, s, sym):
"""
plots directions with specified symbol
Parameters
__________
fignum : matplotlib figure number
DIblock : nested list of dec/inc pairs
s : specimen name
sym : matplotlib symbol (e.g., 'bo' for blue circle)
"""
# make the stereonet
plt.figure(num=fignum)
if len(DIblock) < 1:
return
# plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plot_net(fignum)
#
# put on the directions
#
plot_di_sym(fignum, DIblock, sym) # plot directions with symbols in sym
plt.axis("equal")
plt.text(-1.1, 1.15, s) | plots directions with specified symbol
Parameters
__________
fignum : matplotlib figure number
DIblock : nested list of dec/inc pairs
s : specimen name
sym : matplotlib symbol (e.g., 'bo' for blue circle) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1505-L1528 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_teq | def plot_teq(fignum, araiblock, s, pars):
"""
plots directions of pTRM steps and zero field steps
Parameters
__________
fignum : figure number for matplotlib object
araiblock : nested list of data from pmag.sortarai()
s : specimen name
pars : default is "",
otherwise is dictionary with keys:
'measurement_step_min' and 'measurement_step_max'
Effects
_______
makes the equal area projection with color coded symbols
red circles: ZI steps
blue squares: IZ steps
yellow : pTRM steps
"""
first_Z, first_I = araiblock[0], araiblock[1]
# make the stereonet
plt.figure(num=fignum)
plt.clf()
ZIblock, IZblock, pTblock = [], [], []
for zrec in first_Z: # sort out the zerofield steps
if zrec[4] == 1: # this is a ZI step
ZIblock.append([zrec[1], zrec[2]])
else:
IZblock.append([zrec[1], zrec[2]])
plot_net(fignum)
if pars != "":
min, max = float(pars["measurement_step_min"]), float(
pars["measurement_step_max"])
else:
min, max = first_I[0][0], first_I[-1][0]
for irec in first_I:
if irec[1] != 0 and irec[1] != 0 and irec[0] >= min and irec[0] <= max:
pTblock.append([irec[1], irec[2]])
if len(ZIblock) < 1 and len(IZblock) < 1 and len(pTblock) < 1:
return
if not isServer:
plt.figtext(.02, .01, version_num)
#
# put on the directions
#
sym = {'lower': ['o', 'r'], 'upper': ['o', 'm']}
if len(ZIblock) > 0:
plot_di_sym(fignum, ZIblock, sym) # plot ZI directions
sym = {'lower': ['s', 'b'], 'upper': ['s', 'c']}
if len(IZblock) > 0:
plot_di_sym(fignum, IZblock, sym) # plot IZ directions
sym = {'lower': ['^', 'g'], 'upper': ['^', 'y']}
if len(pTblock) > 0:
plot_di_sym(fignum, pTblock, sym) # plot pTRM directions
plt.axis("equal")
plt.text(-1.1, 1.15, s) | python | def plot_teq(fignum, araiblock, s, pars):
"""
plots directions of pTRM steps and zero field steps
Parameters
__________
fignum : figure number for matplotlib object
araiblock : nested list of data from pmag.sortarai()
s : specimen name
pars : default is "",
otherwise is dictionary with keys:
'measurement_step_min' and 'measurement_step_max'
Effects
_______
makes the equal area projection with color coded symbols
red circles: ZI steps
blue squares: IZ steps
yellow : pTRM steps
"""
first_Z, first_I = araiblock[0], araiblock[1]
# make the stereonet
plt.figure(num=fignum)
plt.clf()
ZIblock, IZblock, pTblock = [], [], []
for zrec in first_Z: # sort out the zerofield steps
if zrec[4] == 1: # this is a ZI step
ZIblock.append([zrec[1], zrec[2]])
else:
IZblock.append([zrec[1], zrec[2]])
plot_net(fignum)
if pars != "":
min, max = float(pars["measurement_step_min"]), float(
pars["measurement_step_max"])
else:
min, max = first_I[0][0], first_I[-1][0]
for irec in first_I:
if irec[1] != 0 and irec[1] != 0 and irec[0] >= min and irec[0] <= max:
pTblock.append([irec[1], irec[2]])
if len(ZIblock) < 1 and len(IZblock) < 1 and len(pTblock) < 1:
return
if not isServer:
plt.figtext(.02, .01, version_num)
#
# put on the directions
#
sym = {'lower': ['o', 'r'], 'upper': ['o', 'm']}
if len(ZIblock) > 0:
plot_di_sym(fignum, ZIblock, sym) # plot ZI directions
sym = {'lower': ['s', 'b'], 'upper': ['s', 'c']}
if len(IZblock) > 0:
plot_di_sym(fignum, IZblock, sym) # plot IZ directions
sym = {'lower': ['^', 'g'], 'upper': ['^', 'y']}
if len(pTblock) > 0:
plot_di_sym(fignum, pTblock, sym) # plot pTRM directions
plt.axis("equal")
plt.text(-1.1, 1.15, s) | plots directions of pTRM steps and zero field steps
Parameters
__________
fignum : figure number for matplotlib object
araiblock : nested list of data from pmag.sortarai()
s : specimen name
pars : default is "",
otherwise is dictionary with keys:
'measurement_step_min' and 'measurement_step_max'
Effects
_______
makes the equal area projection with color coded symbols
red circles: ZI steps
blue squares: IZ steps
yellow : pTRM steps | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1532-L1590 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | save_plots | def save_plots(Figs, filenames, **kwargs):
"""
Parameters
----------
Figs : dict
dictionary of plots, e.g. {'eqarea': 1, ...}
filenames : dict
dictionary of filenames, e.g. {'eqarea': 'mc01a_eqarea.svg', ...}
dict keys should correspond with Figs
"""
saved = []
for key in list(Figs.keys()):
try:
plt.figure(num=Figs[key])
fname = filenames[key]
if set_env.IS_WIN: # always truncate filenames if on Windows
fname = os.path.split(fname)[1]
if not isServer: # remove illegal ':' character for windows
fname = fname.replace(':', '_')
if 'incl_directory' in kwargs.keys() and not set_env.IS_WIN:
if kwargs['incl_directory']:
pass # do not flatten file name
else:
fname = fname.replace('/', '-') # flatten file name
else:
fname = fname.replace('/', '-') # flatten file name
if 'dpi' in list(kwargs.keys()):
plt.savefig(fname, dpi=kwargs['dpi'])
elif isServer:
plt.savefig(fname, dpi=240)
else:
plt.savefig(fname)
if verbose:
print(Figs[key], " saved in ", fname)
saved.append(fname)
plt.close(Figs[key])
except Exception as ex:
print(type(ex), ex)
print('could not save: ', Figs[key], filenames[key])
print("output file format not supported ")
return saved | python | def save_plots(Figs, filenames, **kwargs):
"""
Parameters
----------
Figs : dict
dictionary of plots, e.g. {'eqarea': 1, ...}
filenames : dict
dictionary of filenames, e.g. {'eqarea': 'mc01a_eqarea.svg', ...}
dict keys should correspond with Figs
"""
saved = []
for key in list(Figs.keys()):
try:
plt.figure(num=Figs[key])
fname = filenames[key]
if set_env.IS_WIN: # always truncate filenames if on Windows
fname = os.path.split(fname)[1]
if not isServer: # remove illegal ':' character for windows
fname = fname.replace(':', '_')
if 'incl_directory' in kwargs.keys() and not set_env.IS_WIN:
if kwargs['incl_directory']:
pass # do not flatten file name
else:
fname = fname.replace('/', '-') # flatten file name
else:
fname = fname.replace('/', '-') # flatten file name
if 'dpi' in list(kwargs.keys()):
plt.savefig(fname, dpi=kwargs['dpi'])
elif isServer:
plt.savefig(fname, dpi=240)
else:
plt.savefig(fname)
if verbose:
print(Figs[key], " saved in ", fname)
saved.append(fname)
plt.close(Figs[key])
except Exception as ex:
print(type(ex), ex)
print('could not save: ', Figs[key], filenames[key])
print("output file format not supported ")
return saved | Parameters
----------
Figs : dict
dictionary of plots, e.g. {'eqarea': 1, ...}
filenames : dict
dictionary of filenames, e.g. {'eqarea': 'mc01a_eqarea.svg', ...}
dict keys should correspond with Figs | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1593-L1633 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_evec | def plot_evec(fignum, Vs, symsize, title):
"""
plots eigenvector directions of S vectors
Paramters
________
fignum : matplotlib figure number
Vs : nested list of eigenvectors
symsize : size in pts for symbol
title : title for plot
"""
#
plt.figure(num=fignum)
plt.text(-1.1, 1.15, title)
# plot V1s as squares, V2s as triangles and V3s as circles
symb, symkey = ['s', 'v', 'o'], 0
col = ['r', 'b', 'k'] # plot V1s rec, V2s blue, V3s black
for VEC in range(3):
X, Y = [], []
for Vdirs in Vs:
#
#
# plot the V1 data first
#
XY = pmag.dimap(Vdirs[VEC][0], Vdirs[VEC][1])
X.append(XY[0])
Y.append(XY[1])
plt.scatter(X, Y, s=symsize,
marker=symb[VEC], c=col[VEC], edgecolors='none')
plt.axis("equal") | python | def plot_evec(fignum, Vs, symsize, title):
"""
plots eigenvector directions of S vectors
Paramters
________
fignum : matplotlib figure number
Vs : nested list of eigenvectors
symsize : size in pts for symbol
title : title for plot
"""
#
plt.figure(num=fignum)
plt.text(-1.1, 1.15, title)
# plot V1s as squares, V2s as triangles and V3s as circles
symb, symkey = ['s', 'v', 'o'], 0
col = ['r', 'b', 'k'] # plot V1s rec, V2s blue, V3s black
for VEC in range(3):
X, Y = [], []
for Vdirs in Vs:
#
#
# plot the V1 data first
#
XY = pmag.dimap(Vdirs[VEC][0], Vdirs[VEC][1])
X.append(XY[0])
Y.append(XY[1])
plt.scatter(X, Y, s=symsize,
marker=symb[VEC], c=col[VEC], edgecolors='none')
plt.axis("equal") | plots eigenvector directions of S vectors
Paramters
________
fignum : matplotlib figure number
Vs : nested list of eigenvectors
symsize : size in pts for symbol
title : title for plot | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1637-L1666 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_ell | def plot_ell(fignum, pars, col, lower, plot):
"""
function to calcualte/plot points on an ellipse about Pdec,Pdip with angle beta,gamma
Parameters
_________
fignum : matplotlib figure number
pars : list of [Pdec, Pinc, beta, Bdec, Binc, gamma, Gdec, Ginc ]
where P is direction, Bdec,Binc are beta direction, and Gdec,Ginc are gamma direction
col : color for ellipse
lower : boolean, if True, lower hemisphere projection
plot : boolean, if False, return the points, if False, make the plot
"""
plt.figure(num=fignum)
rad = old_div(np.pi, 180.)
Pdec, Pinc, beta, Bdec, Binc, gamma, Gdec, Ginc = pars[0], pars[
1], pars[2], pars[3], pars[4], pars[5], pars[6], pars[7]
if beta > 90. or gamma > 90:
beta = 180. - beta
gamma = 180. - gamma
Pdec = Pdec - 180.
Pinc = -Pinc
beta, gamma = beta * rad, gamma * rad # convert to radians
X_ell, Y_ell, X_up, Y_up, PTS = [], [], [], [], []
nums = 201
xnum = old_div(float(nums - 1.), 2.)
# set up t matrix
t = [[0, 0, 0], [0, 0, 0], [0, 0, 0]]
X = pmag.dir2cart((Pdec, Pinc, 1.0)) # convert to cartesian coordintes
if lower == 1 and X[2] < 0:
for i in range(3):
X[i] = -X[i]
# set up rotation matrix t
t[0][2] = X[0]
t[1][2] = X[1]
t[2][2] = X[2]
X = pmag.dir2cart((Bdec, Binc, 1.0))
if lower == 1 and X[2] < 0:
for i in range(3):
X[i] = -X[i]
t[0][0] = X[0]
t[1][0] = X[1]
t[2][0] = X[2]
X = pmag.dir2cart((Gdec, Ginc, 1.0))
if lower == 1 and X[2] < 0:
for i in range(3):
X[i] = -X[i]
t[0][1] = X[0]
t[1][1] = X[1]
t[2][1] = X[2]
# set up v matrix
v = [0, 0, 0]
for i in range(nums): # incremental point along ellipse
psi = float(i) * np.pi / xnum
v[0] = np.sin(beta) * np.cos(psi)
v[1] = np.sin(gamma) * np.sin(psi)
v[2] = np.sqrt(1. - v[0]**2 - v[1]**2)
elli = [0, 0, 0]
# calculate points on the ellipse
for j in range(3):
for k in range(3):
# cartesian coordinate j of ellipse
elli[j] = elli[j] + t[j][k] * v[k]
pts = pmag.cart2dir(elli)
PTS.append([pts[0], pts[1]])
# put on an equal area projection
R = old_div(np.sqrt(
1. - abs(elli[2])), (np.sqrt(elli[0]**2 + elli[1]**2)))
if elli[2] <= 0:
# for i in range(3): elli[i]=-elli[i]
X_up.append(elli[1] * R)
Y_up.append(elli[0] * R)
else:
X_ell.append(elli[1] * R)
Y_ell.append(elli[0] * R)
if plot == 1:
col = col[0]+'.'
if X_ell != []:
plt.plot(X_ell, Y_ell, col, markersize=3)
if X_up != []:
plt.plot(X_up, Y_up, col, markersize=3)
else:
return PTS | python | def plot_ell(fignum, pars, col, lower, plot):
"""
function to calcualte/plot points on an ellipse about Pdec,Pdip with angle beta,gamma
Parameters
_________
fignum : matplotlib figure number
pars : list of [Pdec, Pinc, beta, Bdec, Binc, gamma, Gdec, Ginc ]
where P is direction, Bdec,Binc are beta direction, and Gdec,Ginc are gamma direction
col : color for ellipse
lower : boolean, if True, lower hemisphere projection
plot : boolean, if False, return the points, if False, make the plot
"""
plt.figure(num=fignum)
rad = old_div(np.pi, 180.)
Pdec, Pinc, beta, Bdec, Binc, gamma, Gdec, Ginc = pars[0], pars[
1], pars[2], pars[3], pars[4], pars[5], pars[6], pars[7]
if beta > 90. or gamma > 90:
beta = 180. - beta
gamma = 180. - gamma
Pdec = Pdec - 180.
Pinc = -Pinc
beta, gamma = beta * rad, gamma * rad # convert to radians
X_ell, Y_ell, X_up, Y_up, PTS = [], [], [], [], []
nums = 201
xnum = old_div(float(nums - 1.), 2.)
# set up t matrix
t = [[0, 0, 0], [0, 0, 0], [0, 0, 0]]
X = pmag.dir2cart((Pdec, Pinc, 1.0)) # convert to cartesian coordintes
if lower == 1 and X[2] < 0:
for i in range(3):
X[i] = -X[i]
# set up rotation matrix t
t[0][2] = X[0]
t[1][2] = X[1]
t[2][2] = X[2]
X = pmag.dir2cart((Bdec, Binc, 1.0))
if lower == 1 and X[2] < 0:
for i in range(3):
X[i] = -X[i]
t[0][0] = X[0]
t[1][0] = X[1]
t[2][0] = X[2]
X = pmag.dir2cart((Gdec, Ginc, 1.0))
if lower == 1 and X[2] < 0:
for i in range(3):
X[i] = -X[i]
t[0][1] = X[0]
t[1][1] = X[1]
t[2][1] = X[2]
# set up v matrix
v = [0, 0, 0]
for i in range(nums): # incremental point along ellipse
psi = float(i) * np.pi / xnum
v[0] = np.sin(beta) * np.cos(psi)
v[1] = np.sin(gamma) * np.sin(psi)
v[2] = np.sqrt(1. - v[0]**2 - v[1]**2)
elli = [0, 0, 0]
# calculate points on the ellipse
for j in range(3):
for k in range(3):
# cartesian coordinate j of ellipse
elli[j] = elli[j] + t[j][k] * v[k]
pts = pmag.cart2dir(elli)
PTS.append([pts[0], pts[1]])
# put on an equal area projection
R = old_div(np.sqrt(
1. - abs(elli[2])), (np.sqrt(elli[0]**2 + elli[1]**2)))
if elli[2] <= 0:
# for i in range(3): elli[i]=-elli[i]
X_up.append(elli[1] * R)
Y_up.append(elli[0] * R)
else:
X_ell.append(elli[1] * R)
Y_ell.append(elli[0] * R)
if plot == 1:
col = col[0]+'.'
if X_ell != []:
plt.plot(X_ell, Y_ell, col, markersize=3)
if X_up != []:
plt.plot(X_up, Y_up, col, markersize=3)
else:
return PTS | function to calcualte/plot points on an ellipse about Pdec,Pdip with angle beta,gamma
Parameters
_________
fignum : matplotlib figure number
pars : list of [Pdec, Pinc, beta, Bdec, Binc, gamma, Gdec, Ginc ]
where P is direction, Bdec,Binc are beta direction, and Gdec,Ginc are gamma direction
col : color for ellipse
lower : boolean, if True, lower hemisphere projection
plot : boolean, if False, return the points, if False, make the plot | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1670-L1751 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_strat | def plot_strat(fignum, data, labels):
"""
plots a time/depth series
Parameters
_________
fignum : matplotlib figure number
data : nested list of [X,Y] pairs
labels : [xlabel, ylabel, title]
"""
vertical_plot_init(fignum, 10, 3)
xlab, ylab, title = labels[0], labels[1], labels[2]
X, Y = [], []
for rec in data:
X.append(rec[0])
Y.append(rec[1])
plt.plot(X, Y)
plt.plot(X, Y, 'ro')
plt.xlabel(xlab)
plt.ylabel(ylab)
plt.title(title) | python | def plot_strat(fignum, data, labels):
"""
plots a time/depth series
Parameters
_________
fignum : matplotlib figure number
data : nested list of [X,Y] pairs
labels : [xlabel, ylabel, title]
"""
vertical_plot_init(fignum, 10, 3)
xlab, ylab, title = labels[0], labels[1], labels[2]
X, Y = [], []
for rec in data:
X.append(rec[0])
Y.append(rec[1])
plt.plot(X, Y)
plt.plot(X, Y, 'ro')
plt.xlabel(xlab)
plt.ylabel(ylab)
plt.title(title) | plots a time/depth series
Parameters
_________
fignum : matplotlib figure number
data : nested list of [X,Y] pairs
labels : [xlabel, ylabel, title] | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1771-L1790 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_cdf | def plot_cdf(fignum, data, xlab, sym, title, **kwargs):
""" Makes a plot of the cumulative distribution function.
Parameters
__________
fignum : matplotlib figure number
data : list of data to be plotted - doesn't need to be sorted
sym : matplotlib symbol for plotting, e.g., 'r--' for a red dashed line
**kwargs : optional dictionary with {'color': color, 'linewidth':linewidth}
Returns
__________
x : sorted list of data
y : fraction of cdf
"""
#
#if len(sym)==1:sym=sym+'-'
fig = plt.figure(num=fignum)
# sdata=np.array(data).sort()
sdata = []
for d in data:
sdata.append(d) # have to copy the data to avoid overwriting it!
sdata.sort()
X, Y = [], []
color = ""
for j in range(len(sdata)):
Y.append(old_div(float(j), float(len(sdata))))
X.append(sdata[j])
if 'color' in list(kwargs.keys()):
color = kwargs['color']
if 'linewidth' in list(kwargs.keys()):
lw = kwargs['linewidth']
else:
lw = 1
if color != "":
plt.plot(X, Y, color=sym, linewidth=lw)
else:
plt.plot(X, Y, sym, linewidth=lw)
plt.xlabel(xlab)
plt.ylabel('Cumulative Distribution')
plt.title(title)
return X, Y | python | def plot_cdf(fignum, data, xlab, sym, title, **kwargs):
""" Makes a plot of the cumulative distribution function.
Parameters
__________
fignum : matplotlib figure number
data : list of data to be plotted - doesn't need to be sorted
sym : matplotlib symbol for plotting, e.g., 'r--' for a red dashed line
**kwargs : optional dictionary with {'color': color, 'linewidth':linewidth}
Returns
__________
x : sorted list of data
y : fraction of cdf
"""
#
#if len(sym)==1:sym=sym+'-'
fig = plt.figure(num=fignum)
# sdata=np.array(data).sort()
sdata = []
for d in data:
sdata.append(d) # have to copy the data to avoid overwriting it!
sdata.sort()
X, Y = [], []
color = ""
for j in range(len(sdata)):
Y.append(old_div(float(j), float(len(sdata))))
X.append(sdata[j])
if 'color' in list(kwargs.keys()):
color = kwargs['color']
if 'linewidth' in list(kwargs.keys()):
lw = kwargs['linewidth']
else:
lw = 1
if color != "":
plt.plot(X, Y, color=sym, linewidth=lw)
else:
plt.plot(X, Y, sym, linewidth=lw)
plt.xlabel(xlab)
plt.ylabel('Cumulative Distribution')
plt.title(title)
return X, Y | Makes a plot of the cumulative distribution function.
Parameters
__________
fignum : matplotlib figure number
data : list of data to be plotted - doesn't need to be sorted
sym : matplotlib symbol for plotting, e.g., 'r--' for a red dashed line
**kwargs : optional dictionary with {'color': color, 'linewidth':linewidth}
Returns
__________
x : sorted list of data
y : fraction of cdf | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1796-L1837 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_hs | def plot_hs(fignum, Ys, c, ls):
"""
plots horizontal lines at Ys values
Parameters
_________
fignum : matplotlib figure number
Ys : list of Y values for lines
c : color for lines
ls : linestyle for lines
"""
fig = plt.figure(num=fignum)
for yv in Ys:
bounds = plt.axis()
plt.axhline(y=yv, xmin=0, xmax=1, linewidth=1, color=c, linestyle=ls) | python | def plot_hs(fignum, Ys, c, ls):
"""
plots horizontal lines at Ys values
Parameters
_________
fignum : matplotlib figure number
Ys : list of Y values for lines
c : color for lines
ls : linestyle for lines
"""
fig = plt.figure(num=fignum)
for yv in Ys:
bounds = plt.axis()
plt.axhline(y=yv, xmin=0, xmax=1, linewidth=1, color=c, linestyle=ls) | plots horizontal lines at Ys values
Parameters
_________
fignum : matplotlib figure number
Ys : list of Y values for lines
c : color for lines
ls : linestyle for lines | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1841-L1855 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_vs | def plot_vs(fignum, Xs, c, ls):
"""
plots vertical lines at Xs values
Parameters
_________
fignum : matplotlib figure number
Xs : list of X values for lines
c : color for lines
ls : linestyle for lines
"""
fig = plt.figure(num=fignum)
for xv in Xs:
bounds = plt.axis()
plt.axvline(
x=xv, ymin=bounds[2], ymax=bounds[3], linewidth=1, color=c, linestyle=ls) | python | def plot_vs(fignum, Xs, c, ls):
"""
plots vertical lines at Xs values
Parameters
_________
fignum : matplotlib figure number
Xs : list of X values for lines
c : color for lines
ls : linestyle for lines
"""
fig = plt.figure(num=fignum)
for xv in Xs:
bounds = plt.axis()
plt.axvline(
x=xv, ymin=bounds[2], ymax=bounds[3], linewidth=1, color=c, linestyle=ls) | plots vertical lines at Xs values
Parameters
_________
fignum : matplotlib figure number
Xs : list of X values for lines
c : color for lines
ls : linestyle for lines | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1859-L1874 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_ts | def plot_ts(fignum, dates, ts):
"""
plot the geomagnetic polarity time scale
Parameters
__________
fignum : matplotlib figure number
dates : bounding dates for plot
ts : time scale ck95, gts04, or gts12
"""
vertical_plot_init(fignum, 10, 3)
TS, Chrons = pmag.get_ts(ts)
p = 1
X, Y = [], []
for d in TS:
if d <= dates[1]:
if d >= dates[0]:
if len(X) == 0:
ind = TS.index(d)
X.append(TS[ind - 1])
Y.append(p % 2)
X.append(d)
Y.append(p % 2)
p += 1
X.append(d)
Y.append(p % 2)
else:
X.append(dates[1])
Y.append(p % 2)
plt.plot(X, Y, 'k')
plot_vs(fignum, dates, 'w', '-')
plot_hs(fignum, [1.1, -.1], 'w', '-')
plt.xlabel("Age (Ma): " + ts)
isign = -1
for c in Chrons:
off = -.1
isign = -1 * isign
if isign > 0:
off = 1.05
if c[1] >= X[0] and c[1] < X[-1]:
plt.text(c[1] - .2, off, c[0])
return | python | def plot_ts(fignum, dates, ts):
"""
plot the geomagnetic polarity time scale
Parameters
__________
fignum : matplotlib figure number
dates : bounding dates for plot
ts : time scale ck95, gts04, or gts12
"""
vertical_plot_init(fignum, 10, 3)
TS, Chrons = pmag.get_ts(ts)
p = 1
X, Y = [], []
for d in TS:
if d <= dates[1]:
if d >= dates[0]:
if len(X) == 0:
ind = TS.index(d)
X.append(TS[ind - 1])
Y.append(p % 2)
X.append(d)
Y.append(p % 2)
p += 1
X.append(d)
Y.append(p % 2)
else:
X.append(dates[1])
Y.append(p % 2)
plt.plot(X, Y, 'k')
plot_vs(fignum, dates, 'w', '-')
plot_hs(fignum, [1.1, -.1], 'w', '-')
plt.xlabel("Age (Ma): " + ts)
isign = -1
for c in Chrons:
off = -.1
isign = -1 * isign
if isign > 0:
off = 1.05
if c[1] >= X[0] and c[1] < X[-1]:
plt.text(c[1] - .2, off, c[0])
return | plot the geomagnetic polarity time scale
Parameters
__________
fignum : matplotlib figure number
dates : bounding dates for plot
ts : time scale ck95, gts04, or gts12 | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L1877-L1918 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_delta_m | def plot_delta_m(fignum, B, DM, Bcr, s):
"""
function to plot Delta M curves
Parameters
__________
fignum : matplotlib figure number
B : array of field values
DM : array of difference between top and bottom curves in hysteresis loop
Bcr : coercivity of remanence
s : specimen name
"""
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.plot(B, DM, 'b')
plt.xlabel('B (T)')
plt.ylabel('Delta M')
linex = [0, Bcr, Bcr]
liney = [old_div(DM[0], 2.), old_div(DM[0], 2.), 0]
plt.plot(linex, liney, 'r')
plt.title(s) | python | def plot_delta_m(fignum, B, DM, Bcr, s):
"""
function to plot Delta M curves
Parameters
__________
fignum : matplotlib figure number
B : array of field values
DM : array of difference between top and bottom curves in hysteresis loop
Bcr : coercivity of remanence
s : specimen name
"""
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.plot(B, DM, 'b')
plt.xlabel('B (T)')
plt.ylabel('Delta M')
linex = [0, Bcr, Bcr]
liney = [old_div(DM[0], 2.), old_div(DM[0], 2.), 0]
plt.plot(linex, liney, 'r')
plt.title(s) | function to plot Delta M curves
Parameters
__________
fignum : matplotlib figure number
B : array of field values
DM : array of difference between top and bottom curves in hysteresis loop
Bcr : coercivity of remanence
s : specimen name | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2045-L2067 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_d_delta_m | def plot_d_delta_m(fignum, Bdm, DdeltaM, s):
"""
function to plot d (Delta M)/dB curves
Parameters
__________
fignum : matplotlib figure number
Bdm : change in field
Ddelta M : change in delta M
s : specimen name
"""
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
start = len(Bdm) - len(DdeltaM)
plt.plot(Bdm[start:], DdeltaM, 'b')
plt.xlabel('B (T)')
plt.ylabel('d (Delta M)/dB')
plt.title(s) | python | def plot_d_delta_m(fignum, Bdm, DdeltaM, s):
"""
function to plot d (Delta M)/dB curves
Parameters
__________
fignum : matplotlib figure number
Bdm : change in field
Ddelta M : change in delta M
s : specimen name
"""
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
start = len(Bdm) - len(DdeltaM)
plt.plot(Bdm[start:], DdeltaM, 'b')
plt.xlabel('B (T)')
plt.ylabel('d (Delta M)/dB')
plt.title(s) | function to plot d (Delta M)/dB curves
Parameters
__________
fignum : matplotlib figure number
Bdm : change in field
Ddelta M : change in delta M
s : specimen name | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2071-L2090 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_imag | def plot_imag(fignum, Bimag, Mimag, s):
"""
function to plot d (Delta M)/dB curves
"""
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.plot(Bimag, Mimag, 'r')
plt.xlabel('B (T)')
plt.ylabel('M/Ms')
plt.axvline(0, color='k')
plt.title(s) | python | def plot_imag(fignum, Bimag, Mimag, s):
"""
function to plot d (Delta M)/dB curves
"""
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.plot(Bimag, Mimag, 'r')
plt.xlabel('B (T)')
plt.ylabel('M/Ms')
plt.axvline(0, color='k')
plt.title(s) | function to plot d (Delta M)/dB curves | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2094-L2106 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_hdd | def plot_hdd(HDD, B, M, s):
"""
Function to make hysteresis, deltaM and DdeltaM plots
Parameters:
_______________
Input
HDD : dictionary with figure numbers for the keys:
'hyst' : hysteresis plot normalized to maximum value
'deltaM' : Delta M plot
'DdeltaM' : differential of Delta M plot
B : list of field values in tesla
M : list of magnetizations in arbitrary units
s : specimen name string
Ouput
hpars : dictionary of hysteresis parameters with keys:
'hysteresis_xhf', 'hysteresis_ms_moment', 'hysteresis_mr_moment', 'hysteresis_bc'
"""
hpars, deltaM, Bdm = plot_hys(
HDD['hyst'], B, M, s) # Moff is the "fixed" loop data
DdeltaM = []
Mhalf = ""
for k in range(2, len(Bdm)):
# differnential
DdeltaM.append(
old_div(abs(deltaM[k] - deltaM[k - 2]), (Bdm[k] - Bdm[k - 2])))
for k in range(len(deltaM)):
if old_div(deltaM[k], deltaM[0]) < 0.5:
Mhalf = k
break
try:
Bhf = Bdm[Mhalf - 1:Mhalf + 1]
Mhf = deltaM[Mhalf - 1:Mhalf + 1]
# best fit line through two bounding points
poly = np.polyfit(Bhf, Mhf, 1)
Bcr = old_div((.5 * deltaM[0] - poly[1]), poly[0])
hpars['hysteresis_bcr'] = '%8.3e' % (Bcr)
hpars['magic_method_codes'] = "LP-BCR-HDM"
if HDD['deltaM'] != 0:
plot_delta_m(HDD['deltaM'], Bdm, deltaM, Bcr, s)
plt.axhline(0, color='k')
plt.axvline(0, color='k')
plot_d_delta_m(HDD['DdeltaM'], Bdm, DdeltaM, s)
except:
hpars['hysteresis_bcr'] = '0'
hpars['magic_method_codes'] = ""
return hpars | python | def plot_hdd(HDD, B, M, s):
"""
Function to make hysteresis, deltaM and DdeltaM plots
Parameters:
_______________
Input
HDD : dictionary with figure numbers for the keys:
'hyst' : hysteresis plot normalized to maximum value
'deltaM' : Delta M plot
'DdeltaM' : differential of Delta M plot
B : list of field values in tesla
M : list of magnetizations in arbitrary units
s : specimen name string
Ouput
hpars : dictionary of hysteresis parameters with keys:
'hysteresis_xhf', 'hysteresis_ms_moment', 'hysteresis_mr_moment', 'hysteresis_bc'
"""
hpars, deltaM, Bdm = plot_hys(
HDD['hyst'], B, M, s) # Moff is the "fixed" loop data
DdeltaM = []
Mhalf = ""
for k in range(2, len(Bdm)):
# differnential
DdeltaM.append(
old_div(abs(deltaM[k] - deltaM[k - 2]), (Bdm[k] - Bdm[k - 2])))
for k in range(len(deltaM)):
if old_div(deltaM[k], deltaM[0]) < 0.5:
Mhalf = k
break
try:
Bhf = Bdm[Mhalf - 1:Mhalf + 1]
Mhf = deltaM[Mhalf - 1:Mhalf + 1]
# best fit line through two bounding points
poly = np.polyfit(Bhf, Mhf, 1)
Bcr = old_div((.5 * deltaM[0] - poly[1]), poly[0])
hpars['hysteresis_bcr'] = '%8.3e' % (Bcr)
hpars['magic_method_codes'] = "LP-BCR-HDM"
if HDD['deltaM'] != 0:
plot_delta_m(HDD['deltaM'], Bdm, deltaM, Bcr, s)
plt.axhline(0, color='k')
plt.axvline(0, color='k')
plot_d_delta_m(HDD['DdeltaM'], Bdm, DdeltaM, s)
except:
hpars['hysteresis_bcr'] = '0'
hpars['magic_method_codes'] = ""
return hpars | Function to make hysteresis, deltaM and DdeltaM plots
Parameters:
_______________
Input
HDD : dictionary with figure numbers for the keys:
'hyst' : hysteresis plot normalized to maximum value
'deltaM' : Delta M plot
'DdeltaM' : differential of Delta M plot
B : list of field values in tesla
M : list of magnetizations in arbitrary units
s : specimen name string
Ouput
hpars : dictionary of hysteresis parameters with keys:
'hysteresis_xhf', 'hysteresis_ms_moment', 'hysteresis_mr_moment', 'hysteresis_bc' | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2110-L2156 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_day | def plot_day(fignum, BcrBc, S, sym, **kwargs):
"""
function to plot Day plots
Parameters
_________
fignum : matplotlib figure number
BcrBc : list or array ratio of coercivity of remenance to coercivity
S : list or array ratio of saturation remanence to saturation magnetization (squareness)
sym : matplotlib symbol (e.g., 'rs' for red squares)
**kwargs : dictionary with {'names':[list of names for symbols]}
"""
plt.figure(num=fignum)
plt.plot(BcrBc, S, sym)
plt.axhline(0, color='k')
plt.axhline(.05, color='k')
plt.axhline(.5, color='k')
plt.axvline(1, color='k')
plt.axvline(4, color='k')
plt.xlabel('Bcr/Bc')
plt.ylabel('Mr/Ms')
plt.title('Day Plot')
plt.xlim(0, 6)
#bounds= plt.axis()
#plt.axis([0, bounds[1],0, 1])
mu_o = 4. * np.pi * 1e-7
Bc_sd = 46e-3 # (MV1H) dunlop and carter-stiglitz 2006 (in T)
Bc_md = 5.56e-3 # (041183) dunlop and carter-stiglitz 2006 (in T)
chi_sd = 5.20e6 * mu_o # now in T
chi_md = 4.14e6 * mu_o # now in T
chi_r_sd = 4.55e6 * mu_o # now in T
chi_r_md = 0.88e6 * mu_o # now in T
Bcr_sd, Bcr_md = 52.5e-3, 26.1e-3 # (MV1H and 041183 in DC06 in tesla)
Ms = 480e3 # A/m
p = .1 # from Dunlop 2002
N = old_div(1., 3.) # demagnetizing factor
f_sd = np.arange(1., 0., -.01) # fraction of sd
f_md = 1. - f_sd # fraction of md
f_sp = 1. - f_sd # fraction of sp
# Mr/Ms ratios for USD,MD and Jax shaped
sdrat, mdrat, cbrat = 0.498, 0.048, 0.6
Mrat = f_sd * sdrat + f_md * mdrat # linear mixing - eq. 9 in Dunlop 2002
Bc = old_div((f_sd * chi_sd * Bc_sd + f_md * chi_md * Bc_md),
(f_sd * chi_sd + f_md * chi_md)) # eq. 10 in Dunlop 2002
Bcr = old_div((f_sd * chi_r_sd * Bcr_sd + f_md * chi_r_md * Bcr_md),
(f_sd * chi_r_sd + f_md * chi_r_md)) # eq. 11 in Dunlop 2002
chi_sps = np.arange(1, 5) * chi_sd
plt.plot(old_div(Bcr, Bc), Mrat, 'r-')
if 'names' in list(kwargs.keys()):
names = kwargs['names']
for k in range(len(names)):
plt.text(BcrBc[k], S[k], names[k]) | python | def plot_day(fignum, BcrBc, S, sym, **kwargs):
"""
function to plot Day plots
Parameters
_________
fignum : matplotlib figure number
BcrBc : list or array ratio of coercivity of remenance to coercivity
S : list or array ratio of saturation remanence to saturation magnetization (squareness)
sym : matplotlib symbol (e.g., 'rs' for red squares)
**kwargs : dictionary with {'names':[list of names for symbols]}
"""
plt.figure(num=fignum)
plt.plot(BcrBc, S, sym)
plt.axhline(0, color='k')
plt.axhline(.05, color='k')
plt.axhline(.5, color='k')
plt.axvline(1, color='k')
plt.axvline(4, color='k')
plt.xlabel('Bcr/Bc')
plt.ylabel('Mr/Ms')
plt.title('Day Plot')
plt.xlim(0, 6)
#bounds= plt.axis()
#plt.axis([0, bounds[1],0, 1])
mu_o = 4. * np.pi * 1e-7
Bc_sd = 46e-3 # (MV1H) dunlop and carter-stiglitz 2006 (in T)
Bc_md = 5.56e-3 # (041183) dunlop and carter-stiglitz 2006 (in T)
chi_sd = 5.20e6 * mu_o # now in T
chi_md = 4.14e6 * mu_o # now in T
chi_r_sd = 4.55e6 * mu_o # now in T
chi_r_md = 0.88e6 * mu_o # now in T
Bcr_sd, Bcr_md = 52.5e-3, 26.1e-3 # (MV1H and 041183 in DC06 in tesla)
Ms = 480e3 # A/m
p = .1 # from Dunlop 2002
N = old_div(1., 3.) # demagnetizing factor
f_sd = np.arange(1., 0., -.01) # fraction of sd
f_md = 1. - f_sd # fraction of md
f_sp = 1. - f_sd # fraction of sp
# Mr/Ms ratios for USD,MD and Jax shaped
sdrat, mdrat, cbrat = 0.498, 0.048, 0.6
Mrat = f_sd * sdrat + f_md * mdrat # linear mixing - eq. 9 in Dunlop 2002
Bc = old_div((f_sd * chi_sd * Bc_sd + f_md * chi_md * Bc_md),
(f_sd * chi_sd + f_md * chi_md)) # eq. 10 in Dunlop 2002
Bcr = old_div((f_sd * chi_r_sd * Bcr_sd + f_md * chi_r_md * Bcr_md),
(f_sd * chi_r_sd + f_md * chi_r_md)) # eq. 11 in Dunlop 2002
chi_sps = np.arange(1, 5) * chi_sd
plt.plot(old_div(Bcr, Bc), Mrat, 'r-')
if 'names' in list(kwargs.keys()):
names = kwargs['names']
for k in range(len(names)):
plt.text(BcrBc[k], S[k], names[k]) | function to plot Day plots
Parameters
_________
fignum : matplotlib figure number
BcrBc : list or array ratio of coercivity of remenance to coercivity
S : list or array ratio of saturation remanence to saturation magnetization (squareness)
sym : matplotlib symbol (e.g., 'rs' for red squares)
**kwargs : dictionary with {'names':[list of names for symbols]} | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2160-L2211 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_s_bc | def plot_s_bc(fignum, Bc, S, sym):
"""
function to plot Squareness,Coercivity
Parameters
__________
fignum : matplotlib figure number
Bc : list or array coercivity values
S : list or array of ratio of saturation remanence to saturation
sym : matplotlib symbol (e.g., 'g^' for green triangles)
"""
plt.figure(num=fignum)
plt.plot(Bc, S, sym)
plt.xlabel('Bc')
plt.ylabel('Mr/Ms')
plt.title('Squareness-Coercivity Plot')
bounds = plt.axis()
plt.axis([0, bounds[1], 0, 1]) | python | def plot_s_bc(fignum, Bc, S, sym):
"""
function to plot Squareness,Coercivity
Parameters
__________
fignum : matplotlib figure number
Bc : list or array coercivity values
S : list or array of ratio of saturation remanence to saturation
sym : matplotlib symbol (e.g., 'g^' for green triangles)
"""
plt.figure(num=fignum)
plt.plot(Bc, S, sym)
plt.xlabel('Bc')
plt.ylabel('Mr/Ms')
plt.title('Squareness-Coercivity Plot')
bounds = plt.axis()
plt.axis([0, bounds[1], 0, 1]) | function to plot Squareness,Coercivity
Parameters
__________
fignum : matplotlib figure number
Bc : list or array coercivity values
S : list or array of ratio of saturation remanence to saturation
sym : matplotlib symbol (e.g., 'g^' for green triangles) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2215-L2232 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_s_bcr | def plot_s_bcr(fignum, Bcr, S, sym):
"""
function to plot Squareness,Coercivity of remanence
Parameters
__________
fignum : matplotlib figure number
Bcr : list or array coercivity of remenence values
S : list or array of ratio of saturation remanence to saturation
sym : matplotlib symbol (e.g., 'g^' for green triangles)
"""
plt.figure(num=fignum)
plt.plot(Bcr, S, sym)
plt.xlabel('Bcr')
plt.ylabel('Mr/Ms')
plt.title('Squareness-Bcr Plot')
bounds = plt.axis()
plt.axis([0, bounds[1], 0, 1]) | python | def plot_s_bcr(fignum, Bcr, S, sym):
"""
function to plot Squareness,Coercivity of remanence
Parameters
__________
fignum : matplotlib figure number
Bcr : list or array coercivity of remenence values
S : list or array of ratio of saturation remanence to saturation
sym : matplotlib symbol (e.g., 'g^' for green triangles)
"""
plt.figure(num=fignum)
plt.plot(Bcr, S, sym)
plt.xlabel('Bcr')
plt.ylabel('Mr/Ms')
plt.title('Squareness-Bcr Plot')
bounds = plt.axis()
plt.axis([0, bounds[1], 0, 1]) | function to plot Squareness,Coercivity of remanence
Parameters
__________
fignum : matplotlib figure number
Bcr : list or array coercivity of remenence values
S : list or array of ratio of saturation remanence to saturation
sym : matplotlib symbol (e.g., 'g^' for green triangles) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2236-L2253 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_bcr | def plot_bcr(fignum, Bcr1, Bcr2):
"""
function to plot two estimates of Bcr against each other
"""
plt.figure(num=fignum)
plt.plot(Bcr1, Bcr2, 'ro')
plt.xlabel('Bcr1')
plt.ylabel('Bcr2')
plt.title('Compare coercivity of remanence') | python | def plot_bcr(fignum, Bcr1, Bcr2):
"""
function to plot two estimates of Bcr against each other
"""
plt.figure(num=fignum)
plt.plot(Bcr1, Bcr2, 'ro')
plt.xlabel('Bcr1')
plt.ylabel('Bcr2')
plt.title('Compare coercivity of remanence') | function to plot two estimates of Bcr against each other | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2257-L2265 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_hpars | def plot_hpars(HDD, hpars, sym):
"""
function to plot hysteresis parameters
deprecated (used in hysteresis_magic)
"""
plt.figure(num=HDD['hyst'])
X, Y = [], []
X.append(0)
Y.append(old_div(float(hpars['hysteresis_mr_moment']), float(
hpars['hysteresis_ms_moment'])))
X.append(float(hpars['hysteresis_bc']))
Y.append(0)
plt.plot(X, Y, sym)
bounds = plt.axis()
n4 = 'Ms: ' + '%8.2e' % (float(hpars['hysteresis_ms_moment'])) + ' Am^2'
plt.text(bounds[1] - .9 * bounds[1], -.9, n4)
n1 = 'Mr: ' + '%8.2e' % (float(hpars['hysteresis_mr_moment'])) + ' Am^2'
plt.text(bounds[1] - .9 * bounds[1], -.7, n1)
n2 = 'Bc: ' + '%8.2e' % (float(hpars['hysteresis_bc'])) + ' T'
plt.text(bounds[1] - .9 * bounds[1], -.5, n2)
if 'hysteresis_xhf' in list(hpars.keys()):
n3 = r'Xhf: ' + '%8.2e' % (float(hpars['hysteresis_xhf'])) + ' m^3'
plt.text(bounds[1] - .9 * bounds[1], -.3, n3)
plt.figure(num=HDD['deltaM'])
X, Y, Bcr = [], [], ""
if 'hysteresis_bcr' in list(hpars.keys()):
X.append(float(hpars['hysteresis_bcr']))
Y.append(0)
Bcr = float(hpars['hysteresis_bcr'])
plt.plot(X, Y, sym)
bounds = plt.axis()
if Bcr != "":
n1 = 'Bcr: ' + '%8.2e' % (Bcr) + ' T'
plt.text(bounds[1] - .5 * bounds[1], .9 * bounds[3], n1) | python | def plot_hpars(HDD, hpars, sym):
"""
function to plot hysteresis parameters
deprecated (used in hysteresis_magic)
"""
plt.figure(num=HDD['hyst'])
X, Y = [], []
X.append(0)
Y.append(old_div(float(hpars['hysteresis_mr_moment']), float(
hpars['hysteresis_ms_moment'])))
X.append(float(hpars['hysteresis_bc']))
Y.append(0)
plt.plot(X, Y, sym)
bounds = plt.axis()
n4 = 'Ms: ' + '%8.2e' % (float(hpars['hysteresis_ms_moment'])) + ' Am^2'
plt.text(bounds[1] - .9 * bounds[1], -.9, n4)
n1 = 'Mr: ' + '%8.2e' % (float(hpars['hysteresis_mr_moment'])) + ' Am^2'
plt.text(bounds[1] - .9 * bounds[1], -.7, n1)
n2 = 'Bc: ' + '%8.2e' % (float(hpars['hysteresis_bc'])) + ' T'
plt.text(bounds[1] - .9 * bounds[1], -.5, n2)
if 'hysteresis_xhf' in list(hpars.keys()):
n3 = r'Xhf: ' + '%8.2e' % (float(hpars['hysteresis_xhf'])) + ' m^3'
plt.text(bounds[1] - .9 * bounds[1], -.3, n3)
plt.figure(num=HDD['deltaM'])
X, Y, Bcr = [], [], ""
if 'hysteresis_bcr' in list(hpars.keys()):
X.append(float(hpars['hysteresis_bcr']))
Y.append(0)
Bcr = float(hpars['hysteresis_bcr'])
plt.plot(X, Y, sym)
bounds = plt.axis()
if Bcr != "":
n1 = 'Bcr: ' + '%8.2e' % (Bcr) + ' T'
plt.text(bounds[1] - .5 * bounds[1], .9 * bounds[3], n1) | function to plot hysteresis parameters
deprecated (used in hysteresis_magic) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2268-L2301 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_irm | def plot_irm(fignum, B, M, title):
"""
function to plot IRM backfield curves
Parameters
_________
fignum : matplotlib figure number
B : list or array of field values
M : list or array of magnetizations
title : string title for plot
"""
rpars = {}
Mnorm = []
backfield = 0
X, Y = [], []
for k in range(len(B)):
if M[k] < 0:
break
if k <= 5:
kmin = 0
else:
kmin = k - 5
for k in range(kmin, k + 1):
X.append(B[k])
if B[k] < 0:
backfield = 1
Y.append(M[k])
if backfield == 1:
poly = np.polyfit(X, Y, 1)
if poly[0] != 0:
bcr = (old_div(-poly[1], poly[0]))
else:
bcr = 0
rpars['remanence_mr_moment'] = '%8.3e' % (M[0])
rpars['remanence_bcr'] = '%8.3e' % (-bcr)
rpars['magic_method_codes'] = 'LP-BCR-BF'
if M[0] != 0:
for m in M:
Mnorm.append(old_div(m, M[0])) # normalize to unity Msat
title = title + ':' + '%8.3e' % (M[0])
else:
if M[-1] != 0:
for m in M:
Mnorm.append(old_div(m, M[-1])) # normalize to unity Msat
title = title + ':' + '%8.3e' % (M[-1])
# do plots if desired
if fignum != 0 and M[0] != 0: # skip plot for fignum = 0
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.plot(B, Mnorm)
plt.axhline(0, color='k')
plt.axvline(0, color='k')
plt.xlabel('B (T)')
plt.ylabel('M/Mr')
plt.title(title)
if backfield == 1:
plt.scatter([bcr], [0], marker='s', c='b')
bounds = plt.axis()
n1 = 'Bcr: ' + '%8.2e' % (-bcr) + ' T'
plt.figtext(.2, .5, n1)
n2 = 'Mr: ' + '%8.2e' % (M[0]) + ' Am^2'
plt.figtext(.2, .45, n2)
elif fignum != 0:
plt.figure(num=fignum)
# plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
print('M[0]=0, skipping specimen')
return rpars | python | def plot_irm(fignum, B, M, title):
"""
function to plot IRM backfield curves
Parameters
_________
fignum : matplotlib figure number
B : list or array of field values
M : list or array of magnetizations
title : string title for plot
"""
rpars = {}
Mnorm = []
backfield = 0
X, Y = [], []
for k in range(len(B)):
if M[k] < 0:
break
if k <= 5:
kmin = 0
else:
kmin = k - 5
for k in range(kmin, k + 1):
X.append(B[k])
if B[k] < 0:
backfield = 1
Y.append(M[k])
if backfield == 1:
poly = np.polyfit(X, Y, 1)
if poly[0] != 0:
bcr = (old_div(-poly[1], poly[0]))
else:
bcr = 0
rpars['remanence_mr_moment'] = '%8.3e' % (M[0])
rpars['remanence_bcr'] = '%8.3e' % (-bcr)
rpars['magic_method_codes'] = 'LP-BCR-BF'
if M[0] != 0:
for m in M:
Mnorm.append(old_div(m, M[0])) # normalize to unity Msat
title = title + ':' + '%8.3e' % (M[0])
else:
if M[-1] != 0:
for m in M:
Mnorm.append(old_div(m, M[-1])) # normalize to unity Msat
title = title + ':' + '%8.3e' % (M[-1])
# do plots if desired
if fignum != 0 and M[0] != 0: # skip plot for fignum = 0
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.plot(B, Mnorm)
plt.axhline(0, color='k')
plt.axvline(0, color='k')
plt.xlabel('B (T)')
plt.ylabel('M/Mr')
plt.title(title)
if backfield == 1:
plt.scatter([bcr], [0], marker='s', c='b')
bounds = plt.axis()
n1 = 'Bcr: ' + '%8.2e' % (-bcr) + ' T'
plt.figtext(.2, .5, n1)
n2 = 'Mr: ' + '%8.2e' % (M[0]) + ' Am^2'
plt.figtext(.2, .45, n2)
elif fignum != 0:
plt.figure(num=fignum)
# plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
print('M[0]=0, skipping specimen')
return rpars | function to plot IRM backfield curves
Parameters
_________
fignum : matplotlib figure number
B : list or array of field values
M : list or array of magnetizations
title : string title for plot | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2305-L2375 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_xtf | def plot_xtf(fignum, XTF, Fs, e, b):
"""
function to plot series of chi measurements as a function of temperature, holding field constant and varying frequency
"""
plt.figure(num=fignum)
plt.xlabel('Temperature (K)')
plt.ylabel('Susceptibility (m^3/kg)')
k = 0
Flab = []
for freq in XTF:
T, X = [], []
for xt in freq:
X.append(xt[0])
T.append(xt[1])
plt.plot(T, X)
plt.text(T[-1], X[-1], str(int(Fs[k])) + ' Hz')
# Flab.append(str(int(Fs[k]))+' Hz')
k += 1
plt.title(e + ': B = ' + '%8.1e' % (b) + ' T') | python | def plot_xtf(fignum, XTF, Fs, e, b):
"""
function to plot series of chi measurements as a function of temperature, holding field constant and varying frequency
"""
plt.figure(num=fignum)
plt.xlabel('Temperature (K)')
plt.ylabel('Susceptibility (m^3/kg)')
k = 0
Flab = []
for freq in XTF:
T, X = [], []
for xt in freq:
X.append(xt[0])
T.append(xt[1])
plt.plot(T, X)
plt.text(T[-1], X[-1], str(int(Fs[k])) + ' Hz')
# Flab.append(str(int(Fs[k]))+' Hz')
k += 1
plt.title(e + ': B = ' + '%8.1e' % (b) + ' T') | function to plot series of chi measurements as a function of temperature, holding field constant and varying frequency | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2378-L2396 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_xtb | def plot_xtb(fignum, XTB, Bs, e, f):
""" function to plot series of chi measurements as a function of temperature, holding frequency constant and varying B
"""
plt.figure(num=fignum)
plt.xlabel('Temperature (K)')
plt.ylabel('Susceptibility (m^3/kg)')
k = 0
Blab = []
for field in XTB:
T, X = [], []
for xt in field:
X.append(xt[0])
T.append(xt[1])
plt.plot(T, X)
plt.text(T[-1], X[-1], '%8.2e' % (Bs[k]) + ' T')
# Blab.append('%8.1e'%(Bs[k])+' T')
k += 1
plt.title(e + ': f = ' + '%i' % (int(f)) + ' Hz') | python | def plot_xtb(fignum, XTB, Bs, e, f):
""" function to plot series of chi measurements as a function of temperature, holding frequency constant and varying B
"""
plt.figure(num=fignum)
plt.xlabel('Temperature (K)')
plt.ylabel('Susceptibility (m^3/kg)')
k = 0
Blab = []
for field in XTB:
T, X = [], []
for xt in field:
X.append(xt[0])
T.append(xt[1])
plt.plot(T, X)
plt.text(T[-1], X[-1], '%8.2e' % (Bs[k]) + ' T')
# Blab.append('%8.1e'%(Bs[k])+' T')
k += 1
plt.title(e + ': f = ' + '%i' % (int(f)) + ' Hz') | function to plot series of chi measurements as a function of temperature, holding frequency constant and varying B | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2401-L2418 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_xft | def plot_xft(fignum, XF, T, e, b):
""" function to plot series of chi measurements as a function of temperature, holding field constant and varying frequency
"""
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.xlabel('Frequency (Hz)')
plt.ylabel('Susceptibility (m^3/kg)')
k = 0
F, X = [], []
for xf in XF:
X.append(xf[0])
F.append(xf[1])
plt.plot(F, X)
plt.semilogx()
plt.title(e + ': B = ' + '%8.1e' % (b) + ' T')
plt.legend(['%i' % (int(T)) + ' K']) | python | def plot_xft(fignum, XF, T, e, b):
""" function to plot series of chi measurements as a function of temperature, holding field constant and varying frequency
"""
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.xlabel('Frequency (Hz)')
plt.ylabel('Susceptibility (m^3/kg)')
k = 0
F, X = [], []
for xf in XF:
X.append(xf[0])
F.append(xf[1])
plt.plot(F, X)
plt.semilogx()
plt.title(e + ': B = ' + '%8.1e' % (b) + ' T')
plt.legend(['%i' % (int(T)) + ' K']) | function to plot series of chi measurements as a function of temperature, holding field constant and varying frequency | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2423-L2441 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_xbt | def plot_xbt(fignum, XB, T, e, b):
""" function to plot series of chi measurements as a function of temperature, holding field constant and varying frequency
"""
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.xlabel('Field (T)')
plt.ylabel('Susceptibility (m^3/kg)')
k = 0
B, X = [], []
for xb in XB:
X.append(xb[0])
B.append(xb[1])
plt.plot(B, X)
plt.legend(['%i' % (int(T)) + ' K'])
plt.title(e + ': f = ' + '%i' % (int(f)) + ' Hz') | python | def plot_xbt(fignum, XB, T, e, b):
""" function to plot series of chi measurements as a function of temperature, holding field constant and varying frequency
"""
plt.figure(num=fignum)
plt.clf()
if not isServer:
plt.figtext(.02, .01, version_num)
plt.xlabel('Field (T)')
plt.ylabel('Susceptibility (m^3/kg)')
k = 0
B, X = [], []
for xb in XB:
X.append(xb[0])
B.append(xb[1])
plt.plot(B, X)
plt.legend(['%i' % (int(T)) + ' K'])
plt.title(e + ': f = ' + '%i' % (int(f)) + ' Hz') | function to plot series of chi measurements as a function of temperature, holding field constant and varying frequency | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2445-L2461 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_ltc | def plot_ltc(LTC_CM, LTC_CT, LTC_WM, LTC_WT, e):
"""
function to plot low temperature cycling experiments
"""
leglist, init = [], 0
if len(LTC_CM) > 2:
if init == 0:
plot_init(1, 5, 5)
plt.plot(LTC_CT, LTC_CM, 'b')
leglist.append('RT SIRM, measured while cooling')
init = 1
if len(LTC_WM) > 2:
if init == 0:
plot_init(1, 5, 5)
plt.plot(LTC_WT, LTC_WM, 'r')
leglist.append('RT SIRM, measured while warming')
if init != 0:
plt.legend(leglist, 'lower left')
plt.xlabel('Temperature (K)')
plt.ylabel('Magnetization (Am^2/kg)')
if len(LTC_CM) > 2:
plt.plot(LTC_CT, LTC_CM, 'bo')
if len(LTC_WM) > 2:
plt.plot(LTC_WT, LTC_WM, 'ro')
plt.title(e) | python | def plot_ltc(LTC_CM, LTC_CT, LTC_WM, LTC_WT, e):
"""
function to plot low temperature cycling experiments
"""
leglist, init = [], 0
if len(LTC_CM) > 2:
if init == 0:
plot_init(1, 5, 5)
plt.plot(LTC_CT, LTC_CM, 'b')
leglist.append('RT SIRM, measured while cooling')
init = 1
if len(LTC_WM) > 2:
if init == 0:
plot_init(1, 5, 5)
plt.plot(LTC_WT, LTC_WM, 'r')
leglist.append('RT SIRM, measured while warming')
if init != 0:
plt.legend(leglist, 'lower left')
plt.xlabel('Temperature (K)')
plt.ylabel('Magnetization (Am^2/kg)')
if len(LTC_CM) > 2:
plt.plot(LTC_CT, LTC_CM, 'bo')
if len(LTC_WM) > 2:
plt.plot(LTC_WT, LTC_WM, 'ro')
plt.title(e) | function to plot low temperature cycling experiments | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2465-L2489 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_conf | def plot_conf(fignum, s, datablock, pars, new):
"""
plots directions and confidence ellipses
"""
# make the stereonet
if new == 1:
plot_net(fignum)
#
# plot the data
#
DIblock = []
for plotrec in datablock:
DIblock.append((float(plotrec["dec"]), float(plotrec["inc"])))
if len(DIblock) > 0:
plot_di(fignum, DIblock) # plot directed lines
#
# put on the mean direction
#
x, y = [], []
XY = pmag.dimap(float(pars[0]), float(pars[1]))
x.append(XY[0])
y.append(XY[1])
plt.figure(num=fignum)
if new == 1:
plt.scatter(x, y, marker='d', s=80, c='r')
else:
if float(pars[1] > 0):
plt.scatter(x, y, marker='^', s=100, c='r')
else:
plt.scatter(x, y, marker='^', s=100, c='y')
plt.title(s)
#
# plot the ellipse
#
plot_ell(fignum, pars, 'r-,', 0, 1) | python | def plot_conf(fignum, s, datablock, pars, new):
"""
plots directions and confidence ellipses
"""
# make the stereonet
if new == 1:
plot_net(fignum)
#
# plot the data
#
DIblock = []
for plotrec in datablock:
DIblock.append((float(plotrec["dec"]), float(plotrec["inc"])))
if len(DIblock) > 0:
plot_di(fignum, DIblock) # plot directed lines
#
# put on the mean direction
#
x, y = [], []
XY = pmag.dimap(float(pars[0]), float(pars[1]))
x.append(XY[0])
y.append(XY[1])
plt.figure(num=fignum)
if new == 1:
plt.scatter(x, y, marker='d', s=80, c='r')
else:
if float(pars[1] > 0):
plt.scatter(x, y, marker='^', s=100, c='r')
else:
plt.scatter(x, y, marker='^', s=100, c='y')
plt.title(s)
#
# plot the ellipse
#
plot_ell(fignum, pars, 'r-,', 0, 1) | plots directions and confidence ellipses | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2742-L2776 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | add_borders | def add_borders(Figs, titles, border_color='#000000', text_color='#800080', con_id=""):
"""
Formatting for generating plots on the server
Default border color: black
Default text color: purple
"""
def split_title(s):
"""
Add '\n's to split of overly long titles
"""
s_list = s.split(",")
lines = []
tot = 0
line = []
for i in s_list:
tot += len(i)
if tot < 30:
line.append(i + ",")
else:
lines.append(" ".join(line))
line = [i]
tot = 0
lines.append(" ".join(line))
return "\n".join(lines).strip(',')
# format contribution id if available
if con_id:
if not str(con_id).startswith("/"):
con_id = "/" + str(con_id)
import datetime
now = datetime.datetime.utcnow()
for key in list(Figs.keys()):
fig = plt.figure(Figs[key])
plot_title = split_title(titles[key]).strip().strip('\n')
fig.set_figheight(5.5)
#get returns Bbox with x0, y0, x1, y1
pos = fig.gca().get_position()
# tweak some of the default values
w = pos.x1 - pos.x0
h = (pos.y1 - pos.y0) / 1.1
x = pos.x0
y = pos.y0 * 1.3
# set takes: left, bottom, width, height
fig.gca().set_position([x, y, w, h])
# add an axis covering the entire figure
border_ax = fig.add_axes([0, 0, 1, 1])
border_ax.set_frame_on(False)
border_ax.set_xticks([])
border_ax.set_yticks([])
# add a border
if "\n" in plot_title:
y_val = 1.0 # lower border
#fig.set_figheight(6.25)
else:
y_val = 1.04 # higher border
#border_ax.text(-0.02, y_val, " # |",
# horizontalalignment='left',
# verticalalignment='top',
# color=text_color,
# bbox=dict(edgecolor=border_color,
# facecolor='#FFFFFF', linewidth=0.25),
# size=50)
#border_ax.text(-0.02, 0, "| # |",
# horizontalalignment='left',
# verticalalignment='bottom',
# color=text_color,
# bbox=dict(edgecolor=border_color,
# facecolor='#FFFFFF', linewidth=0.25),
# size=20)#18)
# add text
border_ax.text((4. / fig.get_figwidth()) * 0.015, 0.03, now.strftime("%Y-%m-%d, %I:%M:%S {}".format('UT')),
horizontalalignment='left',
verticalalignment='top',
color=text_color,
size=10)
border_ax.text(0.5, 0.98, plot_title,
horizontalalignment='center',
verticalalignment='top',
color=text_color,
size=20)
border_ax.text(1 - (4. / fig.get_figwidth()) * 0.015, 0.03, 'earthref.org/MagIC{}'.format(con_id),
horizontalalignment='right',
verticalalignment='top',
color=text_color,
size=10)
return Figs | python | def add_borders(Figs, titles, border_color='#000000', text_color='#800080', con_id=""):
"""
Formatting for generating plots on the server
Default border color: black
Default text color: purple
"""
def split_title(s):
"""
Add '\n's to split of overly long titles
"""
s_list = s.split(",")
lines = []
tot = 0
line = []
for i in s_list:
tot += len(i)
if tot < 30:
line.append(i + ",")
else:
lines.append(" ".join(line))
line = [i]
tot = 0
lines.append(" ".join(line))
return "\n".join(lines).strip(',')
# format contribution id if available
if con_id:
if not str(con_id).startswith("/"):
con_id = "/" + str(con_id)
import datetime
now = datetime.datetime.utcnow()
for key in list(Figs.keys()):
fig = plt.figure(Figs[key])
plot_title = split_title(titles[key]).strip().strip('\n')
fig.set_figheight(5.5)
#get returns Bbox with x0, y0, x1, y1
pos = fig.gca().get_position()
# tweak some of the default values
w = pos.x1 - pos.x0
h = (pos.y1 - pos.y0) / 1.1
x = pos.x0
y = pos.y0 * 1.3
# set takes: left, bottom, width, height
fig.gca().set_position([x, y, w, h])
# add an axis covering the entire figure
border_ax = fig.add_axes([0, 0, 1, 1])
border_ax.set_frame_on(False)
border_ax.set_xticks([])
border_ax.set_yticks([])
# add a border
if "\n" in plot_title:
y_val = 1.0 # lower border
#fig.set_figheight(6.25)
else:
y_val = 1.04 # higher border
#border_ax.text(-0.02, y_val, " # |",
# horizontalalignment='left',
# verticalalignment='top',
# color=text_color,
# bbox=dict(edgecolor=border_color,
# facecolor='#FFFFFF', linewidth=0.25),
# size=50)
#border_ax.text(-0.02, 0, "| # |",
# horizontalalignment='left',
# verticalalignment='bottom',
# color=text_color,
# bbox=dict(edgecolor=border_color,
# facecolor='#FFFFFF', linewidth=0.25),
# size=20)#18)
# add text
border_ax.text((4. / fig.get_figwidth()) * 0.015, 0.03, now.strftime("%Y-%m-%d, %I:%M:%S {}".format('UT')),
horizontalalignment='left',
verticalalignment='top',
color=text_color,
size=10)
border_ax.text(0.5, 0.98, plot_title,
horizontalalignment='center',
verticalalignment='top',
color=text_color,
size=20)
border_ax.text(1 - (4. / fig.get_figwidth()) * 0.015, 0.03, 'earthref.org/MagIC{}'.format(con_id),
horizontalalignment='right',
verticalalignment='top',
color=text_color,
size=10)
return Figs | Formatting for generating plots on the server
Default border color: black
Default text color: purple | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2872-L2964 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_map_basemap | def plot_map_basemap(fignum, lats, lons, Opts):
"""
plot_map_basemap(fignum, lats,lons,Opts)
makes a basemap with lats/lons
requires working installation of Basemap
Parameters:
_______________
fignum : matplotlib figure number
lats : array or list of latitudes
lons : array or list of longitudes
Opts : dictionary of plotting options:
Opts.keys=
latmin : minimum latitude for plot
latmax : maximum latitude for plot
lonmin : minimum longitude for plot
lonmax : maximum longitude
lat_0 : central latitude
lon_0 : central longitude
proj : projection [basemap projections, e.g., moll=Mollweide, merc=Mercator, ortho=orthorhombic,
lcc=Lambert Conformal]
sym : matplotlib symbol
symsize : symbol size in pts
edge : markeredgecolor
pltgrid : plot the grid [1,0]
res : resolution [c,l,i,h] for crude, low, intermediate, high
boundinglat : bounding latitude
sym : matplotlib symbol for plotting
symsize : matplotlib symbol size for plotting
names : list of names for lats/lons (if empty, none will be plotted)
pltgrd : if True, put on grid lines
padlat : padding of latitudes
padlon : padding of longitudes
gridspace : grid line spacing
details : dictionary with keys:
coasts : if True, plot coastlines
rivers : if True, plot rivers
states : if True, plot states
countries : if True, plot countries
ocean : if True, plot ocean
fancy : if True, plot etopo 20 grid
NB: etopo must be installed
if Opts keys not set :these are the defaults:
Opts={'latmin':-90,'latmax':90,'lonmin':0,'lonmax':360,'lat_0':0,'lon_0':0,'proj':'moll','sym':'ro,'symsize':5,'pltgrid':1,'res':'c','boundinglat':0.,'padlon':0,'padlat':0,'gridspace':30,'details':all False,'edge':None}
"""
if not has_basemap:
print('-W- Basemap must be installed to run plot_map_basemap')
return
fig = plt.figure(num=fignum)
rgba_land = (255, 255, 150, 255)
rgba_ocean = (200, 250, 255, 255)
ExMer = ['sinus', 'moll', 'lcc']
# draw meridian labels on the bottom [left,right,top,bottom]
mlabels = [0, 0, 0, 1]
plabels = [1, 0, 0, 0] # draw parallel labels on the left
# set default Options
Opts_defaults = {'latmin': -90, 'latmax': 90, 'lonmin': 0, 'lonmax': 360,
'lat_0': 0, 'lon_0': 0, 'proj': 'moll', 'sym': 'ro', 'symsize': 5,
'edge': None, 'pltgrid': 1, 'res': 'c', 'boundinglat': 0.,
'padlon': 0, 'padlat': 0, 'gridspace': 30,
'details': {'fancy': 0, 'coasts': 0, 'rivers': 0, 'states': 0, 'countries': 0, 'ocean': 0}}
for key in Opts_defaults.keys():
if key not in Opts.keys() and key != 'details':
Opts[key] = Opts_defaults[key]
if key == 'details':
if key not in Opts.keys():
Opts[key] = Opts_defaults[key]
for detail_key in Opts_defaults[key].keys():
if detail_key not in Opts[key].keys():
Opts[key][detail_key] = Opts_defaults[key][detail_key]
if Opts['proj'] in ExMer:
mlabels = [0, 0, 0, 0]
if Opts['proj'] not in ExMer:
m = Basemap(projection=Opts['proj'], lat_0=Opts['lat_0'],
lon_0=Opts['lon_0'], resolution=Opts['res'])
plabels = [0, 0, 0, 0]
else:
m = Basemap(llcrnrlon=Opts['lonmin'], llcrnrlat=Opts['latmin'], urcrnrlat=Opts['latmax'], urcrnrlon=Opts['lonmax'],
projection=Opts['proj'], lat_0=Opts['lat_0'], lon_0=Opts['lon_0'], lat_ts=0., resolution=Opts['res'], boundinglat=Opts['boundinglat'])
if 'details' in list(Opts.keys()):
if Opts['details']['fancy'] == 1:
from mpl_toolkits.basemap import basemap_datadir
EDIR = basemap_datadir + "/"
etopo = np.loadtxt(EDIR + 'etopo20data.gz')
elons = np.loadtxt(EDIR + 'etopo20lons.gz')
elats = np.loadtxt(EDIR + 'etopo20lats.gz')
x, y = m(*np.meshgrid(elons, elats))
cs = m.contourf(x, y, etopo, 30, cmap=color_map.jet)
if Opts['details']['coasts'] == 1:
m.drawcoastlines(color='k')
if Opts['details']['rivers'] == 1:
m.drawrivers(color='b')
if Opts['details']['states'] == 1:
m.drawstates(color='r')
if Opts['details']['countries'] == 1:
m.drawcountries(color='g')
if Opts['details']['ocean'] == 1:
try:
m.drawlsmask(land_color=rgba_land,
ocean_color=rgba_ocean, lsmask_lats=None)
except TypeError:
# this is caused by basemap function: _readlsmask
# interacting with numpy
# (a float is provided, numpy wants an int).
# hopefully will be fixed eventually.
pass
if Opts['pltgrid'] == 0.:
circles = np.arange(Opts['latmin'], Opts['latmax'] + 15., 15.)
meridians = np.arange(Opts['lonmin'], Opts['lonmax'] + 30., 30.)
elif Opts['pltgrid'] > 0:
if Opts['proj'] in ExMer or Opts['proj'] == 'lcc':
circles = np.arange(-90, 180. +
Opts['gridspace'], Opts['gridspace'])
meridians = np.arange(0, 360., Opts['gridspace'])
else:
g = Opts['gridspace']
latmin, lonmin = g * \
int(old_div(Opts['latmin'], g)), g * \
int(old_div(Opts['lonmin'], g))
latmax, lonmax = g * \
int(old_div(Opts['latmax'], g)), g * \
int(old_div(Opts['lonmax'], g))
# circles=np.arange(latmin-2.*Opts['padlat'],latmax+2.*Opts['padlat'],Opts['gridspace'])
# meridians=np.arange(lonmin-2.*Opts['padlon'],lonmax+2.*Opts['padlon'],Opts['gridspace'])
meridians = np.arange(0, 360, 30)
circles = np.arange(-90, 90, 30)
if Opts['pltgrid'] >= 0:
# m.drawparallels(circles,color='black',labels=plabels)
# m.drawmeridians(meridians,color='black',labels=mlabels)
# skip the labels - they are ugly
m.drawparallels(circles, color='black')
# skip the labels - they are ugly
m.drawmeridians(meridians, color='black')
m.drawmapboundary()
prn_name, symsize = 0, 5
if 'names' in Opts.keys() and len(Opts['names']) > 0:
names = Opts['names']
if len(names) > 0:
prn_name = 1
#
X, Y, T, k = [], [], [], 0
if 'symsize' in list(Opts.keys()):
symsize = Opts['symsize']
if Opts['sym'][-1] != '-': # just plot points
X, Y = m(lons, lats)
if prn_name == 1:
for pt in range(len(lats)):
T.append(plt.text(X[pt] + 5000, Y[pt] - 5000, names[pt]))
m.plot(X, Y, Opts['sym'], markersize=symsize,
markeredgecolor=Opts['edge'])
else: # for lines, need to separate chunks using lat==100.
chunk = 1
while k < len(lats) - 1:
if lats[k] <= 90: # part of string
x, y = m(lons[k], lats[k])
if x < 1e20:
X.append(x)
if y < 1e20:
Y.append(y) # exclude off the map points
if prn_name == 1:
T.append(plt.text(x + 5000, y - 5000, names[k]))
k += 1
else: # need to skip 100.0s and move to next chunk
# plot previous chunk
m.plot(X, Y, Opts['sym'], markersize=symsize,
markeredgecolor=Opts['edge'])
chunk += 1
while lats[k] > 90. and k < len(lats) - 1:
k += 1 # skip bad points
X, Y, T = [], [], []
if len(X) > 0:
m.plot(X, Y, Opts['sym'], markersize=symsize,
markeredgecolor=Opts['edge']) | python | def plot_map_basemap(fignum, lats, lons, Opts):
"""
plot_map_basemap(fignum, lats,lons,Opts)
makes a basemap with lats/lons
requires working installation of Basemap
Parameters:
_______________
fignum : matplotlib figure number
lats : array or list of latitudes
lons : array or list of longitudes
Opts : dictionary of plotting options:
Opts.keys=
latmin : minimum latitude for plot
latmax : maximum latitude for plot
lonmin : minimum longitude for plot
lonmax : maximum longitude
lat_0 : central latitude
lon_0 : central longitude
proj : projection [basemap projections, e.g., moll=Mollweide, merc=Mercator, ortho=orthorhombic,
lcc=Lambert Conformal]
sym : matplotlib symbol
symsize : symbol size in pts
edge : markeredgecolor
pltgrid : plot the grid [1,0]
res : resolution [c,l,i,h] for crude, low, intermediate, high
boundinglat : bounding latitude
sym : matplotlib symbol for plotting
symsize : matplotlib symbol size for plotting
names : list of names for lats/lons (if empty, none will be plotted)
pltgrd : if True, put on grid lines
padlat : padding of latitudes
padlon : padding of longitudes
gridspace : grid line spacing
details : dictionary with keys:
coasts : if True, plot coastlines
rivers : if True, plot rivers
states : if True, plot states
countries : if True, plot countries
ocean : if True, plot ocean
fancy : if True, plot etopo 20 grid
NB: etopo must be installed
if Opts keys not set :these are the defaults:
Opts={'latmin':-90,'latmax':90,'lonmin':0,'lonmax':360,'lat_0':0,'lon_0':0,'proj':'moll','sym':'ro,'symsize':5,'pltgrid':1,'res':'c','boundinglat':0.,'padlon':0,'padlat':0,'gridspace':30,'details':all False,'edge':None}
"""
if not has_basemap:
print('-W- Basemap must be installed to run plot_map_basemap')
return
fig = plt.figure(num=fignum)
rgba_land = (255, 255, 150, 255)
rgba_ocean = (200, 250, 255, 255)
ExMer = ['sinus', 'moll', 'lcc']
# draw meridian labels on the bottom [left,right,top,bottom]
mlabels = [0, 0, 0, 1]
plabels = [1, 0, 0, 0] # draw parallel labels on the left
# set default Options
Opts_defaults = {'latmin': -90, 'latmax': 90, 'lonmin': 0, 'lonmax': 360,
'lat_0': 0, 'lon_0': 0, 'proj': 'moll', 'sym': 'ro', 'symsize': 5,
'edge': None, 'pltgrid': 1, 'res': 'c', 'boundinglat': 0.,
'padlon': 0, 'padlat': 0, 'gridspace': 30,
'details': {'fancy': 0, 'coasts': 0, 'rivers': 0, 'states': 0, 'countries': 0, 'ocean': 0}}
for key in Opts_defaults.keys():
if key not in Opts.keys() and key != 'details':
Opts[key] = Opts_defaults[key]
if key == 'details':
if key not in Opts.keys():
Opts[key] = Opts_defaults[key]
for detail_key in Opts_defaults[key].keys():
if detail_key not in Opts[key].keys():
Opts[key][detail_key] = Opts_defaults[key][detail_key]
if Opts['proj'] in ExMer:
mlabels = [0, 0, 0, 0]
if Opts['proj'] not in ExMer:
m = Basemap(projection=Opts['proj'], lat_0=Opts['lat_0'],
lon_0=Opts['lon_0'], resolution=Opts['res'])
plabels = [0, 0, 0, 0]
else:
m = Basemap(llcrnrlon=Opts['lonmin'], llcrnrlat=Opts['latmin'], urcrnrlat=Opts['latmax'], urcrnrlon=Opts['lonmax'],
projection=Opts['proj'], lat_0=Opts['lat_0'], lon_0=Opts['lon_0'], lat_ts=0., resolution=Opts['res'], boundinglat=Opts['boundinglat'])
if 'details' in list(Opts.keys()):
if Opts['details']['fancy'] == 1:
from mpl_toolkits.basemap import basemap_datadir
EDIR = basemap_datadir + "/"
etopo = np.loadtxt(EDIR + 'etopo20data.gz')
elons = np.loadtxt(EDIR + 'etopo20lons.gz')
elats = np.loadtxt(EDIR + 'etopo20lats.gz')
x, y = m(*np.meshgrid(elons, elats))
cs = m.contourf(x, y, etopo, 30, cmap=color_map.jet)
if Opts['details']['coasts'] == 1:
m.drawcoastlines(color='k')
if Opts['details']['rivers'] == 1:
m.drawrivers(color='b')
if Opts['details']['states'] == 1:
m.drawstates(color='r')
if Opts['details']['countries'] == 1:
m.drawcountries(color='g')
if Opts['details']['ocean'] == 1:
try:
m.drawlsmask(land_color=rgba_land,
ocean_color=rgba_ocean, lsmask_lats=None)
except TypeError:
# this is caused by basemap function: _readlsmask
# interacting with numpy
# (a float is provided, numpy wants an int).
# hopefully will be fixed eventually.
pass
if Opts['pltgrid'] == 0.:
circles = np.arange(Opts['latmin'], Opts['latmax'] + 15., 15.)
meridians = np.arange(Opts['lonmin'], Opts['lonmax'] + 30., 30.)
elif Opts['pltgrid'] > 0:
if Opts['proj'] in ExMer or Opts['proj'] == 'lcc':
circles = np.arange(-90, 180. +
Opts['gridspace'], Opts['gridspace'])
meridians = np.arange(0, 360., Opts['gridspace'])
else:
g = Opts['gridspace']
latmin, lonmin = g * \
int(old_div(Opts['latmin'], g)), g * \
int(old_div(Opts['lonmin'], g))
latmax, lonmax = g * \
int(old_div(Opts['latmax'], g)), g * \
int(old_div(Opts['lonmax'], g))
# circles=np.arange(latmin-2.*Opts['padlat'],latmax+2.*Opts['padlat'],Opts['gridspace'])
# meridians=np.arange(lonmin-2.*Opts['padlon'],lonmax+2.*Opts['padlon'],Opts['gridspace'])
meridians = np.arange(0, 360, 30)
circles = np.arange(-90, 90, 30)
if Opts['pltgrid'] >= 0:
# m.drawparallels(circles,color='black',labels=plabels)
# m.drawmeridians(meridians,color='black',labels=mlabels)
# skip the labels - they are ugly
m.drawparallels(circles, color='black')
# skip the labels - they are ugly
m.drawmeridians(meridians, color='black')
m.drawmapboundary()
prn_name, symsize = 0, 5
if 'names' in Opts.keys() and len(Opts['names']) > 0:
names = Opts['names']
if len(names) > 0:
prn_name = 1
#
X, Y, T, k = [], [], [], 0
if 'symsize' in list(Opts.keys()):
symsize = Opts['symsize']
if Opts['sym'][-1] != '-': # just plot points
X, Y = m(lons, lats)
if prn_name == 1:
for pt in range(len(lats)):
T.append(plt.text(X[pt] + 5000, Y[pt] - 5000, names[pt]))
m.plot(X, Y, Opts['sym'], markersize=symsize,
markeredgecolor=Opts['edge'])
else: # for lines, need to separate chunks using lat==100.
chunk = 1
while k < len(lats) - 1:
if lats[k] <= 90: # part of string
x, y = m(lons[k], lats[k])
if x < 1e20:
X.append(x)
if y < 1e20:
Y.append(y) # exclude off the map points
if prn_name == 1:
T.append(plt.text(x + 5000, y - 5000, names[k]))
k += 1
else: # need to skip 100.0s and move to next chunk
# plot previous chunk
m.plot(X, Y, Opts['sym'], markersize=symsize,
markeredgecolor=Opts['edge'])
chunk += 1
while lats[k] > 90. and k < len(lats) - 1:
k += 1 # skip bad points
X, Y, T = [], [], []
if len(X) > 0:
m.plot(X, Y, Opts['sym'], markersize=symsize,
markeredgecolor=Opts['edge']) | plot_map_basemap(fignum, lats,lons,Opts)
makes a basemap with lats/lons
requires working installation of Basemap
Parameters:
_______________
fignum : matplotlib figure number
lats : array or list of latitudes
lons : array or list of longitudes
Opts : dictionary of plotting options:
Opts.keys=
latmin : minimum latitude for plot
latmax : maximum latitude for plot
lonmin : minimum longitude for plot
lonmax : maximum longitude
lat_0 : central latitude
lon_0 : central longitude
proj : projection [basemap projections, e.g., moll=Mollweide, merc=Mercator, ortho=orthorhombic,
lcc=Lambert Conformal]
sym : matplotlib symbol
symsize : symbol size in pts
edge : markeredgecolor
pltgrid : plot the grid [1,0]
res : resolution [c,l,i,h] for crude, low, intermediate, high
boundinglat : bounding latitude
sym : matplotlib symbol for plotting
symsize : matplotlib symbol size for plotting
names : list of names for lats/lons (if empty, none will be plotted)
pltgrd : if True, put on grid lines
padlat : padding of latitudes
padlon : padding of longitudes
gridspace : grid line spacing
details : dictionary with keys:
coasts : if True, plot coastlines
rivers : if True, plot rivers
states : if True, plot states
countries : if True, plot countries
ocean : if True, plot ocean
fancy : if True, plot etopo 20 grid
NB: etopo must be installed
if Opts keys not set :these are the defaults:
Opts={'latmin':-90,'latmax':90,'lonmin':0,'lonmax':360,'lat_0':0,'lon_0':0,'proj':'moll','sym':'ro,'symsize':5,'pltgrid':1,'res':'c','boundinglat':0.,'padlon':0,'padlat':0,'gridspace':30,'details':all False,'edge':None} | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L2967-L3140 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_map | def plot_map(fignum, lats, lons, Opts):
"""
makes a cartopy map with lats/lons
Requires installation of cartopy
Parameters:
_______________
fignum : matplotlib figure number
lats : array or list of latitudes
lons : array or list of longitudes
Opts : dictionary of plotting options:
Opts.keys=
proj : projection [supported cartopy projections:
pc = Plate Carree
aea = Albers Equal Area
aeqd = Azimuthal Equidistant
lcc = Lambert Conformal
lcyl = Lambert Cylindrical
merc = Mercator
mill = Miller Cylindrical
moll = Mollweide [default]
ortho = Orthographic
robin = Robinson
sinu = Sinusoidal
stere = Stereographic
tmerc = Transverse Mercator
utm = UTM [set zone and south keys in Opts]
laea = Lambert Azimuthal Equal Area
geos = Geostationary
npstere = North-Polar Stereographic
spstere = South-Polar Stereographic
latmin : minimum latitude for plot
latmax : maximum latitude for plot
lonmin : minimum longitude for plot
lonmax : maximum longitude
lat_0 : central latitude
lon_0 : central longitude
sym : matplotlib symbol
symsize : symbol size in pts
edge : markeredgecolor
cmap : matplotlib color map
res : resolution [c,l,i,h] for low/crude, intermediate, high
boundinglat : bounding latitude
sym : matplotlib symbol for plotting
symsize : matplotlib symbol size for plotting
names : list of names for lats/lons (if empty, none will be plotted)
pltgrd : if True, put on grid lines
padlat : padding of latitudes
padlon : padding of longitudes
gridspace : grid line spacing
global : global projection [default is True]
oceancolor : 'azure'
landcolor : 'bisque' [choose any of the valid color names for matplotlib
see https://matplotlib.org/examples/color/named_colors.html
details : dictionary with keys:
coasts : if True, plot coastlines
rivers : if True, plot rivers
states : if True, plot states
countries : if True, plot countries
ocean : if True, plot ocean
fancy : if True, plot etopo 20 grid
NB: etopo must be installed
if Opts keys not set :these are the defaults:
Opts={'latmin':-90,'latmax':90,'lonmin':0,'lonmax':360,'lat_0':0,'lon_0':0,'proj':'moll','sym':'ro,'symsize':5,'edge':'black','pltgrid':1,'res':'c','boundinglat':0.,'padlon':0,'padlat':0,'gridspace':30,'details':all False,'edge':None,'cmap':'jet','fancy':0,'zone':'','south':False,'oceancolor':'azure','landcolor':'bisque'}
"""
if not has_cartopy:
print('This function requires installation of cartopy')
return
from matplotlib import cm
# draw meridian labels on the bottom [left,right,top,bottom]
mlabels = [0, 0, 0, 1]
plabels = [1, 0, 0, 0] # draw parallel labels on the left
Opts_defaults = {'latmin': -90, 'latmax': 90, 'lonmin': 0, 'lonmax': 360,
'lat_0': 0, 'lon_0': 0, 'proj': 'moll', 'sym': 'ro', 'symsize': 5,
'edge': None, 'pltgrid': 1, 'res': 'c', 'boundinglat': 0.,
'padlon': 0, 'padlat': 0, 'gridspace': 30, 'global': 1, 'cmap': 'jet','oceancolor':'azure','landcolor':'bisque',
'details': {'fancy': 0, 'coasts': 0, 'rivers': 0, 'states': 0, 'countries': 0, 'ocean': 0},
'edgecolor': 'face'}
for key in Opts_defaults.keys():
if key not in Opts.keys() and key != 'details':
Opts[key] = Opts_defaults[key]
if key == 'details':
if key not in Opts.keys():
Opts[key] = Opts_defaults[key]
for detail_key in Opts_defaults[key].keys():
if detail_key not in Opts[key].keys():
Opts[key][detail_key] = Opts_defaults[key][detail_key]
if Opts['proj'] == 'pc':
ax = plt.axes(projection=ccrs.PlateCarree())
ax.set_extent([Opts['lonmin'], Opts['lonmax'], Opts['latmin'], Opts['latmax']],
crs=ccrs.PlateCarree())
if Opts['proj'] == 'aea':
ax = plt.axes(projection=ccrs.AlbersEqualArea(
central_longitude=Opts['lon_0'],
central_latitude=Opts['lat_0'],
false_easting=0.0, false_northing=0.0, standard_parallels=(20.0, 50.0),
globe=None))
if Opts['proj'] == 'lcc':
proj = ccrs.LambertConformal(central_longitude=Opts['lon_0'], central_latitude=Opts['lat_0'],\
false_easting=0.0, false_northing=0.0, standard_parallels=(20.0, 50.0),
globe=None)
fig=plt.figure(fignum,figsize=(6,6),frameon=True)
ax = plt.axes(projection=proj)
ax.set_extent([Opts['lonmin'], Opts['lonmax'], Opts['latmin'], Opts['latmax']],
crs=ccrs.PlateCarree())
if Opts['proj'] == 'lcyl':
ax = plt.axes(projection=ccrs.LambertCylindrical(
central_longitude=Opts['lon_0']))
if Opts['proj'] == 'merc':
ax = plt.axes(projection=ccrs.Mercator(
central_longitude=Opts['lon_0'], min_latitude=Opts['latmin'],
max_latitude=Opts['latmax'], latitude_true_scale=0.0, globe=None))
ax.set_extent([Opts['lonmin'],Opts['lonmax'],\
Opts['latmin'],Opts['latmax']])
if Opts['proj'] == 'mill':
ax = plt.axes(projection=ccrs.Miller(
central_longitude=Opts['lon_0']))
if Opts['proj'] == 'moll':
ax = plt.axes(projection=ccrs.Mollweide(
central_longitude=Opts['lat_0'], globe=None))
if Opts['proj'] == 'ortho':
ax = plt.axes(projection=ccrs.Orthographic(
central_longitude=Opts['lon_0'],
central_latitude=Opts['lat_0']))
if Opts['proj'] == 'robin':
ax = plt.axes(projection=ccrs.Robinson(
central_longitude=Opts['lon_0'],
globe=None))
if Opts['proj'] == 'sinu':
ax = plt.axes(projection=ccrs.Sinusoidal(
central_longitude=Opts['lon_0'],
false_easting=0.0, false_northing=0.0,
globe=None))
if Opts['proj'] == 'stere':
ax = plt.axes(projection=ccrs.Stereographic(
central_longitude=Opts['lon_0'],
false_easting=0.0, false_northing=0.0,
true_scale_latitude=None,
scale_factor=None,
globe=None))
if Opts['proj'] == 'tmerc':
ax = plt.axes(projection=ccrs.TransverseMercator(
central_longitude=Opts['lon_0'], central_latitude=Opts['lat_0'],
false_easting=0.0, false_northing=0.0,
scale_factor=None,
globe=None))
if Opts['proj'] == 'utm':
ax = plt.axes(projection=ccrs.UTM(
zone=Opts['zone'],
southern_hemisphere=Opts['south'],
globe=None))
if Opts['proj'] == 'geos':
ax = plt.axes(projection=ccrs.Geostationary(
central_longitude=Opts['lon_0'],
false_easting=0.0, false_northing=0.0,
satellite_height=35785831,
sweep_axis='y',
globe=None))
if Opts['proj'] == 'laea':
ax = plt.axes(projection=ccrs.LambertAzimuthalEqualArea(
central_longitude=Opts['lon_0'], central_latitude=Opts['lat_0'],
false_easting=0.0, false_northing=0.0,
globe=None))
if Opts['proj'] == 'npstere':
ax = plt.axes(projection=ccrs.NorthPolarStereo(
central_longitude=Opts['lon_0'],
true_scale_latitude=None,
globe=None))
if Opts['proj'] == 'spstere':
ax = plt.axes(projection=ccrs.SouthPolarStereo(
central_longitude=Opts['lon_0'],
true_scale_latitude=None,
globe=None))
if 'details' in list(Opts.keys()):
if Opts['details']['fancy'] == 1:
pmag_data_dir = find_pmag_dir.get_data_files_dir()
EDIR = os.path.join(pmag_data_dir, "etopo20")
etopo_path = os.path.join(EDIR, 'etopo20data.gz')
etopo = np.loadtxt(os.path.join(EDIR, 'etopo20data.gz'))
elons = np.loadtxt(os.path.join(EDIR, 'etopo20lons.gz'))
elats = np.loadtxt(os.path.join(EDIR, 'etopo20lats.gz'))
xx, yy = np.meshgrid(elons, elats)
levels = np.arange(-10000, 8000, 500) # define contour intervals
m = ax.contourf(xx, yy, etopo, levels,
transform=ccrs.PlateCarree(),
cmap=Opts['cmap'])
cbar=plt.colorbar(m)
if Opts['details']['coasts'] == 1:
if Opts['res']=='c' or Opts['res']=='l':
ax.coastlines(resolution='110m')
elif Opts['res']=='i':
ax.coastlines(resolution='50m')
elif Opts['res']=='h':
ax.coastlines(resolution='10m')
if Opts['details']['rivers'] == 1:
ax.add_feature(cfeature.RIVERS)
if Opts['details']['states'] == 1:
states_provinces = cfeature.NaturalEarthFeature(
category='cultural',
name='admin_1_states_provinces_lines',
scale='50m',
edgecolor='black',
facecolor='none',
linestyle='dotted')
ax.add_feature(states_provinces)
if Opts['details']['countries'] == 1:
ax.add_feature(BORDERS, linestyle='-', linewidth=2)
if Opts['details']['ocean'] == 1:
ax.add_feature(OCEAN, color=Opts['oceancolor'])
ax.add_feature(LAND, color=Opts['landcolor'])
ax.add_feature(LAKES, color=Opts['oceancolor'])
if Opts['proj'] in ['merc', 'pc','lcc']:
if Opts['pltgrid']:
if Opts['proj']=='lcc':
fig.canvas.draw()
#xticks=list(np.arange(Opts['lonmin'],Opts['lonmax']+Opts['gridspace'],Opts['gridspace']))
#yticks=list(np.arange(Opts['latmin'],Opts['latmax']+Opts['gridspace'],Opts['gridspace']))
xticks=list(np.arange(-180,180,Opts['gridspace']))
yticks=list(np.arange(-90,90,Opts['gridspace']))
ax.gridlines(ylocs=yticks,xlocs=xticks,linewidth=2,
linestyle='dotted')
ax.xaxis.set_major_formatter(LONGITUDE_FORMATTER) # you need this here
ax.yaxis.set_major_formatter(LATITUDE_FORMATTER)# you need this here, too
try:
import pmagpy.lcc_ticks as lcc_ticks
lcc_ticks.lambert_xticks(ax, xticks)
lcc_ticks.lambert_yticks(ax, yticks)
except:
print ('plotting of tick marks on Lambert Conformal requires the package "shapely".\n Try importing with "conda install -c conda-forge shapely"')
else:
gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=2,
linestyle='dotted', draw_labels=True)
gl.ylocator = mticker.FixedLocator(np.arange(-80, 81, Opts['gridspace']))
gl.xlocator = mticker.FixedLocator(np.arange(-180, 181, Opts['gridspace']))
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
gl.xlabels_top = False
else:
gl = ax.gridlines(crs=ccrs.PlateCarree(),
linewidth=2, linestyle='dotted')
elif Opts['pltgrid']:
print('gridlines only supported for PlateCarree, Lambert Conformal, and Mercator plots currently')
prn_name, symsize = 0, 5
# if 'names' in list(Opts.keys()) > 0:
# names = Opts['names']
# if len(names) > 0:
# prn_name = 1
##
X, Y, T, k = [], [], [], 0
if 'symsize' in list(Opts.keys()):
symsize = Opts['symsize']
if Opts['sym'][-1] != '-': # just plot points
color, symbol = Opts['sym'][0], Opts['sym'][1]
ax.scatter(lons, lats, s=Opts['symsize'], c=color, marker=symbol,
transform=ccrs.Geodetic(), edgecolors=Opts['edgecolor'])
if prn_name == 1:
print('labels not yet implemented in plot_map')
# for pt in range(len(lats)):
# T.append(plt.text(X[pt] + 5000, Y[pt] - 5000, names[pt]))
else: # for lines, need to separate chunks using lat==100.
ax.plot(lons, lats, Opts['sym'], transform=ccrs.Geodetic())
if Opts['global']:
ax.set_global() | python | def plot_map(fignum, lats, lons, Opts):
"""
makes a cartopy map with lats/lons
Requires installation of cartopy
Parameters:
_______________
fignum : matplotlib figure number
lats : array or list of latitudes
lons : array or list of longitudes
Opts : dictionary of plotting options:
Opts.keys=
proj : projection [supported cartopy projections:
pc = Plate Carree
aea = Albers Equal Area
aeqd = Azimuthal Equidistant
lcc = Lambert Conformal
lcyl = Lambert Cylindrical
merc = Mercator
mill = Miller Cylindrical
moll = Mollweide [default]
ortho = Orthographic
robin = Robinson
sinu = Sinusoidal
stere = Stereographic
tmerc = Transverse Mercator
utm = UTM [set zone and south keys in Opts]
laea = Lambert Azimuthal Equal Area
geos = Geostationary
npstere = North-Polar Stereographic
spstere = South-Polar Stereographic
latmin : minimum latitude for plot
latmax : maximum latitude for plot
lonmin : minimum longitude for plot
lonmax : maximum longitude
lat_0 : central latitude
lon_0 : central longitude
sym : matplotlib symbol
symsize : symbol size in pts
edge : markeredgecolor
cmap : matplotlib color map
res : resolution [c,l,i,h] for low/crude, intermediate, high
boundinglat : bounding latitude
sym : matplotlib symbol for plotting
symsize : matplotlib symbol size for plotting
names : list of names for lats/lons (if empty, none will be plotted)
pltgrd : if True, put on grid lines
padlat : padding of latitudes
padlon : padding of longitudes
gridspace : grid line spacing
global : global projection [default is True]
oceancolor : 'azure'
landcolor : 'bisque' [choose any of the valid color names for matplotlib
see https://matplotlib.org/examples/color/named_colors.html
details : dictionary with keys:
coasts : if True, plot coastlines
rivers : if True, plot rivers
states : if True, plot states
countries : if True, plot countries
ocean : if True, plot ocean
fancy : if True, plot etopo 20 grid
NB: etopo must be installed
if Opts keys not set :these are the defaults:
Opts={'latmin':-90,'latmax':90,'lonmin':0,'lonmax':360,'lat_0':0,'lon_0':0,'proj':'moll','sym':'ro,'symsize':5,'edge':'black','pltgrid':1,'res':'c','boundinglat':0.,'padlon':0,'padlat':0,'gridspace':30,'details':all False,'edge':None,'cmap':'jet','fancy':0,'zone':'','south':False,'oceancolor':'azure','landcolor':'bisque'}
"""
if not has_cartopy:
print('This function requires installation of cartopy')
return
from matplotlib import cm
# draw meridian labels on the bottom [left,right,top,bottom]
mlabels = [0, 0, 0, 1]
plabels = [1, 0, 0, 0] # draw parallel labels on the left
Opts_defaults = {'latmin': -90, 'latmax': 90, 'lonmin': 0, 'lonmax': 360,
'lat_0': 0, 'lon_0': 0, 'proj': 'moll', 'sym': 'ro', 'symsize': 5,
'edge': None, 'pltgrid': 1, 'res': 'c', 'boundinglat': 0.,
'padlon': 0, 'padlat': 0, 'gridspace': 30, 'global': 1, 'cmap': 'jet','oceancolor':'azure','landcolor':'bisque',
'details': {'fancy': 0, 'coasts': 0, 'rivers': 0, 'states': 0, 'countries': 0, 'ocean': 0},
'edgecolor': 'face'}
for key in Opts_defaults.keys():
if key not in Opts.keys() and key != 'details':
Opts[key] = Opts_defaults[key]
if key == 'details':
if key not in Opts.keys():
Opts[key] = Opts_defaults[key]
for detail_key in Opts_defaults[key].keys():
if detail_key not in Opts[key].keys():
Opts[key][detail_key] = Opts_defaults[key][detail_key]
if Opts['proj'] == 'pc':
ax = plt.axes(projection=ccrs.PlateCarree())
ax.set_extent([Opts['lonmin'], Opts['lonmax'], Opts['latmin'], Opts['latmax']],
crs=ccrs.PlateCarree())
if Opts['proj'] == 'aea':
ax = plt.axes(projection=ccrs.AlbersEqualArea(
central_longitude=Opts['lon_0'],
central_latitude=Opts['lat_0'],
false_easting=0.0, false_northing=0.0, standard_parallels=(20.0, 50.0),
globe=None))
if Opts['proj'] == 'lcc':
proj = ccrs.LambertConformal(central_longitude=Opts['lon_0'], central_latitude=Opts['lat_0'],\
false_easting=0.0, false_northing=0.0, standard_parallels=(20.0, 50.0),
globe=None)
fig=plt.figure(fignum,figsize=(6,6),frameon=True)
ax = plt.axes(projection=proj)
ax.set_extent([Opts['lonmin'], Opts['lonmax'], Opts['latmin'], Opts['latmax']],
crs=ccrs.PlateCarree())
if Opts['proj'] == 'lcyl':
ax = plt.axes(projection=ccrs.LambertCylindrical(
central_longitude=Opts['lon_0']))
if Opts['proj'] == 'merc':
ax = plt.axes(projection=ccrs.Mercator(
central_longitude=Opts['lon_0'], min_latitude=Opts['latmin'],
max_latitude=Opts['latmax'], latitude_true_scale=0.0, globe=None))
ax.set_extent([Opts['lonmin'],Opts['lonmax'],\
Opts['latmin'],Opts['latmax']])
if Opts['proj'] == 'mill':
ax = plt.axes(projection=ccrs.Miller(
central_longitude=Opts['lon_0']))
if Opts['proj'] == 'moll':
ax = plt.axes(projection=ccrs.Mollweide(
central_longitude=Opts['lat_0'], globe=None))
if Opts['proj'] == 'ortho':
ax = plt.axes(projection=ccrs.Orthographic(
central_longitude=Opts['lon_0'],
central_latitude=Opts['lat_0']))
if Opts['proj'] == 'robin':
ax = plt.axes(projection=ccrs.Robinson(
central_longitude=Opts['lon_0'],
globe=None))
if Opts['proj'] == 'sinu':
ax = plt.axes(projection=ccrs.Sinusoidal(
central_longitude=Opts['lon_0'],
false_easting=0.0, false_northing=0.0,
globe=None))
if Opts['proj'] == 'stere':
ax = plt.axes(projection=ccrs.Stereographic(
central_longitude=Opts['lon_0'],
false_easting=0.0, false_northing=0.0,
true_scale_latitude=None,
scale_factor=None,
globe=None))
if Opts['proj'] == 'tmerc':
ax = plt.axes(projection=ccrs.TransverseMercator(
central_longitude=Opts['lon_0'], central_latitude=Opts['lat_0'],
false_easting=0.0, false_northing=0.0,
scale_factor=None,
globe=None))
if Opts['proj'] == 'utm':
ax = plt.axes(projection=ccrs.UTM(
zone=Opts['zone'],
southern_hemisphere=Opts['south'],
globe=None))
if Opts['proj'] == 'geos':
ax = plt.axes(projection=ccrs.Geostationary(
central_longitude=Opts['lon_0'],
false_easting=0.0, false_northing=0.0,
satellite_height=35785831,
sweep_axis='y',
globe=None))
if Opts['proj'] == 'laea':
ax = plt.axes(projection=ccrs.LambertAzimuthalEqualArea(
central_longitude=Opts['lon_0'], central_latitude=Opts['lat_0'],
false_easting=0.0, false_northing=0.0,
globe=None))
if Opts['proj'] == 'npstere':
ax = plt.axes(projection=ccrs.NorthPolarStereo(
central_longitude=Opts['lon_0'],
true_scale_latitude=None,
globe=None))
if Opts['proj'] == 'spstere':
ax = plt.axes(projection=ccrs.SouthPolarStereo(
central_longitude=Opts['lon_0'],
true_scale_latitude=None,
globe=None))
if 'details' in list(Opts.keys()):
if Opts['details']['fancy'] == 1:
pmag_data_dir = find_pmag_dir.get_data_files_dir()
EDIR = os.path.join(pmag_data_dir, "etopo20")
etopo_path = os.path.join(EDIR, 'etopo20data.gz')
etopo = np.loadtxt(os.path.join(EDIR, 'etopo20data.gz'))
elons = np.loadtxt(os.path.join(EDIR, 'etopo20lons.gz'))
elats = np.loadtxt(os.path.join(EDIR, 'etopo20lats.gz'))
xx, yy = np.meshgrid(elons, elats)
levels = np.arange(-10000, 8000, 500) # define contour intervals
m = ax.contourf(xx, yy, etopo, levels,
transform=ccrs.PlateCarree(),
cmap=Opts['cmap'])
cbar=plt.colorbar(m)
if Opts['details']['coasts'] == 1:
if Opts['res']=='c' or Opts['res']=='l':
ax.coastlines(resolution='110m')
elif Opts['res']=='i':
ax.coastlines(resolution='50m')
elif Opts['res']=='h':
ax.coastlines(resolution='10m')
if Opts['details']['rivers'] == 1:
ax.add_feature(cfeature.RIVERS)
if Opts['details']['states'] == 1:
states_provinces = cfeature.NaturalEarthFeature(
category='cultural',
name='admin_1_states_provinces_lines',
scale='50m',
edgecolor='black',
facecolor='none',
linestyle='dotted')
ax.add_feature(states_provinces)
if Opts['details']['countries'] == 1:
ax.add_feature(BORDERS, linestyle='-', linewidth=2)
if Opts['details']['ocean'] == 1:
ax.add_feature(OCEAN, color=Opts['oceancolor'])
ax.add_feature(LAND, color=Opts['landcolor'])
ax.add_feature(LAKES, color=Opts['oceancolor'])
if Opts['proj'] in ['merc', 'pc','lcc']:
if Opts['pltgrid']:
if Opts['proj']=='lcc':
fig.canvas.draw()
#xticks=list(np.arange(Opts['lonmin'],Opts['lonmax']+Opts['gridspace'],Opts['gridspace']))
#yticks=list(np.arange(Opts['latmin'],Opts['latmax']+Opts['gridspace'],Opts['gridspace']))
xticks=list(np.arange(-180,180,Opts['gridspace']))
yticks=list(np.arange(-90,90,Opts['gridspace']))
ax.gridlines(ylocs=yticks,xlocs=xticks,linewidth=2,
linestyle='dotted')
ax.xaxis.set_major_formatter(LONGITUDE_FORMATTER) # you need this here
ax.yaxis.set_major_formatter(LATITUDE_FORMATTER)# you need this here, too
try:
import pmagpy.lcc_ticks as lcc_ticks
lcc_ticks.lambert_xticks(ax, xticks)
lcc_ticks.lambert_yticks(ax, yticks)
except:
print ('plotting of tick marks on Lambert Conformal requires the package "shapely".\n Try importing with "conda install -c conda-forge shapely"')
else:
gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=2,
linestyle='dotted', draw_labels=True)
gl.ylocator = mticker.FixedLocator(np.arange(-80, 81, Opts['gridspace']))
gl.xlocator = mticker.FixedLocator(np.arange(-180, 181, Opts['gridspace']))
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
gl.xlabels_top = False
else:
gl = ax.gridlines(crs=ccrs.PlateCarree(),
linewidth=2, linestyle='dotted')
elif Opts['pltgrid']:
print('gridlines only supported for PlateCarree, Lambert Conformal, and Mercator plots currently')
prn_name, symsize = 0, 5
# if 'names' in list(Opts.keys()) > 0:
# names = Opts['names']
# if len(names) > 0:
# prn_name = 1
##
X, Y, T, k = [], [], [], 0
if 'symsize' in list(Opts.keys()):
symsize = Opts['symsize']
if Opts['sym'][-1] != '-': # just plot points
color, symbol = Opts['sym'][0], Opts['sym'][1]
ax.scatter(lons, lats, s=Opts['symsize'], c=color, marker=symbol,
transform=ccrs.Geodetic(), edgecolors=Opts['edgecolor'])
if prn_name == 1:
print('labels not yet implemented in plot_map')
# for pt in range(len(lats)):
# T.append(plt.text(X[pt] + 5000, Y[pt] - 5000, names[pt]))
else: # for lines, need to separate chunks using lat==100.
ax.plot(lons, lats, Opts['sym'], transform=ccrs.Geodetic())
if Opts['global']:
ax.set_global() | makes a cartopy map with lats/lons
Requires installation of cartopy
Parameters:
_______________
fignum : matplotlib figure number
lats : array or list of latitudes
lons : array or list of longitudes
Opts : dictionary of plotting options:
Opts.keys=
proj : projection [supported cartopy projections:
pc = Plate Carree
aea = Albers Equal Area
aeqd = Azimuthal Equidistant
lcc = Lambert Conformal
lcyl = Lambert Cylindrical
merc = Mercator
mill = Miller Cylindrical
moll = Mollweide [default]
ortho = Orthographic
robin = Robinson
sinu = Sinusoidal
stere = Stereographic
tmerc = Transverse Mercator
utm = UTM [set zone and south keys in Opts]
laea = Lambert Azimuthal Equal Area
geos = Geostationary
npstere = North-Polar Stereographic
spstere = South-Polar Stereographic
latmin : minimum latitude for plot
latmax : maximum latitude for plot
lonmin : minimum longitude for plot
lonmax : maximum longitude
lat_0 : central latitude
lon_0 : central longitude
sym : matplotlib symbol
symsize : symbol size in pts
edge : markeredgecolor
cmap : matplotlib color map
res : resolution [c,l,i,h] for low/crude, intermediate, high
boundinglat : bounding latitude
sym : matplotlib symbol for plotting
symsize : matplotlib symbol size for plotting
names : list of names for lats/lons (if empty, none will be plotted)
pltgrd : if True, put on grid lines
padlat : padding of latitudes
padlon : padding of longitudes
gridspace : grid line spacing
global : global projection [default is True]
oceancolor : 'azure'
landcolor : 'bisque' [choose any of the valid color names for matplotlib
see https://matplotlib.org/examples/color/named_colors.html
details : dictionary with keys:
coasts : if True, plot coastlines
rivers : if True, plot rivers
states : if True, plot states
countries : if True, plot countries
ocean : if True, plot ocean
fancy : if True, plot etopo 20 grid
NB: etopo must be installed
if Opts keys not set :these are the defaults:
Opts={'latmin':-90,'latmax':90,'lonmin':0,'lonmax':360,'lat_0':0,'lon_0':0,'proj':'moll','sym':'ro,'symsize':5,'edge':'black','pltgrid':1,'res':'c','boundinglat':0.,'padlon':0,'padlat':0,'gridspace':30,'details':all False,'edge':None,'cmap':'jet','fancy':0,'zone':'','south':False,'oceancolor':'azure','landcolor':'bisque'} | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L3143-L3412 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_mag_map_basemap | def plot_mag_map_basemap(fignum, element, lons, lats, element_type, cmap='RdYlBu', lon_0=0, date=""):
"""
makes a color contour map of geomagnetic field element
Parameters
____________
fignum : matplotlib figure number
element : field element array from pmag.do_mag_map for plotting
lons : longitude array from pmag.do_mag_map for plotting
lats : latitude array from pmag.do_mag_map for plotting
element_type : [B,Br,I,D] geomagnetic element type
B : field intensity
Br : radial field intensity
I : inclinations
D : declinations
Optional
_________
cmap : matplotlib color map
lon_0 : central longitude of the Hammer projection
date : date used for field evaluation,
if custom ghfile was used, supply filename
Effects
______________
plots a Hammer projection color contour with the desired field element
"""
if not has_basemap:
print('-W- Basemap must be installed to run plot_mag_map_basemap')
return
from matplotlib import cm # matplotlib's color map module
lincr = 1
if type(date) != str:
date = str(date)
fig = plt.figure(fignum)
m = Basemap(projection='hammer', lon_0=lon_0)
x, y = m(*meshgrid(lons, lats))
m.drawcoastlines()
if element_type == 'B':
levmax = element.max()+lincr
levmin = round(element.min()-lincr)
levels = np.arange(levmin, levmax, lincr)
cs = m.contourf(x, y, element, levels=levels, cmap=cmap)
plt.title('Field strength ($\mu$T): '+date)
if element_type == 'Br':
levmax = element.max()+lincr
levmin = round(element.min()-lincr)
cs = m.contourf(x, y, element, levels=np.arange(
levmin, levmax, lincr), cmap=cmap)
plt.title('Radial field strength ($\mu$T): '+date)
if element_type == 'I':
levmax = element.max()+lincr
levmin = round(element.min()-lincr)
cs = m.contourf(
x, y, element, levels=np.arange(-90, 100, 20), cmap=cmap)
m.contour(x, y, element, levels=np.arange(-80, 90, 10), colors='black')
plt.title('Field inclination: '+date)
if element_type == 'D':
# cs=m.contourf(x,y,element,levels=np.arange(-180,180,10),cmap=cmap)
cs = m.contourf(
x, y, element, levels=np.arange(-180, 180, 10), cmap=cmap)
m.contour(x, y, element, levels=np.arange(-180, 180, 10), colors='black')
plt.title('Field declination: '+date)
cbar = m.colorbar(cs, location='bottom') | python | def plot_mag_map_basemap(fignum, element, lons, lats, element_type, cmap='RdYlBu', lon_0=0, date=""):
"""
makes a color contour map of geomagnetic field element
Parameters
____________
fignum : matplotlib figure number
element : field element array from pmag.do_mag_map for plotting
lons : longitude array from pmag.do_mag_map for plotting
lats : latitude array from pmag.do_mag_map for plotting
element_type : [B,Br,I,D] geomagnetic element type
B : field intensity
Br : radial field intensity
I : inclinations
D : declinations
Optional
_________
cmap : matplotlib color map
lon_0 : central longitude of the Hammer projection
date : date used for field evaluation,
if custom ghfile was used, supply filename
Effects
______________
plots a Hammer projection color contour with the desired field element
"""
if not has_basemap:
print('-W- Basemap must be installed to run plot_mag_map_basemap')
return
from matplotlib import cm # matplotlib's color map module
lincr = 1
if type(date) != str:
date = str(date)
fig = plt.figure(fignum)
m = Basemap(projection='hammer', lon_0=lon_0)
x, y = m(*meshgrid(lons, lats))
m.drawcoastlines()
if element_type == 'B':
levmax = element.max()+lincr
levmin = round(element.min()-lincr)
levels = np.arange(levmin, levmax, lincr)
cs = m.contourf(x, y, element, levels=levels, cmap=cmap)
plt.title('Field strength ($\mu$T): '+date)
if element_type == 'Br':
levmax = element.max()+lincr
levmin = round(element.min()-lincr)
cs = m.contourf(x, y, element, levels=np.arange(
levmin, levmax, lincr), cmap=cmap)
plt.title('Radial field strength ($\mu$T): '+date)
if element_type == 'I':
levmax = element.max()+lincr
levmin = round(element.min()-lincr)
cs = m.contourf(
x, y, element, levels=np.arange(-90, 100, 20), cmap=cmap)
m.contour(x, y, element, levels=np.arange(-80, 90, 10), colors='black')
plt.title('Field inclination: '+date)
if element_type == 'D':
# cs=m.contourf(x,y,element,levels=np.arange(-180,180,10),cmap=cmap)
cs = m.contourf(
x, y, element, levels=np.arange(-180, 180, 10), cmap=cmap)
m.contour(x, y, element, levels=np.arange(-180, 180, 10), colors='black')
plt.title('Field declination: '+date)
cbar = m.colorbar(cs, location='bottom') | makes a color contour map of geomagnetic field element
Parameters
____________
fignum : matplotlib figure number
element : field element array from pmag.do_mag_map for plotting
lons : longitude array from pmag.do_mag_map for plotting
lats : latitude array from pmag.do_mag_map for plotting
element_type : [B,Br,I,D] geomagnetic element type
B : field intensity
Br : radial field intensity
I : inclinations
D : declinations
Optional
_________
cmap : matplotlib color map
lon_0 : central longitude of the Hammer projection
date : date used for field evaluation,
if custom ghfile was used, supply filename
Effects
______________
plots a Hammer projection color contour with the desired field element | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L3415-L3478 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_mag_map | def plot_mag_map(fignum, element, lons, lats, element_type, cmap='coolwarm', lon_0=0, date="", contours=False, proj='PlateCarree'):
"""
makes a color contour map of geomagnetic field element
Parameters
____________
fignum : matplotlib figure number
element : field element array from pmag.do_mag_map for plotting
lons : longitude array from pmag.do_mag_map for plotting
lats : latitude array from pmag.do_mag_map for plotting
element_type : [B,Br,I,D] geomagnetic element type
B : field intensity
Br : radial field intensity
I : inclinations
D : declinations
Optional
_________
contours : plot the contour lines on top of the heat map if True
proj : cartopy projection ['PlateCarree','Mollweide']
NB: The Mollweide projection can only be reliably with cartopy=0.17.0; otherwise use lon_0=0. Also, for declinations, PlateCarree is recommended.
cmap : matplotlib color map - see https://matplotlib.org/examples/color/colormaps_reference.html for options
lon_0 : central longitude of the Mollweide projection
date : date used for field evaluation,
if custom ghfile was used, supply filename
Effects
______________
plots a color contour map with the desired field element
"""
if not has_cartopy:
print('This function requires installation of cartopy')
return
from matplotlib import cm
if lon_0 == 180:
lon_0 = 179.99
if lon_0 > 180:
lon_0 = lon_0-360.
lincr = 1
if type(date) != str:
date = str(date)
if proj == 'PlateCarree':
fig = plt.figure(fignum)
ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=lon_0))
if proj == 'Mollweide':
fig = plt.figure(fignum)
# this issue is fixed in >=0.17
if not LooseVersion(Cartopy.__version__) > LooseVersion('0.16.0'):
if lon_0 != 0:
print('This projection requires lon_0=0')
return
ax = plt.axes(projection=ccrs.Mollweide(central_longitude=lon_0))
xx, yy = np.meshgrid(lons, lats)
levmax = 5*round(element.max()/5)+5
levmin = 5*round(element.min()/5)-5
if element_type == 'Br' or element_type == 'B':
plt.contourf(xx, yy, element,
levels=np.arange(levmin, levmax, 1),
cmap=cmap, transform=ccrs.PlateCarree())
cbar = plt.colorbar(orientation='horizontal')
if contours:
plt.contour(xx, yy, element, levels=np.arange(levmin, levmax, 10),
colors='black', transform=ccrs.PlateCarree())
if element_type == 'Br':
plt.title('Radial field strength ($\mu$T): '+date)
else:
plt.title('Total field strength ($\mu$T): '+date)
if element_type == 'I':
plt.contourf(xx, yy, element,
levels=np.arange(-90, 90, lincr),
cmap=cmap, transform=ccrs.PlateCarree())
cbar = plt.colorbar(orientation='horizontal')
if contours:
plt.contour(xx, yy, element, levels=np.arange(-80, 90, 10),
colors='black', transform=ccrs.PlateCarree())
plt.title('Field inclination: '+date)
if element_type == 'D':
plt.contourf(xx, yy, element,
levels=np.arange(-180, 180, 10),
cmap=cmap, transform=ccrs.PlateCarree())
cbar = plt.colorbar(orientation='horizontal')
if contours:
plt.contour(xx, yy, element, levels=np.arange(-180, 180, 10),
colors='black', transform=ccrs.PlateCarree())
plt.title('Field declination: '+date)
ax.coastlines()
ax.set_global()
return ax | python | def plot_mag_map(fignum, element, lons, lats, element_type, cmap='coolwarm', lon_0=0, date="", contours=False, proj='PlateCarree'):
"""
makes a color contour map of geomagnetic field element
Parameters
____________
fignum : matplotlib figure number
element : field element array from pmag.do_mag_map for plotting
lons : longitude array from pmag.do_mag_map for plotting
lats : latitude array from pmag.do_mag_map for plotting
element_type : [B,Br,I,D] geomagnetic element type
B : field intensity
Br : radial field intensity
I : inclinations
D : declinations
Optional
_________
contours : plot the contour lines on top of the heat map if True
proj : cartopy projection ['PlateCarree','Mollweide']
NB: The Mollweide projection can only be reliably with cartopy=0.17.0; otherwise use lon_0=0. Also, for declinations, PlateCarree is recommended.
cmap : matplotlib color map - see https://matplotlib.org/examples/color/colormaps_reference.html for options
lon_0 : central longitude of the Mollweide projection
date : date used for field evaluation,
if custom ghfile was used, supply filename
Effects
______________
plots a color contour map with the desired field element
"""
if not has_cartopy:
print('This function requires installation of cartopy')
return
from matplotlib import cm
if lon_0 == 180:
lon_0 = 179.99
if lon_0 > 180:
lon_0 = lon_0-360.
lincr = 1
if type(date) != str:
date = str(date)
if proj == 'PlateCarree':
fig = plt.figure(fignum)
ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=lon_0))
if proj == 'Mollweide':
fig = plt.figure(fignum)
# this issue is fixed in >=0.17
if not LooseVersion(Cartopy.__version__) > LooseVersion('0.16.0'):
if lon_0 != 0:
print('This projection requires lon_0=0')
return
ax = plt.axes(projection=ccrs.Mollweide(central_longitude=lon_0))
xx, yy = np.meshgrid(lons, lats)
levmax = 5*round(element.max()/5)+5
levmin = 5*round(element.min()/5)-5
if element_type == 'Br' or element_type == 'B':
plt.contourf(xx, yy, element,
levels=np.arange(levmin, levmax, 1),
cmap=cmap, transform=ccrs.PlateCarree())
cbar = plt.colorbar(orientation='horizontal')
if contours:
plt.contour(xx, yy, element, levels=np.arange(levmin, levmax, 10),
colors='black', transform=ccrs.PlateCarree())
if element_type == 'Br':
plt.title('Radial field strength ($\mu$T): '+date)
else:
plt.title('Total field strength ($\mu$T): '+date)
if element_type == 'I':
plt.contourf(xx, yy, element,
levels=np.arange(-90, 90, lincr),
cmap=cmap, transform=ccrs.PlateCarree())
cbar = plt.colorbar(orientation='horizontal')
if contours:
plt.contour(xx, yy, element, levels=np.arange(-80, 90, 10),
colors='black', transform=ccrs.PlateCarree())
plt.title('Field inclination: '+date)
if element_type == 'D':
plt.contourf(xx, yy, element,
levels=np.arange(-180, 180, 10),
cmap=cmap, transform=ccrs.PlateCarree())
cbar = plt.colorbar(orientation='horizontal')
if contours:
plt.contour(xx, yy, element, levels=np.arange(-180, 180, 10),
colors='black', transform=ccrs.PlateCarree())
plt.title('Field declination: '+date)
ax.coastlines()
ax.set_global()
return ax | makes a color contour map of geomagnetic field element
Parameters
____________
fignum : matplotlib figure number
element : field element array from pmag.do_mag_map for plotting
lons : longitude array from pmag.do_mag_map for plotting
lats : latitude array from pmag.do_mag_map for plotting
element_type : [B,Br,I,D] geomagnetic element type
B : field intensity
Br : radial field intensity
I : inclinations
D : declinations
Optional
_________
contours : plot the contour lines on top of the heat map if True
proj : cartopy projection ['PlateCarree','Mollweide']
NB: The Mollweide projection can only be reliably with cartopy=0.17.0; otherwise use lon_0=0. Also, for declinations, PlateCarree is recommended.
cmap : matplotlib color map - see https://matplotlib.org/examples/color/colormaps_reference.html for options
lon_0 : central longitude of the Mollweide projection
date : date used for field evaluation,
if custom ghfile was used, supply filename
Effects
______________
plots a color contour map with the desired field element | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L3481-L3570 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_eq_cont | def plot_eq_cont(fignum, DIblock, color_map='coolwarm'):
"""
plots dec inc block as a color contour
Parameters
__________________
Input:
fignum : figure number
DIblock : nested pairs of [Declination, Inclination]
color_map : matplotlib color map [default is coolwarm]
Output:
figure
"""
import random
plt.figure(num=fignum)
plt.axis("off")
XY = []
centres = []
counter = 0
for rec in DIblock:
counter = counter + 1
X = pmag.dir2cart([rec[0], rec[1], 1.])
# from Collinson 1983
R = old_div(np.sqrt(1. - X[2]), (np.sqrt(X[0]**2 + X[1]**2)))
XY.append([X[0] * R, X[1] * R])
# radius of the circle
radius = (old_div(3., (np.sqrt(np.pi * (9. + float(counter)))))) + 0.01
num = 2. * (old_div(1., radius)) # number of circles
# a,b are the extent of the grids over which the circles are equispaced
a1, a2 = (0. - (radius * num / 2.)), (0. + (radius * num / 2.))
b1, b2 = (0. - (radius * num / 2.)), (0. + (radius * num / 2.))
# this is to get an array (a list of list wont do) of x,y values
xlist = np.linspace(a1, a2, int(np.ceil(num)))
ylist = np.linspace(b1, b2, int(np.ceil(num)))
X, Y = np.meshgrid(xlist, ylist)
# to put z in the array I just multiply both x,y with zero. I will add to
# the zero values later
Z = X * Y * 0.
# keeping the centres of the circles as a separate list instead of in
# array helps later
for j in range(len(ylist)):
for i in range(len(xlist)):
centres.append([xlist[i], ylist[j]])
# the following lines are to figure out what happens at the edges where part of a circle might lie outside
# a thousand random numbers are generated within the x,y limit of the circles and tested whether it is contained in
# the eq area net space....their ratio gives the fraction of circle
# contained in the net
fraction = []
beta, alpha = 0.001, 0.001 # to avoid those 'division by float' thingy
for i in range(0, int(np.ceil(num))**2):
if np.sqrt(((centres[i][0])**2) + ((centres[i][1])**2)) - 1. < radius:
for j in range(1, 1000):
rnd1 = random.uniform(
centres[i][0] - radius, centres[i][0] + radius)
rnd2 = random.uniform(
centres[i][1] - radius, centres[i][1] + radius)
if ((centres[i][0] - rnd1)**2 + (centres[i][1] - rnd2)**2) <= radius**2:
if (rnd1**2) + (rnd2**2) < 1.:
alpha = alpha + 1.
beta = beta + 1.
else:
alpha = alpha + 1.
fraction.append(old_div(alpha, beta))
alpha, beta = 0.001, 0.001
else:
fraction.append(1.) # if the whole circle lies in the net
# for every circle count the number of points lying in it
count = 0
dotspercircle = 0.
for j in range(0, int(np.ceil(num))):
for i in range(0, int(np.ceil(num))):
for k in range(0, counter):
if (XY[k][0] - centres[count][0])**2 + (XY[k][1] - centres[count][1])**2 <= radius**2:
dotspercircle += 1.
Z[i][j] = Z[i][j] + (dotspercircle * fraction[count])
count += 1
dotspercircle = 0.
im = plt.imshow(Z, interpolation='bilinear', origin='lower',
# cmap=plt.color_map.hot, extent=(-1., 1., -1., 1.))
cmap=color_map, extent=(-1., 1., -1., 1.))
plt.colorbar(shrink=0.5)
x, y = [], []
# Draws the border
for i in range(0, 360):
x.append(np.sin((old_div(np.pi, 180.)) * float(i)))
y.append(np.cos((old_div(np.pi, 180.)) * float(i)))
plt.plot(x, y, 'w-')
x, y = [], []
# the map will be a square of 1X1..this is how I erase the redundant area
for j in range(1, 4):
for i in range(0, 360):
x.append(np.sin((old_div(np.pi, 180.)) * float(i))
* (1. + (old_div(float(j), 10.))))
y.append(np.cos((old_div(np.pi, 180.)) * float(i))
* (1. + (old_div(float(j), 10.))))
plt.plot(x, y, 'w-', linewidth=26)
x, y = [], []
# the axes
plt.axis("equal") | python | def plot_eq_cont(fignum, DIblock, color_map='coolwarm'):
"""
plots dec inc block as a color contour
Parameters
__________________
Input:
fignum : figure number
DIblock : nested pairs of [Declination, Inclination]
color_map : matplotlib color map [default is coolwarm]
Output:
figure
"""
import random
plt.figure(num=fignum)
plt.axis("off")
XY = []
centres = []
counter = 0
for rec in DIblock:
counter = counter + 1
X = pmag.dir2cart([rec[0], rec[1], 1.])
# from Collinson 1983
R = old_div(np.sqrt(1. - X[2]), (np.sqrt(X[0]**2 + X[1]**2)))
XY.append([X[0] * R, X[1] * R])
# radius of the circle
radius = (old_div(3., (np.sqrt(np.pi * (9. + float(counter)))))) + 0.01
num = 2. * (old_div(1., radius)) # number of circles
# a,b are the extent of the grids over which the circles are equispaced
a1, a2 = (0. - (radius * num / 2.)), (0. + (radius * num / 2.))
b1, b2 = (0. - (radius * num / 2.)), (0. + (radius * num / 2.))
# this is to get an array (a list of list wont do) of x,y values
xlist = np.linspace(a1, a2, int(np.ceil(num)))
ylist = np.linspace(b1, b2, int(np.ceil(num)))
X, Y = np.meshgrid(xlist, ylist)
# to put z in the array I just multiply both x,y with zero. I will add to
# the zero values later
Z = X * Y * 0.
# keeping the centres of the circles as a separate list instead of in
# array helps later
for j in range(len(ylist)):
for i in range(len(xlist)):
centres.append([xlist[i], ylist[j]])
# the following lines are to figure out what happens at the edges where part of a circle might lie outside
# a thousand random numbers are generated within the x,y limit of the circles and tested whether it is contained in
# the eq area net space....their ratio gives the fraction of circle
# contained in the net
fraction = []
beta, alpha = 0.001, 0.001 # to avoid those 'division by float' thingy
for i in range(0, int(np.ceil(num))**2):
if np.sqrt(((centres[i][0])**2) + ((centres[i][1])**2)) - 1. < radius:
for j in range(1, 1000):
rnd1 = random.uniform(
centres[i][0] - radius, centres[i][0] + radius)
rnd2 = random.uniform(
centres[i][1] - radius, centres[i][1] + radius)
if ((centres[i][0] - rnd1)**2 + (centres[i][1] - rnd2)**2) <= radius**2:
if (rnd1**2) + (rnd2**2) < 1.:
alpha = alpha + 1.
beta = beta + 1.
else:
alpha = alpha + 1.
fraction.append(old_div(alpha, beta))
alpha, beta = 0.001, 0.001
else:
fraction.append(1.) # if the whole circle lies in the net
# for every circle count the number of points lying in it
count = 0
dotspercircle = 0.
for j in range(0, int(np.ceil(num))):
for i in range(0, int(np.ceil(num))):
for k in range(0, counter):
if (XY[k][0] - centres[count][0])**2 + (XY[k][1] - centres[count][1])**2 <= radius**2:
dotspercircle += 1.
Z[i][j] = Z[i][j] + (dotspercircle * fraction[count])
count += 1
dotspercircle = 0.
im = plt.imshow(Z, interpolation='bilinear', origin='lower',
# cmap=plt.color_map.hot, extent=(-1., 1., -1., 1.))
cmap=color_map, extent=(-1., 1., -1., 1.))
plt.colorbar(shrink=0.5)
x, y = [], []
# Draws the border
for i in range(0, 360):
x.append(np.sin((old_div(np.pi, 180.)) * float(i)))
y.append(np.cos((old_div(np.pi, 180.)) * float(i)))
plt.plot(x, y, 'w-')
x, y = [], []
# the map will be a square of 1X1..this is how I erase the redundant area
for j in range(1, 4):
for i in range(0, 360):
x.append(np.sin((old_div(np.pi, 180.)) * float(i))
* (1. + (old_div(float(j), 10.))))
y.append(np.cos((old_div(np.pi, 180.)) * float(i))
* (1. + (old_div(float(j), 10.))))
plt.plot(x, y, 'w-', linewidth=26)
x, y = [], []
# the axes
plt.axis("equal") | plots dec inc block as a color contour
Parameters
__________________
Input:
fignum : figure number
DIblock : nested pairs of [Declination, Inclination]
color_map : matplotlib color map [default is coolwarm]
Output:
figure | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L3573-L3671 |
PmagPy/PmagPy | pmagpy/pmagplotlib.py | plot_ts | def plot_ts(ax, agemin, agemax, timescale='gts12', ylabel="Age (Ma)"):
"""
Make a time scale plot between specified ages.
Parameters:
------------
ax : figure object
agemin : Minimum age for timescale
agemax : Maximum age for timescale
timescale : Time Scale [ default is Gradstein et al., (2012)]
for other options see pmag.get_ts()
ylabel : if set, plot as ylabel
"""
ax.set_title(timescale.upper())
ax.axis([-.25, 1.5, agemax, agemin])
ax.axes.get_xaxis().set_visible(False)
# get dates and chron names for timescale
TS, Chrons = pmag.get_ts(timescale)
X, Y, Y2 = [0, 1], [], []
cnt = 0
if agemin < TS[1]: # in the Brunhes
Y = [agemin, agemin] # minimum age
Y1 = [TS[1], TS[1]] # age of the B/M boundary
ax.fill_between(X, Y, Y1, facecolor='black') # color in Brunhes, black
for d in TS[1:]:
pol = cnt % 2
cnt += 1
if d <= agemax and d >= agemin:
ind = TS.index(d)
Y = [TS[ind], TS[ind]]
Y1 = [TS[ind+1], TS[ind+1]]
if pol:
# fill in every other time
ax.fill_between(X, Y, Y1, facecolor='black')
ax.plot([0, 1, 1, 0, 0], [agemin, agemin, agemax, agemax, agemin], 'k-')
plt.yticks(np.arange(agemin, agemax+1, 1))
if ylabel != "":
ax.set_ylabel(ylabel)
ax2 = ax.twinx()
ax2.axis('off')
for k in range(len(Chrons)-1):
c = Chrons[k]
cnext = Chrons[k+1]
d = cnext[1]-(cnext[1]-c[1])/3.
if d >= agemin and d < agemax:
# make the Chron boundary tick
ax2.plot([1, 1.5], [c[1], c[1]], 'k-')
ax2.text(1.05, d, c[0])
ax2.axis([-.25, 1.5, agemax, agemin]) | python | def plot_ts(ax, agemin, agemax, timescale='gts12', ylabel="Age (Ma)"):
"""
Make a time scale plot between specified ages.
Parameters:
------------
ax : figure object
agemin : Minimum age for timescale
agemax : Maximum age for timescale
timescale : Time Scale [ default is Gradstein et al., (2012)]
for other options see pmag.get_ts()
ylabel : if set, plot as ylabel
"""
ax.set_title(timescale.upper())
ax.axis([-.25, 1.5, agemax, agemin])
ax.axes.get_xaxis().set_visible(False)
# get dates and chron names for timescale
TS, Chrons = pmag.get_ts(timescale)
X, Y, Y2 = [0, 1], [], []
cnt = 0
if agemin < TS[1]: # in the Brunhes
Y = [agemin, agemin] # minimum age
Y1 = [TS[1], TS[1]] # age of the B/M boundary
ax.fill_between(X, Y, Y1, facecolor='black') # color in Brunhes, black
for d in TS[1:]:
pol = cnt % 2
cnt += 1
if d <= agemax and d >= agemin:
ind = TS.index(d)
Y = [TS[ind], TS[ind]]
Y1 = [TS[ind+1], TS[ind+1]]
if pol:
# fill in every other time
ax.fill_between(X, Y, Y1, facecolor='black')
ax.plot([0, 1, 1, 0, 0], [agemin, agemin, agemax, agemax, agemin], 'k-')
plt.yticks(np.arange(agemin, agemax+1, 1))
if ylabel != "":
ax.set_ylabel(ylabel)
ax2 = ax.twinx()
ax2.axis('off')
for k in range(len(Chrons)-1):
c = Chrons[k]
cnext = Chrons[k+1]
d = cnext[1]-(cnext[1]-c[1])/3.
if d >= agemin and d < agemax:
# make the Chron boundary tick
ax2.plot([1, 1.5], [c[1], c[1]], 'k-')
ax2.text(1.05, d, c[0])
ax2.axis([-.25, 1.5, agemax, agemin]) | Make a time scale plot between specified ages.
Parameters:
------------
ax : figure object
agemin : Minimum age for timescale
agemax : Maximum age for timescale
timescale : Time Scale [ default is Gradstein et al., (2012)]
for other options see pmag.get_ts()
ylabel : if set, plot as ylabel | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmagplotlib.py#L3674-L3722 |
PmagPy/PmagPy | programs/quick_hyst2.py | main | def main():
"""
NAME
quick_hyst.py
DESCRIPTION
makes plots of hysteresis data
SYNTAX
quick_hyst.py [command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f: specify input file, default is magic_measurements.txt
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg]
"""
args = sys.argv
PLT = 1
plots = 0
user, meas_file = "", "magic_measurements.txt"
pltspec = ""
dir_path = '.'
fmt = 'png'
verbose = pmagplotlib.verbose
version_num = pmag.get_version()
if '-WD' in args:
ind = args.index('-WD')
dir_path = args[ind+1]
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-usr" in args:
ind = args.index("-usr")
user = args[ind+1]
if '-f' in args:
ind = args.index("-f")
meas_file = args[ind+1]
if '-sav' in args:
verbose = 0
plots = 1
if '-spc' in args:
ind = args.index("-spc")
pltspec = args[ind+1]
verbose = 0
plots = 1
if '-fmt' in args:
ind = args.index("-fmt")
fmt = args[ind+1]
meas_file = dir_path+'/'+meas_file
#
#
meas_data, file_type = pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print(main.__doc__)
print('bad file')
sys.exit()
#
# initialize some variables
# define figure numbers for hyst,deltaM,DdeltaM curves
HystRecs, RemRecs = [], []
HDD = {}
HDD['hyst'] = 1
pmagplotlib.plot_init(HDD['hyst'], 5, 5)
#
# get list of unique experiment names and specimen names
#
experiment_names, sids = [], []
hyst_data = pmag.get_dictitem(
meas_data, 'magic_method_codes', 'LP-HYS', 'has') # get all hysteresis data
for rec in hyst_data:
if 'er_synthetic_name' in rec.keys() and rec['er_synthetic_name'] != "":
rec['er_specimen_name'] = rec['er_synthetic_name']
if rec['magic_experiment_name'] not in experiment_names:
experiment_names.append(rec['magic_experiment_name'])
if rec['er_specimen_name'] not in sids:
sids.append(rec['er_specimen_name'])
if 'measurement_temp' not in rec.keys():
# assume room T measurement unless otherwise specified
rec['measurement_temp'] = '300'
#
k = 0
if pltspec != "":
k = sids.index(pltspec)
intlist = ['measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass']
while k < len(sids):
locname, site, sample, synth = '', '', '', ''
s = sids[k]
hmeths = []
if verbose:
print(s, k+1, 'out of ', len(sids))
#
#
B, M = [], [] # B,M for hysteresis, Bdcd,Mdcd for irm-dcd data
# get all measurements for this specimen
spec = pmag.get_dictitem(hyst_data, 'er_specimen_name', s, 'T')
if 'er_location_name' in spec[0].keys():
locname = spec[0]['er_location_name']
if 'er_site_name' in spec[0].keys():
site = spec[0]['er_site_name']
if 'er_sample_name' in spec[0].keys():
sample = spec[0]['er_sample_name']
if 'er_synthetic_name' in spec[0].keys():
synth = spec[0]['er_synthetic_name']
for m in intlist:
# get all non-blank data for this specimen
meas_data = pmag.get_dictitem(spec, m, '', 'F')
if len(meas_data) > 0:
break
c = ['k-', 'b-', 'c-', 'g-', 'm-', 'r-', 'y-']
cnum = 0
if len(meas_data) > 0:
Temps = []
xlab, ylab, title = '', '', ''
for rec in meas_data:
if rec['measurement_temp'] not in Temps:
Temps.append(rec['measurement_temp'])
for t in Temps:
print('working on t: ', t)
t_data = pmag.get_dictitem(
meas_data, 'measurement_temp', t, 'T')
B, M = [], []
for rec in t_data:
B.append(float(rec['measurement_lab_field_dc']))
M.append(float(rec[m]))
# now plot the hysteresis curve(s)
#
if len(B) > 0:
B = numpy.array(B)
M = numpy.array(M)
if t == Temps[-1]:
xlab = 'Field (T)'
ylab = m
title = 'Hysteresis: '+s
if t == Temps[0]:
pmagplotlib.clearFIG(HDD['hyst'])
pmagplotlib.plot_xy(
HDD['hyst'], B, M, sym=c[cnum], xlab=xlab, ylab=ylab, title=title)
pmagplotlib.plot_xy(HDD['hyst'], [
1.1*B.min(), 1.1*B.max()], [0, 0], sym='k-', xlab=xlab, ylab=ylab, title=title)
pmagplotlib.plot_xy(HDD['hyst'], [0, 0], [
1.1*M.min(), 1.1*M.max()], sym='k-', xlab=xlab, ylab=ylab, title=title)
if verbose:
pmagplotlib.draw_figs(HDD)
cnum += 1
if cnum == len(c):
cnum = 0
#
files = {}
if plots:
if pltspec != "":
s = pltspec
files = {}
for key in HDD.keys():
if pmagplotlib.isServer: # use server plot naming convention
if synth == '':
filename = "LO:_"+locname+'_SI:_'+site + \
'_SA:_'+sample+'_SP:_'+s+'_TY:_'+key+'_.'+fmt
else:
filename = 'SY:_'+synth+'_TY:_'+key+'_.'+fmt
files[key] = filename
else: # use more readable plot naming convention
if synth == '':
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
else:
filename = synth+'_'+key+'.fmt'
files[key] = filename
pmagplotlib.save_plots(HDD, files)
if pltspec != "":
sys.exit()
if verbose:
pmagplotlib.draw_figs(HDD)
ans = raw_input(
"S[a]ve plots, [s]pecimen name, [q]uit, <return> to continue\n ")
if ans == "a":
files = {}
for key in HDD.keys():
if pmagplotlib.isServer:
print('server')
files[key] = "LO:_"+locname+'_SI:_'+site + \
'_SA:_'+sample+'_SP:_'+s+'_TY:_'+key+'_.'+fmt
else:
print('not server')
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key] = filename
print('files', files)
pmagplotlib.save_plots(HDD, files)
if ans == '':
k += 1
if ans == "p":
del HystRecs[-1]
k -= 1
if ans == 'q':
print("Good bye")
sys.exit()
if ans == 's':
keepon = 1
specimen = raw_input(
'Enter desired specimen name (or first part there of): ')
while keepon == 1:
try:
k = sids.index(specimen)
keepon = 0
except:
tmplist = []
for qq in range(len(sids)):
if specimen in sids[qq]:
tmplist.append(sids[qq])
print(specimen, " not found, but this was: ")
print(tmplist)
specimen = raw_input('Select one or try again\n ')
k = sids.index(specimen)
else:
k += 1
if len(B) == 0:
if verbose:
print('skipping this one - no hysteresis data')
k += 1 | python | def main():
"""
NAME
quick_hyst.py
DESCRIPTION
makes plots of hysteresis data
SYNTAX
quick_hyst.py [command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f: specify input file, default is magic_measurements.txt
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg]
"""
args = sys.argv
PLT = 1
plots = 0
user, meas_file = "", "magic_measurements.txt"
pltspec = ""
dir_path = '.'
fmt = 'png'
verbose = pmagplotlib.verbose
version_num = pmag.get_version()
if '-WD' in args:
ind = args.index('-WD')
dir_path = args[ind+1]
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-usr" in args:
ind = args.index("-usr")
user = args[ind+1]
if '-f' in args:
ind = args.index("-f")
meas_file = args[ind+1]
if '-sav' in args:
verbose = 0
plots = 1
if '-spc' in args:
ind = args.index("-spc")
pltspec = args[ind+1]
verbose = 0
plots = 1
if '-fmt' in args:
ind = args.index("-fmt")
fmt = args[ind+1]
meas_file = dir_path+'/'+meas_file
#
#
meas_data, file_type = pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print(main.__doc__)
print('bad file')
sys.exit()
#
# initialize some variables
# define figure numbers for hyst,deltaM,DdeltaM curves
HystRecs, RemRecs = [], []
HDD = {}
HDD['hyst'] = 1
pmagplotlib.plot_init(HDD['hyst'], 5, 5)
#
# get list of unique experiment names and specimen names
#
experiment_names, sids = [], []
hyst_data = pmag.get_dictitem(
meas_data, 'magic_method_codes', 'LP-HYS', 'has') # get all hysteresis data
for rec in hyst_data:
if 'er_synthetic_name' in rec.keys() and rec['er_synthetic_name'] != "":
rec['er_specimen_name'] = rec['er_synthetic_name']
if rec['magic_experiment_name'] not in experiment_names:
experiment_names.append(rec['magic_experiment_name'])
if rec['er_specimen_name'] not in sids:
sids.append(rec['er_specimen_name'])
if 'measurement_temp' not in rec.keys():
# assume room T measurement unless otherwise specified
rec['measurement_temp'] = '300'
#
k = 0
if pltspec != "":
k = sids.index(pltspec)
intlist = ['measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass']
while k < len(sids):
locname, site, sample, synth = '', '', '', ''
s = sids[k]
hmeths = []
if verbose:
print(s, k+1, 'out of ', len(sids))
#
#
B, M = [], [] # B,M for hysteresis, Bdcd,Mdcd for irm-dcd data
# get all measurements for this specimen
spec = pmag.get_dictitem(hyst_data, 'er_specimen_name', s, 'T')
if 'er_location_name' in spec[0].keys():
locname = spec[0]['er_location_name']
if 'er_site_name' in spec[0].keys():
site = spec[0]['er_site_name']
if 'er_sample_name' in spec[0].keys():
sample = spec[0]['er_sample_name']
if 'er_synthetic_name' in spec[0].keys():
synth = spec[0]['er_synthetic_name']
for m in intlist:
# get all non-blank data for this specimen
meas_data = pmag.get_dictitem(spec, m, '', 'F')
if len(meas_data) > 0:
break
c = ['k-', 'b-', 'c-', 'g-', 'm-', 'r-', 'y-']
cnum = 0
if len(meas_data) > 0:
Temps = []
xlab, ylab, title = '', '', ''
for rec in meas_data:
if rec['measurement_temp'] not in Temps:
Temps.append(rec['measurement_temp'])
for t in Temps:
print('working on t: ', t)
t_data = pmag.get_dictitem(
meas_data, 'measurement_temp', t, 'T')
B, M = [], []
for rec in t_data:
B.append(float(rec['measurement_lab_field_dc']))
M.append(float(rec[m]))
# now plot the hysteresis curve(s)
#
if len(B) > 0:
B = numpy.array(B)
M = numpy.array(M)
if t == Temps[-1]:
xlab = 'Field (T)'
ylab = m
title = 'Hysteresis: '+s
if t == Temps[0]:
pmagplotlib.clearFIG(HDD['hyst'])
pmagplotlib.plot_xy(
HDD['hyst'], B, M, sym=c[cnum], xlab=xlab, ylab=ylab, title=title)
pmagplotlib.plot_xy(HDD['hyst'], [
1.1*B.min(), 1.1*B.max()], [0, 0], sym='k-', xlab=xlab, ylab=ylab, title=title)
pmagplotlib.plot_xy(HDD['hyst'], [0, 0], [
1.1*M.min(), 1.1*M.max()], sym='k-', xlab=xlab, ylab=ylab, title=title)
if verbose:
pmagplotlib.draw_figs(HDD)
cnum += 1
if cnum == len(c):
cnum = 0
#
files = {}
if plots:
if pltspec != "":
s = pltspec
files = {}
for key in HDD.keys():
if pmagplotlib.isServer: # use server plot naming convention
if synth == '':
filename = "LO:_"+locname+'_SI:_'+site + \
'_SA:_'+sample+'_SP:_'+s+'_TY:_'+key+'_.'+fmt
else:
filename = 'SY:_'+synth+'_TY:_'+key+'_.'+fmt
files[key] = filename
else: # use more readable plot naming convention
if synth == '':
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
else:
filename = synth+'_'+key+'.fmt'
files[key] = filename
pmagplotlib.save_plots(HDD, files)
if pltspec != "":
sys.exit()
if verbose:
pmagplotlib.draw_figs(HDD)
ans = raw_input(
"S[a]ve plots, [s]pecimen name, [q]uit, <return> to continue\n ")
if ans == "a":
files = {}
for key in HDD.keys():
if pmagplotlib.isServer:
print('server')
files[key] = "LO:_"+locname+'_SI:_'+site + \
'_SA:_'+sample+'_SP:_'+s+'_TY:_'+key+'_.'+fmt
else:
print('not server')
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key] = filename
print('files', files)
pmagplotlib.save_plots(HDD, files)
if ans == '':
k += 1
if ans == "p":
del HystRecs[-1]
k -= 1
if ans == 'q':
print("Good bye")
sys.exit()
if ans == 's':
keepon = 1
specimen = raw_input(
'Enter desired specimen name (or first part there of): ')
while keepon == 1:
try:
k = sids.index(specimen)
keepon = 0
except:
tmplist = []
for qq in range(len(sids)):
if specimen in sids[qq]:
tmplist.append(sids[qq])
print(specimen, " not found, but this was: ")
print(tmplist)
specimen = raw_input('Select one or try again\n ')
k = sids.index(specimen)
else:
k += 1
if len(B) == 0:
if verbose:
print('skipping this one - no hysteresis data')
k += 1 | NAME
quick_hyst.py
DESCRIPTION
makes plots of hysteresis data
SYNTAX
quick_hyst.py [command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f: specify input file, default is magic_measurements.txt
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg] | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/programs/quick_hyst2.py#L13-L248 |
PmagPy/PmagPy | programs/conversion_scripts2/jr6_txt_magic2.py | main | def main(command_line=True, **kwargs):
"""
NAME
jr6_txt_magic.py
DESCRIPTION
converts JR6 .txt format files to magic_measurements format files
SYNTAX
jr6_txt_magic.py [command line options]
OPTIONS
-h: prints the help message and quits.
-f FILE: specify input file, or
-F FILE: specify output file, default is magic_measurements.txt
-Fsa: specify er_samples format file for appending, default is new er_samples.txt (Not working yet)
-spc NUM : specify number of characters to designate a specimen, default = 1
-loc LOCNAME : specify location/study name
-A: don't average replicate measurements
-ncn NCON: specify sample naming convention (6 and 7 not yet implemented)
-mcd [SO-MAG,SO-SUN,SO-SIGHT...] supply how these samples were oriented
-v NUM : specify the volume of the sample, default 2.5cm^3.
Sample naming convention:
[1] XXXXY: where XXXX is an arbitrary length site designation and Y
is the single character sample designation. e.g., TG001a is the
first sample from site TG001. [default]
[2] XXXX-YY: YY sample from site XXXX (XXX, YY of arbitary length)
[3] XXXX.YY: YY sample from site XXXX (XXX, YY of arbitary length)
[4-Z] XXXX[YYY]: YYY is sample designation with Z characters from site XXX
[5] site name same as sample
[6] site is entered under a separate column NOT CURRENTLY SUPPORTED
[7-Z] [XXXX]YYY: XXXX is site designation with Z characters with sample name XXXXYYYY
NB: all others you will have to customize your self
or e-mail [email protected] for help.
INPUT
JR6 .txt format file
"""
# initialize some stuff
noave=0
volume = 2.5 * 1e-6 # default volume is 2.5 cm^3 (2.5 * 1e-6 meters^3)
inst=""
samp_con,Z='1',""
missing=1
demag="N"
er_location_name="unknown"
citation='This study'
args=sys.argv
meth_code="LP-NO"
specnum=-1
MagRecs=[]
version_num=pmag.get_version()
Samps=[] # keeps track of sample orientations
user=""
mag_file=""
dir_path='.'
ErSamps=[]
SampOuts=[]
samp_file = 'er_samples.txt'
meas_file = 'magic_measurements.txt'
#
# get command line arguments
#
if command_line:
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
if '-ID' in sys.argv:
ind = sys.argv.index('-ID')
input_dir_path = sys.argv[ind+1]
else:
input_dir_path = dir_path
output_dir_path = dir_path
if "-h" in args:
print(main.__doc__)
return False
if '-F' in args:
ind=args.index("-F")
meas_file = args[ind+1]
if '-Fsa' in args:
ind = args.index("-Fsa")
samp_file = args[ind+1]
#try:
# open(samp_file,'r')
# ErSamps,file_type=pmag.magic_read(samp_file)
# print 'sample information will be appended to ', samp_file
#except:
# print samp_file,' not found: sample information will be stored in new er_samples.txt file'
# samp_file = output_dir_path+'/er_samples.txt'
if '-f' in args:
ind = args.index("-f")
mag_file= args[ind+1]
if "-spc" in args:
ind = args.index("-spc")
specnum = int(args[ind+1])
if "-ncn" in args:
ind=args.index("-ncn")
samp_con=sys.argv[ind+1]
if "-loc" in args:
ind=args.index("-loc")
er_location_name=args[ind+1]
if "-A" in args: noave=1
if "-mcd" in args:
ind=args.index("-mcd")
meth_code=args[ind+1]
if "-v" in args:
ind=args.index("-v")
volume=float(args[ind+1]) * 1e-6
if not command_line:
dir_path = kwargs.get('dir_path', '.')
input_dir_path = kwargs.get('input_dir_path', dir_path)
output_dir_path = dir_path
meas_file = kwargs.get('meas_file', 'magic_measurements.txt')
mag_file = kwargs.get('mag_file')
samp_file = kwargs.get('samp_file', 'er_samples.txt')
specnum = kwargs.get('specnum', 1)
samp_con = kwargs.get('samp_con', '1')
er_location_name = kwargs.get('er_location_name', '')
noave = kwargs.get('noave', 0) # default (0) means DO average
meth_code = kwargs.get('meth_code', "LP-NO")
volume = float(kwargs.get('volume', 0))
if not volume:
volume = 2.5 * 1e-6 #default volume is a 2.5 cm cube, translated to meters cubed
else:
#convert cm^3 to m^3
volume *= 1e-6
# format variables
mag_file = input_dir_path+"/" + mag_file
meas_file = output_dir_path+"/" + meas_file
samp_file = output_dir_path+"/" + samp_file
if specnum!=0:
specnum=-specnum
if "4" in samp_con:
if "-" not in samp_con:
print("option [4] must be in form 4-Z where Z is an integer")
return False, "option [4] must be in form 4-Z where Z is an integer"
else:
Z=samp_con.split("-")[1]
samp_con="4"
if "7" in samp_con:
if "-" not in samp_con:
print("option [7] must be in form 7-Z where Z is an integer")
return False, "option [7] must be in form 7-Z where Z is an integer"
else:
Z=samp_con.split("-")[1]
samp_con="7"
ErSampRec,ErSiteRec={},{}
# parse data
data=open(mag_file,'r')
line=data.readline()
line=data.readline()
line=data.readline()
while line !='':
parsedLine=line.split()
sampleName=parsedLine[0]
demagLevel=parsedLine[2]
date=parsedLine[3]
line=data.readline()
line=data.readline()
line=data.readline()
line=data.readline()
parsedLine=line.split()
specimenAngleDec=parsedLine[1]
specimenAngleInc=parsedLine[2]
while parsedLine[0] != 'MEAN' :
line=data.readline()
parsedLine=line.split()
if len(parsedLine) == 0:
parsedLine=["Hello"]
Mx=parsedLine[1]
My=parsedLine[2]
Mz=parsedLine[3]
line=data.readline()
line=data.readline()
parsedLine=line.split()
splitExp = parsedLine[2].split('A')
intensityVolStr=parsedLine[1] + splitExp[0]
intensityVol = float(intensityVolStr)
# check and see if Prec is too big and messes with the parcing.
precisionStr=''
if len(parsedLine) == 6: #normal line
precisionStr=parsedLine[5][0:-1]
else:
precisionStr=parsedLine[4][0:-1]
precisionPer = float(precisionStr)
precision=intensityVol*precisionPer/100
while parsedLine[0] != 'SPEC.' :
line=data.readline()
parsedLine=line.split()
if len(parsedLine) == 0:
parsedLine=["Hello"]
specimenDec=parsedLine[2]
specimenInc=parsedLine[3]
line=data.readline()
line=data.readline()
parsedLine=line.split()
geographicDec=parsedLine[1]
geographicInc=parsedLine[2]
# Add data to various MagIC data tables.
er_specimen_name = sampleName
if specnum!=0:
er_sample_name=er_specimen_name[:specnum]
else:
er_sample_name=er_specimen_name
if int(samp_con) in [1, 2, 3, 4, 5, 7]:
er_site_name=pmag.parse_site(er_sample_name,samp_con,Z)
else:
print("-W- Using unreognized sample convention option: ", samp_con)
# else:
# if 'er_site_name' in ErSampRec.keys():er_site_name=ErSampRec['er_site_name']
# if 'er_location_name' in ErSampRec.keys():er_location_name=ErSampRec['er_location_name']
# check sample list(SampOuts) to see if sample already exists in list before adding new sample info
sampleFlag=0
for sampRec in SampOuts:
if sampRec['er_sample_name'] == er_sample_name:
sampleFlag=1
break
if sampleFlag == 0:
ErSampRec['er_sample_name']=er_sample_name
ErSampRec['sample_azimuth']=specimenAngleDec
sample_dip=str(float(specimenAngleInc)-90.0) #convert to magic orientation
ErSampRec['sample_dip']=sample_dip
ErSampRec['magic_method_codes']=meth_code
ErSampRec['er_location_name']=er_location_name
ErSampRec['er_site_name']=er_site_name
ErSampRec['er_citation_names']='This study'
SampOuts.append(ErSampRec.copy())
MagRec={}
MagRec['measurement_description']='Date: '+date
MagRec["er_citation_names"]="This study"
MagRec['er_location_name']=er_location_name
MagRec['er_site_name']=er_site_name
MagRec['er_sample_name']=er_sample_name
MagRec['magic_software_packages']=version_num
MagRec["treatment_temp"]='%8.3e' % (273) # room temp in kelvin
MagRec["measurement_temp"]='%8.3e' % (273) # room temp in kelvin
MagRec["measurement_flag"]='g'
MagRec["measurement_standard"]='u'
MagRec["measurement_number"]='1'
MagRec["er_specimen_name"]=er_specimen_name
MagRec["treatment_ac_field"]='0'
if demagLevel == 'NRM':
meas_type="LT-NO"
elif demagLevel[0] == 'A':
meas_type="LT-AF-Z"
treat=float(demagLevel[1:])
MagRec["treatment_ac_field"]='%8.3e' %(treat*1e-3) # convert from mT to tesla
elif demagLevel[0] == 'T':
meas_type="LT-T-Z"
treat=float(demagLevel[1:])
MagRec["treatment_temp"]='%8.3e' % (treat+273.) # temp in kelvin
else:
print("measurement type unknown", demag_level)
return False, "measurement type unknown"
MagRec["measurement_magn_moment"]=str(intensityVol*volume) # Am^2
MagRec["measurement_magn_volume"]=intensityVolStr # A/m
MagRec["measurement_dec"]=specimenDec
MagRec["measurement_inc"]=specimenInc
MagRec['magic_method_codes']=meas_type
MagRecs.append(MagRec.copy())
#read lines till end of record
line=data.readline()
line=data.readline()
line=data.readline()
line=data.readline()
line=data.readline()
# read all the rest of the special characters. Some data files not consistantly formatted.
while (len(line) <=3 and line!=''):
line=data.readline()
#end of data while loop
MagOuts=pmag.measurements_methods(MagRecs,noave)
pmag.magic_write(samp_file,SampOuts,'er_samples')
print("sample orientations put in ",samp_file)
pmag.magic_write(meas_file,MagOuts,'magic_measurements')
print("results put in ",meas_file)
return True, meas_file | python | def main(command_line=True, **kwargs):
"""
NAME
jr6_txt_magic.py
DESCRIPTION
converts JR6 .txt format files to magic_measurements format files
SYNTAX
jr6_txt_magic.py [command line options]
OPTIONS
-h: prints the help message and quits.
-f FILE: specify input file, or
-F FILE: specify output file, default is magic_measurements.txt
-Fsa: specify er_samples format file for appending, default is new er_samples.txt (Not working yet)
-spc NUM : specify number of characters to designate a specimen, default = 1
-loc LOCNAME : specify location/study name
-A: don't average replicate measurements
-ncn NCON: specify sample naming convention (6 and 7 not yet implemented)
-mcd [SO-MAG,SO-SUN,SO-SIGHT...] supply how these samples were oriented
-v NUM : specify the volume of the sample, default 2.5cm^3.
Sample naming convention:
[1] XXXXY: where XXXX is an arbitrary length site designation and Y
is the single character sample designation. e.g., TG001a is the
first sample from site TG001. [default]
[2] XXXX-YY: YY sample from site XXXX (XXX, YY of arbitary length)
[3] XXXX.YY: YY sample from site XXXX (XXX, YY of arbitary length)
[4-Z] XXXX[YYY]: YYY is sample designation with Z characters from site XXX
[5] site name same as sample
[6] site is entered under a separate column NOT CURRENTLY SUPPORTED
[7-Z] [XXXX]YYY: XXXX is site designation with Z characters with sample name XXXXYYYY
NB: all others you will have to customize your self
or e-mail [email protected] for help.
INPUT
JR6 .txt format file
"""
# initialize some stuff
noave=0
volume = 2.5 * 1e-6 # default volume is 2.5 cm^3 (2.5 * 1e-6 meters^3)
inst=""
samp_con,Z='1',""
missing=1
demag="N"
er_location_name="unknown"
citation='This study'
args=sys.argv
meth_code="LP-NO"
specnum=-1
MagRecs=[]
version_num=pmag.get_version()
Samps=[] # keeps track of sample orientations
user=""
mag_file=""
dir_path='.'
ErSamps=[]
SampOuts=[]
samp_file = 'er_samples.txt'
meas_file = 'magic_measurements.txt'
#
# get command line arguments
#
if command_line:
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
if '-ID' in sys.argv:
ind = sys.argv.index('-ID')
input_dir_path = sys.argv[ind+1]
else:
input_dir_path = dir_path
output_dir_path = dir_path
if "-h" in args:
print(main.__doc__)
return False
if '-F' in args:
ind=args.index("-F")
meas_file = args[ind+1]
if '-Fsa' in args:
ind = args.index("-Fsa")
samp_file = args[ind+1]
#try:
# open(samp_file,'r')
# ErSamps,file_type=pmag.magic_read(samp_file)
# print 'sample information will be appended to ', samp_file
#except:
# print samp_file,' not found: sample information will be stored in new er_samples.txt file'
# samp_file = output_dir_path+'/er_samples.txt'
if '-f' in args:
ind = args.index("-f")
mag_file= args[ind+1]
if "-spc" in args:
ind = args.index("-spc")
specnum = int(args[ind+1])
if "-ncn" in args:
ind=args.index("-ncn")
samp_con=sys.argv[ind+1]
if "-loc" in args:
ind=args.index("-loc")
er_location_name=args[ind+1]
if "-A" in args: noave=1
if "-mcd" in args:
ind=args.index("-mcd")
meth_code=args[ind+1]
if "-v" in args:
ind=args.index("-v")
volume=float(args[ind+1]) * 1e-6
if not command_line:
dir_path = kwargs.get('dir_path', '.')
input_dir_path = kwargs.get('input_dir_path', dir_path)
output_dir_path = dir_path
meas_file = kwargs.get('meas_file', 'magic_measurements.txt')
mag_file = kwargs.get('mag_file')
samp_file = kwargs.get('samp_file', 'er_samples.txt')
specnum = kwargs.get('specnum', 1)
samp_con = kwargs.get('samp_con', '1')
er_location_name = kwargs.get('er_location_name', '')
noave = kwargs.get('noave', 0) # default (0) means DO average
meth_code = kwargs.get('meth_code', "LP-NO")
volume = float(kwargs.get('volume', 0))
if not volume:
volume = 2.5 * 1e-6 #default volume is a 2.5 cm cube, translated to meters cubed
else:
#convert cm^3 to m^3
volume *= 1e-6
# format variables
mag_file = input_dir_path+"/" + mag_file
meas_file = output_dir_path+"/" + meas_file
samp_file = output_dir_path+"/" + samp_file
if specnum!=0:
specnum=-specnum
if "4" in samp_con:
if "-" not in samp_con:
print("option [4] must be in form 4-Z where Z is an integer")
return False, "option [4] must be in form 4-Z where Z is an integer"
else:
Z=samp_con.split("-")[1]
samp_con="4"
if "7" in samp_con:
if "-" not in samp_con:
print("option [7] must be in form 7-Z where Z is an integer")
return False, "option [7] must be in form 7-Z where Z is an integer"
else:
Z=samp_con.split("-")[1]
samp_con="7"
ErSampRec,ErSiteRec={},{}
# parse data
data=open(mag_file,'r')
line=data.readline()
line=data.readline()
line=data.readline()
while line !='':
parsedLine=line.split()
sampleName=parsedLine[0]
demagLevel=parsedLine[2]
date=parsedLine[3]
line=data.readline()
line=data.readline()
line=data.readline()
line=data.readline()
parsedLine=line.split()
specimenAngleDec=parsedLine[1]
specimenAngleInc=parsedLine[2]
while parsedLine[0] != 'MEAN' :
line=data.readline()
parsedLine=line.split()
if len(parsedLine) == 0:
parsedLine=["Hello"]
Mx=parsedLine[1]
My=parsedLine[2]
Mz=parsedLine[3]
line=data.readline()
line=data.readline()
parsedLine=line.split()
splitExp = parsedLine[2].split('A')
intensityVolStr=parsedLine[1] + splitExp[0]
intensityVol = float(intensityVolStr)
# check and see if Prec is too big and messes with the parcing.
precisionStr=''
if len(parsedLine) == 6: #normal line
precisionStr=parsedLine[5][0:-1]
else:
precisionStr=parsedLine[4][0:-1]
precisionPer = float(precisionStr)
precision=intensityVol*precisionPer/100
while parsedLine[0] != 'SPEC.' :
line=data.readline()
parsedLine=line.split()
if len(parsedLine) == 0:
parsedLine=["Hello"]
specimenDec=parsedLine[2]
specimenInc=parsedLine[3]
line=data.readline()
line=data.readline()
parsedLine=line.split()
geographicDec=parsedLine[1]
geographicInc=parsedLine[2]
# Add data to various MagIC data tables.
er_specimen_name = sampleName
if specnum!=0:
er_sample_name=er_specimen_name[:specnum]
else:
er_sample_name=er_specimen_name
if int(samp_con) in [1, 2, 3, 4, 5, 7]:
er_site_name=pmag.parse_site(er_sample_name,samp_con,Z)
else:
print("-W- Using unreognized sample convention option: ", samp_con)
# else:
# if 'er_site_name' in ErSampRec.keys():er_site_name=ErSampRec['er_site_name']
# if 'er_location_name' in ErSampRec.keys():er_location_name=ErSampRec['er_location_name']
# check sample list(SampOuts) to see if sample already exists in list before adding new sample info
sampleFlag=0
for sampRec in SampOuts:
if sampRec['er_sample_name'] == er_sample_name:
sampleFlag=1
break
if sampleFlag == 0:
ErSampRec['er_sample_name']=er_sample_name
ErSampRec['sample_azimuth']=specimenAngleDec
sample_dip=str(float(specimenAngleInc)-90.0) #convert to magic orientation
ErSampRec['sample_dip']=sample_dip
ErSampRec['magic_method_codes']=meth_code
ErSampRec['er_location_name']=er_location_name
ErSampRec['er_site_name']=er_site_name
ErSampRec['er_citation_names']='This study'
SampOuts.append(ErSampRec.copy())
MagRec={}
MagRec['measurement_description']='Date: '+date
MagRec["er_citation_names"]="This study"
MagRec['er_location_name']=er_location_name
MagRec['er_site_name']=er_site_name
MagRec['er_sample_name']=er_sample_name
MagRec['magic_software_packages']=version_num
MagRec["treatment_temp"]='%8.3e' % (273) # room temp in kelvin
MagRec["measurement_temp"]='%8.3e' % (273) # room temp in kelvin
MagRec["measurement_flag"]='g'
MagRec["measurement_standard"]='u'
MagRec["measurement_number"]='1'
MagRec["er_specimen_name"]=er_specimen_name
MagRec["treatment_ac_field"]='0'
if demagLevel == 'NRM':
meas_type="LT-NO"
elif demagLevel[0] == 'A':
meas_type="LT-AF-Z"
treat=float(demagLevel[1:])
MagRec["treatment_ac_field"]='%8.3e' %(treat*1e-3) # convert from mT to tesla
elif demagLevel[0] == 'T':
meas_type="LT-T-Z"
treat=float(demagLevel[1:])
MagRec["treatment_temp"]='%8.3e' % (treat+273.) # temp in kelvin
else:
print("measurement type unknown", demag_level)
return False, "measurement type unknown"
MagRec["measurement_magn_moment"]=str(intensityVol*volume) # Am^2
MagRec["measurement_magn_volume"]=intensityVolStr # A/m
MagRec["measurement_dec"]=specimenDec
MagRec["measurement_inc"]=specimenInc
MagRec['magic_method_codes']=meas_type
MagRecs.append(MagRec.copy())
#read lines till end of record
line=data.readline()
line=data.readline()
line=data.readline()
line=data.readline()
line=data.readline()
# read all the rest of the special characters. Some data files not consistantly formatted.
while (len(line) <=3 and line!=''):
line=data.readline()
#end of data while loop
MagOuts=pmag.measurements_methods(MagRecs,noave)
pmag.magic_write(samp_file,SampOuts,'er_samples')
print("sample orientations put in ",samp_file)
pmag.magic_write(meas_file,MagOuts,'magic_measurements')
print("results put in ",meas_file)
return True, meas_file | NAME
jr6_txt_magic.py
DESCRIPTION
converts JR6 .txt format files to magic_measurements format files
SYNTAX
jr6_txt_magic.py [command line options]
OPTIONS
-h: prints the help message and quits.
-f FILE: specify input file, or
-F FILE: specify output file, default is magic_measurements.txt
-Fsa: specify er_samples format file for appending, default is new er_samples.txt (Not working yet)
-spc NUM : specify number of characters to designate a specimen, default = 1
-loc LOCNAME : specify location/study name
-A: don't average replicate measurements
-ncn NCON: specify sample naming convention (6 and 7 not yet implemented)
-mcd [SO-MAG,SO-SUN,SO-SIGHT...] supply how these samples were oriented
-v NUM : specify the volume of the sample, default 2.5cm^3.
Sample naming convention:
[1] XXXXY: where XXXX is an arbitrary length site designation and Y
is the single character sample designation. e.g., TG001a is the
first sample from site TG001. [default]
[2] XXXX-YY: YY sample from site XXXX (XXX, YY of arbitary length)
[3] XXXX.YY: YY sample from site XXXX (XXX, YY of arbitary length)
[4-Z] XXXX[YYY]: YYY is sample designation with Z characters from site XXX
[5] site name same as sample
[6] site is entered under a separate column NOT CURRENTLY SUPPORTED
[7-Z] [XXXX]YYY: XXXX is site designation with Z characters with sample name XXXXYYYY
NB: all others you will have to customize your self
or e-mail [email protected] for help.
INPUT
JR6 .txt format file | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/programs/conversion_scripts2/jr6_txt_magic2.py#L7-L307 |
PmagPy/PmagPy | pmagpy/nlt.py | funk | def funk(p, x, y):
"""
Function misfit evaluation for best-fit tanh curve
f(x[:]) = alpha*tanh(beta*x[:])
alpha = params[0]
beta = params[1]
funk(params) = sqrt(sum((y[:] - f(x[:]))**2)/len(y[:]))
Output is RMS misfit
x=xx[0][:]
y=xx[1][:]q
"""
alpha=p[0]
beta=p[1]
dev=0
for i in range(len(x)):
dev=dev+((y[i]-(alpha*math.tanh(beta*x[i])))**2)
rms=math.sqrt(old_div(dev,float(len(y))))
return rms | python | def funk(p, x, y):
"""
Function misfit evaluation for best-fit tanh curve
f(x[:]) = alpha*tanh(beta*x[:])
alpha = params[0]
beta = params[1]
funk(params) = sqrt(sum((y[:] - f(x[:]))**2)/len(y[:]))
Output is RMS misfit
x=xx[0][:]
y=xx[1][:]q
"""
alpha=p[0]
beta=p[1]
dev=0
for i in range(len(x)):
dev=dev+((y[i]-(alpha*math.tanh(beta*x[i])))**2)
rms=math.sqrt(old_div(dev,float(len(y))))
return rms | Function misfit evaluation for best-fit tanh curve
f(x[:]) = alpha*tanh(beta*x[:])
alpha = params[0]
beta = params[1]
funk(params) = sqrt(sum((y[:] - f(x[:]))**2)/len(y[:]))
Output is RMS misfit
x=xx[0][:]
y=xx[1][:]q | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/nlt.py#L15-L32 |
PmagPy/PmagPy | pmagpy/nlt.py | compare | def compare(a, b):
"""
Compare items in 2 arrays. Returns sum(abs(a(i)-b(i)))
"""
s=0
for i in range(len(a)):
s=s+abs(a[i]-b[i])
return s | python | def compare(a, b):
"""
Compare items in 2 arrays. Returns sum(abs(a(i)-b(i)))
"""
s=0
for i in range(len(a)):
s=s+abs(a[i]-b[i])
return s | Compare items in 2 arrays. Returns sum(abs(a(i)-b(i))) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/nlt.py#L34-L41 |
PmagPy/PmagPy | pmagpy/nlt.py | TRM | def TRM(f,a,b):
"""
Calculate TRM using tanh relationship
TRM(f)=a*math.tanh(b*f)
"""
m = float(a) * math.tanh(float(b) * float(f))
return float(m) | python | def TRM(f,a,b):
"""
Calculate TRM using tanh relationship
TRM(f)=a*math.tanh(b*f)
"""
m = float(a) * math.tanh(float(b) * float(f))
return float(m) | Calculate TRM using tanh relationship
TRM(f)=a*math.tanh(b*f) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/nlt.py#L43-L49 |
PmagPy/PmagPy | pmagpy/nlt.py | TRMinv | def TRMinv(m,a,b):
WARN = True # Warn, rather than stop if I encounter a NaN...
"""
Calculate applied field from TRM using tanh relationship
TRMinv(m)=(1/b)*atanh(m/a)
"""
if float(a)==0:
print('ERROR: TRMinv: a==0.')
if not WARN : sys.exit()
if float(b)==0:
print('ERROR: TRMinv: b==0.')
if not WARN : sys.exit()
x = (old_div(float(m), float(a)))
if (1-x)<=0:
print('ERROR: TRMinv: (1-x)==0.')
return -1
if not WARN : sys.exit()
f = (old_div(1.,float(b))) * 0.5 * math.log (old_div((1+x), (1-x)))
return float(f) | python | def TRMinv(m,a,b):
WARN = True # Warn, rather than stop if I encounter a NaN...
"""
Calculate applied field from TRM using tanh relationship
TRMinv(m)=(1/b)*atanh(m/a)
"""
if float(a)==0:
print('ERROR: TRMinv: a==0.')
if not WARN : sys.exit()
if float(b)==0:
print('ERROR: TRMinv: b==0.')
if not WARN : sys.exit()
x = (old_div(float(m), float(a)))
if (1-x)<=0:
print('ERROR: TRMinv: (1-x)==0.')
return -1
if not WARN : sys.exit()
f = (old_div(1.,float(b))) * 0.5 * math.log (old_div((1+x), (1-x)))
return float(f) | Calculate applied field from TRM using tanh relationship
TRMinv(m)=(1/b)*atanh(m/a) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/nlt.py#L52-L70 |
PmagPy/PmagPy | pmagpy/nlt.py | NRM | def NRM(f,a,b,best):
WARN = True # Warn, rather than stop if I encounter a NaN...
"""
Calculate NRM expected lab field and estimated ancient field
NRM(blab,best)= (best/blab)*TRM(blab)
"""
if float(f)==0:
print('ERROR: NRM: f==0.')
if not WARN : sys.exit()
m = (old_div(float(best),float(f))) * TRM(f,a,b)
return float(m) | python | def NRM(f,a,b,best):
WARN = True # Warn, rather than stop if I encounter a NaN...
"""
Calculate NRM expected lab field and estimated ancient field
NRM(blab,best)= (best/blab)*TRM(blab)
"""
if float(f)==0:
print('ERROR: NRM: f==0.')
if not WARN : sys.exit()
m = (old_div(float(best),float(f))) * TRM(f,a,b)
return float(m) | Calculate NRM expected lab field and estimated ancient field
NRM(blab,best)= (best/blab)*TRM(blab) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/nlt.py#L72-L82 |
PmagPy/PmagPy | programs/plotdi_e.py | main | def main():
"""
NAME
plotdi_e.py
DESCRIPTION
plots equal area projection from dec inc data and cones of confidence
(Fisher, kent or Bingham or bootstrap).
INPUT FORMAT
takes dec/inc as first two columns in space delimited file
SYNTAX
plotdi_e.py [command line options]
OPTIONS
-h prints help message and quits
-i for interactive parameter entry
-f FILE, sets input filename on command line
-Fish plots unit vector mean direction, alpha95
-Bing plots Principal direction, Bingham confidence ellipse
-Kent plots unit vector mean direction, confidence ellipse
-Boot E plots unit vector mean direction, bootstrapped confidence ellipse
-Boot V plots unit vector mean direction, distribution of bootstrapped means
"""
dist='F' # default distribution is Fisherian
mode=1
title=""
EQ={'eq':1}
if len(sys.argv) > 0:
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-i' in sys.argv: # ask for filename
file=input("Enter file name with dec, inc data: ")
dist=input("Enter desired distrubution: [Fish]er, [Bing]ham, [Kent] [Boot] [default is Fisher]: ")
if dist=="":dist="F"
if dist=="Bing":dist="B"
if dist=="Kent":dist="K"
if dist=="Boot":
type=input(" Ellipses or distribution of vectors? [E]/V ")
if type=="" or type=="E":
dist="BE"
else:
dist="BE"
else:
#
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
else:
print('you must specify a file name')
print(main.__doc__)
sys.exit()
if '-Bing' in sys.argv:dist='B'
if '-Kent' in sys.argv:dist='K'
if '-Boot' in sys.argv:
ind=sys.argv.index('-Boot')
type=sys.argv[ind+1]
if type=='E':
dist='BE'
elif type=='V':
dist='BV'
EQ['bdirs']=2
pmagplotlib.plot_init(EQ['bdirs'],5,5)
else:
print(main.__doc__)
sys.exit()
pmagplotlib.plot_init(EQ['eq'],5,5)
#
# get to work
f=open(file,'r')
data=f.readlines()
#
DIs= [] # set up list for dec inc data
DiRecs=[]
pars=[]
nDIs,rDIs,npars,rpars=[],[],[],[]
mode =1
for line in data: # read in the data from standard input
DiRec={}
rec=line.split() # split each line on space to get records
DIs.append((float(rec[0]),float(rec[1]),1.))
DiRec['dec']=rec[0]
DiRec['inc']=rec[1]
DiRec['direction_type']='l'
DiRecs.append(DiRec)
# split into two modes
ppars=pmag.doprinc(DIs) # get principal directions
for rec in DIs:
angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
if angle>90.:
rDIs.append(rec)
else:
nDIs.append(rec)
if dist=='B': # do on whole dataset
title="Bingham confidence ellipse"
bpars=pmag.dobingham(DIs)
for key in list(bpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(bpars[key]))
if key=='n':print(" ",key, ' %i'%(bpars[key]))
npars.append(bpars['dec'])
npars.append(bpars['inc'])
npars.append(bpars['Zeta'])
npars.append(bpars['Zdec'])
npars.append(bpars['Zinc'])
npars.append(bpars['Eta'])
npars.append(bpars['Edec'])
npars.append(bpars['Einc'])
if dist=='F':
title="Fisher confidence cone"
if len(nDIs)>3:
fpars=pmag.fisher_mean(nDIs)
print("mode ",mode)
for key in list(fpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(fpars[key]))
if key=='n':print(" ",key, ' %i'%(fpars[key]))
mode+=1
npars.append(fpars['dec'])
npars.append(fpars['inc'])
npars.append(fpars['alpha95']) # Beta
npars.append(fpars['dec'])
isign=abs(fpars['inc']) / fpars['inc']
npars.append(fpars['inc']-isign*90.) #Beta inc
npars.append(fpars['alpha95']) # gamma
npars.append(fpars['dec']+90.) # Beta dec
npars.append(0.) #Beta inc
if len(rDIs)>3:
fpars=pmag.fisher_mean(rDIs)
print("mode ",mode)
for key in list(fpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(fpars[key]))
if key=='n':print(" ",key, ' %i'%(fpars[key]))
mode+=1
rpars.append(fpars['dec'])
rpars.append(fpars['inc'])
rpars.append(fpars['alpha95']) # Beta
rpars.append(fpars['dec'])
isign=abs(fpars['inc']) / fpars['inc']
rpars.append(fpars['inc']-isign*90.) #Beta inc
rpars.append(fpars['alpha95']) # gamma
rpars.append(fpars['dec']+90.) # Beta dec
rpars.append(0.) #Beta inc
if dist=='K':
title="Kent confidence ellipse"
if len(nDIs)>3:
kpars=pmag.dokent(nDIs,len(nDIs))
print("mode ",mode)
for key in list(kpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(kpars[key]))
if key=='n':print(" ",key, ' %i'%(kpars[key]))
mode+=1
npars.append(kpars['dec'])
npars.append(kpars['inc'])
npars.append(kpars['Zeta'])
npars.append(kpars['Zdec'])
npars.append(kpars['Zinc'])
npars.append(kpars['Eta'])
npars.append(kpars['Edec'])
npars.append(kpars['Einc'])
if len(rDIs)>3:
kpars=pmag.dokent(rDIs,len(rDIs))
print("mode ",mode)
for key in list(kpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(kpars[key]))
if key=='n':print(" ",key, ' %i'%(kpars[key]))
mode+=1
rpars.append(kpars['dec'])
rpars.append(kpars['inc'])
rpars.append(kpars['Zeta'])
rpars.append(kpars['Zdec'])
rpars.append(kpars['Zinc'])
rpars.append(kpars['Eta'])
rpars.append(kpars['Edec'])
rpars.append(kpars['Einc'])
else: # assume bootstrap
if dist=='BE':
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
Bkpars=pmag.dokent(BnDIs,1.)
print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n':print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
npars.append(Bkpars['dec'])
npars.append(Bkpars['inc'])
npars.append(Bkpars['Zeta'])
npars.append(Bkpars['Zdec'])
npars.append(Bkpars['Zinc'])
npars.append(Bkpars['Eta'])
npars.append(Bkpars['Edec'])
npars.append(Bkpars['Einc'])
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
Bkpars=pmag.dokent(BrDIs,1.)
print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n':print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
rpars.append(Bkpars['dec'])
rpars.append(Bkpars['inc'])
rpars.append(Bkpars['Zeta'])
rpars.append(Bkpars['Zdec'])
rpars.append(Bkpars['Zinc'])
rpars.append(Bkpars['Eta'])
rpars.append(Bkpars['Edec'])
rpars.append(Bkpars['Einc'])
title="Bootstrapped confidence ellipse"
elif dist=='BV':
if len(nDIs)>5:
pmagplotlib.plot_eq(EQ['eq'],nDIs,'Data')
BnDIs=pmag.di_boot(nDIs)
pmagplotlib.plot_eq(EQ['bdirs'],BnDIs,'Bootstrapped Eigenvectors')
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
if len(nDIs)>5: # plot on existing plots
pmagplotlib.plot_di(EQ['eq'],rDIs)
pmagplotlib.plot_di(EQ['bdirs'],BrDIs)
else:
pmagplotlib.plot_eq(EQ['eq'],rDIs,'Data')
pmagplotlib.plot_eq(EQ['bdirs'],BrDIs,'Bootstrapped Eigenvectors')
pmagplotlib.draw_figs(EQ)
ans=input('s[a]ve, [q]uit ')
if ans=='q':sys.exit()
if ans=='a':
files={}
for key in list(EQ.keys()):
files[key]='BE_'+key+'.svg'
pmagplotlib.save_plots(EQ,files)
sys.exit()
if len(nDIs)>5:
pmagplotlib.plot_conf(EQ['eq'],title,DiRecs,npars,1)
if len(rDIs)>5 and dist!='B':
pmagplotlib.plot_conf(EQ['eq'],title,[],rpars,0)
elif len(rDIs)>5 and dist!='B':
pmagplotlib.plot_conf(EQ['eq'],title,DiRecs,rpars,1)
pmagplotlib.draw_figs(EQ)
ans=input('s[a]ve, [q]uit ')
if ans=='q':sys.exit()
if ans=='a':
files={}
for key in list(EQ.keys()):
files[key]=key+'.svg'
pmagplotlib.save_plots(EQ,files) | python | def main():
"""
NAME
plotdi_e.py
DESCRIPTION
plots equal area projection from dec inc data and cones of confidence
(Fisher, kent or Bingham or bootstrap).
INPUT FORMAT
takes dec/inc as first two columns in space delimited file
SYNTAX
plotdi_e.py [command line options]
OPTIONS
-h prints help message and quits
-i for interactive parameter entry
-f FILE, sets input filename on command line
-Fish plots unit vector mean direction, alpha95
-Bing plots Principal direction, Bingham confidence ellipse
-Kent plots unit vector mean direction, confidence ellipse
-Boot E plots unit vector mean direction, bootstrapped confidence ellipse
-Boot V plots unit vector mean direction, distribution of bootstrapped means
"""
dist='F' # default distribution is Fisherian
mode=1
title=""
EQ={'eq':1}
if len(sys.argv) > 0:
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-i' in sys.argv: # ask for filename
file=input("Enter file name with dec, inc data: ")
dist=input("Enter desired distrubution: [Fish]er, [Bing]ham, [Kent] [Boot] [default is Fisher]: ")
if dist=="":dist="F"
if dist=="Bing":dist="B"
if dist=="Kent":dist="K"
if dist=="Boot":
type=input(" Ellipses or distribution of vectors? [E]/V ")
if type=="" or type=="E":
dist="BE"
else:
dist="BE"
else:
#
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
else:
print('you must specify a file name')
print(main.__doc__)
sys.exit()
if '-Bing' in sys.argv:dist='B'
if '-Kent' in sys.argv:dist='K'
if '-Boot' in sys.argv:
ind=sys.argv.index('-Boot')
type=sys.argv[ind+1]
if type=='E':
dist='BE'
elif type=='V':
dist='BV'
EQ['bdirs']=2
pmagplotlib.plot_init(EQ['bdirs'],5,5)
else:
print(main.__doc__)
sys.exit()
pmagplotlib.plot_init(EQ['eq'],5,5)
#
# get to work
f=open(file,'r')
data=f.readlines()
#
DIs= [] # set up list for dec inc data
DiRecs=[]
pars=[]
nDIs,rDIs,npars,rpars=[],[],[],[]
mode =1
for line in data: # read in the data from standard input
DiRec={}
rec=line.split() # split each line on space to get records
DIs.append((float(rec[0]),float(rec[1]),1.))
DiRec['dec']=rec[0]
DiRec['inc']=rec[1]
DiRec['direction_type']='l'
DiRecs.append(DiRec)
# split into two modes
ppars=pmag.doprinc(DIs) # get principal directions
for rec in DIs:
angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
if angle>90.:
rDIs.append(rec)
else:
nDIs.append(rec)
if dist=='B': # do on whole dataset
title="Bingham confidence ellipse"
bpars=pmag.dobingham(DIs)
for key in list(bpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(bpars[key]))
if key=='n':print(" ",key, ' %i'%(bpars[key]))
npars.append(bpars['dec'])
npars.append(bpars['inc'])
npars.append(bpars['Zeta'])
npars.append(bpars['Zdec'])
npars.append(bpars['Zinc'])
npars.append(bpars['Eta'])
npars.append(bpars['Edec'])
npars.append(bpars['Einc'])
if dist=='F':
title="Fisher confidence cone"
if len(nDIs)>3:
fpars=pmag.fisher_mean(nDIs)
print("mode ",mode)
for key in list(fpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(fpars[key]))
if key=='n':print(" ",key, ' %i'%(fpars[key]))
mode+=1
npars.append(fpars['dec'])
npars.append(fpars['inc'])
npars.append(fpars['alpha95']) # Beta
npars.append(fpars['dec'])
isign=abs(fpars['inc']) / fpars['inc']
npars.append(fpars['inc']-isign*90.) #Beta inc
npars.append(fpars['alpha95']) # gamma
npars.append(fpars['dec']+90.) # Beta dec
npars.append(0.) #Beta inc
if len(rDIs)>3:
fpars=pmag.fisher_mean(rDIs)
print("mode ",mode)
for key in list(fpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(fpars[key]))
if key=='n':print(" ",key, ' %i'%(fpars[key]))
mode+=1
rpars.append(fpars['dec'])
rpars.append(fpars['inc'])
rpars.append(fpars['alpha95']) # Beta
rpars.append(fpars['dec'])
isign=abs(fpars['inc']) / fpars['inc']
rpars.append(fpars['inc']-isign*90.) #Beta inc
rpars.append(fpars['alpha95']) # gamma
rpars.append(fpars['dec']+90.) # Beta dec
rpars.append(0.) #Beta inc
if dist=='K':
title="Kent confidence ellipse"
if len(nDIs)>3:
kpars=pmag.dokent(nDIs,len(nDIs))
print("mode ",mode)
for key in list(kpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(kpars[key]))
if key=='n':print(" ",key, ' %i'%(kpars[key]))
mode+=1
npars.append(kpars['dec'])
npars.append(kpars['inc'])
npars.append(kpars['Zeta'])
npars.append(kpars['Zdec'])
npars.append(kpars['Zinc'])
npars.append(kpars['Eta'])
npars.append(kpars['Edec'])
npars.append(kpars['Einc'])
if len(rDIs)>3:
kpars=pmag.dokent(rDIs,len(rDIs))
print("mode ",mode)
for key in list(kpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(kpars[key]))
if key=='n':print(" ",key, ' %i'%(kpars[key]))
mode+=1
rpars.append(kpars['dec'])
rpars.append(kpars['inc'])
rpars.append(kpars['Zeta'])
rpars.append(kpars['Zdec'])
rpars.append(kpars['Zinc'])
rpars.append(kpars['Eta'])
rpars.append(kpars['Edec'])
rpars.append(kpars['Einc'])
else: # assume bootstrap
if dist=='BE':
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
Bkpars=pmag.dokent(BnDIs,1.)
print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n':print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
npars.append(Bkpars['dec'])
npars.append(Bkpars['inc'])
npars.append(Bkpars['Zeta'])
npars.append(Bkpars['Zdec'])
npars.append(Bkpars['Zinc'])
npars.append(Bkpars['Eta'])
npars.append(Bkpars['Edec'])
npars.append(Bkpars['Einc'])
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
Bkpars=pmag.dokent(BrDIs,1.)
print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n':print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n':print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
rpars.append(Bkpars['dec'])
rpars.append(Bkpars['inc'])
rpars.append(Bkpars['Zeta'])
rpars.append(Bkpars['Zdec'])
rpars.append(Bkpars['Zinc'])
rpars.append(Bkpars['Eta'])
rpars.append(Bkpars['Edec'])
rpars.append(Bkpars['Einc'])
title="Bootstrapped confidence ellipse"
elif dist=='BV':
if len(nDIs)>5:
pmagplotlib.plot_eq(EQ['eq'],nDIs,'Data')
BnDIs=pmag.di_boot(nDIs)
pmagplotlib.plot_eq(EQ['bdirs'],BnDIs,'Bootstrapped Eigenvectors')
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
if len(nDIs)>5: # plot on existing plots
pmagplotlib.plot_di(EQ['eq'],rDIs)
pmagplotlib.plot_di(EQ['bdirs'],BrDIs)
else:
pmagplotlib.plot_eq(EQ['eq'],rDIs,'Data')
pmagplotlib.plot_eq(EQ['bdirs'],BrDIs,'Bootstrapped Eigenvectors')
pmagplotlib.draw_figs(EQ)
ans=input('s[a]ve, [q]uit ')
if ans=='q':sys.exit()
if ans=='a':
files={}
for key in list(EQ.keys()):
files[key]='BE_'+key+'.svg'
pmagplotlib.save_plots(EQ,files)
sys.exit()
if len(nDIs)>5:
pmagplotlib.plot_conf(EQ['eq'],title,DiRecs,npars,1)
if len(rDIs)>5 and dist!='B':
pmagplotlib.plot_conf(EQ['eq'],title,[],rpars,0)
elif len(rDIs)>5 and dist!='B':
pmagplotlib.plot_conf(EQ['eq'],title,DiRecs,rpars,1)
pmagplotlib.draw_figs(EQ)
ans=input('s[a]ve, [q]uit ')
if ans=='q':sys.exit()
if ans=='a':
files={}
for key in list(EQ.keys()):
files[key]=key+'.svg'
pmagplotlib.save_plots(EQ,files) | NAME
plotdi_e.py
DESCRIPTION
plots equal area projection from dec inc data and cones of confidence
(Fisher, kent or Bingham or bootstrap).
INPUT FORMAT
takes dec/inc as first two columns in space delimited file
SYNTAX
plotdi_e.py [command line options]
OPTIONS
-h prints help message and quits
-i for interactive parameter entry
-f FILE, sets input filename on command line
-Fish plots unit vector mean direction, alpha95
-Bing plots Principal direction, Bingham confidence ellipse
-Kent plots unit vector mean direction, confidence ellipse
-Boot E plots unit vector mean direction, bootstrapped confidence ellipse
-Boot V plots unit vector mean direction, distribution of bootstrapped means | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/programs/plotdi_e.py#L11-L257 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.init_UI | def init_UI(self):
"""
Builds User Interface for the interpretation Editor
"""
#set fonts
FONT_WEIGHT=1
if sys.platform.startswith('win'): FONT_WEIGHT=-1
font1 = wx.Font(9+FONT_WEIGHT, wx.SWISS, wx.NORMAL, wx.NORMAL, False, self.font_type)
font2 = wx.Font(12+FONT_WEIGHT, wx.SWISS, wx.NORMAL, wx.NORMAL, False, self.font_type)
#if you're on mac do some funny stuff to make it look okay
is_mac = False
if sys.platform.startswith("darwin"):
is_mac = True
self.search_bar = wx.SearchCtrl(self.panel, size=(350*self.GUI_RESOLUTION,25) ,style=wx.TE_PROCESS_ENTER | wx.TE_PROCESS_TAB | wx.TE_NOHIDESEL)
self.Bind(wx.EVT_TEXT_ENTER, self.on_enter_search_bar,self.search_bar)
self.Bind(wx.EVT_SEARCHCTRL_SEARCH_BTN, self.on_enter_search_bar,self.search_bar)
self.search_bar.SetHelpText(dieh.search_help)
# self.Bind(wx.EVT_TEXT, self.on_complete_search_bar,self.search_bar)
#build logger
self.logger = wx.ListCtrl(self.panel, -1, size=(100*self.GUI_RESOLUTION,475*self.GUI_RESOLUTION),style=wx.LC_REPORT)
self.logger.SetFont(font1)
self.logger.InsertColumn(0, 'specimen',width=75*self.GUI_RESOLUTION)
self.logger.InsertColumn(1, 'fit name',width=65*self.GUI_RESOLUTION)
self.logger.InsertColumn(2, 'max',width=55*self.GUI_RESOLUTION)
self.logger.InsertColumn(3, 'min',width=55*self.GUI_RESOLUTION)
self.logger.InsertColumn(4, 'n',width=25*self.GUI_RESOLUTION)
self.logger.InsertColumn(5, 'fit type',width=60*self.GUI_RESOLUTION)
self.logger.InsertColumn(6, 'dec',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(7, 'inc',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(8, 'mad',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(9, 'dang',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(10, 'a95',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(11, 'K',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(12, 'R',width=45*self.GUI_RESOLUTION)
self.Bind(wx.EVT_LIST_ITEM_ACTIVATED, self.OnClick_listctrl, self.logger)
self.Bind(wx.EVT_LIST_ITEM_RIGHT_CLICK,self.OnRightClickListctrl,self.logger)
self.logger.SetHelpText(dieh.logger_help)
#set fit attributes boxsizers
self.display_sizer = wx.StaticBoxSizer(wx.StaticBox(self.panel, wx.ID_ANY, "display options"), wx.HORIZONTAL)
self.name_sizer = wx.StaticBoxSizer(wx.StaticBox(self.panel, wx.ID_ANY, "fit name/color"), wx.VERTICAL)
self.bounds_sizer = wx.StaticBoxSizer(wx.StaticBox(self.panel, wx.ID_ANY, "fit bounds"), wx.VERTICAL)
self.buttons_sizer = wx.StaticBoxSizer(wx.StaticBox(self.panel, wx.ID_ANY), wx.VERTICAL)
#logger display selection box
UPPER_LEVEL = self.parent.level_box.GetValue()
if UPPER_LEVEL=='sample':
name_choices = self.parent.samples
if UPPER_LEVEL=='site':
name_choices = self.parent.sites
if UPPER_LEVEL=='location':
name_choices = self.parent.locations
if UPPER_LEVEL=='study':
name_choices = ['this study']
self.level_box = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), value=UPPER_LEVEL, choices=['sample','site','location','study'], style=wx.CB_DROPDOWN|wx.TE_READONLY)
self.Bind(wx.EVT_COMBOBOX, self.on_select_high_level,self.level_box)
self.level_box.SetHelpText(dieh.level_box_help)
self.level_names = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), value=self.parent.level_names.GetValue(), choices=name_choices, style=wx.CB_DROPDOWN|wx.TE_READONLY)
self.Bind(wx.EVT_COMBOBOX, self.on_select_level_name,self.level_names)
self.level_names.SetHelpText(dieh.level_names_help)
#mean type and plot display boxes
self.mean_type_box = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), value=self.parent.mean_type_box.GetValue(), choices=['Fisher','Fisher by polarity','None'], style=wx.CB_DROPDOWN|wx.TE_READONLY, name="high_type")
self.Bind(wx.EVT_COMBOBOX, self.on_select_mean_type_box,self.mean_type_box)
self.mean_type_box.SetHelpText(dieh.mean_type_help)
self.mean_fit_box = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), value=self.parent.mean_fit, choices=(['None','All'] + self.parent.fit_list), style=wx.CB_DROPDOWN|wx.TE_READONLY, name="high_type")
self.Bind(wx.EVT_COMBOBOX, self.on_select_mean_fit_box,self.mean_fit_box)
self.mean_fit_box.SetHelpText(dieh.mean_fit_help)
#show box
if UPPER_LEVEL == "study" or UPPER_LEVEL == "location":
show_box_choices = ['specimens','samples','sites']
if UPPER_LEVEL == "site":
show_box_choices = ['specimens','samples']
if UPPER_LEVEL == "sample":
show_box_choices = ['specimens']
self.show_box = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), value='specimens', choices=show_box_choices, style=wx.CB_DROPDOWN|wx.TE_READONLY,name="high_elements")
self.Bind(wx.EVT_COMBOBOX, self.on_select_show_box,self.show_box)
self.show_box.SetHelpText(dieh.show_help)
#coordinates box
self.coordinates_box = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), choices=self.parent.coordinate_list, value=self.parent.coordinates_box.GetValue(), style=wx.CB_DROPDOWN|wx.TE_READONLY, name="coordinates")
self.Bind(wx.EVT_COMBOBOX, self.on_select_coordinates,self.coordinates_box)
self.coordinates_box.SetHelpText(dieh.coordinates_box_help)
#bounds select boxes
self.tmin_box = wx.ComboBox(self.panel, -1, size=(80*self.GUI_RESOLUTION, 25), choices=[''] + self.parent.T_list, style=wx.CB_DROPDOWN|wx.TE_READONLY, name="lower bound")
self.tmin_box.SetHelpText(dieh.tmin_box_help)
self.tmax_box = wx.ComboBox(self.panel, -1, size=(80*self.GUI_RESOLUTION, 25), choices=[''] + self.parent.T_list, style=wx.CB_DROPDOWN|wx.TE_READONLY, name="upper bound")
self.tmax_box.SetHelpText(dieh.tmax_box_help)
#color box
self.color_dict = self.parent.color_dict
self.color_box = wx.ComboBox(self.panel, -1, size=(80*self.GUI_RESOLUTION, 25), choices=[''] + sorted(self.color_dict.keys()), style=wx.CB_DROPDOWN|wx.TE_PROCESS_ENTER, name="color")
self.Bind(wx.EVT_TEXT_ENTER, self.add_new_color, self.color_box)
self.color_box.SetHelpText(dieh.color_box_help)
#name box
self.name_box = wx.TextCtrl(self.panel, -1, size=(80*self.GUI_RESOLUTION, 25), name="name")
self.name_box.SetHelpText(dieh.name_box_help)
#more mac stuff
h_size_buttons,button_spacing = 25,5.5
if is_mac: h_size_buttons,button_spacing = 18,0.
#buttons
self.add_all_button = wx.Button(self.panel, id=-1, label='add new fit to all specimens',size=(160*self.GUI_RESOLUTION,h_size_buttons))
self.add_all_button.SetFont(font1)
self.Bind(wx.EVT_BUTTON, self.add_fit_to_all, self.add_all_button)
self.add_all_button.SetHelpText(dieh.add_all_help)
self.add_fit_button = wx.Button(self.panel, id=-1, label='add fit to highlighted specimens',size=(160*self.GUI_RESOLUTION,h_size_buttons))
self.add_fit_button.SetFont(font1)
self.Bind(wx.EVT_BUTTON, self.add_highlighted_fits, self.add_fit_button)
self.add_fit_button.SetHelpText(dieh.add_fit_btn_help)
self.delete_fit_button = wx.Button(self.panel, id=-1, label='delete highlighted fits',size=(160*self.GUI_RESOLUTION,h_size_buttons))
self.delete_fit_button.SetFont(font1)
self.Bind(wx.EVT_BUTTON, self.delete_highlighted_fits, self.delete_fit_button)
self.delete_fit_button.SetHelpText(dieh.delete_fit_btn_help)
self.apply_changes_button = wx.Button(self.panel, id=-1, label='apply changes to highlighted fits',size=(160*self.GUI_RESOLUTION,h_size_buttons))
self.apply_changes_button.SetFont(font1)
self.Bind(wx.EVT_BUTTON, self.apply_changes, self.apply_changes_button)
self.apply_changes_button.SetHelpText(dieh.apply_changes_help)
#windows
display_window_0 = wx.GridSizer(2, 1, 10*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
display_window_1 = wx.GridSizer(2, 1, 10*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
display_window_2 = wx.GridSizer(2, 1, 10*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
name_window = wx.GridSizer(2, 1, 10*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
bounds_window = wx.GridSizer(2, 1, 10*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
buttons1_window = wx.GridSizer(4, 1, 5*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
display_window_0.AddMany( [(self.coordinates_box, wx.ALIGN_LEFT),
(self.show_box, wx.ALIGN_LEFT)] )
display_window_1.AddMany( [(self.level_box, wx.ALIGN_LEFT),
(self.level_names, wx.ALIGN_LEFT)] )
display_window_2.AddMany( [(self.mean_type_box, wx.ALIGN_LEFT),
(self.mean_fit_box, wx.ALIGN_LEFT)] )
name_window.AddMany( [(self.name_box, wx.ALIGN_LEFT),
(self.color_box, wx.ALIGN_LEFT)] )
bounds_window.AddMany( [(self.tmin_box, wx.ALIGN_LEFT),
(self.tmax_box, wx.ALIGN_LEFT)] )
buttons1_window.AddMany( [(self.add_fit_button, wx.ALL|wx.ALIGN_CENTER|wx.SHAPED, 0),
(self.add_all_button, wx.ALL|wx.ALIGN_CENTER|wx.SHAPED, 0),
(self.delete_fit_button, wx.ALL|wx.ALIGN_CENTER|wx.SHAPED, 0),
(self.apply_changes_button, wx.ALL|wx.ALIGN_CENTER|wx.SHAPED, 0)])
self.display_sizer.Add(display_window_0, 1, wx.TOP|wx.EXPAND, 8)
self.display_sizer.Add(display_window_1, 1, wx.TOP | wx.LEFT|wx.EXPAND, 8)
self.display_sizer.Add(display_window_2, 1, wx.TOP | wx.LEFT|wx.EXPAND, 8)
self.name_sizer.Add(name_window, 1, wx.TOP, 5.5)
self.bounds_sizer.Add(bounds_window, 1, wx.TOP, 5.5)
self.buttons_sizer.Add(buttons1_window, 1, wx.TOP, 0)
#duplicate high levels plot
self.fig = Figure((2.5*self.GUI_RESOLUTION, 2.5*self.GUI_RESOLUTION), dpi=100)
self.canvas = FigCanvas(self.panel, -1, self.fig, )
self.toolbar = NavigationToolbar(self.canvas)
self.toolbar.Hide()
self.toolbar.zoom()
self.high_EA_setting = "Zoom"
self.canvas.Bind(wx.EVT_LEFT_DCLICK,self.on_equalarea_high_select)
self.canvas.Bind(wx.EVT_MOTION,self.on_change_high_mouse_cursor)
self.canvas.Bind(wx.EVT_MIDDLE_DOWN,self.home_high_equalarea)
self.canvas.Bind(wx.EVT_RIGHT_DOWN,self.pan_zoom_high_equalarea)
self.canvas.SetHelpText(dieh.eqarea_help)
self.eqarea = self.fig.add_subplot(111)
draw_net(self.eqarea)
#Higher Level Statistics Box
self.stats_sizer = wx.StaticBoxSizer( wx.StaticBox( self.panel, wx.ID_ANY,"mean statistics" ), wx.VERTICAL)
for parameter in ['mean_type','dec','inc','alpha95','K','R','n_lines','n_planes']:
COMMAND="self.%s_window=wx.TextCtrl(self.panel,style=wx.TE_CENTER|wx.TE_READONLY,size=(100*self.GUI_RESOLUTION,25))"%parameter
exec(COMMAND)
COMMAND="self.%s_window.SetBackgroundColour(wx.WHITE)"%parameter
exec(COMMAND)
COMMAND="self.%s_window.SetFont(font2)"%parameter
exec(COMMAND)
COMMAND="self.%s_outer_window = wx.GridSizer(1,2,5*self.GUI_RESOLUTION,15*self.GUI_RESOLUTION)"%parameter
exec(COMMAND)
COMMAND="""self.%s_outer_window.AddMany([
(wx.StaticText(self.panel,label='%s',style=wx.TE_CENTER),wx.EXPAND),
(self.%s_window, wx.EXPAND)])"""%(parameter,parameter,parameter)
exec(COMMAND)
COMMAND="self.stats_sizer.Add(self.%s_outer_window, 1, wx.ALIGN_LEFT|wx.EXPAND, 0)"%parameter
exec(COMMAND)
self.switch_stats_button = wx.SpinButton(self.panel, id=wx.ID_ANY, style=wx.SP_HORIZONTAL|wx.SP_ARROW_KEYS|wx.SP_WRAP, name="change stats")
self.Bind(wx.EVT_SPIN, self.on_select_stats_button,self.switch_stats_button)
self.switch_stats_button.SetHelpText(dieh.switch_stats_btn_help)
#construct panel
hbox0 = wx.BoxSizer(wx.HORIZONTAL)
hbox0.Add(self.name_sizer,flag=wx.ALIGN_TOP|wx.EXPAND,border=8)
hbox0.Add(self.bounds_sizer,flag=wx.ALIGN_TOP|wx.EXPAND,border=8)
vbox0 = wx.BoxSizer(wx.VERTICAL)
vbox0.Add(hbox0,flag=wx.ALIGN_TOP,border=8)
vbox0.Add(self.buttons_sizer,flag=wx.ALIGN_TOP,border=8)
hbox1 = wx.BoxSizer(wx.HORIZONTAL)
hbox1.Add(vbox0,flag=wx.ALIGN_TOP,border=8)
hbox1.Add(self.stats_sizer,flag=wx.ALIGN_TOP,border=8)
hbox1.Add(self.switch_stats_button,flag=wx.ALIGN_TOP|wx.EXPAND,border=8)
vbox1 = wx.BoxSizer(wx.VERTICAL)
vbox1.Add(self.display_sizer,flag=wx.ALIGN_TOP,border=8)
vbox1.Add(hbox1,flag=wx.ALIGN_TOP,border=8)
vbox1.Add(self.canvas,proportion=1,flag=wx.ALIGN_CENTER_HORIZONTAL | wx.ALIGN_CENTER_VERTICAL | wx.EXPAND,border=8)
vbox2 = wx.BoxSizer(wx.VERTICAL)
vbox2.Add(self.search_bar,proportion=.5,flag=wx.ALIGN_LEFT | wx.ALIGN_BOTTOM | wx.EXPAND, border=8)
vbox2.Add(self.logger,proportion=1,flag=wx.ALIGN_LEFT|wx.EXPAND,border=8)
hbox2 = wx.BoxSizer(wx.HORIZONTAL)
hbox2.Add(vbox2,proportion=1,flag=wx.ALIGN_LEFT|wx.EXPAND)
hbox2.Add(vbox1,flag=wx.ALIGN_TOP|wx.EXPAND)
self.panel.SetSizerAndFit(hbox2)
hbox2.Fit(self) | python | def init_UI(self):
"""
Builds User Interface for the interpretation Editor
"""
#set fonts
FONT_WEIGHT=1
if sys.platform.startswith('win'): FONT_WEIGHT=-1
font1 = wx.Font(9+FONT_WEIGHT, wx.SWISS, wx.NORMAL, wx.NORMAL, False, self.font_type)
font2 = wx.Font(12+FONT_WEIGHT, wx.SWISS, wx.NORMAL, wx.NORMAL, False, self.font_type)
#if you're on mac do some funny stuff to make it look okay
is_mac = False
if sys.platform.startswith("darwin"):
is_mac = True
self.search_bar = wx.SearchCtrl(self.panel, size=(350*self.GUI_RESOLUTION,25) ,style=wx.TE_PROCESS_ENTER | wx.TE_PROCESS_TAB | wx.TE_NOHIDESEL)
self.Bind(wx.EVT_TEXT_ENTER, self.on_enter_search_bar,self.search_bar)
self.Bind(wx.EVT_SEARCHCTRL_SEARCH_BTN, self.on_enter_search_bar,self.search_bar)
self.search_bar.SetHelpText(dieh.search_help)
# self.Bind(wx.EVT_TEXT, self.on_complete_search_bar,self.search_bar)
#build logger
self.logger = wx.ListCtrl(self.panel, -1, size=(100*self.GUI_RESOLUTION,475*self.GUI_RESOLUTION),style=wx.LC_REPORT)
self.logger.SetFont(font1)
self.logger.InsertColumn(0, 'specimen',width=75*self.GUI_RESOLUTION)
self.logger.InsertColumn(1, 'fit name',width=65*self.GUI_RESOLUTION)
self.logger.InsertColumn(2, 'max',width=55*self.GUI_RESOLUTION)
self.logger.InsertColumn(3, 'min',width=55*self.GUI_RESOLUTION)
self.logger.InsertColumn(4, 'n',width=25*self.GUI_RESOLUTION)
self.logger.InsertColumn(5, 'fit type',width=60*self.GUI_RESOLUTION)
self.logger.InsertColumn(6, 'dec',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(7, 'inc',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(8, 'mad',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(9, 'dang',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(10, 'a95',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(11, 'K',width=45*self.GUI_RESOLUTION)
self.logger.InsertColumn(12, 'R',width=45*self.GUI_RESOLUTION)
self.Bind(wx.EVT_LIST_ITEM_ACTIVATED, self.OnClick_listctrl, self.logger)
self.Bind(wx.EVT_LIST_ITEM_RIGHT_CLICK,self.OnRightClickListctrl,self.logger)
self.logger.SetHelpText(dieh.logger_help)
#set fit attributes boxsizers
self.display_sizer = wx.StaticBoxSizer(wx.StaticBox(self.panel, wx.ID_ANY, "display options"), wx.HORIZONTAL)
self.name_sizer = wx.StaticBoxSizer(wx.StaticBox(self.panel, wx.ID_ANY, "fit name/color"), wx.VERTICAL)
self.bounds_sizer = wx.StaticBoxSizer(wx.StaticBox(self.panel, wx.ID_ANY, "fit bounds"), wx.VERTICAL)
self.buttons_sizer = wx.StaticBoxSizer(wx.StaticBox(self.panel, wx.ID_ANY), wx.VERTICAL)
#logger display selection box
UPPER_LEVEL = self.parent.level_box.GetValue()
if UPPER_LEVEL=='sample':
name_choices = self.parent.samples
if UPPER_LEVEL=='site':
name_choices = self.parent.sites
if UPPER_LEVEL=='location':
name_choices = self.parent.locations
if UPPER_LEVEL=='study':
name_choices = ['this study']
self.level_box = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), value=UPPER_LEVEL, choices=['sample','site','location','study'], style=wx.CB_DROPDOWN|wx.TE_READONLY)
self.Bind(wx.EVT_COMBOBOX, self.on_select_high_level,self.level_box)
self.level_box.SetHelpText(dieh.level_box_help)
self.level_names = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), value=self.parent.level_names.GetValue(), choices=name_choices, style=wx.CB_DROPDOWN|wx.TE_READONLY)
self.Bind(wx.EVT_COMBOBOX, self.on_select_level_name,self.level_names)
self.level_names.SetHelpText(dieh.level_names_help)
#mean type and plot display boxes
self.mean_type_box = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), value=self.parent.mean_type_box.GetValue(), choices=['Fisher','Fisher by polarity','None'], style=wx.CB_DROPDOWN|wx.TE_READONLY, name="high_type")
self.Bind(wx.EVT_COMBOBOX, self.on_select_mean_type_box,self.mean_type_box)
self.mean_type_box.SetHelpText(dieh.mean_type_help)
self.mean_fit_box = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), value=self.parent.mean_fit, choices=(['None','All'] + self.parent.fit_list), style=wx.CB_DROPDOWN|wx.TE_READONLY, name="high_type")
self.Bind(wx.EVT_COMBOBOX, self.on_select_mean_fit_box,self.mean_fit_box)
self.mean_fit_box.SetHelpText(dieh.mean_fit_help)
#show box
if UPPER_LEVEL == "study" or UPPER_LEVEL == "location":
show_box_choices = ['specimens','samples','sites']
if UPPER_LEVEL == "site":
show_box_choices = ['specimens','samples']
if UPPER_LEVEL == "sample":
show_box_choices = ['specimens']
self.show_box = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), value='specimens', choices=show_box_choices, style=wx.CB_DROPDOWN|wx.TE_READONLY,name="high_elements")
self.Bind(wx.EVT_COMBOBOX, self.on_select_show_box,self.show_box)
self.show_box.SetHelpText(dieh.show_help)
#coordinates box
self.coordinates_box = wx.ComboBox(self.panel, -1, size=(110*self.GUI_RESOLUTION, 25), choices=self.parent.coordinate_list, value=self.parent.coordinates_box.GetValue(), style=wx.CB_DROPDOWN|wx.TE_READONLY, name="coordinates")
self.Bind(wx.EVT_COMBOBOX, self.on_select_coordinates,self.coordinates_box)
self.coordinates_box.SetHelpText(dieh.coordinates_box_help)
#bounds select boxes
self.tmin_box = wx.ComboBox(self.panel, -1, size=(80*self.GUI_RESOLUTION, 25), choices=[''] + self.parent.T_list, style=wx.CB_DROPDOWN|wx.TE_READONLY, name="lower bound")
self.tmin_box.SetHelpText(dieh.tmin_box_help)
self.tmax_box = wx.ComboBox(self.panel, -1, size=(80*self.GUI_RESOLUTION, 25), choices=[''] + self.parent.T_list, style=wx.CB_DROPDOWN|wx.TE_READONLY, name="upper bound")
self.tmax_box.SetHelpText(dieh.tmax_box_help)
#color box
self.color_dict = self.parent.color_dict
self.color_box = wx.ComboBox(self.panel, -1, size=(80*self.GUI_RESOLUTION, 25), choices=[''] + sorted(self.color_dict.keys()), style=wx.CB_DROPDOWN|wx.TE_PROCESS_ENTER, name="color")
self.Bind(wx.EVT_TEXT_ENTER, self.add_new_color, self.color_box)
self.color_box.SetHelpText(dieh.color_box_help)
#name box
self.name_box = wx.TextCtrl(self.panel, -1, size=(80*self.GUI_RESOLUTION, 25), name="name")
self.name_box.SetHelpText(dieh.name_box_help)
#more mac stuff
h_size_buttons,button_spacing = 25,5.5
if is_mac: h_size_buttons,button_spacing = 18,0.
#buttons
self.add_all_button = wx.Button(self.panel, id=-1, label='add new fit to all specimens',size=(160*self.GUI_RESOLUTION,h_size_buttons))
self.add_all_button.SetFont(font1)
self.Bind(wx.EVT_BUTTON, self.add_fit_to_all, self.add_all_button)
self.add_all_button.SetHelpText(dieh.add_all_help)
self.add_fit_button = wx.Button(self.panel, id=-1, label='add fit to highlighted specimens',size=(160*self.GUI_RESOLUTION,h_size_buttons))
self.add_fit_button.SetFont(font1)
self.Bind(wx.EVT_BUTTON, self.add_highlighted_fits, self.add_fit_button)
self.add_fit_button.SetHelpText(dieh.add_fit_btn_help)
self.delete_fit_button = wx.Button(self.panel, id=-1, label='delete highlighted fits',size=(160*self.GUI_RESOLUTION,h_size_buttons))
self.delete_fit_button.SetFont(font1)
self.Bind(wx.EVT_BUTTON, self.delete_highlighted_fits, self.delete_fit_button)
self.delete_fit_button.SetHelpText(dieh.delete_fit_btn_help)
self.apply_changes_button = wx.Button(self.panel, id=-1, label='apply changes to highlighted fits',size=(160*self.GUI_RESOLUTION,h_size_buttons))
self.apply_changes_button.SetFont(font1)
self.Bind(wx.EVT_BUTTON, self.apply_changes, self.apply_changes_button)
self.apply_changes_button.SetHelpText(dieh.apply_changes_help)
#windows
display_window_0 = wx.GridSizer(2, 1, 10*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
display_window_1 = wx.GridSizer(2, 1, 10*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
display_window_2 = wx.GridSizer(2, 1, 10*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
name_window = wx.GridSizer(2, 1, 10*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
bounds_window = wx.GridSizer(2, 1, 10*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
buttons1_window = wx.GridSizer(4, 1, 5*self.GUI_RESOLUTION, 19*self.GUI_RESOLUTION)
display_window_0.AddMany( [(self.coordinates_box, wx.ALIGN_LEFT),
(self.show_box, wx.ALIGN_LEFT)] )
display_window_1.AddMany( [(self.level_box, wx.ALIGN_LEFT),
(self.level_names, wx.ALIGN_LEFT)] )
display_window_2.AddMany( [(self.mean_type_box, wx.ALIGN_LEFT),
(self.mean_fit_box, wx.ALIGN_LEFT)] )
name_window.AddMany( [(self.name_box, wx.ALIGN_LEFT),
(self.color_box, wx.ALIGN_LEFT)] )
bounds_window.AddMany( [(self.tmin_box, wx.ALIGN_LEFT),
(self.tmax_box, wx.ALIGN_LEFT)] )
buttons1_window.AddMany( [(self.add_fit_button, wx.ALL|wx.ALIGN_CENTER|wx.SHAPED, 0),
(self.add_all_button, wx.ALL|wx.ALIGN_CENTER|wx.SHAPED, 0),
(self.delete_fit_button, wx.ALL|wx.ALIGN_CENTER|wx.SHAPED, 0),
(self.apply_changes_button, wx.ALL|wx.ALIGN_CENTER|wx.SHAPED, 0)])
self.display_sizer.Add(display_window_0, 1, wx.TOP|wx.EXPAND, 8)
self.display_sizer.Add(display_window_1, 1, wx.TOP | wx.LEFT|wx.EXPAND, 8)
self.display_sizer.Add(display_window_2, 1, wx.TOP | wx.LEFT|wx.EXPAND, 8)
self.name_sizer.Add(name_window, 1, wx.TOP, 5.5)
self.bounds_sizer.Add(bounds_window, 1, wx.TOP, 5.5)
self.buttons_sizer.Add(buttons1_window, 1, wx.TOP, 0)
#duplicate high levels plot
self.fig = Figure((2.5*self.GUI_RESOLUTION, 2.5*self.GUI_RESOLUTION), dpi=100)
self.canvas = FigCanvas(self.panel, -1, self.fig, )
self.toolbar = NavigationToolbar(self.canvas)
self.toolbar.Hide()
self.toolbar.zoom()
self.high_EA_setting = "Zoom"
self.canvas.Bind(wx.EVT_LEFT_DCLICK,self.on_equalarea_high_select)
self.canvas.Bind(wx.EVT_MOTION,self.on_change_high_mouse_cursor)
self.canvas.Bind(wx.EVT_MIDDLE_DOWN,self.home_high_equalarea)
self.canvas.Bind(wx.EVT_RIGHT_DOWN,self.pan_zoom_high_equalarea)
self.canvas.SetHelpText(dieh.eqarea_help)
self.eqarea = self.fig.add_subplot(111)
draw_net(self.eqarea)
#Higher Level Statistics Box
self.stats_sizer = wx.StaticBoxSizer( wx.StaticBox( self.panel, wx.ID_ANY,"mean statistics" ), wx.VERTICAL)
for parameter in ['mean_type','dec','inc','alpha95','K','R','n_lines','n_planes']:
COMMAND="self.%s_window=wx.TextCtrl(self.panel,style=wx.TE_CENTER|wx.TE_READONLY,size=(100*self.GUI_RESOLUTION,25))"%parameter
exec(COMMAND)
COMMAND="self.%s_window.SetBackgroundColour(wx.WHITE)"%parameter
exec(COMMAND)
COMMAND="self.%s_window.SetFont(font2)"%parameter
exec(COMMAND)
COMMAND="self.%s_outer_window = wx.GridSizer(1,2,5*self.GUI_RESOLUTION,15*self.GUI_RESOLUTION)"%parameter
exec(COMMAND)
COMMAND="""self.%s_outer_window.AddMany([
(wx.StaticText(self.panel,label='%s',style=wx.TE_CENTER),wx.EXPAND),
(self.%s_window, wx.EXPAND)])"""%(parameter,parameter,parameter)
exec(COMMAND)
COMMAND="self.stats_sizer.Add(self.%s_outer_window, 1, wx.ALIGN_LEFT|wx.EXPAND, 0)"%parameter
exec(COMMAND)
self.switch_stats_button = wx.SpinButton(self.panel, id=wx.ID_ANY, style=wx.SP_HORIZONTAL|wx.SP_ARROW_KEYS|wx.SP_WRAP, name="change stats")
self.Bind(wx.EVT_SPIN, self.on_select_stats_button,self.switch_stats_button)
self.switch_stats_button.SetHelpText(dieh.switch_stats_btn_help)
#construct panel
hbox0 = wx.BoxSizer(wx.HORIZONTAL)
hbox0.Add(self.name_sizer,flag=wx.ALIGN_TOP|wx.EXPAND,border=8)
hbox0.Add(self.bounds_sizer,flag=wx.ALIGN_TOP|wx.EXPAND,border=8)
vbox0 = wx.BoxSizer(wx.VERTICAL)
vbox0.Add(hbox0,flag=wx.ALIGN_TOP,border=8)
vbox0.Add(self.buttons_sizer,flag=wx.ALIGN_TOP,border=8)
hbox1 = wx.BoxSizer(wx.HORIZONTAL)
hbox1.Add(vbox0,flag=wx.ALIGN_TOP,border=8)
hbox1.Add(self.stats_sizer,flag=wx.ALIGN_TOP,border=8)
hbox1.Add(self.switch_stats_button,flag=wx.ALIGN_TOP|wx.EXPAND,border=8)
vbox1 = wx.BoxSizer(wx.VERTICAL)
vbox1.Add(self.display_sizer,flag=wx.ALIGN_TOP,border=8)
vbox1.Add(hbox1,flag=wx.ALIGN_TOP,border=8)
vbox1.Add(self.canvas,proportion=1,flag=wx.ALIGN_CENTER_HORIZONTAL | wx.ALIGN_CENTER_VERTICAL | wx.EXPAND,border=8)
vbox2 = wx.BoxSizer(wx.VERTICAL)
vbox2.Add(self.search_bar,proportion=.5,flag=wx.ALIGN_LEFT | wx.ALIGN_BOTTOM | wx.EXPAND, border=8)
vbox2.Add(self.logger,proportion=1,flag=wx.ALIGN_LEFT|wx.EXPAND,border=8)
hbox2 = wx.BoxSizer(wx.HORIZONTAL)
hbox2.Add(vbox2,proportion=1,flag=wx.ALIGN_LEFT|wx.EXPAND)
hbox2.Add(vbox1,flag=wx.ALIGN_TOP|wx.EXPAND)
self.panel.SetSizerAndFit(hbox2)
hbox2.Fit(self) | Builds User Interface for the interpretation Editor | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L55-L285 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.update_editor | def update_editor(self):
"""
updates the logger and plot on the interpretation editor window
"""
self.fit_list = []
self.search_choices = []
for specimen in self.specimens_list:
if specimen not in self.parent.pmag_results_data['specimens']: continue
self.fit_list += [(fit,specimen) for fit in self.parent.pmag_results_data['specimens'][specimen]]
self.logger.DeleteAllItems()
offset = 0
for i in range(len(self.fit_list)):
i -= offset
v = self.update_logger_entry(i)
if v == "s": offset += 1 | python | def update_editor(self):
"""
updates the logger and plot on the interpretation editor window
"""
self.fit_list = []
self.search_choices = []
for specimen in self.specimens_list:
if specimen not in self.parent.pmag_results_data['specimens']: continue
self.fit_list += [(fit,specimen) for fit in self.parent.pmag_results_data['specimens'][specimen]]
self.logger.DeleteAllItems()
offset = 0
for i in range(len(self.fit_list)):
i -= offset
v = self.update_logger_entry(i)
if v == "s": offset += 1 | updates the logger and plot on the interpretation editor window | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L408-L424 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.update_logger_entry | def update_logger_entry(self,i):
"""
helper function that given a index in this objects fit_list parameter inserts a entry at that index
@param: i -> index in fit_list to find the (specimen_name,fit object) tup that determines all the data for this logger entry.
"""
if i < len(self.fit_list):
tup = self.fit_list[i]
elif i < self.logger.GetItemCount():
self.logger.DeleteItem(i)
return
else: return
coordinate_system = self.parent.COORDINATE_SYSTEM
fit = tup[0]
pars = fit.get(coordinate_system)
fmin,fmax,n,ftype,dec,inc,mad,dang,a95,sk,sr2 = "","","","","","","","","","",""
specimen = tup[1]
if coordinate_system=='geographic':
block_key = 'zijdblock_geo'
elif coordinate_system=='tilt-corrected':
block_key = 'zijdblock_tilt'
else:
block_key = 'zijdblock'
name = fit.name
if pars == {} and self.parent.Data[specimen][block_key] != []:
fit.put(specimen, coordinate_system, self.parent.get_PCA_parameters(specimen,fit,fit.tmin,fit.tmax,coordinate_system,fit.PCA_type))
pars = fit.get(coordinate_system)
if self.parent.Data[specimen][block_key]==[]:
spars = fit.get('specimen')
fmin = fit.tmin
fmax = fit.tmax
if 'specimen_n' in list(spars.keys()): n = str(spars['specimen_n'])
else: n = 'No Data'
if 'calculation_type' in list(spars.keys()): ftype = spars['calculation_type']
else: ftype = 'No Data'
dec = 'No Data'
inc = 'No Data'
mad = 'No Data'
dang = 'No Data'
a95 = 'No Data'
sk = 'No Data'
sr2 = 'No Data'
else:
if 'measurement_step_min' in list(pars.keys()): fmin = str(fit.tmin)
else: fmin = "N/A"
if 'measurement_step_max' in list(pars.keys()): fmax = str(fit.tmax)
else: fmax = "N/A"
if 'specimen_n' in list(pars.keys()): n = str(pars['specimen_n'])
else: n = "N/A"
if 'calculation_type' in list(pars.keys()): ftype = pars['calculation_type']
else: ftype = "N/A"
if 'specimen_dec' in list(pars.keys()): dec = "%.1f"%pars['specimen_dec']
else: dec = "N/A"
if 'specimen_inc' in list(pars.keys()): inc = "%.1f"%pars['specimen_inc']
else: inc = "N/A"
if 'specimen_mad' in list(pars.keys()): mad = "%.1f"%pars['specimen_mad']
else: mad = "N/A"
if 'specimen_dang' in list(pars.keys()): dang = "%.1f"%pars['specimen_dang']
else: dang = "N/A"
if 'specimen_alpha95' in list(pars.keys()): a95 = "%.1f"%pars['specimen_alpha95']
else: a95 = "N/A"
if 'specimen_k' in list(pars.keys()): sk = "%.1f"%pars['specimen_k']
else: sk = "N/A"
if 'specimen_r' in list(pars.keys()): sr2 = "%.1f"%pars['specimen_r']
else: sr2 = "N/A"
if self.search_query != "":
entry = (specimen+name+fmin+fmax+n+ftype+dec+inc+mad+dang+a95+sk+sr2).replace(" ","").lower()
if self.search_query not in entry:
self.fit_list.pop(i)
if i < self.logger.GetItemCount():
self.logger.DeleteItem(i)
return "s"
for e in (specimen,name,fmin,fmax,n,ftype,dec,inc,mad,dang,a95,sk,sr2):
if e not in self.search_choices:
self.search_choices.append(e)
if i < self.logger.GetItemCount():
self.logger.DeleteItem(i)
self.logger.InsertItem(i, str(specimen))
self.logger.SetItem(i, 1, name)
self.logger.SetItem(i, 2, fmin)
self.logger.SetItem(i, 3, fmax)
self.logger.SetItem(i, 4, n)
self.logger.SetItem(i, 5, ftype)
self.logger.SetItem(i, 6, dec)
self.logger.SetItem(i, 7, inc)
self.logger.SetItem(i, 8, mad)
self.logger.SetItem(i, 9, dang)
self.logger.SetItem(i, 10, a95)
self.logger.SetItem(i, 11, sk)
self.logger.SetItem(i, 12, sr2)
self.logger.SetItemBackgroundColour(i,"WHITE")
a,b = False,False
if fit in self.parent.bad_fits:
self.logger.SetItemBackgroundColour(i,"red")
b = True
if self.parent.current_fit == fit:
self.logger.SetItemBackgroundColour(i,"LIGHT BLUE")
self.logger_focus(i)
self.current_fit_index = i
a = True
if a and b:
self.logger.SetItemBackgroundColour(i,"red") | python | def update_logger_entry(self,i):
"""
helper function that given a index in this objects fit_list parameter inserts a entry at that index
@param: i -> index in fit_list to find the (specimen_name,fit object) tup that determines all the data for this logger entry.
"""
if i < len(self.fit_list):
tup = self.fit_list[i]
elif i < self.logger.GetItemCount():
self.logger.DeleteItem(i)
return
else: return
coordinate_system = self.parent.COORDINATE_SYSTEM
fit = tup[0]
pars = fit.get(coordinate_system)
fmin,fmax,n,ftype,dec,inc,mad,dang,a95,sk,sr2 = "","","","","","","","","","",""
specimen = tup[1]
if coordinate_system=='geographic':
block_key = 'zijdblock_geo'
elif coordinate_system=='tilt-corrected':
block_key = 'zijdblock_tilt'
else:
block_key = 'zijdblock'
name = fit.name
if pars == {} and self.parent.Data[specimen][block_key] != []:
fit.put(specimen, coordinate_system, self.parent.get_PCA_parameters(specimen,fit,fit.tmin,fit.tmax,coordinate_system,fit.PCA_type))
pars = fit.get(coordinate_system)
if self.parent.Data[specimen][block_key]==[]:
spars = fit.get('specimen')
fmin = fit.tmin
fmax = fit.tmax
if 'specimen_n' in list(spars.keys()): n = str(spars['specimen_n'])
else: n = 'No Data'
if 'calculation_type' in list(spars.keys()): ftype = spars['calculation_type']
else: ftype = 'No Data'
dec = 'No Data'
inc = 'No Data'
mad = 'No Data'
dang = 'No Data'
a95 = 'No Data'
sk = 'No Data'
sr2 = 'No Data'
else:
if 'measurement_step_min' in list(pars.keys()): fmin = str(fit.tmin)
else: fmin = "N/A"
if 'measurement_step_max' in list(pars.keys()): fmax = str(fit.tmax)
else: fmax = "N/A"
if 'specimen_n' in list(pars.keys()): n = str(pars['specimen_n'])
else: n = "N/A"
if 'calculation_type' in list(pars.keys()): ftype = pars['calculation_type']
else: ftype = "N/A"
if 'specimen_dec' in list(pars.keys()): dec = "%.1f"%pars['specimen_dec']
else: dec = "N/A"
if 'specimen_inc' in list(pars.keys()): inc = "%.1f"%pars['specimen_inc']
else: inc = "N/A"
if 'specimen_mad' in list(pars.keys()): mad = "%.1f"%pars['specimen_mad']
else: mad = "N/A"
if 'specimen_dang' in list(pars.keys()): dang = "%.1f"%pars['specimen_dang']
else: dang = "N/A"
if 'specimen_alpha95' in list(pars.keys()): a95 = "%.1f"%pars['specimen_alpha95']
else: a95 = "N/A"
if 'specimen_k' in list(pars.keys()): sk = "%.1f"%pars['specimen_k']
else: sk = "N/A"
if 'specimen_r' in list(pars.keys()): sr2 = "%.1f"%pars['specimen_r']
else: sr2 = "N/A"
if self.search_query != "":
entry = (specimen+name+fmin+fmax+n+ftype+dec+inc+mad+dang+a95+sk+sr2).replace(" ","").lower()
if self.search_query not in entry:
self.fit_list.pop(i)
if i < self.logger.GetItemCount():
self.logger.DeleteItem(i)
return "s"
for e in (specimen,name,fmin,fmax,n,ftype,dec,inc,mad,dang,a95,sk,sr2):
if e not in self.search_choices:
self.search_choices.append(e)
if i < self.logger.GetItemCount():
self.logger.DeleteItem(i)
self.logger.InsertItem(i, str(specimen))
self.logger.SetItem(i, 1, name)
self.logger.SetItem(i, 2, fmin)
self.logger.SetItem(i, 3, fmax)
self.logger.SetItem(i, 4, n)
self.logger.SetItem(i, 5, ftype)
self.logger.SetItem(i, 6, dec)
self.logger.SetItem(i, 7, inc)
self.logger.SetItem(i, 8, mad)
self.logger.SetItem(i, 9, dang)
self.logger.SetItem(i, 10, a95)
self.logger.SetItem(i, 11, sk)
self.logger.SetItem(i, 12, sr2)
self.logger.SetItemBackgroundColour(i,"WHITE")
a,b = False,False
if fit in self.parent.bad_fits:
self.logger.SetItemBackgroundColour(i,"red")
b = True
if self.parent.current_fit == fit:
self.logger.SetItemBackgroundColour(i,"LIGHT BLUE")
self.logger_focus(i)
self.current_fit_index = i
a = True
if a and b:
self.logger.SetItemBackgroundColour(i,"red") | helper function that given a index in this objects fit_list parameter inserts a entry at that index
@param: i -> index in fit_list to find the (specimen_name,fit object) tup that determines all the data for this logger entry. | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L426-L531 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.change_selected | def change_selected(self,new_fit):
"""
updates passed in fit or index as current fit for the editor (does not affect parent),
if no parameters are passed in it sets first fit as current
@param: new_fit -> fit object to highlight as selected
"""
if len(self.fit_list)==0: return
if self.search_query and self.parent.current_fit not in [x[0] for x in self.fit_list]: return
if self.current_fit_index == None:
if not self.parent.current_fit: return
for i,(fit,specimen) in enumerate(self.fit_list):
if fit == self.parent.current_fit:
self.current_fit_index = i
break
i = 0
if isinstance(new_fit, Fit):
for i, (fit,speci) in enumerate(self.fit_list):
if fit == new_fit:
break
elif type(new_fit) is int:
i = new_fit
elif new_fit != None:
print(('cannot select fit of type: ' + str(type(new_fit))))
if self.current_fit_index != None and \
len(self.fit_list) > 0 and \
self.fit_list[self.current_fit_index][0] in self.parent.bad_fits:
self.logger.SetItemBackgroundColour(self.current_fit_index,"")
else:
self.logger.SetItemBackgroundColour(self.current_fit_index,"WHITE")
self.current_fit_index = i
if self.fit_list[self.current_fit_index][0] in self.parent.bad_fits:
self.logger.SetItemBackgroundColour(self.current_fit_index,"red")
else:
self.logger.SetItemBackgroundColour(self.current_fit_index,"LIGHT BLUE") | python | def change_selected(self,new_fit):
"""
updates passed in fit or index as current fit for the editor (does not affect parent),
if no parameters are passed in it sets first fit as current
@param: new_fit -> fit object to highlight as selected
"""
if len(self.fit_list)==0: return
if self.search_query and self.parent.current_fit not in [x[0] for x in self.fit_list]: return
if self.current_fit_index == None:
if not self.parent.current_fit: return
for i,(fit,specimen) in enumerate(self.fit_list):
if fit == self.parent.current_fit:
self.current_fit_index = i
break
i = 0
if isinstance(new_fit, Fit):
for i, (fit,speci) in enumerate(self.fit_list):
if fit == new_fit:
break
elif type(new_fit) is int:
i = new_fit
elif new_fit != None:
print(('cannot select fit of type: ' + str(type(new_fit))))
if self.current_fit_index != None and \
len(self.fit_list) > 0 and \
self.fit_list[self.current_fit_index][0] in self.parent.bad_fits:
self.logger.SetItemBackgroundColour(self.current_fit_index,"")
else:
self.logger.SetItemBackgroundColour(self.current_fit_index,"WHITE")
self.current_fit_index = i
if self.fit_list[self.current_fit_index][0] in self.parent.bad_fits:
self.logger.SetItemBackgroundColour(self.current_fit_index,"red")
else:
self.logger.SetItemBackgroundColour(self.current_fit_index,"LIGHT BLUE") | updates passed in fit or index as current fit for the editor (does not affect parent),
if no parameters are passed in it sets first fit as current
@param: new_fit -> fit object to highlight as selected | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L540-L573 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.logger_focus | def logger_focus(self,i,focus_shift=16):
"""
focuses the logger on an index 12 entries below i
@param: i -> index to focus on
"""
if self.logger.GetItemCount()-1 > i+focus_shift:
i += focus_shift
else:
i = self.logger.GetItemCount()-1
self.logger.Focus(i) | python | def logger_focus(self,i,focus_shift=16):
"""
focuses the logger on an index 12 entries below i
@param: i -> index to focus on
"""
if self.logger.GetItemCount()-1 > i+focus_shift:
i += focus_shift
else:
i = self.logger.GetItemCount()-1
self.logger.Focus(i) | focuses the logger on an index 12 entries below i
@param: i -> index to focus on | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L575-L584 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.OnClick_listctrl | def OnClick_listctrl(self, event):
"""
Edits the logger and the Zeq_GUI parent object to select the fit that was newly selected by a double click
@param: event -> wx.ListCtrlEvent that triggered this function
"""
i = event.GetIndex()
if self.parent.current_fit == self.fit_list[i][0]: return
self.parent.initialize_CART_rot(self.fit_list[i][1])
si = self.parent.specimens.index(self.fit_list[i][1])
self.parent.specimens_box.SetSelection(si)
self.parent.select_specimen(self.fit_list[i][1])
self.change_selected(i)
fi = 0
while (self.parent.s == self.fit_list[i][1] and i >= 0): i,fi = (i-1,fi+1)
self.parent.update_fit_box()
self.parent.fit_box.SetSelection(fi-1)
self.parent.update_selection() | python | def OnClick_listctrl(self, event):
"""
Edits the logger and the Zeq_GUI parent object to select the fit that was newly selected by a double click
@param: event -> wx.ListCtrlEvent that triggered this function
"""
i = event.GetIndex()
if self.parent.current_fit == self.fit_list[i][0]: return
self.parent.initialize_CART_rot(self.fit_list[i][1])
si = self.parent.specimens.index(self.fit_list[i][1])
self.parent.specimens_box.SetSelection(si)
self.parent.select_specimen(self.fit_list[i][1])
self.change_selected(i)
fi = 0
while (self.parent.s == self.fit_list[i][1] and i >= 0): i,fi = (i-1,fi+1)
self.parent.update_fit_box()
self.parent.fit_box.SetSelection(fi-1)
self.parent.update_selection() | Edits the logger and the Zeq_GUI parent object to select the fit that was newly selected by a double click
@param: event -> wx.ListCtrlEvent that triggered this function | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L586-L602 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.OnRightClickListctrl | def OnRightClickListctrl(self, event):
"""
Edits the logger and the Zeq_GUI parent object so that the selected interpretation is now marked as bad
@param: event -> wx.ListCtrlEvent that triggered this function
"""
i = event.GetIndex()
fit,spec = self.fit_list[i][0],self.fit_list[i][1]
if fit in self.parent.bad_fits:
if not self.parent.mark_fit_good(fit,spec=spec): return
if i == self.current_fit_index:
self.logger.SetItemBackgroundColour(i,"LIGHT BLUE")
else:
self.logger.SetItemBackgroundColour(i,"WHITE")
else:
if not self.parent.mark_fit_bad(fit): return
if i == self.current_fit_index:
self.logger.SetItemBackgroundColour(i,"red")
else:
self.logger.SetItemBackgroundColour(i,"red")
self.parent.calculate_high_levels_data()
self.parent.plot_high_levels_data()
self.logger_focus(i) | python | def OnRightClickListctrl(self, event):
"""
Edits the logger and the Zeq_GUI parent object so that the selected interpretation is now marked as bad
@param: event -> wx.ListCtrlEvent that triggered this function
"""
i = event.GetIndex()
fit,spec = self.fit_list[i][0],self.fit_list[i][1]
if fit in self.parent.bad_fits:
if not self.parent.mark_fit_good(fit,spec=spec): return
if i == self.current_fit_index:
self.logger.SetItemBackgroundColour(i,"LIGHT BLUE")
else:
self.logger.SetItemBackgroundColour(i,"WHITE")
else:
if not self.parent.mark_fit_bad(fit): return
if i == self.current_fit_index:
self.logger.SetItemBackgroundColour(i,"red")
else:
self.logger.SetItemBackgroundColour(i,"red")
self.parent.calculate_high_levels_data()
self.parent.plot_high_levels_data()
self.logger_focus(i) | Edits the logger and the Zeq_GUI parent object so that the selected interpretation is now marked as bad
@param: event -> wx.ListCtrlEvent that triggered this function | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L604-L625 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.on_select_show_box | def on_select_show_box(self,event):
"""
Changes the type of mean shown on the high levels mean plot so that single dots represent one of whatever the value of this box is.
@param: event -> the wx.COMBOBOXEVENT that triggered this function
"""
self.parent.UPPER_LEVEL_SHOW=self.show_box.GetValue()
self.parent.calculate_high_levels_data()
self.parent.plot_high_levels_data() | python | def on_select_show_box(self,event):
"""
Changes the type of mean shown on the high levels mean plot so that single dots represent one of whatever the value of this box is.
@param: event -> the wx.COMBOBOXEVENT that triggered this function
"""
self.parent.UPPER_LEVEL_SHOW=self.show_box.GetValue()
self.parent.calculate_high_levels_data()
self.parent.plot_high_levels_data() | Changes the type of mean shown on the high levels mean plot so that single dots represent one of whatever the value of this box is.
@param: event -> the wx.COMBOBOXEVENT that triggered this function | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L669-L676 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.on_select_high_level | def on_select_high_level(self,event,called_by_parent=False):
"""
alters the possible entries in level_names combobox to give the user selections for which specimen interpretations to display in the logger
@param: event -> the wx.COMBOBOXEVENT that triggered this function
"""
UPPER_LEVEL=self.level_box.GetValue()
if UPPER_LEVEL=='sample':
self.level_names.SetItems(self.parent.samples)
self.level_names.SetStringSelection(self.parent.Data_hierarchy['sample_of_specimen'][self.parent.s])
if UPPER_LEVEL=='site':
self.level_names.SetItems(self.parent.sites)
self.level_names.SetStringSelection(self.parent.Data_hierarchy['site_of_specimen'][self.parent.s])
if UPPER_LEVEL=='location':
self.level_names.SetItems(self.parent.locations)
self.level_names.SetStringSelection(self.parent.Data_hierarchy['location_of_specimen'][self.parent.s])
if UPPER_LEVEL=='study':
self.level_names.SetItems(['this study'])
self.level_names.SetStringSelection('this study')
if not called_by_parent:
self.parent.level_box.SetStringSelection(UPPER_LEVEL)
self.parent.onSelect_high_level(event,True)
self.on_select_level_name(event) | python | def on_select_high_level(self,event,called_by_parent=False):
"""
alters the possible entries in level_names combobox to give the user selections for which specimen interpretations to display in the logger
@param: event -> the wx.COMBOBOXEVENT that triggered this function
"""
UPPER_LEVEL=self.level_box.GetValue()
if UPPER_LEVEL=='sample':
self.level_names.SetItems(self.parent.samples)
self.level_names.SetStringSelection(self.parent.Data_hierarchy['sample_of_specimen'][self.parent.s])
if UPPER_LEVEL=='site':
self.level_names.SetItems(self.parent.sites)
self.level_names.SetStringSelection(self.parent.Data_hierarchy['site_of_specimen'][self.parent.s])
if UPPER_LEVEL=='location':
self.level_names.SetItems(self.parent.locations)
self.level_names.SetStringSelection(self.parent.Data_hierarchy['location_of_specimen'][self.parent.s])
if UPPER_LEVEL=='study':
self.level_names.SetItems(['this study'])
self.level_names.SetStringSelection('this study')
if not called_by_parent:
self.parent.level_box.SetStringSelection(UPPER_LEVEL)
self.parent.onSelect_high_level(event,True)
self.on_select_level_name(event) | alters the possible entries in level_names combobox to give the user selections for which specimen interpretations to display in the logger
@param: event -> the wx.COMBOBOXEVENT that triggered this function | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L679-L706 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.on_select_level_name | def on_select_level_name(self,event,called_by_parent=False):
"""
change this objects specimens_list to control which specimen interpretatoins are displayed in this objects logger
@param: event -> the wx.ComboBoxEvent that triggered this function
"""
high_level_name=str(self.level_names.GetValue())
if self.level_box.GetValue()=='sample':
self.specimens_list=self.parent.Data_hierarchy['samples'][high_level_name]['specimens']
elif self.level_box.GetValue()=='site':
self.specimens_list=self.parent.Data_hierarchy['sites'][high_level_name]['specimens']
elif self.level_box.GetValue()=='location':
self.specimens_list=self.parent.Data_hierarchy['locations'][high_level_name]['specimens']
elif self.level_box.GetValue()=='study':
self.specimens_list=self.parent.Data_hierarchy['study']['this study']['specimens']
if not called_by_parent:
self.parent.level_names.SetStringSelection(high_level_name)
self.parent.onSelect_level_name(event,True)
self.specimens_list.sort(key=spec_key_func)
self.update_editor() | python | def on_select_level_name(self,event,called_by_parent=False):
"""
change this objects specimens_list to control which specimen interpretatoins are displayed in this objects logger
@param: event -> the wx.ComboBoxEvent that triggered this function
"""
high_level_name=str(self.level_names.GetValue())
if self.level_box.GetValue()=='sample':
self.specimens_list=self.parent.Data_hierarchy['samples'][high_level_name]['specimens']
elif self.level_box.GetValue()=='site':
self.specimens_list=self.parent.Data_hierarchy['sites'][high_level_name]['specimens']
elif self.level_box.GetValue()=='location':
self.specimens_list=self.parent.Data_hierarchy['locations'][high_level_name]['specimens']
elif self.level_box.GetValue()=='study':
self.specimens_list=self.parent.Data_hierarchy['study']['this study']['specimens']
if not called_by_parent:
self.parent.level_names.SetStringSelection(high_level_name)
self.parent.onSelect_level_name(event,True)
self.specimens_list.sort(key=spec_key_func)
self.update_editor() | change this objects specimens_list to control which specimen interpretatoins are displayed in this objects logger
@param: event -> the wx.ComboBoxEvent that triggered this function | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L708-L729 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.on_select_mean_type_box | def on_select_mean_type_box(self, event):
"""
set parent Zeq_GUI to reflect change in this box and change the
@param: event -> the wx.ComboBoxEvent that triggered this function
"""
new_mean_type = self.mean_type_box.GetValue()
if new_mean_type == "None":
self.parent.clear_high_level_pars()
self.parent.mean_type_box.SetStringSelection(new_mean_type)
self.parent.onSelect_mean_type_box(event) | python | def on_select_mean_type_box(self, event):
"""
set parent Zeq_GUI to reflect change in this box and change the
@param: event -> the wx.ComboBoxEvent that triggered this function
"""
new_mean_type = self.mean_type_box.GetValue()
if new_mean_type == "None":
self.parent.clear_high_level_pars()
self.parent.mean_type_box.SetStringSelection(new_mean_type)
self.parent.onSelect_mean_type_box(event) | set parent Zeq_GUI to reflect change in this box and change the
@param: event -> the wx.ComboBoxEvent that triggered this function | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L731-L740 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.on_select_mean_fit_box | def on_select_mean_fit_box(self, event):
"""
set parent Zeq_GUI to reflect the change in this box then replot the high level means plot
@param: event -> the wx.COMBOBOXEVENT that triggered this function
"""
new_mean_fit = self.mean_fit_box.GetValue()
self.parent.mean_fit_box.SetStringSelection(new_mean_fit)
self.parent.onSelect_mean_fit_box(event) | python | def on_select_mean_fit_box(self, event):
"""
set parent Zeq_GUI to reflect the change in this box then replot the high level means plot
@param: event -> the wx.COMBOBOXEVENT that triggered this function
"""
new_mean_fit = self.mean_fit_box.GetValue()
self.parent.mean_fit_box.SetStringSelection(new_mean_fit)
self.parent.onSelect_mean_fit_box(event) | set parent Zeq_GUI to reflect the change in this box then replot the high level means plot
@param: event -> the wx.COMBOBOXEVENT that triggered this function | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L742-L749 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.add_highlighted_fits | def add_highlighted_fits(self, evnet):
"""
adds a new interpretation to each specimen highlighted in logger if multiple interpretations are highlighted of the same specimen only one new interpretation is added
@param: event -> the wx.ButtonEvent that triggered this function
"""
specimens = []
next_i = self.logger.GetNextSelected(-1)
if next_i == -1: return
while next_i != -1:
fit,specimen = self.fit_list[next_i]
if specimen in specimens:
next_i = self.logger.GetNextSelected(next_i)
continue
else: specimens.append(specimen)
next_i = self.logger.GetNextSelected(next_i)
for specimen in specimens:
self.add_fit_to_specimen(specimen)
self.update_editor()
self.parent.update_selection() | python | def add_highlighted_fits(self, evnet):
"""
adds a new interpretation to each specimen highlighted in logger if multiple interpretations are highlighted of the same specimen only one new interpretation is added
@param: event -> the wx.ButtonEvent that triggered this function
"""
specimens = []
next_i = self.logger.GetNextSelected(-1)
if next_i == -1: return
while next_i != -1:
fit,specimen = self.fit_list[next_i]
if specimen in specimens:
next_i = self.logger.GetNextSelected(next_i)
continue
else: specimens.append(specimen)
next_i = self.logger.GetNextSelected(next_i)
for specimen in specimens:
self.add_fit_to_specimen(specimen)
self.update_editor()
self.parent.update_selection() | adds a new interpretation to each specimen highlighted in logger if multiple interpretations are highlighted of the same specimen only one new interpretation is added
@param: event -> the wx.ButtonEvent that triggered this function | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L761-L782 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.delete_highlighted_fits | def delete_highlighted_fits(self, event):
"""
iterates through all highlighted fits in the logger of this object and removes them from the logger and the Zeq_GUI parent object
@param: event -> the wx.ButtonEvent that triggered this function
"""
next_i = -1
deleted_items = []
while True:
next_i = self.logger.GetNextSelected(next_i)
if next_i == -1:
break
deleted_items.append(next_i)
deleted_items.sort(reverse=True)
for item in deleted_items:
self.delete_entry(index=item)
self.parent.update_selection() | python | def delete_highlighted_fits(self, event):
"""
iterates through all highlighted fits in the logger of this object and removes them from the logger and the Zeq_GUI parent object
@param: event -> the wx.ButtonEvent that triggered this function
"""
next_i = -1
deleted_items = []
while True:
next_i = self.logger.GetNextSelected(next_i)
if next_i == -1:
break
deleted_items.append(next_i)
deleted_items.sort(reverse=True)
for item in deleted_items:
self.delete_entry(index=item)
self.parent.update_selection() | iterates through all highlighted fits in the logger of this object and removes them from the logger and the Zeq_GUI parent object
@param: event -> the wx.ButtonEvent that triggered this function | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L818-L834 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.delete_entry | def delete_entry(self, fit = None, index = None):
"""
deletes the single item from the logger of this object that corrisponds to either the passed in fit or index. Note this function mutaits the logger of this object if deleting more than one entry be sure to pass items to delete in from highest index to lowest or else odd things can happen.
@param: fit -> Fit object to delete from this objects logger
@param: index -> integer index of the entry to delete from this objects logger
"""
if type(index) == int and not fit:
fit,specimen = self.fit_list[index]
if fit and type(index) == int:
for i, (f,s) in enumerate(self.fit_list):
if fit == f:
index,specimen = i,s
break
if index == self.current_fit_index: self.current_fit_index = None
if fit not in self.parent.pmag_results_data['specimens'][specimen]:
print(("cannot remove item (entry #: " + str(index) + ") as it doesn't exist, this is a dumb bug contact devs"))
self.logger.DeleteItem(index)
return
self.parent.pmag_results_data['specimens'][specimen].remove(fit)
del self.fit_list[index]
self.logger.DeleteItem(index) | python | def delete_entry(self, fit = None, index = None):
"""
deletes the single item from the logger of this object that corrisponds to either the passed in fit or index. Note this function mutaits the logger of this object if deleting more than one entry be sure to pass items to delete in from highest index to lowest or else odd things can happen.
@param: fit -> Fit object to delete from this objects logger
@param: index -> integer index of the entry to delete from this objects logger
"""
if type(index) == int and not fit:
fit,specimen = self.fit_list[index]
if fit and type(index) == int:
for i, (f,s) in enumerate(self.fit_list):
if fit == f:
index,specimen = i,s
break
if index == self.current_fit_index: self.current_fit_index = None
if fit not in self.parent.pmag_results_data['specimens'][specimen]:
print(("cannot remove item (entry #: " + str(index) + ") as it doesn't exist, this is a dumb bug contact devs"))
self.logger.DeleteItem(index)
return
self.parent.pmag_results_data['specimens'][specimen].remove(fit)
del self.fit_list[index]
self.logger.DeleteItem(index) | deletes the single item from the logger of this object that corrisponds to either the passed in fit or index. Note this function mutaits the logger of this object if deleting more than one entry be sure to pass items to delete in from highest index to lowest or else odd things can happen.
@param: fit -> Fit object to delete from this objects logger
@param: index -> integer index of the entry to delete from this objects logger | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L836-L857 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.apply_changes | def apply_changes(self, event):
"""
applies the changes in the various attribute boxes of this object to all highlighted fit objects in the logger, these changes are reflected both in this object and in the Zeq_GUI parent object.
@param: event -> the wx.ButtonEvent that triggered this function
"""
new_name = self.name_box.GetLineText(0)
new_color = self.color_box.GetValue()
new_tmin = self.tmin_box.GetValue()
new_tmax = self.tmax_box.GetValue()
next_i = -1
changed_i = []
while True:
next_i = self.logger.GetNextSelected(next_i)
if next_i == -1:
break
specimen = self.fit_list[next_i][1]
fit = self.fit_list[next_i][0]
if new_name:
if new_name not in [x.name for x in self.parent.pmag_results_data['specimens'][specimen]]: fit.name = new_name
if new_color:
fit.color = self.color_dict[new_color]
#testing
not_both = True
if new_tmin and new_tmax:
if fit == self.parent.current_fit:
self.parent.tmin_box.SetStringSelection(new_tmin)
self.parent.tmax_box.SetStringSelection(new_tmax)
fit.put(specimen,self.parent.COORDINATE_SYSTEM, self.parent.get_PCA_parameters(specimen,fit,new_tmin,new_tmax,self.parent.COORDINATE_SYSTEM,fit.PCA_type))
not_both = False
if new_tmin and not_both:
if fit == self.parent.current_fit:
self.parent.tmin_box.SetStringSelection(new_tmin)
fit.put(specimen,self.parent.COORDINATE_SYSTEM, self.parent.get_PCA_parameters(specimen,fit,new_tmin,fit.tmax,self.parent.COORDINATE_SYSTEM,fit.PCA_type))
if new_tmax and not_both:
if fit == self.parent.current_fit:
self.parent.tmax_box.SetStringSelection(new_tmax)
fit.put(specimen,self.parent.COORDINATE_SYSTEM, self.parent.get_PCA_parameters(specimen,fit,fit.tmin,new_tmax,self.parent.COORDINATE_SYSTEM,fit.PCA_type))
changed_i.append(next_i)
offset = 0
for i in changed_i:
i -= offset
v = self.update_logger_entry(i)
if v == "s":
offset += 1
self.parent.update_selection() | python | def apply_changes(self, event):
"""
applies the changes in the various attribute boxes of this object to all highlighted fit objects in the logger, these changes are reflected both in this object and in the Zeq_GUI parent object.
@param: event -> the wx.ButtonEvent that triggered this function
"""
new_name = self.name_box.GetLineText(0)
new_color = self.color_box.GetValue()
new_tmin = self.tmin_box.GetValue()
new_tmax = self.tmax_box.GetValue()
next_i = -1
changed_i = []
while True:
next_i = self.logger.GetNextSelected(next_i)
if next_i == -1:
break
specimen = self.fit_list[next_i][1]
fit = self.fit_list[next_i][0]
if new_name:
if new_name not in [x.name for x in self.parent.pmag_results_data['specimens'][specimen]]: fit.name = new_name
if new_color:
fit.color = self.color_dict[new_color]
#testing
not_both = True
if new_tmin and new_tmax:
if fit == self.parent.current_fit:
self.parent.tmin_box.SetStringSelection(new_tmin)
self.parent.tmax_box.SetStringSelection(new_tmax)
fit.put(specimen,self.parent.COORDINATE_SYSTEM, self.parent.get_PCA_parameters(specimen,fit,new_tmin,new_tmax,self.parent.COORDINATE_SYSTEM,fit.PCA_type))
not_both = False
if new_tmin and not_both:
if fit == self.parent.current_fit:
self.parent.tmin_box.SetStringSelection(new_tmin)
fit.put(specimen,self.parent.COORDINATE_SYSTEM, self.parent.get_PCA_parameters(specimen,fit,new_tmin,fit.tmax,self.parent.COORDINATE_SYSTEM,fit.PCA_type))
if new_tmax and not_both:
if fit == self.parent.current_fit:
self.parent.tmax_box.SetStringSelection(new_tmax)
fit.put(specimen,self.parent.COORDINATE_SYSTEM, self.parent.get_PCA_parameters(specimen,fit,fit.tmin,new_tmax,self.parent.COORDINATE_SYSTEM,fit.PCA_type))
changed_i.append(next_i)
offset = 0
for i in changed_i:
i -= offset
v = self.update_logger_entry(i)
if v == "s":
offset += 1
self.parent.update_selection() | applies the changes in the various attribute boxes of this object to all highlighted fit objects in the logger, these changes are reflected both in this object and in the Zeq_GUI parent object.
@param: event -> the wx.ButtonEvent that triggered this function | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L859-L907 |
PmagPy/PmagPy | dialogs/demag_interpretation_editor.py | InterpretationEditorFrame.pan_zoom_high_equalarea | def pan_zoom_high_equalarea(self,event):
"""
Uses the toolbar for the canvas to change the function from zoom to pan or pan to zoom
@param: event -> the wx.MouseEvent that triggered this funciton
"""
if event.LeftIsDown() or event.ButtonDClick():
return
elif self.high_EA_setting == "Zoom":
self.high_EA_setting = "Pan"
try: self.toolbar.pan('off')
except TypeError: pass
elif self.high_EA_setting == "Pan":
self.high_EA_setting = "Zoom"
try: self.toolbar.zoom()
except TypeError: pass
else:
self.high_EA_setting = "Zoom"
try: self.toolbar.zoom()
except TypeError: pass | python | def pan_zoom_high_equalarea(self,event):
"""
Uses the toolbar for the canvas to change the function from zoom to pan or pan to zoom
@param: event -> the wx.MouseEvent that triggered this funciton
"""
if event.LeftIsDown() or event.ButtonDClick():
return
elif self.high_EA_setting == "Zoom":
self.high_EA_setting = "Pan"
try: self.toolbar.pan('off')
except TypeError: pass
elif self.high_EA_setting == "Pan":
self.high_EA_setting = "Zoom"
try: self.toolbar.zoom()
except TypeError: pass
else:
self.high_EA_setting = "Zoom"
try: self.toolbar.zoom()
except TypeError: pass | Uses the toolbar for the canvas to change the function from zoom to pan or pan to zoom
@param: event -> the wx.MouseEvent that triggered this funciton | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/demag_interpretation_editor.py#L935-L953 |
PmagPy/PmagPy | programs/tk03.py | main | def main():
"""
NAME
tk03.py
DESCRIPTION
generates set of vectors drawn from TK03.gad at given lat and
rotated about vertical axis by given Dec
INPUT (COMMAND LINE ENTRY)
OUTPUT
dec, inc, int
SYNTAX
tk03.py [command line options] [> OutputFileName]
OPTIONS
-n N specify N, default is 100
-d D specify mean Dec, default is 0
-lat LAT specify latitude, default is 0
-rev include reversals
-t INT truncates intensities to >INT uT
-G2 FRAC specify average g_2^0 fraction (default is 0)
-G3 FRAC specify average g_3^0 fraction (default is 0)
"""
N, L, D, R = 100, 0., 0., 0
G2, G3 = 0., 0.
cnt = 1
Imax = 0
if len(sys.argv) != 0 and '-h' in sys.argv:
print(main.__doc__)
sys.exit()
else:
if '-n' in sys.argv:
ind = sys.argv.index('-n')
N = int(sys.argv[ind + 1])
if '-d' in sys.argv:
ind = sys.argv.index('-d')
D = float(sys.argv[ind + 1])
if '-lat' in sys.argv:
ind = sys.argv.index('-lat')
L = float(sys.argv[ind + 1])
if '-t' in sys.argv:
ind = sys.argv.index('-t')
Imax = 1e3 * float(sys.argv[ind + 1])
if '-rev' in sys.argv:
R = 1
if '-G2' in sys.argv:
ind = sys.argv.index('-G2')
G2 = float(sys.argv[ind + 1])
if '-G3' in sys.argv:
ind = sys.argv.index('-G3')
G3 = float(sys.argv[ind + 1])
for k in range(N):
gh = pmag.mktk03(8, k, G2, G3) # terms and random seed
# get a random longitude, between 0 and 359
lon = random.randint(0, 360)
vec = pmag.getvec(gh, L, lon) # send field model and lat to getvec
if vec[2] >= Imax:
vec[0] += D
if k % 2 == 0 and R == 1:
vec[0] += 180.
vec[1] = -vec[1]
if vec[0] >= 360.:
vec[0] -= 360.
print('%7.1f %7.1f %8.2f ' % (vec[0], vec[1], vec[2])) | python | def main():
"""
NAME
tk03.py
DESCRIPTION
generates set of vectors drawn from TK03.gad at given lat and
rotated about vertical axis by given Dec
INPUT (COMMAND LINE ENTRY)
OUTPUT
dec, inc, int
SYNTAX
tk03.py [command line options] [> OutputFileName]
OPTIONS
-n N specify N, default is 100
-d D specify mean Dec, default is 0
-lat LAT specify latitude, default is 0
-rev include reversals
-t INT truncates intensities to >INT uT
-G2 FRAC specify average g_2^0 fraction (default is 0)
-G3 FRAC specify average g_3^0 fraction (default is 0)
"""
N, L, D, R = 100, 0., 0., 0
G2, G3 = 0., 0.
cnt = 1
Imax = 0
if len(sys.argv) != 0 and '-h' in sys.argv:
print(main.__doc__)
sys.exit()
else:
if '-n' in sys.argv:
ind = sys.argv.index('-n')
N = int(sys.argv[ind + 1])
if '-d' in sys.argv:
ind = sys.argv.index('-d')
D = float(sys.argv[ind + 1])
if '-lat' in sys.argv:
ind = sys.argv.index('-lat')
L = float(sys.argv[ind + 1])
if '-t' in sys.argv:
ind = sys.argv.index('-t')
Imax = 1e3 * float(sys.argv[ind + 1])
if '-rev' in sys.argv:
R = 1
if '-G2' in sys.argv:
ind = sys.argv.index('-G2')
G2 = float(sys.argv[ind + 1])
if '-G3' in sys.argv:
ind = sys.argv.index('-G3')
G3 = float(sys.argv[ind + 1])
for k in range(N):
gh = pmag.mktk03(8, k, G2, G3) # terms and random seed
# get a random longitude, between 0 and 359
lon = random.randint(0, 360)
vec = pmag.getvec(gh, L, lon) # send field model and lat to getvec
if vec[2] >= Imax:
vec[0] += D
if k % 2 == 0 and R == 1:
vec[0] += 180.
vec[1] = -vec[1]
if vec[0] >= 360.:
vec[0] -= 360.
print('%7.1f %7.1f %8.2f ' % (vec[0], vec[1], vec[2])) | NAME
tk03.py
DESCRIPTION
generates set of vectors drawn from TK03.gad at given lat and
rotated about vertical axis by given Dec
INPUT (COMMAND LINE ENTRY)
OUTPUT
dec, inc, int
SYNTAX
tk03.py [command line options] [> OutputFileName]
OPTIONS
-n N specify N, default is 100
-d D specify mean Dec, default is 0
-lat LAT specify latitude, default is 0
-rev include reversals
-t INT truncates intensities to >INT uT
-G2 FRAC specify average g_2^0 fraction (default is 0)
-G3 FRAC specify average g_3^0 fraction (default is 0) | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/programs/tk03.py#L9-L74 |
PmagPy/PmagPy | programs/gaussian.py | main | def main():
"""
NAME
gaussian.py
DESCRIPTION
generates set of normally distribed data from specified distribution
INPUT (COMMAND LINE ENTRY)
OUTPUT
x
SYNTAX
gaussian.py [command line options]
OPTIONS
-h prints help message and quits
-s specify standard deviation as next argument, default is 1
-n specify N as next argument, default is 100
-m specify mean as next argument, default is 0
-F specify output file
"""
N,mean,sigma=100,0,1.
outfile=""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
else:
if '-s' in sys.argv:
ind=sys.argv.index('-s')
sigma=float(sys.argv[ind+1])
if '-n' in sys.argv:
ind=sys.argv.index('-n')
N=int(sys.argv[ind+1])
if '-m' in sys.argv:
ind=sys.argv.index('-m')
mean=float(sys.argv[ind+1])
if '-F' in sys.argv:
ind=sys.argv.index('-F')
outfile=sys.argv[ind+1]
out=open(outfile,'w')
for k in range(N):
x='%f'%(pmag.gaussdev(mean,sigma)) # send kappa to fshdev
if outfile=="":
print(x)
else:
out.write(x+'\n') | python | def main():
"""
NAME
gaussian.py
DESCRIPTION
generates set of normally distribed data from specified distribution
INPUT (COMMAND LINE ENTRY)
OUTPUT
x
SYNTAX
gaussian.py [command line options]
OPTIONS
-h prints help message and quits
-s specify standard deviation as next argument, default is 1
-n specify N as next argument, default is 100
-m specify mean as next argument, default is 0
-F specify output file
"""
N,mean,sigma=100,0,1.
outfile=""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
else:
if '-s' in sys.argv:
ind=sys.argv.index('-s')
sigma=float(sys.argv[ind+1])
if '-n' in sys.argv:
ind=sys.argv.index('-n')
N=int(sys.argv[ind+1])
if '-m' in sys.argv:
ind=sys.argv.index('-m')
mean=float(sys.argv[ind+1])
if '-F' in sys.argv:
ind=sys.argv.index('-F')
outfile=sys.argv[ind+1]
out=open(outfile,'w')
for k in range(N):
x='%f'%(pmag.gaussdev(mean,sigma)) # send kappa to fshdev
if outfile=="":
print(x)
else:
out.write(x+'\n') | NAME
gaussian.py
DESCRIPTION
generates set of normally distribed data from specified distribution
INPUT (COMMAND LINE ENTRY)
OUTPUT
x
SYNTAX
gaussian.py [command line options]
OPTIONS
-h prints help message and quits
-s specify standard deviation as next argument, default is 1
-n specify N as next argument, default is 100
-m specify mean as next argument, default is 0
-F specify output file | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/programs/gaussian.py#L7-L54 |
PmagPy/PmagPy | programs/qqunf.py | main | def main():
"""
NAME
qqunf.py
DESCRIPTION
makes qq plot from input data against uniform distribution
SYNTAX
qqunf.py [command line options]
OPTIONS
-h help message
-f FILE, specify file on command line
"""
fmt,plot='svg',0
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
elif '-f' in sys.argv: # ask for filename
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'r')
input=f.readlines()
Data=[]
for line in input:
line.replace('\n','')
if '\t' in line: # read in the data from standard input
rec=line.split('\t') # split each line on space to get records
else:
rec=line.split() # split each line on space to get records
Data.append(float(rec[0]))
#
if len(Data) >=10:
QQ={'unf1':1}
pmagplotlib.plot_init(QQ['unf1'],5,5)
pmagplotlib.plot_qq_unf(QQ['unf1'],Data,'QQ-Uniform') # make plot
else:
print('you need N> 10')
sys.exit()
pmagplotlib.draw_figs(QQ)
files={}
for key in list(QQ.keys()):
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
EQ = pmagplotlib.add_borders(EQ,titles,black,purple)
pmagplotlib.save_plots(QQ,files)
elif plot==1:
files['qq']=file+'.'+fmt
pmagplotlib.save_plots(QQ,files)
else:
ans=input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.save_plots(QQ,files) | python | def main():
"""
NAME
qqunf.py
DESCRIPTION
makes qq plot from input data against uniform distribution
SYNTAX
qqunf.py [command line options]
OPTIONS
-h help message
-f FILE, specify file on command line
"""
fmt,plot='svg',0
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
elif '-f' in sys.argv: # ask for filename
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'r')
input=f.readlines()
Data=[]
for line in input:
line.replace('\n','')
if '\t' in line: # read in the data from standard input
rec=line.split('\t') # split each line on space to get records
else:
rec=line.split() # split each line on space to get records
Data.append(float(rec[0]))
#
if len(Data) >=10:
QQ={'unf1':1}
pmagplotlib.plot_init(QQ['unf1'],5,5)
pmagplotlib.plot_qq_unf(QQ['unf1'],Data,'QQ-Uniform') # make plot
else:
print('you need N> 10')
sys.exit()
pmagplotlib.draw_figs(QQ)
files={}
for key in list(QQ.keys()):
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
EQ = pmagplotlib.add_borders(EQ,titles,black,purple)
pmagplotlib.save_plots(QQ,files)
elif plot==1:
files['qq']=file+'.'+fmt
pmagplotlib.save_plots(QQ,files)
else:
ans=input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a": pmagplotlib.save_plots(QQ,files) | NAME
qqunf.py
DESCRIPTION
makes qq plot from input data against uniform distribution
SYNTAX
qqunf.py [command line options]
OPTIONS
-h help message
-f FILE, specify file on command line | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/programs/qqunf.py#L10-L68 |
PmagPy/PmagPy | programs/qqplot.py | main | def main():
"""
NAME
qqplot.py
DESCRIPTION
makes qq plot of input data against a Normal distribution.
INPUT FORMAT
takes real numbers in single column
SYNTAX
qqplot.py [-h][-i][-f FILE]
OPTIONS
-f FILE, specify file on command line
-fmt [png,svg,jpg,eps] set plot output format [default is svg]
-sav saves and quits
OUTPUT
calculates the K-S D and the D expected for a normal distribution
when D<Dc, distribution is normal (at 95% level of confidence).
"""
fmt,plot='svg',0
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-sav' in sys.argv: plot=1
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-f' in sys.argv: # ask for filename
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'r')
data=f.readlines()
X= [] # set up list for data
for line in data: # read in the data from standard input
rec=line.split() # split each line on space to get records
X.append(float(rec[0])) # append data to X
#
QQ={'qq':1}
pmagplotlib.plot_init(QQ['qq'],5,5)
pmagplotlib.plot_qq_norm(QQ['qq'],X,'Q-Q Plot') # make plot
if plot==0:
pmagplotlib.draw_figs(QQ)
files={}
for key in list(QQ.keys()):
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Q-Q Plot'
QQ = pmagplotlib.add_borders(EQ,titles,black,purple)
pmagplotlib.save_plots(QQ,files)
elif plot==0:
ans=input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a":
pmagplotlib.save_plots(QQ,files)
else:
pmagplotlib.save_plots(QQ,files) | python | def main():
"""
NAME
qqplot.py
DESCRIPTION
makes qq plot of input data against a Normal distribution.
INPUT FORMAT
takes real numbers in single column
SYNTAX
qqplot.py [-h][-i][-f FILE]
OPTIONS
-f FILE, specify file on command line
-fmt [png,svg,jpg,eps] set plot output format [default is svg]
-sav saves and quits
OUTPUT
calculates the K-S D and the D expected for a normal distribution
when D<Dc, distribution is normal (at 95% level of confidence).
"""
fmt,plot='svg',0
if '-h' in sys.argv: # check if help is needed
print(main.__doc__)
sys.exit() # graceful quit
if '-sav' in sys.argv: plot=1
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-f' in sys.argv: # ask for filename
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
f=open(file,'r')
data=f.readlines()
X= [] # set up list for data
for line in data: # read in the data from standard input
rec=line.split() # split each line on space to get records
X.append(float(rec[0])) # append data to X
#
QQ={'qq':1}
pmagplotlib.plot_init(QQ['qq'],5,5)
pmagplotlib.plot_qq_norm(QQ['qq'],X,'Q-Q Plot') # make plot
if plot==0:
pmagplotlib.draw_figs(QQ)
files={}
for key in list(QQ.keys()):
files[key]=key+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Q-Q Plot'
QQ = pmagplotlib.add_borders(EQ,titles,black,purple)
pmagplotlib.save_plots(QQ,files)
elif plot==0:
ans=input(" S[a]ve to save plot, [q]uit without saving: ")
if ans=="a":
pmagplotlib.save_plots(QQ,files)
else:
pmagplotlib.save_plots(QQ,files) | NAME
qqplot.py
DESCRIPTION
makes qq plot of input data against a Normal distribution.
INPUT FORMAT
takes real numbers in single column
SYNTAX
qqplot.py [-h][-i][-f FILE]
OPTIONS
-f FILE, specify file on command line
-fmt [png,svg,jpg,eps] set plot output format [default is svg]
-sav saves and quits
OUTPUT
calculates the K-S D and the D expected for a normal distribution
when D<Dc, distribution is normal (at 95% level of confidence). | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/programs/qqplot.py#L11-L74 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.InitUI | def InitUI(self):
"""
initialize window
"""
self.main_sizer = wx.BoxSizer(wx.VERTICAL)
if self.grid_type in self.contribution.tables:
dataframe = self.contribution.tables[self.grid_type]
else:
dataframe = None
self.grid_builder = GridBuilder(self.contribution, self.grid_type,
self.panel, parent_type=self.parent_type,
reqd_headers=self.reqd_headers,
exclude_cols=self.exclude_cols,
huge=self.huge)
self.grid = self.grid_builder.make_grid()
self.grid.InitUI()
## Column management buttons
self.add_cols_button = wx.Button(self.panel, label="Add additional columns",
name='add_cols_btn',
size=(170, 20))
self.Bind(wx.EVT_BUTTON, self.on_add_cols, self.add_cols_button)
self.remove_cols_button = wx.Button(self.panel, label="Remove columns",
name='remove_cols_btn',
size=(170, 20))
self.Bind(wx.EVT_BUTTON, self.on_remove_cols, self.remove_cols_button)
## Row management buttons
self.remove_row_button = wx.Button(self.panel, label="Remove last row",
name='remove_last_row_btn')
self.Bind(wx.EVT_BUTTON, self.on_remove_row, self.remove_row_button)
many_rows_box = wx.BoxSizer(wx.HORIZONTAL)
self.add_many_rows_button = wx.Button(self.panel, label="Add row(s)",
name='add_many_rows_btn')
self.rows_spin_ctrl = wx.SpinCtrl(self.panel, value='1', initial=1,
name='rows_spin_ctrl')
many_rows_box.Add(self.add_many_rows_button, flag=wx.ALIGN_CENTRE)
many_rows_box.Add(self.rows_spin_ctrl)
self.Bind(wx.EVT_BUTTON, self.on_add_rows, self.add_many_rows_button)
self.deleteRowButton = wx.Button(self.panel, id=-1,
label='Delete selected row(s)',
name='delete_row_btn')
self.Bind(wx.EVT_BUTTON, lambda event: self.on_remove_row(event, False), self.deleteRowButton)
self.deleteRowButton.Disable()
# measurements table should not be able to add new rows
# that should be done elsewhere
if self.huge:
self.add_many_rows_button.Disable()
self.rows_spin_ctrl.Disable()
self.remove_row_button.Disable()
# can't remove cols (seg fault), but can add them
#self.add_cols_button.Disable()
self.remove_cols_button.Disable()
## Data management buttons
self.importButton = wx.Button(self.panel, id=-1,
label='Import MagIC-format file',
name='import_btn')
self.Bind(wx.EVT_BUTTON, self.onImport, self.importButton)
self.exitButton = wx.Button(self.panel, id=-1,
label='Save and close grid',
name='save_and_quit_btn')
self.Bind(wx.EVT_BUTTON, self.onSave, self.exitButton)
self.cancelButton = wx.Button(self.panel, id=-1, label='Cancel',
name='cancel_btn')
self.Bind(wx.EVT_BUTTON, self.onCancelButton, self.cancelButton)
self.Bind(wx.EVT_CLOSE, self.onCancelButton)
## Input/output buttons
self.copyButton = wx.Button(self.panel, id=-1,
label="Start copy mode",
name="copy_mode_btn")
self.Bind(wx.EVT_BUTTON, self.onCopyMode, self.copyButton)
self.selectAllButton = wx.Button(self.panel, id=-1,
label="Copy all cells",
name="select_all_btn")
self.Bind(wx.EVT_BUTTON, self.onSelectAll, self.selectAllButton)
self.copySelectionButton = wx.Button(self.panel, id=-1,
label="Copy selected cells",
name="copy_selection_btn")
self.Bind(wx.EVT_BUTTON, self.onCopySelection, self.copySelectionButton)
self.copySelectionButton.Disable()
## Help message and button
# button
self.toggle_help_btn = wx.Button(self.panel, id=-1, label="Show help",
name='toggle_help_btn')
self.Bind(wx.EVT_BUTTON, self.toggle_help, self.toggle_help_btn)
# message
self.help_msg_boxsizer = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, name='help_msg_boxsizer'), wx.VERTICAL)
if self.grid_type == 'measurements':
self.default_msg_text = "Edit measurements here.\nIn general, measurements should be imported directly into Pmag GUI,\nwhich has protocols for converting many lab formats into the MagIC format.\nIf we are missing your particular lab format, please let us know: https://github.com/PmagPy/PmagPy/issues.\nThis grid is just meant for looking at your measurements and doing small edits.\nCurrently, you can't add/remove rows here. You can add columns and edit cell values."
else:
self.default_msg_text = 'Edit {} here.\nYou can add or remove both rows and columns, however required columns may not be deleted.\nControlled vocabularies are indicated by **, and will have drop-down-menus.\nSuggested vocabularies are indicated by ^^, and also have drop-down-menus.\nTo edit all values in a column, click the column header.\nYou can cut and paste a block of cells from an Excel-like file.\nJust click the top left cell and use command "v".'.format(self.grid_type)
txt = ''
if self.grid_type == 'locations':
txt = '\n\nNote: you can fill in location start/end latitude/longitude here.\nHowever, if you add sites in step 2, the program will calculate those values automatically,\nbased on site latitudes/logitudes.\nThese values will be written to your upload file.'
if self.grid_type == 'samples':
txt = "\n\nNote: you can fill in lithology, class, and type for each sample here.\nHowever, if the sample's class, lithology, and type are the same as its parent site,\nthose values will propagate down, and will be written to your sample file automatically."
if self.grid_type == 'specimens':
txt = "\n\nNote: you can fill in lithology, class, and type for each specimen here.\nHowever, if the specimen's class, lithology, and type are the same as its parent sample,\nthose values will propagate down, and will be written to your specimen file automatically."
if self.grid_type == 'ages':
txt = "\n\nNote: only ages for which you provide data will be written to your upload file."
self.default_msg_text += txt
self.msg_text = wx.StaticText(self.panel, label=self.default_msg_text,
style=wx.TE_CENTER, name='msg text')
self.help_msg_boxsizer.Add(self.msg_text)
self.help_msg_boxsizer.ShowItems(False)
## Code message and button
# button
self.toggle_codes_btn = wx.Button(self.panel, id=-1,
label="Show method codes",
name='toggle_codes_btn')
self.Bind(wx.EVT_BUTTON, self.toggle_codes, self.toggle_codes_btn)
# message
self.code_msg_boxsizer = pw.MethodCodeDemystifier(self.panel, self.contribution.vocab)
self.code_msg_boxsizer.ShowItems(False)
## Add content to sizers
self.hbox = wx.BoxSizer(wx.HORIZONTAL)
col_btn_vbox = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, label='Columns',
name='manage columns'), wx.VERTICAL)
row_btn_vbox = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, label='Rows',
name='manage rows'), wx.VERTICAL)
self.main_btn_vbox = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, label='Manage data',
name='manage data'), wx.VERTICAL)
input_output_vbox = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, label='In/Out',
name='manage in out'), wx.VERTICAL)
col_btn_vbox.Add(self.add_cols_button, flag=wx.ALL, border=5)
col_btn_vbox.Add(self.remove_cols_button, flag=wx.ALL, border=5)
row_btn_vbox.Add(many_rows_box, flag=wx.ALL, border=5)
row_btn_vbox.Add(self.remove_row_button, flag=wx.ALL, border=5)
row_btn_vbox.Add(self.deleteRowButton, flag=wx.ALL, border=5)
self.main_btn_vbox.Add(self.importButton, flag=wx.ALL, border=5)
self.main_btn_vbox.Add(self.exitButton, flag=wx.ALL, border=5)
self.main_btn_vbox.Add(self.cancelButton, flag=wx.ALL, border=5)
input_output_vbox.Add(self.copyButton, flag=wx.ALL, border=5)
input_output_vbox.Add(self.selectAllButton, flag=wx.ALL, border=5)
input_output_vbox.Add(self.copySelectionButton, flag=wx.ALL, border=5)
self.hbox.Add(col_btn_vbox)
self.hbox.Add(row_btn_vbox)
self.hbox.Add(self.main_btn_vbox)
self.hbox.Add(input_output_vbox)
#self.panel.Bind(wx.grid.EVT_GRID_LABEL_LEFT_CLICK, self.onLeftClickLabel, self.grid)
self.grid.Bind(wx.grid.EVT_GRID_LABEL_LEFT_CLICK, self.onLeftClickLabel, self.grid)
#
self.Bind(wx.EVT_KEY_DOWN, self.on_key_down)
self.panel.Bind(wx.EVT_TEXT_PASTE, self.do_fit)
# add actual data!
self.grid_builder.add_data_to_grid(self.grid, self.grid_type)
# fill in some default values
self.grid_builder.fill_defaults()
# set scrollbars
self.grid.set_scrollbars()
## this would be a way to prevent editing
## some cells in age grid.
## with multiple types of ages, though,
## this doesn't make much sense
#if self.grid_type == 'ages':
# attr = wx.grid.GridCellAttr()
# attr.SetReadOnly(True)
# self.grid.SetColAttr(1, attr)
self.drop_down_menu = drop_down_menus.Menus(self.grid_type, self.contribution, self.grid)
self.grid_box = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, name='grid container'), wx.VERTICAL)
self.grid_box.Add(self.grid, 1, flag=wx.ALL|wx.EXPAND, border=5)
# final layout, set size
self.main_sizer.Add(self.hbox, flag=wx.ALL|wx.ALIGN_CENTER,#|wx.SHAPED,
border=20)
self.main_sizer.Add(self.toggle_help_btn, 0,
flag=wx.BOTTOM|wx.ALIGN_CENTRE,#|wx.SHAPED,
border=5)
self.main_sizer.Add(self.help_msg_boxsizer, 0,
flag=wx.BOTTOM|wx.ALIGN_CENTRE,
border=10)
self.main_sizer.Add(self.toggle_codes_btn, 0,
flag=wx.BOTTOM|wx.ALIGN_CENTRE,#|wx.SHAPED,
border=5)
self.main_sizer.Add(self.code_msg_boxsizer, 0,
flag=wx.BOTTOM|wx.ALIGN_CENTRE,#|wx.SHAPED,
border=5)
self.main_sizer.Add(self.grid_box, 2, flag=wx.ALL|wx.ALIGN_CENTER|wx.EXPAND, border=10)
self.panel.SetSizer(self.main_sizer)
panel_sizer = wx.BoxSizer(wx.VERTICAL)
panel_sizer.Add(self.panel, 1, wx.EXPAND)
self.SetSizer(panel_sizer)
panel_sizer.Fit(self)
## this keeps sizing correct if the user resizes the window manually
#self.Bind(wx.EVT_SIZE, self.do_fit)
# self.Centre()
self.Show() | python | def InitUI(self):
"""
initialize window
"""
self.main_sizer = wx.BoxSizer(wx.VERTICAL)
if self.grid_type in self.contribution.tables:
dataframe = self.contribution.tables[self.grid_type]
else:
dataframe = None
self.grid_builder = GridBuilder(self.contribution, self.grid_type,
self.panel, parent_type=self.parent_type,
reqd_headers=self.reqd_headers,
exclude_cols=self.exclude_cols,
huge=self.huge)
self.grid = self.grid_builder.make_grid()
self.grid.InitUI()
## Column management buttons
self.add_cols_button = wx.Button(self.panel, label="Add additional columns",
name='add_cols_btn',
size=(170, 20))
self.Bind(wx.EVT_BUTTON, self.on_add_cols, self.add_cols_button)
self.remove_cols_button = wx.Button(self.panel, label="Remove columns",
name='remove_cols_btn',
size=(170, 20))
self.Bind(wx.EVT_BUTTON, self.on_remove_cols, self.remove_cols_button)
## Row management buttons
self.remove_row_button = wx.Button(self.panel, label="Remove last row",
name='remove_last_row_btn')
self.Bind(wx.EVT_BUTTON, self.on_remove_row, self.remove_row_button)
many_rows_box = wx.BoxSizer(wx.HORIZONTAL)
self.add_many_rows_button = wx.Button(self.panel, label="Add row(s)",
name='add_many_rows_btn')
self.rows_spin_ctrl = wx.SpinCtrl(self.panel, value='1', initial=1,
name='rows_spin_ctrl')
many_rows_box.Add(self.add_many_rows_button, flag=wx.ALIGN_CENTRE)
many_rows_box.Add(self.rows_spin_ctrl)
self.Bind(wx.EVT_BUTTON, self.on_add_rows, self.add_many_rows_button)
self.deleteRowButton = wx.Button(self.panel, id=-1,
label='Delete selected row(s)',
name='delete_row_btn')
self.Bind(wx.EVT_BUTTON, lambda event: self.on_remove_row(event, False), self.deleteRowButton)
self.deleteRowButton.Disable()
# measurements table should not be able to add new rows
# that should be done elsewhere
if self.huge:
self.add_many_rows_button.Disable()
self.rows_spin_ctrl.Disable()
self.remove_row_button.Disable()
# can't remove cols (seg fault), but can add them
#self.add_cols_button.Disable()
self.remove_cols_button.Disable()
## Data management buttons
self.importButton = wx.Button(self.panel, id=-1,
label='Import MagIC-format file',
name='import_btn')
self.Bind(wx.EVT_BUTTON, self.onImport, self.importButton)
self.exitButton = wx.Button(self.panel, id=-1,
label='Save and close grid',
name='save_and_quit_btn')
self.Bind(wx.EVT_BUTTON, self.onSave, self.exitButton)
self.cancelButton = wx.Button(self.panel, id=-1, label='Cancel',
name='cancel_btn')
self.Bind(wx.EVT_BUTTON, self.onCancelButton, self.cancelButton)
self.Bind(wx.EVT_CLOSE, self.onCancelButton)
## Input/output buttons
self.copyButton = wx.Button(self.panel, id=-1,
label="Start copy mode",
name="copy_mode_btn")
self.Bind(wx.EVT_BUTTON, self.onCopyMode, self.copyButton)
self.selectAllButton = wx.Button(self.panel, id=-1,
label="Copy all cells",
name="select_all_btn")
self.Bind(wx.EVT_BUTTON, self.onSelectAll, self.selectAllButton)
self.copySelectionButton = wx.Button(self.panel, id=-1,
label="Copy selected cells",
name="copy_selection_btn")
self.Bind(wx.EVT_BUTTON, self.onCopySelection, self.copySelectionButton)
self.copySelectionButton.Disable()
## Help message and button
# button
self.toggle_help_btn = wx.Button(self.panel, id=-1, label="Show help",
name='toggle_help_btn')
self.Bind(wx.EVT_BUTTON, self.toggle_help, self.toggle_help_btn)
# message
self.help_msg_boxsizer = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, name='help_msg_boxsizer'), wx.VERTICAL)
if self.grid_type == 'measurements':
self.default_msg_text = "Edit measurements here.\nIn general, measurements should be imported directly into Pmag GUI,\nwhich has protocols for converting many lab formats into the MagIC format.\nIf we are missing your particular lab format, please let us know: https://github.com/PmagPy/PmagPy/issues.\nThis grid is just meant for looking at your measurements and doing small edits.\nCurrently, you can't add/remove rows here. You can add columns and edit cell values."
else:
self.default_msg_text = 'Edit {} here.\nYou can add or remove both rows and columns, however required columns may not be deleted.\nControlled vocabularies are indicated by **, and will have drop-down-menus.\nSuggested vocabularies are indicated by ^^, and also have drop-down-menus.\nTo edit all values in a column, click the column header.\nYou can cut and paste a block of cells from an Excel-like file.\nJust click the top left cell and use command "v".'.format(self.grid_type)
txt = ''
if self.grid_type == 'locations':
txt = '\n\nNote: you can fill in location start/end latitude/longitude here.\nHowever, if you add sites in step 2, the program will calculate those values automatically,\nbased on site latitudes/logitudes.\nThese values will be written to your upload file.'
if self.grid_type == 'samples':
txt = "\n\nNote: you can fill in lithology, class, and type for each sample here.\nHowever, if the sample's class, lithology, and type are the same as its parent site,\nthose values will propagate down, and will be written to your sample file automatically."
if self.grid_type == 'specimens':
txt = "\n\nNote: you can fill in lithology, class, and type for each specimen here.\nHowever, if the specimen's class, lithology, and type are the same as its parent sample,\nthose values will propagate down, and will be written to your specimen file automatically."
if self.grid_type == 'ages':
txt = "\n\nNote: only ages for which you provide data will be written to your upload file."
self.default_msg_text += txt
self.msg_text = wx.StaticText(self.panel, label=self.default_msg_text,
style=wx.TE_CENTER, name='msg text')
self.help_msg_boxsizer.Add(self.msg_text)
self.help_msg_boxsizer.ShowItems(False)
## Code message and button
# button
self.toggle_codes_btn = wx.Button(self.panel, id=-1,
label="Show method codes",
name='toggle_codes_btn')
self.Bind(wx.EVT_BUTTON, self.toggle_codes, self.toggle_codes_btn)
# message
self.code_msg_boxsizer = pw.MethodCodeDemystifier(self.panel, self.contribution.vocab)
self.code_msg_boxsizer.ShowItems(False)
## Add content to sizers
self.hbox = wx.BoxSizer(wx.HORIZONTAL)
col_btn_vbox = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, label='Columns',
name='manage columns'), wx.VERTICAL)
row_btn_vbox = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, label='Rows',
name='manage rows'), wx.VERTICAL)
self.main_btn_vbox = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, label='Manage data',
name='manage data'), wx.VERTICAL)
input_output_vbox = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, label='In/Out',
name='manage in out'), wx.VERTICAL)
col_btn_vbox.Add(self.add_cols_button, flag=wx.ALL, border=5)
col_btn_vbox.Add(self.remove_cols_button, flag=wx.ALL, border=5)
row_btn_vbox.Add(many_rows_box, flag=wx.ALL, border=5)
row_btn_vbox.Add(self.remove_row_button, flag=wx.ALL, border=5)
row_btn_vbox.Add(self.deleteRowButton, flag=wx.ALL, border=5)
self.main_btn_vbox.Add(self.importButton, flag=wx.ALL, border=5)
self.main_btn_vbox.Add(self.exitButton, flag=wx.ALL, border=5)
self.main_btn_vbox.Add(self.cancelButton, flag=wx.ALL, border=5)
input_output_vbox.Add(self.copyButton, flag=wx.ALL, border=5)
input_output_vbox.Add(self.selectAllButton, flag=wx.ALL, border=5)
input_output_vbox.Add(self.copySelectionButton, flag=wx.ALL, border=5)
self.hbox.Add(col_btn_vbox)
self.hbox.Add(row_btn_vbox)
self.hbox.Add(self.main_btn_vbox)
self.hbox.Add(input_output_vbox)
#self.panel.Bind(wx.grid.EVT_GRID_LABEL_LEFT_CLICK, self.onLeftClickLabel, self.grid)
self.grid.Bind(wx.grid.EVT_GRID_LABEL_LEFT_CLICK, self.onLeftClickLabel, self.grid)
#
self.Bind(wx.EVT_KEY_DOWN, self.on_key_down)
self.panel.Bind(wx.EVT_TEXT_PASTE, self.do_fit)
# add actual data!
self.grid_builder.add_data_to_grid(self.grid, self.grid_type)
# fill in some default values
self.grid_builder.fill_defaults()
# set scrollbars
self.grid.set_scrollbars()
## this would be a way to prevent editing
## some cells in age grid.
## with multiple types of ages, though,
## this doesn't make much sense
#if self.grid_type == 'ages':
# attr = wx.grid.GridCellAttr()
# attr.SetReadOnly(True)
# self.grid.SetColAttr(1, attr)
self.drop_down_menu = drop_down_menus.Menus(self.grid_type, self.contribution, self.grid)
self.grid_box = wx.StaticBoxSizer(wx.StaticBox(self.panel, -1, name='grid container'), wx.VERTICAL)
self.grid_box.Add(self.grid, 1, flag=wx.ALL|wx.EXPAND, border=5)
# final layout, set size
self.main_sizer.Add(self.hbox, flag=wx.ALL|wx.ALIGN_CENTER,#|wx.SHAPED,
border=20)
self.main_sizer.Add(self.toggle_help_btn, 0,
flag=wx.BOTTOM|wx.ALIGN_CENTRE,#|wx.SHAPED,
border=5)
self.main_sizer.Add(self.help_msg_boxsizer, 0,
flag=wx.BOTTOM|wx.ALIGN_CENTRE,
border=10)
self.main_sizer.Add(self.toggle_codes_btn, 0,
flag=wx.BOTTOM|wx.ALIGN_CENTRE,#|wx.SHAPED,
border=5)
self.main_sizer.Add(self.code_msg_boxsizer, 0,
flag=wx.BOTTOM|wx.ALIGN_CENTRE,#|wx.SHAPED,
border=5)
self.main_sizer.Add(self.grid_box, 2, flag=wx.ALL|wx.ALIGN_CENTER|wx.EXPAND, border=10)
self.panel.SetSizer(self.main_sizer)
panel_sizer = wx.BoxSizer(wx.VERTICAL)
panel_sizer.Add(self.panel, 1, wx.EXPAND)
self.SetSizer(panel_sizer)
panel_sizer.Fit(self)
## this keeps sizing correct if the user resizes the window manually
#self.Bind(wx.EVT_SIZE, self.do_fit)
# self.Centre()
self.Show() | initialize window | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L89-L291 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.on_key_down | def on_key_down(self, event):
"""
If user does command v,
re-size window in case pasting has changed the content size.
"""
keycode = event.GetKeyCode()
meta_down = event.MetaDown() or event.GetCmdDown()
if keycode == 86 and meta_down:
# treat it as if it were a wx.EVT_TEXT_SIZE
self.do_fit(event) | python | def on_key_down(self, event):
"""
If user does command v,
re-size window in case pasting has changed the content size.
"""
keycode = event.GetKeyCode()
meta_down = event.MetaDown() or event.GetCmdDown()
if keycode == 86 and meta_down:
# treat it as if it were a wx.EVT_TEXT_SIZE
self.do_fit(event) | If user does command v,
re-size window in case pasting has changed the content size. | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L293-L302 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.do_fit | def do_fit(self, event, min_size=None):
"""
Re-fit the window to the size of the content.
"""
#self.grid.ShowScrollbars(wx.SHOW_SB_NEVER, wx.SHOW_SB_NEVER)
if event:
event.Skip()
self.main_sizer.Fit(self)
disp_size = wx.GetDisplaySize()
actual_size = self.GetSize()
# if there isn't enough room to display new content
# resize the frame
if disp_size[1] - 75 < actual_size[1]:
self.SetSize((actual_size[0], disp_size[1] * .95))
# make sure you adhere to a minimum size
if min_size:
actual_size = self.GetSize()
larger_width = max([actual_size[0], min_size[0]])
larger_height = max([actual_size[1], min_size[1]])
if larger_width > actual_size[0] or larger_height > actual_size[1]:
self.SetSize((larger_width, larger_height))
self.Centre() | python | def do_fit(self, event, min_size=None):
"""
Re-fit the window to the size of the content.
"""
#self.grid.ShowScrollbars(wx.SHOW_SB_NEVER, wx.SHOW_SB_NEVER)
if event:
event.Skip()
self.main_sizer.Fit(self)
disp_size = wx.GetDisplaySize()
actual_size = self.GetSize()
# if there isn't enough room to display new content
# resize the frame
if disp_size[1] - 75 < actual_size[1]:
self.SetSize((actual_size[0], disp_size[1] * .95))
# make sure you adhere to a minimum size
if min_size:
actual_size = self.GetSize()
larger_width = max([actual_size[0], min_size[0]])
larger_height = max([actual_size[1], min_size[1]])
if larger_width > actual_size[0] or larger_height > actual_size[1]:
self.SetSize((larger_width, larger_height))
self.Centre() | Re-fit the window to the size of the content. | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L304-L325 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.toggle_help | def toggle_help(self, event, mode=None):
"""
Show/hide help message on help button click.
"""
# if mode == 'open', show no matter what.
# if mode == 'close', close. otherwise, change state
btn = self.toggle_help_btn
shown = self.help_msg_boxsizer.GetStaticBox().IsShown()
# if mode is specified, do that mode
if mode == 'open':
self.help_msg_boxsizer.ShowItems(True)
btn.SetLabel('Hide help')
elif mode == 'close':
self.help_msg_boxsizer.ShowItems(False)
btn.SetLabel('Show help')
# otherwise, simply toggle states
else:
if shown:
self.help_msg_boxsizer.ShowItems(False)
btn.SetLabel('Show help')
else:
self.help_msg_boxsizer.ShowItems(True)
btn.SetLabel('Hide help')
self.do_fit(None) | python | def toggle_help(self, event, mode=None):
"""
Show/hide help message on help button click.
"""
# if mode == 'open', show no matter what.
# if mode == 'close', close. otherwise, change state
btn = self.toggle_help_btn
shown = self.help_msg_boxsizer.GetStaticBox().IsShown()
# if mode is specified, do that mode
if mode == 'open':
self.help_msg_boxsizer.ShowItems(True)
btn.SetLabel('Hide help')
elif mode == 'close':
self.help_msg_boxsizer.ShowItems(False)
btn.SetLabel('Show help')
# otherwise, simply toggle states
else:
if shown:
self.help_msg_boxsizer.ShowItems(False)
btn.SetLabel('Show help')
else:
self.help_msg_boxsizer.ShowItems(True)
btn.SetLabel('Hide help')
self.do_fit(None) | Show/hide help message on help button click. | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L327-L350 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.toggle_codes | def toggle_codes(self, event):
"""
Show/hide method code explanation widget on button click
"""
btn = event.GetEventObject()
if btn.Label == 'Show method codes':
self.code_msg_boxsizer.ShowItems(True)
btn.SetLabel('Hide method codes')
else:
self.code_msg_boxsizer.ShowItems(False)
btn.SetLabel('Show method codes')
self.do_fit(None) | python | def toggle_codes(self, event):
"""
Show/hide method code explanation widget on button click
"""
btn = event.GetEventObject()
if btn.Label == 'Show method codes':
self.code_msg_boxsizer.ShowItems(True)
btn.SetLabel('Hide method codes')
else:
self.code_msg_boxsizer.ShowItems(False)
btn.SetLabel('Show method codes')
self.do_fit(None) | Show/hide method code explanation widget on button click | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L353-L364 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.remove_col_label | def remove_col_label(self, event=None, col=None):
"""
check to see if column is required
if it is not, delete it from grid
"""
if event:
col = event.GetCol()
if not col:
return
label = self.grid.GetColLabelValue(col)
if '**' in label:
label = label.strip('**')
elif '^^' in label:
label = label.strip('^^')
if label in self.reqd_headers:
pw.simple_warning("That header is required, and cannot be removed")
return False
else:
print('That header is not required:', label)
# remove column from wxPython grid
self.grid.remove_col(col)
# remove column from DataFrame if present
if self.grid_type in self.contribution.tables:
if label in self.contribution.tables[self.grid_type].df.columns:
del self.contribution.tables[self.grid_type].df[label]
# causes resize on each column header delete
# can leave this out if we want.....
self.main_sizer.Fit(self) | python | def remove_col_label(self, event=None, col=None):
"""
check to see if column is required
if it is not, delete it from grid
"""
if event:
col = event.GetCol()
if not col:
return
label = self.grid.GetColLabelValue(col)
if '**' in label:
label = label.strip('**')
elif '^^' in label:
label = label.strip('^^')
if label in self.reqd_headers:
pw.simple_warning("That header is required, and cannot be removed")
return False
else:
print('That header is not required:', label)
# remove column from wxPython grid
self.grid.remove_col(col)
# remove column from DataFrame if present
if self.grid_type in self.contribution.tables:
if label in self.contribution.tables[self.grid_type].df.columns:
del self.contribution.tables[self.grid_type].df[label]
# causes resize on each column header delete
# can leave this out if we want.....
self.main_sizer.Fit(self) | check to see if column is required
if it is not, delete it from grid | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L381-L408 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.on_add_cols | def on_add_cols(self, event):
"""
Show simple dialog that allows user to add a new column name
"""
col_labels = self.grid.col_labels
dia = pw.ChooseOne(self, yes="Add single columns", no="Add groups")
result1 = dia.ShowModal()
if result1 == wx.ID_CANCEL:
return
elif result1 == wx.ID_YES:
items = sorted([col_name for col_name in self.dm.index if col_name not in col_labels])
dia = pw.HeaderDialog(self, 'columns to add',
items1=list(items), groups=[])
dia.Centre()
result2 = dia.ShowModal()
else:
groups = self.dm['group'].unique()
dia = pw.HeaderDialog(self, 'groups to add',
items1=list(groups), groups=True)
dia.Centre()
result2 = dia.ShowModal()
new_headers = []
if result2 == 5100:
new_headers = dia.text_list
# if there is nothing to add, quit
if not new_headers:
return
if result1 == wx.ID_YES:
# add individual headers
errors = self.add_new_grid_headers(new_headers)
else:
# add header groups
errors = self.add_new_header_groups(new_headers)
if errors:
errors_str = ', '.join(errors)
pw.simple_warning('You are already using the following headers: {}\nSo they will not be added'.format(errors_str))
# problem: if widgets above the grid are too wide,
# the grid does not re-size when adding columns
# awkward solution (causes flashing):
if self.grid.GetWindowStyle() != wx.DOUBLE_BORDER:
self.grid.SetWindowStyle(wx.DOUBLE_BORDER)
self.main_sizer.Fit(self)
self.grid.SetWindowStyle(wx.NO_BORDER)
self.Centre()
self.main_sizer.Fit(self)
#
self.grid.changes = set(range(self.grid.GetNumberRows()))
dia.Destroy() | python | def on_add_cols(self, event):
"""
Show simple dialog that allows user to add a new column name
"""
col_labels = self.grid.col_labels
dia = pw.ChooseOne(self, yes="Add single columns", no="Add groups")
result1 = dia.ShowModal()
if result1 == wx.ID_CANCEL:
return
elif result1 == wx.ID_YES:
items = sorted([col_name for col_name in self.dm.index if col_name not in col_labels])
dia = pw.HeaderDialog(self, 'columns to add',
items1=list(items), groups=[])
dia.Centre()
result2 = dia.ShowModal()
else:
groups = self.dm['group'].unique()
dia = pw.HeaderDialog(self, 'groups to add',
items1=list(groups), groups=True)
dia.Centre()
result2 = dia.ShowModal()
new_headers = []
if result2 == 5100:
new_headers = dia.text_list
# if there is nothing to add, quit
if not new_headers:
return
if result1 == wx.ID_YES:
# add individual headers
errors = self.add_new_grid_headers(new_headers)
else:
# add header groups
errors = self.add_new_header_groups(new_headers)
if errors:
errors_str = ', '.join(errors)
pw.simple_warning('You are already using the following headers: {}\nSo they will not be added'.format(errors_str))
# problem: if widgets above the grid are too wide,
# the grid does not re-size when adding columns
# awkward solution (causes flashing):
if self.grid.GetWindowStyle() != wx.DOUBLE_BORDER:
self.grid.SetWindowStyle(wx.DOUBLE_BORDER)
self.main_sizer.Fit(self)
self.grid.SetWindowStyle(wx.NO_BORDER)
self.Centre()
self.main_sizer.Fit(self)
#
self.grid.changes = set(range(self.grid.GetNumberRows()))
dia.Destroy() | Show simple dialog that allows user to add a new column name | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L410-L458 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.add_new_header_groups | def add_new_header_groups(self, groups):
"""
compile list of all headers belonging to all specified groups
eliminate all headers that are already included
add any req'd drop-down menus
return errors
"""
already_present = []
for group in groups:
col_names = self.dm[self.dm['group'] == group].index
for col in col_names:
if col not in self.grid.col_labels:
col_number = self.grid.add_col(col)
# add to appropriate headers list
# add drop down menus for user-added column
if col in self.contribution.vocab.vocabularies:
self.drop_down_menu.add_drop_down(col_number, col)
elif col in self.contribution.vocab.suggested:
self.drop_down_menu.add_drop_down(col_number, col)
elif col in ['specimen', 'sample', 'site', 'location',
'specimens', 'samples', 'sites']:
self.drop_down_menu.add_drop_down(col_number, col)
elif col == 'experiments':
self.drop_down_menu.add_drop_down(col_number, col)
if col == "method_codes":
self.drop_down_menu.add_method_drop_down(col_number, col)
else:
already_present.append(col)
return already_present | python | def add_new_header_groups(self, groups):
"""
compile list of all headers belonging to all specified groups
eliminate all headers that are already included
add any req'd drop-down menus
return errors
"""
already_present = []
for group in groups:
col_names = self.dm[self.dm['group'] == group].index
for col in col_names:
if col not in self.grid.col_labels:
col_number = self.grid.add_col(col)
# add to appropriate headers list
# add drop down menus for user-added column
if col in self.contribution.vocab.vocabularies:
self.drop_down_menu.add_drop_down(col_number, col)
elif col in self.contribution.vocab.suggested:
self.drop_down_menu.add_drop_down(col_number, col)
elif col in ['specimen', 'sample', 'site', 'location',
'specimens', 'samples', 'sites']:
self.drop_down_menu.add_drop_down(col_number, col)
elif col == 'experiments':
self.drop_down_menu.add_drop_down(col_number, col)
if col == "method_codes":
self.drop_down_menu.add_method_drop_down(col_number, col)
else:
already_present.append(col)
return already_present | compile list of all headers belonging to all specified groups
eliminate all headers that are already included
add any req'd drop-down menus
return errors | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L460-L488 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.add_new_grid_headers | def add_new_grid_headers(self, new_headers):
"""
Add in all user-added headers.
If those new headers depend on other headers,
add the other headers too.
"""
already_present = []
for name in new_headers:
if name:
if name not in self.grid.col_labels:
col_number = self.grid.add_col(name)
# add to appropriate headers list
# add drop down menus for user-added column
if name in self.contribution.vocab.vocabularies:
self.drop_down_menu.add_drop_down(col_number, name)
elif name in self.contribution.vocab.suggested:
self.drop_down_menu.add_drop_down(col_number, name)
elif name in ['specimen', 'sample', 'site',
'specimens', 'samples', 'sites']:
self.drop_down_menu.add_drop_down(col_number, name)
elif name == 'experiments':
self.drop_down_menu.add_drop_down(col_number, name)
if name == "method_codes":
self.drop_down_menu.add_method_drop_down(col_number, name)
else:
already_present.append(name)
#pw.simple_warning('You are already using column header: {}'.format(name))
return already_present | python | def add_new_grid_headers(self, new_headers):
"""
Add in all user-added headers.
If those new headers depend on other headers,
add the other headers too.
"""
already_present = []
for name in new_headers:
if name:
if name not in self.grid.col_labels:
col_number = self.grid.add_col(name)
# add to appropriate headers list
# add drop down menus for user-added column
if name in self.contribution.vocab.vocabularies:
self.drop_down_menu.add_drop_down(col_number, name)
elif name in self.contribution.vocab.suggested:
self.drop_down_menu.add_drop_down(col_number, name)
elif name in ['specimen', 'sample', 'site',
'specimens', 'samples', 'sites']:
self.drop_down_menu.add_drop_down(col_number, name)
elif name == 'experiments':
self.drop_down_menu.add_drop_down(col_number, name)
if name == "method_codes":
self.drop_down_menu.add_method_drop_down(col_number, name)
else:
already_present.append(name)
#pw.simple_warning('You are already using column header: {}'.format(name))
return already_present | Add in all user-added headers.
If those new headers depend on other headers,
add the other headers too. | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L490-L517 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.on_add_rows | def on_add_rows(self, event):
"""
add rows to grid
"""
num_rows = self.rows_spin_ctrl.GetValue()
#last_row = self.grid.GetNumberRows()
for row in range(num_rows):
self.grid.add_row()
#if not self.grid.changes:
# self.grid.changes = set([])
#self.grid.changes.add(last_row)
#last_row += 1
self.main_sizer.Fit(self) | python | def on_add_rows(self, event):
"""
add rows to grid
"""
num_rows = self.rows_spin_ctrl.GetValue()
#last_row = self.grid.GetNumberRows()
for row in range(num_rows):
self.grid.add_row()
#if not self.grid.changes:
# self.grid.changes = set([])
#self.grid.changes.add(last_row)
#last_row += 1
self.main_sizer.Fit(self) | add rows to grid | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L545-L557 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.on_remove_row | def on_remove_row(self, event, row_num=-1):
"""
Remove specified grid row.
If no row number is given, remove the last row.
"""
text = "Are you sure? If you select delete you won't be able to retrieve these rows..."
dia = pw.ChooseOne(self, "Yes, delete rows", "Leave rows for now", text)
dia.Centre()
result = dia.ShowModal()
if result == wx.ID_NO:
return
default = (255, 255, 255, 255)
if row_num == -1:
# unhighlight any selected rows:
for row in self.selected_rows:
attr = wx.grid.GridCellAttr()
attr.SetBackgroundColour(default)
self.grid.SetRowAttr(row, attr)
row_num = self.grid.GetNumberRows() - 1
self.deleteRowButton.Disable()
self.selected_rows = {row_num}
# remove row(s) from the contribution
df = self.contribution.tables[self.grid_type].df
row_nums = list(range(len(df)))
df = df.iloc[[i for i in row_nums if i not in self.selected_rows]]
self.contribution.tables[self.grid_type].df = df
# now remove row(s) from grid
# delete rows, adjusting the row # appropriately as you delete
for num, row in enumerate(self.selected_rows):
row -= num
if row < 0:
row = 0
self.grid.remove_row(row)
attr = wx.grid.GridCellAttr()
attr.SetBackgroundColour(default)
self.grid.SetRowAttr(row, attr)
# reset the grid
self.selected_rows = set()
self.deleteRowButton.Disable()
self.grid.Refresh()
self.main_sizer.Fit(self) | python | def on_remove_row(self, event, row_num=-1):
"""
Remove specified grid row.
If no row number is given, remove the last row.
"""
text = "Are you sure? If you select delete you won't be able to retrieve these rows..."
dia = pw.ChooseOne(self, "Yes, delete rows", "Leave rows for now", text)
dia.Centre()
result = dia.ShowModal()
if result == wx.ID_NO:
return
default = (255, 255, 255, 255)
if row_num == -1:
# unhighlight any selected rows:
for row in self.selected_rows:
attr = wx.grid.GridCellAttr()
attr.SetBackgroundColour(default)
self.grid.SetRowAttr(row, attr)
row_num = self.grid.GetNumberRows() - 1
self.deleteRowButton.Disable()
self.selected_rows = {row_num}
# remove row(s) from the contribution
df = self.contribution.tables[self.grid_type].df
row_nums = list(range(len(df)))
df = df.iloc[[i for i in row_nums if i not in self.selected_rows]]
self.contribution.tables[self.grid_type].df = df
# now remove row(s) from grid
# delete rows, adjusting the row # appropriately as you delete
for num, row in enumerate(self.selected_rows):
row -= num
if row < 0:
row = 0
self.grid.remove_row(row)
attr = wx.grid.GridCellAttr()
attr.SetBackgroundColour(default)
self.grid.SetRowAttr(row, attr)
# reset the grid
self.selected_rows = set()
self.deleteRowButton.Disable()
self.grid.Refresh()
self.main_sizer.Fit(self) | Remove specified grid row.
If no row number is given, remove the last row. | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L559-L599 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.onLeftClickLabel | def onLeftClickLabel(self, event):
"""
When user clicks on a grid label,
determine if it is a row label or a col label.
Pass along the event to the appropriate function.
(It will either highlight a column for editing all values,
or highlight a row for deletion).
"""
if event.Col == -1 and event.Row == -1:
pass
if event.Row < 0:
if self.remove_cols_mode:
self.remove_col_label(event)
else:
self.drop_down_menu.on_label_click(event)
else:
if event.Col < 0 and self.grid_type != 'age':
self.onSelectRow(event) | python | def onLeftClickLabel(self, event):
"""
When user clicks on a grid label,
determine if it is a row label or a col label.
Pass along the event to the appropriate function.
(It will either highlight a column for editing all values,
or highlight a row for deletion).
"""
if event.Col == -1 and event.Row == -1:
pass
if event.Row < 0:
if self.remove_cols_mode:
self.remove_col_label(event)
else:
self.drop_down_menu.on_label_click(event)
else:
if event.Col < 0 and self.grid_type != 'age':
self.onSelectRow(event) | When user clicks on a grid label,
determine if it is a row label or a col label.
Pass along the event to the appropriate function.
(It will either highlight a column for editing all values,
or highlight a row for deletion). | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L651-L668 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.onImport | def onImport(self, event):
"""
Import a MagIC-format file
"""
if self.grid.changes:
print("-W- Your changes will be overwritten...")
wind = pw.ChooseOne(self, "Import file anyway", "Save grid first",
"-W- Your grid has unsaved changes which will be overwritten if you import a file now...")
wind.Centre()
res = wind.ShowModal()
# save grid first:
if res == wx.ID_NO:
self.onSave(None, alert=True, destroy=False)
# reset self.changes
self.grid.changes = set()
openFileDialog = wx.FileDialog(self, "Open MagIC-format file", self.WD, "",
"MagIC file|*.*", wx.FD_OPEN | wx.FD_FILE_MUST_EXIST)
result = openFileDialog.ShowModal()
if result == wx.ID_OK:
# get filename
filename = openFileDialog.GetPath()
# make sure the dtype is correct
f = open(filename)
line = f.readline()
if line.startswith("tab"):
delim, dtype = line.split("\t")
else:
delim, dtype = line.split("")
f.close()
dtype = dtype.strip()
if (dtype != self.grid_type) and (dtype + "s" != self.grid_type):
text = "You are currently editing the {} grid, but you are trying to import a {} file.\nPlease open the {} grid and then re-try this import.".format(self.grid_type, dtype, dtype)
pw.simple_warning(text)
return
# grab old data for concatenation
if self.grid_type in self.contribution.tables:
old_df_container = self.contribution.tables[self.grid_type]
else:
old_df_container = None
old_col_names = self.grid.col_labels
# read in new file and update contribution
df_container = cb.MagicDataFrame(filename, dmodel=self.dm,
columns=old_col_names)
# concatenate if possible
if not isinstance(old_df_container, type(None)):
df_container.df = pd.concat([old_df_container.df, df_container.df],
axis=0, sort=True)
self.contribution.tables[df_container.dtype] = df_container
self.grid_builder = GridBuilder(self.contribution, self.grid_type,
self.panel, parent_type=self.parent_type,
reqd_headers=self.reqd_headers)
# delete old grid
self.grid_box.Hide(0)
self.grid_box.Remove(0)
# create new, updated grid
self.grid = self.grid_builder.make_grid()
self.grid.InitUI()
# add data to new grid
self.grid_builder.add_data_to_grid(self.grid, self.grid_type)
# add new grid to sizer and fit everything
self.grid_box.Add(self.grid, flag=wx.ALL, border=5)
self.main_sizer.Fit(self)
self.Centre()
# add any needed drop-down-menus
self.drop_down_menu = drop_down_menus.Menus(self.grid_type,
self.contribution,
self.grid)
# done!
return | python | def onImport(self, event):
"""
Import a MagIC-format file
"""
if self.grid.changes:
print("-W- Your changes will be overwritten...")
wind = pw.ChooseOne(self, "Import file anyway", "Save grid first",
"-W- Your grid has unsaved changes which will be overwritten if you import a file now...")
wind.Centre()
res = wind.ShowModal()
# save grid first:
if res == wx.ID_NO:
self.onSave(None, alert=True, destroy=False)
# reset self.changes
self.grid.changes = set()
openFileDialog = wx.FileDialog(self, "Open MagIC-format file", self.WD, "",
"MagIC file|*.*", wx.FD_OPEN | wx.FD_FILE_MUST_EXIST)
result = openFileDialog.ShowModal()
if result == wx.ID_OK:
# get filename
filename = openFileDialog.GetPath()
# make sure the dtype is correct
f = open(filename)
line = f.readline()
if line.startswith("tab"):
delim, dtype = line.split("\t")
else:
delim, dtype = line.split("")
f.close()
dtype = dtype.strip()
if (dtype != self.grid_type) and (dtype + "s" != self.grid_type):
text = "You are currently editing the {} grid, but you are trying to import a {} file.\nPlease open the {} grid and then re-try this import.".format(self.grid_type, dtype, dtype)
pw.simple_warning(text)
return
# grab old data for concatenation
if self.grid_type in self.contribution.tables:
old_df_container = self.contribution.tables[self.grid_type]
else:
old_df_container = None
old_col_names = self.grid.col_labels
# read in new file and update contribution
df_container = cb.MagicDataFrame(filename, dmodel=self.dm,
columns=old_col_names)
# concatenate if possible
if not isinstance(old_df_container, type(None)):
df_container.df = pd.concat([old_df_container.df, df_container.df],
axis=0, sort=True)
self.contribution.tables[df_container.dtype] = df_container
self.grid_builder = GridBuilder(self.contribution, self.grid_type,
self.panel, parent_type=self.parent_type,
reqd_headers=self.reqd_headers)
# delete old grid
self.grid_box.Hide(0)
self.grid_box.Remove(0)
# create new, updated grid
self.grid = self.grid_builder.make_grid()
self.grid.InitUI()
# add data to new grid
self.grid_builder.add_data_to_grid(self.grid, self.grid_type)
# add new grid to sizer and fit everything
self.grid_box.Add(self.grid, flag=wx.ALL, border=5)
self.main_sizer.Fit(self)
self.Centre()
# add any needed drop-down-menus
self.drop_down_menu = drop_down_menus.Menus(self.grid_type,
self.contribution,
self.grid)
# done!
return | Import a MagIC-format file | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L672-L741 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.onCancelButton | def onCancelButton(self, event):
"""
Quit grid with warning if unsaved changes present
"""
if self.grid.changes:
dlg1 = wx.MessageDialog(self, caption="Message:",
message="Are you sure you want to exit this grid?\nYour changes will not be saved.\n ",
style=wx.OK|wx.CANCEL)
result = dlg1.ShowModal()
if result == wx.ID_OK:
dlg1.Destroy()
self.Destroy()
else:
self.Destroy()
if self.main_frame:
self.main_frame.Show()
self.main_frame.Raise() | python | def onCancelButton(self, event):
"""
Quit grid with warning if unsaved changes present
"""
if self.grid.changes:
dlg1 = wx.MessageDialog(self, caption="Message:",
message="Are you sure you want to exit this grid?\nYour changes will not be saved.\n ",
style=wx.OK|wx.CANCEL)
result = dlg1.ShowModal()
if result == wx.ID_OK:
dlg1.Destroy()
self.Destroy()
else:
self.Destroy()
if self.main_frame:
self.main_frame.Show()
self.main_frame.Raise() | Quit grid with warning if unsaved changes present | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L743-L759 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.onSave | def onSave(self, event, alert=False, destroy=True):
"""
Save grid data
"""
# tidy up drop_down menu
if self.drop_down_menu:
self.drop_down_menu.clean_up()
# then save actual data
self.grid_builder.save_grid_data()
if not event and not alert:
return
# then alert user
wx.MessageBox('Saved!', 'Info',
style=wx.OK | wx.ICON_INFORMATION)
if destroy:
self.Destroy() | python | def onSave(self, event, alert=False, destroy=True):
"""
Save grid data
"""
# tidy up drop_down menu
if self.drop_down_menu:
self.drop_down_menu.clean_up()
# then save actual data
self.grid_builder.save_grid_data()
if not event and not alert:
return
# then alert user
wx.MessageBox('Saved!', 'Info',
style=wx.OK | wx.ICON_INFORMATION)
if destroy:
self.Destroy() | Save grid data | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L762-L777 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.onDragSelection | def onDragSelection(self, event):
"""
Set self.df_slice based on user's selection
"""
if self.grid.GetSelectionBlockTopLeft():
#top_left = self.grid.GetSelectionBlockTopLeft()
#bottom_right = self.grid.GetSelectionBlockBottomRight()
# awkward hack to fix wxPhoenix memory problem, (Github issue #221)
bottom_right = eval(repr(self.grid.GetSelectionBlockBottomRight()).replace("GridCellCoordsArray: ", "").replace("GridCellCoords", ""))
top_left = eval(repr(self.grid.GetSelectionBlockTopLeft()).replace("GridCellCoordsArray: ", "").replace("GridCellCoords", ""))
#
top_left = top_left[0]
bottom_right = bottom_right[0]
else:
return
# GetSelectionBlock returns (row, col)
min_col = top_left[1]
max_col = bottom_right[1]
min_row = top_left[0]
max_row = bottom_right[0]
self.df_slice = self.contribution.tables[self.grid_type].df.iloc[min_row:max_row+1, min_col:max_col+1] | python | def onDragSelection(self, event):
"""
Set self.df_slice based on user's selection
"""
if self.grid.GetSelectionBlockTopLeft():
#top_left = self.grid.GetSelectionBlockTopLeft()
#bottom_right = self.grid.GetSelectionBlockBottomRight()
# awkward hack to fix wxPhoenix memory problem, (Github issue #221)
bottom_right = eval(repr(self.grid.GetSelectionBlockBottomRight()).replace("GridCellCoordsArray: ", "").replace("GridCellCoords", ""))
top_left = eval(repr(self.grid.GetSelectionBlockTopLeft()).replace("GridCellCoordsArray: ", "").replace("GridCellCoords", ""))
#
top_left = top_left[0]
bottom_right = bottom_right[0]
else:
return
# GetSelectionBlock returns (row, col)
min_col = top_left[1]
max_col = bottom_right[1]
min_row = top_left[0]
max_row = bottom_right[0]
self.df_slice = self.contribution.tables[self.grid_type].df.iloc[min_row:max_row+1, min_col:max_col+1] | Set self.df_slice based on user's selection | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L829-L849 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.onKey | def onKey(self, event):
"""
Copy selection if control down and 'c'
"""
if event.CmdDown() or event.ControlDown():
if event.GetKeyCode() == 67:
self.onCopySelection(None) | python | def onKey(self, event):
"""
Copy selection if control down and 'c'
"""
if event.CmdDown() or event.ControlDown():
if event.GetKeyCode() == 67:
self.onCopySelection(None) | Copy selection if control down and 'c' | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L859-L865 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.onSelectAll | def onSelectAll(self, event):
"""
Selects full grid and copies it to the Clipboard
"""
# do clean up here!!!
if self.drop_down_menu:
self.drop_down_menu.clean_up()
# save all grid data
self.grid_builder.save_grid_data()
df = self.contribution.tables[self.grid_type].df
# write df to clipboard for pasting
# header arg determines whether columns are taken
# index arg determines whether index is taken
pd.DataFrame.to_clipboard(df, header=False, index=False)
print('-I- You have copied all cells! You may paste them into a text document or spreadsheet using Command v.') | python | def onSelectAll(self, event):
"""
Selects full grid and copies it to the Clipboard
"""
# do clean up here!!!
if self.drop_down_menu:
self.drop_down_menu.clean_up()
# save all grid data
self.grid_builder.save_grid_data()
df = self.contribution.tables[self.grid_type].df
# write df to clipboard for pasting
# header arg determines whether columns are taken
# index arg determines whether index is taken
pd.DataFrame.to_clipboard(df, header=False, index=False)
print('-I- You have copied all cells! You may paste them into a text document or spreadsheet using Command v.') | Selects full grid and copies it to the Clipboard | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L867-L881 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridFrame.onCopySelection | def onCopySelection(self, event):
"""
Copies self.df_slice to the Clipboard if slice exists
"""
if self.df_slice is not None:
pd.DataFrame.to_clipboard(self.df_slice, header=False, index=False)
self.grid.ClearSelection()
self.df_slice = None
print('-I- You have copied the selected cells. You may paste them into a text document or spreadsheet using Command v.')
else:
print('-W- No cells were copied! You must highlight a selection cells before hitting the copy button. You can do this by clicking and dragging, or by using the Shift key and click.') | python | def onCopySelection(self, event):
"""
Copies self.df_slice to the Clipboard if slice exists
"""
if self.df_slice is not None:
pd.DataFrame.to_clipboard(self.df_slice, header=False, index=False)
self.grid.ClearSelection()
self.df_slice = None
print('-I- You have copied the selected cells. You may paste them into a text document or spreadsheet using Command v.')
else:
print('-W- No cells were copied! You must highlight a selection cells before hitting the copy button. You can do this by clicking and dragging, or by using the Shift key and click.') | Copies self.df_slice to the Clipboard if slice exists | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L884-L894 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridBuilder.make_grid | def make_grid(self):
"""
return grid
"""
changes = None
# if there is a MagicDataFrame, extract data from it
if isinstance(self.magic_dataframe, cb.MagicDataFrame):
# get columns and reorder slightly
col_labels = list(self.magic_dataframe.df.columns)
for ex_col in self.exclude_cols:
col_labels.pop(ex_col)
if self.grid_type == 'ages':
levels = ['specimen', 'sample', 'site', 'location']
for label in levels[:]:
if label in col_labels:
col_labels.remove(label)
else:
levels.remove(label)
col_labels[:0] = levels
else:
if self.parent_type:
if self.parent_type[:-1] in col_labels:
col_labels.remove(self.parent_type[:-1])
col_labels[:0] = [self.parent_type[:-1]]
if self.grid_type[:-1] in col_labels:
col_labels.remove(self.grid_type[:-1])
col_labels[:0] = (self.grid_type[:-1],)
for col in col_labels:
if col not in self.magic_dataframe.df.columns:
self.magic_dataframe.df[col] = None
self.magic_dataframe.df = self.magic_dataframe.df[col_labels]
self.magic_dataframe.sort_dataframe_cols()
col_labels = list(self.magic_dataframe.df.columns)
row_labels = self.magic_dataframe.df.index
# make sure minimum defaults are present
for header in self.reqd_headers:
if header not in col_labels:
changes = set([1])
col_labels.append(header)
# if there is no pre-existing MagicDataFrame,
# make a blank grid with do some defaults:
else:
# default headers
#col_labels = list(self.data_model.get_headers(self.grid_type, 'Names'))
#col_labels[:0] = self.reqd_headers
col_labels = list(self.reqd_headers)
if self.grid_type in ['specimens', 'samples', 'sites']:
col_labels.extend(['age', 'age_sigma'])
## use the following line if you want sorted column labels:
#col_labels = sorted(set(col_labels))
# defaults are different for ages
if self.grid_type == 'ages':
levels = ['specimen', 'sample', 'site', 'location']
for label in levels:
if label in col_labels:
col_labels.remove(label)
col_labels[:0] = levels
else:
if self.parent_type:
col_labels.remove(self.parent_type[:-1])
col_labels[:0] = [self.parent_type[:-1]]
col_labels.remove(self.grid_type[:-1])
col_labels[:0] = [self.grid_type[:-1]]
# make sure all reqd cols are in magic_dataframe
for col in col_labels:
if col not in self.magic_dataframe.df.columns:
self.magic_dataframe.df[col] = None
# make the grid
if not self.huge:
grid = magic_grid.MagicGrid(parent=self.panel, name=self.grid_type,
row_labels=[], col_labels=col_labels)
# make the huge grid
else:
row_labels = self.magic_dataframe.df.index
grid = magic_grid.HugeMagicGrid(parent=self.panel, name=self.grid_type,
row_labels=row_labels, col_labels=col_labels)
grid.do_event_bindings()
grid.changes = changes
self.grid = grid
return grid | python | def make_grid(self):
"""
return grid
"""
changes = None
# if there is a MagicDataFrame, extract data from it
if isinstance(self.magic_dataframe, cb.MagicDataFrame):
# get columns and reorder slightly
col_labels = list(self.magic_dataframe.df.columns)
for ex_col in self.exclude_cols:
col_labels.pop(ex_col)
if self.grid_type == 'ages':
levels = ['specimen', 'sample', 'site', 'location']
for label in levels[:]:
if label in col_labels:
col_labels.remove(label)
else:
levels.remove(label)
col_labels[:0] = levels
else:
if self.parent_type:
if self.parent_type[:-1] in col_labels:
col_labels.remove(self.parent_type[:-1])
col_labels[:0] = [self.parent_type[:-1]]
if self.grid_type[:-1] in col_labels:
col_labels.remove(self.grid_type[:-1])
col_labels[:0] = (self.grid_type[:-1],)
for col in col_labels:
if col not in self.magic_dataframe.df.columns:
self.magic_dataframe.df[col] = None
self.magic_dataframe.df = self.magic_dataframe.df[col_labels]
self.magic_dataframe.sort_dataframe_cols()
col_labels = list(self.magic_dataframe.df.columns)
row_labels = self.magic_dataframe.df.index
# make sure minimum defaults are present
for header in self.reqd_headers:
if header not in col_labels:
changes = set([1])
col_labels.append(header)
# if there is no pre-existing MagicDataFrame,
# make a blank grid with do some defaults:
else:
# default headers
#col_labels = list(self.data_model.get_headers(self.grid_type, 'Names'))
#col_labels[:0] = self.reqd_headers
col_labels = list(self.reqd_headers)
if self.grid_type in ['specimens', 'samples', 'sites']:
col_labels.extend(['age', 'age_sigma'])
## use the following line if you want sorted column labels:
#col_labels = sorted(set(col_labels))
# defaults are different for ages
if self.grid_type == 'ages':
levels = ['specimen', 'sample', 'site', 'location']
for label in levels:
if label in col_labels:
col_labels.remove(label)
col_labels[:0] = levels
else:
if self.parent_type:
col_labels.remove(self.parent_type[:-1])
col_labels[:0] = [self.parent_type[:-1]]
col_labels.remove(self.grid_type[:-1])
col_labels[:0] = [self.grid_type[:-1]]
# make sure all reqd cols are in magic_dataframe
for col in col_labels:
if col not in self.magic_dataframe.df.columns:
self.magic_dataframe.df[col] = None
# make the grid
if not self.huge:
grid = magic_grid.MagicGrid(parent=self.panel, name=self.grid_type,
row_labels=[], col_labels=col_labels)
# make the huge grid
else:
row_labels = self.magic_dataframe.df.index
grid = magic_grid.HugeMagicGrid(parent=self.panel, name=self.grid_type,
row_labels=row_labels, col_labels=col_labels)
grid.do_event_bindings()
grid.changes = changes
self.grid = grid
return grid | return grid | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L948-L1028 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridBuilder.add_age_defaults | def add_age_defaults(self):
"""
Add columns as needed:
age, age_unit, specimen, sample, site, location.
"""
if isinstance(self.magic_dataframe, cb.MagicDataFrame):
for col in ['age', 'age_unit']:
if col not in self.grid.col_labels:
self.grid.add_col(col)
for level in ['locations', 'sites', 'samples', 'specimens']:
if level in self.contribution.tables:
if level[:-1] not in self.grid.col_labels:
self.grid.add_col(level[:-1]) | python | def add_age_defaults(self):
"""
Add columns as needed:
age, age_unit, specimen, sample, site, location.
"""
if isinstance(self.magic_dataframe, cb.MagicDataFrame):
for col in ['age', 'age_unit']:
if col not in self.grid.col_labels:
self.grid.add_col(col)
for level in ['locations', 'sites', 'samples', 'specimens']:
if level in self.contribution.tables:
if level[:-1] not in self.grid.col_labels:
self.grid.add_col(level[:-1]) | Add columns as needed:
age, age_unit, specimen, sample, site, location. | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L1054-L1066 |
PmagPy/PmagPy | dialogs/grid_frame3.py | GridBuilder.current_grid_empty | def current_grid_empty(self):
"""
Check to see if grid is empty except for default values
"""
empty = True
# df IS empty if there are no rows
if not any(self.magic_dataframe.df.index):
empty = True
# df is NOT empty if there are at least two rows
elif len(self.grid.row_labels) > 1:
empty = False
# if there is one row, df MIGHT be empty
else:
# check all the non-null values
non_null_vals = [val for val in self.magic_dataframe.df.values[0] if cb.not_null(val, False)]
for val in non_null_vals:
if not isinstance(val, str):
empty = False
break
# if there are any non-default values, grid is not empty
if val.lower() not in ['this study', 'g', 'i']:
empty = False
break
return empty | python | def current_grid_empty(self):
"""
Check to see if grid is empty except for default values
"""
empty = True
# df IS empty if there are no rows
if not any(self.magic_dataframe.df.index):
empty = True
# df is NOT empty if there are at least two rows
elif len(self.grid.row_labels) > 1:
empty = False
# if there is one row, df MIGHT be empty
else:
# check all the non-null values
non_null_vals = [val for val in self.magic_dataframe.df.values[0] if cb.not_null(val, False)]
for val in non_null_vals:
if not isinstance(val, str):
empty = False
break
# if there are any non-default values, grid is not empty
if val.lower() not in ['this study', 'g', 'i']:
empty = False
break
return empty | Check to see if grid is empty except for default values | https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/dialogs/grid_frame3.py#L1068-L1091 |
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