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geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan._save_potentials | def _save_potentials(self, directory):
"""save potentials to a directory
"""
print('saving potentials')
digits = int(np.ceil(np.log10(self.configs.configs.shape[0])))
for i in range(0, self.configs.configs.shape[0]):
pot_data = self.get_potential(i)
filename_raw = 'pot{0:0' + '{0}'.format(digits) + '}.dat'
filename = directory + os.sep + filename_raw.format(i + 1)
nodes = self.grid.nodes['sorted'][:, 1:3]
all_data = np.hstack((
nodes,
pot_data[0][:, np.newaxis],
pot_data[1][:, np.newaxis],
))
with open(filename, 'wb') as fid:
np.savetxt(fid, all_data) | python | def _save_potentials(self, directory):
"""save potentials to a directory
"""
print('saving potentials')
digits = int(np.ceil(np.log10(self.configs.configs.shape[0])))
for i in range(0, self.configs.configs.shape[0]):
pot_data = self.get_potential(i)
filename_raw = 'pot{0:0' + '{0}'.format(digits) + '}.dat'
filename = directory + os.sep + filename_raw.format(i + 1)
nodes = self.grid.nodes['sorted'][:, 1:3]
all_data = np.hstack((
nodes,
pot_data[0][:, np.newaxis],
pot_data[1][:, np.newaxis],
))
with open(filename, 'wb') as fid:
np.savetxt(fid, all_data) | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L409-L426 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.clear_measurements | def clear_measurements(self):
"""Forget any previous measurements
"""
mid_list = self.assignments.get('measurements', None)
if mid_list is not None:
for mid in mid_list:
self.configs.delete_measurements(mid=mid)
self.assignments['measurements'] = None | python | def clear_measurements(self):
"""Forget any previous measurements
"""
mid_list = self.assignments.get('measurements', None)
if mid_list is not None:
for mid in mid_list:
self.configs.delete_measurements(mid=mid)
self.assignments['measurements'] = None | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L428-L435 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.measurements | def measurements(self):
"""Return the measurements associated with this instance.
if measurements are not present, check if we can model, and then
run CRMod to load the measurements.
"""
# check if we have measurements
mid = self.assignments.get('measurements', None)
if mid is None:
return_value = self.model(
voltages=True,
sensitivities=False,
potentials=False,
)
if return_value is None:
print('cannot model')
return
# retrieve measurements
cids = self.assignments['measurements']
measurements = np.vstack((
self.configs.measurements[cids[0]],
self.configs.measurements[cids[1]],
)).T
return measurements | python | def measurements(self):
"""Return the measurements associated with this instance.
if measurements are not present, check if we can model, and then
run CRMod to load the measurements.
"""
# check if we have measurements
mid = self.assignments.get('measurements', None)
if mid is None:
return_value = self.model(
voltages=True,
sensitivities=False,
potentials=False,
)
if return_value is None:
print('cannot model')
return
# retrieve measurements
cids = self.assignments['measurements']
measurements = np.vstack((
self.configs.measurements[cids[0]],
self.configs.measurements[cids[1]],
)).T
return measurements | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L437-L461 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan._read_sensitivities | def _read_sensitivities(self, sens_dir):
"""import sensitivities from a directory
Note
----
* check that signs are correct in case CRMod switches potential
electrodes
"""
if self.assignments['sensitivities'] is not None:
print('Sensitivities already imported. Will not overwrite!')
return
else:
self.assignments['sensitivities'] = {}
sens_files = sorted(glob(sens_dir + os.sep + 'sens*.dat'))
for nr, filename in enumerate(sens_files):
with open(filename, 'r') as fid:
metadata = np.fromstring(
fid.readline().strip(), sep=' ', count=2
)
meta_re = metadata[0]
meta_im = metadata[1]
sens_data = np.loadtxt(fid)
cids = self.parman.add_data(
sens_data[:, 2:4],
[meta_re, meta_im],
)
# store cids for later retrieval
self.assignments['sensitivities'][nr] = cids | python | def _read_sensitivities(self, sens_dir):
"""import sensitivities from a directory
Note
----
* check that signs are correct in case CRMod switches potential
electrodes
"""
if self.assignments['sensitivities'] is not None:
print('Sensitivities already imported. Will not overwrite!')
return
else:
self.assignments['sensitivities'] = {}
sens_files = sorted(glob(sens_dir + os.sep + 'sens*.dat'))
for nr, filename in enumerate(sens_files):
with open(filename, 'r') as fid:
metadata = np.fromstring(
fid.readline().strip(), sep=' ', count=2
)
meta_re = metadata[0]
meta_im = metadata[1]
sens_data = np.loadtxt(fid)
cids = self.parman.add_data(
sens_data[:, 2:4],
[meta_re, meta_im],
)
# store cids for later retrieval
self.assignments['sensitivities'][nr] = cids | [
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| import sensitivities from a directory
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L500-L532 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan._read_potentials | def _read_potentials(self, pot_dir):
"""import potentials from a directory
"""
if self.assignments['potentials'] is not None:
print('Potentials already imported. Will not overwrite!')
return
else:
self.assignments['potentials'] = {}
pot_files = sorted(glob(pot_dir + os.sep + 'pot*.dat'))
for nr, filename in enumerate(pot_files):
with open(filename, 'r') as fid:
pot_data = np.loadtxt(fid)
nids = self.nodeman.add_data(
pot_data[:, 2:4],
)
# store cids for later retrieval
self.assignments['potentials'][nr] = nids | python | def _read_potentials(self, pot_dir):
"""import potentials from a directory
"""
if self.assignments['potentials'] is not None:
print('Potentials already imported. Will not overwrite!')
return
else:
self.assignments['potentials'] = {}
pot_files = sorted(glob(pot_dir + os.sep + 'pot*.dat'))
for nr, filename in enumerate(pot_files):
with open(filename, 'r') as fid:
pot_data = np.loadtxt(fid)
nids = self.nodeman.add_data(
pot_data[:, 2:4],
)
# store cids for later retrieval
self.assignments['potentials'][nr] = nids | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L534-L552 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.get_potential | def get_potential(self, config_nr):
"""Return potential data for a given measurement configuration.
Parameters
----------
config_nr: int
Number of the configurations. Starts at 0
Returns
-------
pot_data: list with two numpy.ndarrays
First array: magnitude potentials, second array: phase potentials
"""
if self.assignments['potentials'] is None:
self._check_state()
if self.can_model:
self.model(potentials=True)
nids = self.assignments['potentials'][config_nr]
pot_data = [self.nodeman.nodevals[nid] for nid in nids]
return pot_data | python | def get_potential(self, config_nr):
"""Return potential data for a given measurement configuration.
Parameters
----------
config_nr: int
Number of the configurations. Starts at 0
Returns
-------
pot_data: list with two numpy.ndarrays
First array: magnitude potentials, second array: phase potentials
"""
if self.assignments['potentials'] is None:
self._check_state()
if self.can_model:
self.model(potentials=True)
nids = self.assignments['potentials'][config_nr]
pot_data = [self.nodeman.nodevals[nid] for nid in nids]
return pot_data | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L554-L575 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.get_sensitivity | def get_sensitivity(self, config_nr):
"""return a sensitivity, as well as corresponding metadata, for a given
measurement configuration. Indices start at zero.
"""
if self.assignments['sensitivities'] is None:
self._check_state()
if self.can_model:
self.model(sensitivities=True)
cids = self.assignments['sensitivities'][config_nr]
sens_data = [self.parman.parsets[cid] for cid in cids]
meta_data = [self.parman.metadata[cid] for cid in cids]
return sens_data, meta_data | python | def get_sensitivity(self, config_nr):
"""return a sensitivity, as well as corresponding metadata, for a given
measurement configuration. Indices start at zero.
"""
if self.assignments['sensitivities'] is None:
self._check_state()
if self.can_model:
self.model(sensitivities=True)
cids = self.assignments['sensitivities'][config_nr]
sens_data = [self.parman.parsets[cid] for cid in cids]
meta_data = [self.parman.metadata[cid] for cid in cids]
return sens_data, meta_data | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L577-L589 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.read_voltages | def read_voltages(self, voltage_file):
"""import voltages from a volt.dat file
Parameters
----------
voltage_file : string
Path to volt.dat file
"""
measurements_raw = np.loadtxt(
voltage_file,
skiprows=1,
)
measurements = np.atleast_2d(measurements_raw)
# extract measurement configurations
A = (measurements[:, 0] / 1e4).astype(int)
B = (measurements[:, 0] % 1e4).astype(int)
M = (measurements[:, 1] / 1e4).astype(int)
N = (measurements[:, 1] % 1e4).astype(int)
ABMN = np.vstack((A, B, M, N)).T
if self.configs.configs is None:
self.configs.configs = ABMN
else:
# configurations don't match
if not np.all(ABMN == self.configs.configs):
for nr, (old_config, new_config) in enumerate(zip(
self.configs.configs, ABMN)):
if np.all(old_config == new_config):
continue
# check polarity
current_electrodes_are_equal = np.all(
old_config[0:2] == new_config[0:2]
)
voltage_electrodes_are_switched = np.all(
old_config[2:4] == new_config[4:1:-1]
)
if(current_electrodes_are_equal and
voltage_electrodes_are_switched):
if len(self.configs.measurements.keys()) > 0:
raise Exception(
'need to switch electrode polarity, but ' +
'there are already measurements stored for ' +
'the old configuration!')
else:
# switch M/N in configurations
self.configs.configs[nr, :] = new_config
else:
raise Exception(
'There was an error matching configurations of ' +
'voltages with configurations already imported'
)
# add measurements to the config instance
mid_mag = self.configs.add_measurements(
measurements[:, 2]
)
mid_pha = self.configs.add_measurements(
measurements[:, 3]
)
self.assignments['measurements'] = [mid_mag, mid_pha] | python | def read_voltages(self, voltage_file):
"""import voltages from a volt.dat file
Parameters
----------
voltage_file : string
Path to volt.dat file
"""
measurements_raw = np.loadtxt(
voltage_file,
skiprows=1,
)
measurements = np.atleast_2d(measurements_raw)
# extract measurement configurations
A = (measurements[:, 0] / 1e4).astype(int)
B = (measurements[:, 0] % 1e4).astype(int)
M = (measurements[:, 1] / 1e4).astype(int)
N = (measurements[:, 1] % 1e4).astype(int)
ABMN = np.vstack((A, B, M, N)).T
if self.configs.configs is None:
self.configs.configs = ABMN
else:
# configurations don't match
if not np.all(ABMN == self.configs.configs):
for nr, (old_config, new_config) in enumerate(zip(
self.configs.configs, ABMN)):
if np.all(old_config == new_config):
continue
# check polarity
current_electrodes_are_equal = np.all(
old_config[0:2] == new_config[0:2]
)
voltage_electrodes_are_switched = np.all(
old_config[2:4] == new_config[4:1:-1]
)
if(current_electrodes_are_equal and
voltage_electrodes_are_switched):
if len(self.configs.measurements.keys()) > 0:
raise Exception(
'need to switch electrode polarity, but ' +
'there are already measurements stored for ' +
'the old configuration!')
else:
# switch M/N in configurations
self.configs.configs[nr, :] = new_config
else:
raise Exception(
'There was an error matching configurations of ' +
'voltages with configurations already imported'
)
# add measurements to the config instance
mid_mag = self.configs.add_measurements(
measurements[:, 2]
)
mid_pha = self.configs.add_measurements(
measurements[:, 3]
)
self.assignments['measurements'] = [mid_mag, mid_pha] | [
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| import voltages from a volt.dat file
Parameters
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voltage_file : string
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L769-L834 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.model | def model(self,
voltages=True,
sensitivities=False,
potentials=False,
output_directory=None,
silent=False,
):
"""Forward model the tomodir and read in the results
"""
self._check_state()
if self.can_model:
if output_directory is not None:
if not os.path.isdir(output_directory):
os.makedirs(output_directory)
tempdir = output_directory
self._model(voltages, sensitivities, potentials, tempdir)
else:
raise IOError(
'output directory already exists: {0}'.format(
output_directory
)
)
else:
with tempfile.TemporaryDirectory(dir=self.tempdir) as tempdir:
self._model(
voltages, sensitivities, potentials, tempdir,
silent=silent
)
return 1
else:
print('Sorry, not all required information to model are present')
print('Check:')
print('1) configurations present: self.configs.configs')
print('2) is a model present')
return None | python | def model(self,
voltages=True,
sensitivities=False,
potentials=False,
output_directory=None,
silent=False,
):
"""Forward model the tomodir and read in the results
"""
self._check_state()
if self.can_model:
if output_directory is not None:
if not os.path.isdir(output_directory):
os.makedirs(output_directory)
tempdir = output_directory
self._model(voltages, sensitivities, potentials, tempdir)
else:
raise IOError(
'output directory already exists: {0}'.format(
output_directory
)
)
else:
with tempfile.TemporaryDirectory(dir=self.tempdir) as tempdir:
self._model(
voltages, sensitivities, potentials, tempdir,
silent=silent
)
return 1
else:
print('Sorry, not all required information to model are present')
print('Check:')
print('1) configurations present: self.configs.configs')
print('2) is a model present')
return None | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L875-L910 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan._invert | def _invert(self, tempdir, catch_output=True, **kwargs):
"""Internal function than runs an inversion using CRTomo.
Parameters
----------
tempdir : string
directory which to use as a tomodir
catch_output : bool, optional
if True, catch all outputs of the CRTomo call (default: True)
cores : int, optional
how many cores to use. (default 2)
"""
nr_cores = kwargs.get('cores', 2)
print('attempting inversion in directory: {0}'.format(tempdir))
pwd = os.getcwd()
os.chdir(tempdir)
self.save_to_tomodir('.')
os.chdir('exe')
binary = CRBin.get('CRTomo')
print('Using binary: {0}'.format(binary))
print('calling CRTomo')
# store env variable
env_omp = os.environ.get('OMP_NUM_THREADS', '')
os.environ['OMP_NUM_THREADS'] = '{0}'.format(nr_cores)
if catch_output:
subprocess.check_output(
binary,
shell=True,
stderr=subprocess.STDOUT,
)
else:
subprocess.call(
binary,
shell=True,
)
# reset environment variable
os.environ['OMP_NUM_THREADS'] = env_omp
print('finished')
os.chdir(pwd)
self.read_inversion_results(tempdir) | python | def _invert(self, tempdir, catch_output=True, **kwargs):
"""Internal function than runs an inversion using CRTomo.
Parameters
----------
tempdir : string
directory which to use as a tomodir
catch_output : bool, optional
if True, catch all outputs of the CRTomo call (default: True)
cores : int, optional
how many cores to use. (default 2)
"""
nr_cores = kwargs.get('cores', 2)
print('attempting inversion in directory: {0}'.format(tempdir))
pwd = os.getcwd()
os.chdir(tempdir)
self.save_to_tomodir('.')
os.chdir('exe')
binary = CRBin.get('CRTomo')
print('Using binary: {0}'.format(binary))
print('calling CRTomo')
# store env variable
env_omp = os.environ.get('OMP_NUM_THREADS', '')
os.environ['OMP_NUM_THREADS'] = '{0}'.format(nr_cores)
if catch_output:
subprocess.check_output(
binary,
shell=True,
stderr=subprocess.STDOUT,
)
else:
subprocess.call(
binary,
shell=True,
)
# reset environment variable
os.environ['OMP_NUM_THREADS'] = env_omp
print('finished')
os.chdir(pwd)
self.read_inversion_results(tempdir) | [
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Parameters
----------
tempdir : string
directory which to use as a tomodir
catch_output : bool, optional
if True, catch all outputs of the CRTomo call (default: True)
cores : int, optional
how many cores to use. (default 2) | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L912-L954 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.invert | def invert(self, output_directory=None, catch_output=True, **kwargs):
"""Invert this instance, and import the result files
No directories/files will be overwritten. Raise an IOError if the
output directory exists.
Parameters
----------
output_directory: string, optional
use this directory as output directory for the generated tomodir.
If None, then a temporary directory will be used that is deleted
after import.
catch_output: bool, optional
Do not show CRTomo output
cores: int, optional
how many cores to use for CRTomo
Returns
-------
return_code: bool
Return 0 if the inversion completed successfully. Return 1 if no
measurements are present.
"""
self._check_state()
if self.can_invert:
if output_directory is not None:
if not os.path.isdir(output_directory):
os.makedirs(output_directory)
tempdir = output_directory
self._invert(tempdir, catch_output, **kwargs)
else:
raise IOError(
'output directory already exists: {0}'.format(
output_directory
)
)
else:
with tempfile.TemporaryDirectory(dir=self.tempdir) as tempdir:
self._invert(tempdir, catch_output, **kwargs)
return 0
else:
print(
'Sorry, no measurements present, cannot model yet'
)
return 1 | python | def invert(self, output_directory=None, catch_output=True, **kwargs):
"""Invert this instance, and import the result files
No directories/files will be overwritten. Raise an IOError if the
output directory exists.
Parameters
----------
output_directory: string, optional
use this directory as output directory for the generated tomodir.
If None, then a temporary directory will be used that is deleted
after import.
catch_output: bool, optional
Do not show CRTomo output
cores: int, optional
how many cores to use for CRTomo
Returns
-------
return_code: bool
Return 0 if the inversion completed successfully. Return 1 if no
measurements are present.
"""
self._check_state()
if self.can_invert:
if output_directory is not None:
if not os.path.isdir(output_directory):
os.makedirs(output_directory)
tempdir = output_directory
self._invert(tempdir, catch_output, **kwargs)
else:
raise IOError(
'output directory already exists: {0}'.format(
output_directory
)
)
else:
with tempfile.TemporaryDirectory(dir=self.tempdir) as tempdir:
self._invert(tempdir, catch_output, **kwargs)
return 0
else:
print(
'Sorry, no measurements present, cannot model yet'
)
return 1 | [
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No directories/files will be overwritten. Raise an IOError if the
output directory exists.
Parameters
----------
output_directory: string, optional
use this directory as output directory for the generated tomodir.
If None, then a temporary directory will be used that is deleted
after import.
catch_output: bool, optional
Do not show CRTomo output
cores: int, optional
how many cores to use for CRTomo
Returns
-------
return_code: bool
Return 0 if the inversion completed successfully. Return 1 if no
measurements are present. | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L956-L1001 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.read_inversion_results | def read_inversion_results(self, tomodir):
"""Import inversion results from a tomodir into this instance
WARNING: Not finished!
"""
self._read_inversion_results(tomodir)
self._read_inv_ctr(tomodir)
self._read_resm_m(tomodir)
self._read_eps_ctr(tomodir) | python | def read_inversion_results(self, tomodir):
"""Import inversion results from a tomodir into this instance
WARNING: Not finished!
"""
self._read_inversion_results(tomodir)
self._read_inv_ctr(tomodir)
self._read_resm_m(tomodir)
self._read_eps_ctr(tomodir) | [
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| Import inversion results from a tomodir into this instance
WARNING: Not finished! | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L1003-L1011 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.plot_eps_data_hist | def plot_eps_data_hist(self, dfs):
"""Plot histograms of data residuals and data error weighting
TODO:
* add percentage of data below/above the RMS value
"""
# check if this is a DC inversion
if 'datum' in dfs[0]:
dc_inv = True
else:
dc_inv = False
nr_y = len(dfs)
size_y = 5 / 2.54 * nr_y
if dc_inv:
nr_x = 1
else:
nr_x = 3
size_x = 15 / 2.54
fig, axes = plt.subplots(nr_y, nr_x, figsize=(size_x, size_y))
axes = np.atleast_2d(axes)
# plot initial data errors
df = dfs[0]
if dc_inv:
ax = axes[0, 0]
ax.hist(
df['datum'] / df['eps_r'],
100,
)
ax.set_xlabel(r'$-log(|R|) / \epsilon_r$')
ax.set_ylabel(r'count')
else:
# complex inversion
ax = axes[0, 0]
ax.hist(
df['-log(|R|)'] / df['eps'],
100,
)
ax.set_xlabel(r'$-log(|R|)$')
ax.set_ylabel(r'count')
ax = axes[0, 1]
ax.hist(
df['-log(|R|)'] / df['eps_r'],
100,
)
ax.set_xlabel(r'$-log(|R|) / \epsilon_r$')
ax.set_ylabel(r'count')
ax = axes[0, 2]
phase_data = df['-Phase(rad)'] / df['eps_p']
if not np.all(np.isinf(phase_data) | np.isnan(phase_data)):
ax.hist(
phase_data,
100,
)
ax.set_xlabel(r'$-\phi[rad] / \epsilon_p$')
ax.set_ylabel(r'count')
# iterations
for it, df in enumerate(dfs[1:]):
ax = axes[1 + it, 0]
ax.hist(
df['psi'],
100
)
rms = np.sqrt(
1 / df['psi'].shape[0] *
np.sum(
df['psi'] ** 2
)
)
ax.axvline(rms, color='k', linestyle='dashed')
ax.set_title('iteration: {0}'.format(it))
ax.set_xlabel('psi')
ax.set_ylabel(r'count')
ax = axes[1 + it, 1]
Rdat = df['Re(d)']
Rmod = df['Re(f(m))']
ax.scatter(
Rdat,
Rmod,
)
ax.set_xlabel(r'$log(R_{data}~[\Omega])$')
ax.set_ylabel(r'$log(R_{mod}~[\Omega])$')
ax = axes[1 + it, 2]
phidat = df['Im(d)']
phimod = df['Im(f(m))']
ax.scatter(
phidat,
phimod,
)
ax.set_xlabel(r'$\phi_{data}~[mrad]$')
ax.set_ylabel(r'$\phi_{mod}~[mrad]$')
fig.tight_layout()
fig.savefig('eps_plot_hist.png', dpi=300) | python | def plot_eps_data_hist(self, dfs):
"""Plot histograms of data residuals and data error weighting
TODO:
* add percentage of data below/above the RMS value
"""
# check if this is a DC inversion
if 'datum' in dfs[0]:
dc_inv = True
else:
dc_inv = False
nr_y = len(dfs)
size_y = 5 / 2.54 * nr_y
if dc_inv:
nr_x = 1
else:
nr_x = 3
size_x = 15 / 2.54
fig, axes = plt.subplots(nr_y, nr_x, figsize=(size_x, size_y))
axes = np.atleast_2d(axes)
# plot initial data errors
df = dfs[0]
if dc_inv:
ax = axes[0, 0]
ax.hist(
df['datum'] / df['eps_r'],
100,
)
ax.set_xlabel(r'$-log(|R|) / \epsilon_r$')
ax.set_ylabel(r'count')
else:
# complex inversion
ax = axes[0, 0]
ax.hist(
df['-log(|R|)'] / df['eps'],
100,
)
ax.set_xlabel(r'$-log(|R|)$')
ax.set_ylabel(r'count')
ax = axes[0, 1]
ax.hist(
df['-log(|R|)'] / df['eps_r'],
100,
)
ax.set_xlabel(r'$-log(|R|) / \epsilon_r$')
ax.set_ylabel(r'count')
ax = axes[0, 2]
phase_data = df['-Phase(rad)'] / df['eps_p']
if not np.all(np.isinf(phase_data) | np.isnan(phase_data)):
ax.hist(
phase_data,
100,
)
ax.set_xlabel(r'$-\phi[rad] / \epsilon_p$')
ax.set_ylabel(r'count')
# iterations
for it, df in enumerate(dfs[1:]):
ax = axes[1 + it, 0]
ax.hist(
df['psi'],
100
)
rms = np.sqrt(
1 / df['psi'].shape[0] *
np.sum(
df['psi'] ** 2
)
)
ax.axvline(rms, color='k', linestyle='dashed')
ax.set_title('iteration: {0}'.format(it))
ax.set_xlabel('psi')
ax.set_ylabel(r'count')
ax = axes[1 + it, 1]
Rdat = df['Re(d)']
Rmod = df['Re(f(m))']
ax.scatter(
Rdat,
Rmod,
)
ax.set_xlabel(r'$log(R_{data}~[\Omega])$')
ax.set_ylabel(r'$log(R_{mod}~[\Omega])$')
ax = axes[1 + it, 2]
phidat = df['Im(d)']
phimod = df['Im(f(m))']
ax.scatter(
phidat,
phimod,
)
ax.set_xlabel(r'$\phi_{data}~[mrad]$')
ax.set_ylabel(r'$\phi_{mod}~[mrad]$')
fig.tight_layout()
fig.savefig('eps_plot_hist.png', dpi=300) | [
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| Plot histograms of data residuals and data error weighting
TODO:
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L1038-L1140 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan._read_eps_ctr | def _read_eps_ctr(tomodir):
"""Parse a CRTomo eps.ctr file.
TODO: change parameters to only provide eps.ctr file
Parameters
----------
tomodir: string
Path to directory path
Returns
-------
"""
epsctr_file = tomodir + os.sep + 'inv' + os.sep + 'eps.ctr'
if not os.path.isfile(epsctr_file):
print('eps.ctr not found: {0}'.format(epsctr_file))
print(os.getcwd())
return 1
with open(epsctr_file, 'r') as fid:
lines = fid.readlines()
group = itertools.groupby(lines, lambda x: x == '\n')
dfs = []
# group
for x in group:
# print(x)
if not x[0]:
data = [y for y in x[1]]
if data[0].startswith('IT') or data[0].startswith('PIT'):
del(data[0])
data[0] = data[0].replace('-Phase (rad)', '-Phase(rad)')
tfile = StringIO(''.join(data))
df = pd.read_csv(
tfile,
delim_whitespace=True,
na_values=['Infinity'],
)
dfs.append(df)
return dfs | python | def _read_eps_ctr(tomodir):
"""Parse a CRTomo eps.ctr file.
TODO: change parameters to only provide eps.ctr file
Parameters
----------
tomodir: string
Path to directory path
Returns
-------
"""
epsctr_file = tomodir + os.sep + 'inv' + os.sep + 'eps.ctr'
if not os.path.isfile(epsctr_file):
print('eps.ctr not found: {0}'.format(epsctr_file))
print(os.getcwd())
return 1
with open(epsctr_file, 'r') as fid:
lines = fid.readlines()
group = itertools.groupby(lines, lambda x: x == '\n')
dfs = []
# group
for x in group:
# print(x)
if not x[0]:
data = [y for y in x[1]]
if data[0].startswith('IT') or data[0].startswith('PIT'):
del(data[0])
data[0] = data[0].replace('-Phase (rad)', '-Phase(rad)')
tfile = StringIO(''.join(data))
df = pd.read_csv(
tfile,
delim_whitespace=True,
na_values=['Infinity'],
)
dfs.append(df)
return dfs | [
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TODO: change parameters to only provide eps.ctr file
Parameters
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tomodir: string
Path to directory path
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L1218-L1258 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan._read_resm_m | def _read_resm_m(self, tomodir):
"""Read in the resolution matrix of an inversion
Parameters
----------
tomodir: string
directory path to a tomodir
"""
resm_file = tomodir + os.sep + 'inv' + os.sep + 'res_m.diag'
if not os.path.isfile(resm_file):
print('res_m.diag not found: {0}'.format(resm_file))
print(os.getcwd())
return 1
# read header
with open(resm_file, 'rb') as fid:
first_line = fid.readline().strip()
header_raw = np.fromstring(first_line, count=4, sep=' ')
header_raw
# nr_cells = int(header_raw[0])
# lam = float(header_raw[1])
subdata = np.genfromtxt(fid)
print(subdata.shape)
pid = self.parman.add_data(subdata[:, 0])
self.assignments['resm'] = pid | python | def _read_resm_m(self, tomodir):
"""Read in the resolution matrix of an inversion
Parameters
----------
tomodir: string
directory path to a tomodir
"""
resm_file = tomodir + os.sep + 'inv' + os.sep + 'res_m.diag'
if not os.path.isfile(resm_file):
print('res_m.diag not found: {0}'.format(resm_file))
print(os.getcwd())
return 1
# read header
with open(resm_file, 'rb') as fid:
first_line = fid.readline().strip()
header_raw = np.fromstring(first_line, count=4, sep=' ')
header_raw
# nr_cells = int(header_raw[0])
# lam = float(header_raw[1])
subdata = np.genfromtxt(fid)
print(subdata.shape)
pid = self.parman.add_data(subdata[:, 0])
self.assignments['resm'] = pid | [
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Parameters
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tomodir: string
directory path to a tomodir | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L1622-L1648 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.register_forward_model | def register_forward_model(self, pid_mag, pid_pha):
"""Register parameter sets as the forward models for magnitude and
phase
Parameters
----------
pid_mag: int
parameter id corresponding to the magnitude model
pid_pha: int
parameter id corresponding to the phase model
"""
self.register_magnitude_model(pid_mag)
self.register_phase_model(pid_pha) | python | def register_forward_model(self, pid_mag, pid_pha):
"""Register parameter sets as the forward models for magnitude and
phase
Parameters
----------
pid_mag: int
parameter id corresponding to the magnitude model
pid_pha: int
parameter id corresponding to the phase model
"""
self.register_magnitude_model(pid_mag)
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pid_pha: int
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L1686-L1698 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.register_magnitude_model | def register_magnitude_model(self, pid):
"""Set a given parameter model to the forward magnitude model
"""
if self.assignments['forward_model'] is None:
self.assignments['forward_model'] = [None, None]
self.assignments['forward_model'][0] = pid | python | def register_magnitude_model(self, pid):
"""Set a given parameter model to the forward magnitude model
"""
if self.assignments['forward_model'] is None:
self.assignments['forward_model'] = [None, None]
self.assignments['forward_model'][0] = pid | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L1700-L1706 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.register_phase_model | def register_phase_model(self, pid):
"""Set a given parameter model to the forward phase model
"""
if self.assignments['forward_model'] is None:
self.assignments['forward_model'] = [None, None]
self.assignments['forward_model'][1] = pid | python | def register_phase_model(self, pid):
"""Set a given parameter model to the forward phase model
"""
if self.assignments['forward_model'] is None:
self.assignments['forward_model'] = [None, None]
self.assignments['forward_model'][1] = pid | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L1708-L1714 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.add_homogeneous_model | def add_homogeneous_model(self, magnitude, phase=0):
"""Add a homogeneous resistivity model to the tomodir. This is useful
for synthetic measurements.
Parameters
----------
magnitude : float
magnitude [Ohm m] value of the homogeneous model
phase : float, optional
phase [mrad] value of the homogeneous model
Returns
-------
pid_mag : int
ID value of the parameter set of the magnitude model
pid_pha : int
ID value of the parameter set of the phase model
Note that the parameter sets are automatically registered as the
forward models for magnitude and phase values.
"""
if self.assignments['forward_model'] is not None:
print('model already set, will overwrite')
# generate distributions
magnitude_model = np.ones(self.grid.nr_of_elements) * magnitude
phase_model = np.ones(self.grid.nr_of_elements) * phase
pid_mag = self.parman.add_data(magnitude_model)
pid_pha = self.parman.add_data(phase_model)
self.assignments['forward_model'] = [pid_mag, pid_pha]
return pid_mag, pid_pha | python | def add_homogeneous_model(self, magnitude, phase=0):
"""Add a homogeneous resistivity model to the tomodir. This is useful
for synthetic measurements.
Parameters
----------
magnitude : float
magnitude [Ohm m] value of the homogeneous model
phase : float, optional
phase [mrad] value of the homogeneous model
Returns
-------
pid_mag : int
ID value of the parameter set of the magnitude model
pid_pha : int
ID value of the parameter set of the phase model
Note that the parameter sets are automatically registered as the
forward models for magnitude and phase values.
"""
if self.assignments['forward_model'] is not None:
print('model already set, will overwrite')
# generate distributions
magnitude_model = np.ones(self.grid.nr_of_elements) * magnitude
phase_model = np.ones(self.grid.nr_of_elements) * phase
pid_mag = self.parman.add_data(magnitude_model)
pid_pha = self.parman.add_data(phase_model)
self.assignments['forward_model'] = [pid_mag, pid_pha]
return pid_mag, pid_pha | [
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pid_pha : int
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L1716-L1748 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/tdManager.py | tdMan.show_parset | def show_parset(self, pid):
"""Plot a given parameter set
"""
fig, ax = plt.subplots()
self.plot.plot_elements_to_ax(pid, ax=ax)
return fig, ax | python | def show_parset(self, pid):
"""Plot a given parameter set
"""
fig, ax = plt.subplots()
self.plot.plot_elements_to_ax(pid, ax=ax)
return fig, ax | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/tdManager.py#L1882-L1887 | train |
wdv4758h/python-everywhere | setup.py | cythonize | def cythonize(*args, **kwargs):
'''
dirty hack, only import cythonize at the time you use it.
if you don't write Cython extension,
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'''
global cythonize
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return cythonize(*args, **kwargs) | python | def cythonize(*args, **kwargs):
'''
dirty hack, only import cythonize at the time you use it.
if you don't write Cython extension,
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'''
global cythonize
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nhfruchter/pgh-bustime | pghbustime/interface.py | BustimeAPI.response | def response(self, url):
"""Grab an API response."""
resp = requests.get(url).content
return self.parseresponse(resp) | python | def response(self, url):
"""Grab an API response."""
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| b915e8fea28541612f0e79783c2cf12fd3daaac0 | https://github.com/nhfruchter/pgh-bustime/blob/b915e8fea28541612f0e79783c2cf12fd3daaac0/pghbustime/interface.py#L84-L88 | train |
nhfruchter/pgh-bustime | pghbustime/interface.py | BustimeAPI.errorhandle | def errorhandle(self, resp):
"""Parse API error responses and raise appropriate exceptions."""
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errors = parsed[self.RESPONSE_TOKEN][self.ERROR_TOKEN]
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messages = ", ".join([" ".join(["{}: {}".format(k,v) for k, v in e.items()]) for e in errors])
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overlimit = any('transaction limit' in msg.lower() for msg in errors.values())
if overlimit:
raise APILimitExceeded("This API key has used up its daily quota of calls.")
else:
messages = " ".join(["{}: {}".format(k,v) for k, v in errors.items()])
elif self.format == 'xml':
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errors = ET.fromstring(resp).findall(self.ERROR_TOKEN)
messages = ", ".join(err.find('msg').text for err in errors)
else:
raise ValueError("Invalid API response format specified: {}." % self.format)
raise BustimeError("API returned: {}".format(messages)) | python | def errorhandle(self, resp):
"""Parse API error responses and raise appropriate exceptions."""
if self.format == 'json':
parsed = xmltodict.parse(resp)
errors = parsed[self.RESPONSE_TOKEN][self.ERROR_TOKEN]
# Create list of errors if more than one error response is given
if type(errors) is list and len(errors) > 1:
messages = ", ".join([" ".join(["{}: {}".format(k,v) for k, v in e.items()]) for e in errors])
else:
overlimit = any('transaction limit' in msg.lower() for msg in errors.values())
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errors = ET.fromstring(resp).findall(self.ERROR_TOKEN)
messages = ", ".join(err.find('msg').text for err in errors)
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raise BustimeError("API returned: {}".format(messages)) | [
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| b915e8fea28541612f0e79783c2cf12fd3daaac0 | https://github.com/nhfruchter/pgh-bustime/blob/b915e8fea28541612f0e79783c2cf12fd3daaac0/pghbustime/interface.py#L90-L111 | train |
nhfruchter/pgh-bustime | pghbustime/interface.py | BustimeAPI.parseresponse | def parseresponse(self, resp):
"""Parse an API response."""
# Support Python 3's bytes type from socket repsonses
if sys.version_info.major > 2:
resp = resp.decode('utf-8')
if self.RESPONSE_TOKEN not in resp:
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elif self.ERROR_TOKEN in resp:
return self.errorhandle(resp)
else:
if self.format == 'json':
return xmltodict.parse(resp)[self.RESPONSE_TOKEN]
elif self.format == 'xml':
return resp | python | def parseresponse(self, resp):
"""Parse an API response."""
# Support Python 3's bytes type from socket repsonses
if sys.version_info.major > 2:
resp = resp.decode('utf-8')
if self.RESPONSE_TOKEN not in resp:
raise BustimeError("The Bustime API returned an invalid response: {}".format(resp))
elif self.ERROR_TOKEN in resp:
return self.errorhandle(resp)
else:
if self.format == 'json':
return xmltodict.parse(resp)[self.RESPONSE_TOKEN]
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| b915e8fea28541612f0e79783c2cf12fd3daaac0 | https://github.com/nhfruchter/pgh-bustime/blob/b915e8fea28541612f0e79783c2cf12fd3daaac0/pghbustime/interface.py#L113-L127 | train |
zalando-stups/lizzy-client | lizzy_client/utils.py | get_stack_refs | def get_stack_refs(refs: list): # copy pasted from Senza
"""
Returns a list of stack references with name and version.
"""
refs = list(refs)
refs.reverse()
stack_refs = []
last_stack = None
while refs:
ref = refs.pop()
if last_stack is not None and re.compile(r'v[0-9][a-zA-Z0-9-]*$').match(ref):
stack_refs.append(StackReference(last_stack, ref))
else:
try:
with open(ref) as fd:
data = yaml.safe_load(fd)
ref = data['SenzaInfo']['StackName']
except (OSError, IOError):
# It's still possible that the ref is a regex
pass
if refs:
version = refs.pop()
else:
version = None
stack_refs.append(StackReference(ref, version))
last_stack = ref
return stack_refs | python | def get_stack_refs(refs: list): # copy pasted from Senza
"""
Returns a list of stack references with name and version.
"""
refs = list(refs)
refs.reverse()
stack_refs = []
last_stack = None
while refs:
ref = refs.pop()
if last_stack is not None and re.compile(r'v[0-9][a-zA-Z0-9-]*$').match(ref):
stack_refs.append(StackReference(last_stack, ref))
else:
try:
with open(ref) as fd:
data = yaml.safe_load(fd)
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except (OSError, IOError):
# It's still possible that the ref is a regex
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if refs:
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else:
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stack_refs.append(StackReference(ref, version))
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| 0af9733ca5a25ebd0a9dc1453f2a7592efcee56a | https://github.com/zalando-stups/lizzy-client/blob/0af9733ca5a25ebd0a9dc1453f2a7592efcee56a/lizzy_client/utils.py#L35-L62 | train |
rhayes777/PyAutoFit | autofit/mapper/model_mapper.py | ModelMapper.instance_for_arguments | def instance_for_arguments(self, arguments):
"""
Creates a ModelInstance, which has an attribute and class instance corresponding to every PriorModel
attributed to this instance.
Parameters
----------
arguments : dict
The dictionary representation of prior and parameter values. This is created in the model_instance_from_*
routines.
Returns
-------
model_instance : autofit.mapper.model.ModelInstance
An object containing reconstructed model_mapper instances
"""
model_instance = ModelInstance()
for prior_model_tuple in self.prior_model_tuples:
setattr(model_instance, prior_model_tuple.name,
prior_model_tuple.prior_model.instance_for_arguments(arguments))
return model_instance | python | def instance_for_arguments(self, arguments):
"""
Creates a ModelInstance, which has an attribute and class instance corresponding to every PriorModel
attributed to this instance.
Parameters
----------
arguments : dict
The dictionary representation of prior and parameter values. This is created in the model_instance_from_*
routines.
Returns
-------
model_instance : autofit.mapper.model.ModelInstance
An object containing reconstructed model_mapper instances
"""
model_instance = ModelInstance()
for prior_model_tuple in self.prior_model_tuples:
setattr(model_instance, prior_model_tuple.name,
prior_model_tuple.prior_model.instance_for_arguments(arguments))
return model_instance | [
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| a9e6144abb08edfc6a6906c4030d7119bf8d3e14 | https://github.com/rhayes777/PyAutoFit/blob/a9e6144abb08edfc6a6906c4030d7119bf8d3e14/autofit/mapper/model_mapper.py#L378-L402 | train |
rhayes777/PyAutoFit | autofit/mapper/model_mapper.py | ModelMapper.mapper_from_partial_prior_arguments | def mapper_from_partial_prior_arguments(self, arguments):
"""
Creates a new model mapper from a dictionary mapping_matrix existing priors to new priors, keeping existing
priors where no mapping is provided.
Parameters
----------
arguments: {Prior: Prior}
A dictionary mapping_matrix priors to priors
Returns
-------
model_mapper: ModelMapper
A new model mapper with updated priors.
"""
original_prior_dict = {prior: prior for prior in self.priors}
return self.mapper_from_prior_arguments({**original_prior_dict, **arguments}) | python | def mapper_from_partial_prior_arguments(self, arguments):
"""
Creates a new model mapper from a dictionary mapping_matrix existing priors to new priors, keeping existing
priors where no mapping is provided.
Parameters
----------
arguments: {Prior: Prior}
A dictionary mapping_matrix priors to priors
Returns
-------
model_mapper: ModelMapper
A new model mapper with updated priors.
"""
original_prior_dict = {prior: prior for prior in self.priors}
return self.mapper_from_prior_arguments({**original_prior_dict, **arguments}) | [
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| a9e6144abb08edfc6a6906c4030d7119bf8d3e14 | https://github.com/rhayes777/PyAutoFit/blob/a9e6144abb08edfc6a6906c4030d7119bf8d3e14/autofit/mapper/model_mapper.py#L404-L420 | train |
rhayes777/PyAutoFit | autofit/mapper/model_mapper.py | ModelMapper.mapper_from_prior_arguments | def mapper_from_prior_arguments(self, arguments):
"""
Creates a new model mapper from a dictionary mapping_matrix existing priors to new priors.
Parameters
----------
arguments: {Prior: Prior}
A dictionary mapping_matrix priors to priors
Returns
-------
model_mapper: ModelMapper
A new model mapper with updated priors.
"""
mapper = copy.deepcopy(self)
for prior_model_tuple in self.prior_model_tuples:
setattr(mapper, prior_model_tuple.name,
prior_model_tuple.prior_model.gaussian_prior_model_for_arguments(arguments))
return mapper | python | def mapper_from_prior_arguments(self, arguments):
"""
Creates a new model mapper from a dictionary mapping_matrix existing priors to new priors.
Parameters
----------
arguments: {Prior: Prior}
A dictionary mapping_matrix priors to priors
Returns
-------
model_mapper: ModelMapper
A new model mapper with updated priors.
"""
mapper = copy.deepcopy(self)
for prior_model_tuple in self.prior_model_tuples:
setattr(mapper, prior_model_tuple.name,
prior_model_tuple.prior_model.gaussian_prior_model_for_arguments(arguments))
return mapper | [
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| a9e6144abb08edfc6a6906c4030d7119bf8d3e14 | https://github.com/rhayes777/PyAutoFit/blob/a9e6144abb08edfc6a6906c4030d7119bf8d3e14/autofit/mapper/model_mapper.py#L422-L442 | train |
rhayes777/PyAutoFit | autofit/mapper/model_mapper.py | ModelMapper.mapper_from_gaussian_tuples | def mapper_from_gaussian_tuples(self, tuples, a=None, r=None):
"""
Creates a new model mapper from a list of floats describing the mean values of gaussian priors. The widths \
of the new priors are taken from the width_config. The new gaussian priors must be provided in the same \
order as the priors associated with model.
If a is not None then all priors are created with an absolute width of a.
If r is not None then all priors are created with a relative width of r.
Parameters
----------
r
The relative width to be assigned to gaussian priors
a
The absolute width to be assigned to gaussian priors
tuples
A list of tuples each containing the mean and width of a prior
Returns
-------
mapper: ModelMapper
A new model mapper with all priors replaced by gaussian priors.
"""
prior_tuples = self.prior_tuples_ordered_by_id
prior_class_dict = self.prior_class_dict
arguments = {}
for i, prior_tuple in enumerate(prior_tuples):
prior = prior_tuple.prior
cls = prior_class_dict[prior]
mean = tuples[i][0]
if a is not None and r is not None:
raise exc.PriorException("Width of new priors cannot be both relative and absolute.")
if a is not None:
width_type = "a"
value = a
elif r is not None:
width_type = "r"
value = r
else:
width_type, value = conf.instance.prior_width.get_for_nearest_ancestor(cls, prior_tuple.name)
if width_type == "r":
width = value * mean
elif width_type == "a":
width = value
else:
raise exc.PriorException("Prior widths must be relative 'r' or absolute 'a' e.g. a, 1.0")
if isinstance(prior, GaussianPrior):
limits = (prior.lower_limit, prior.upper_limit)
else:
limits = conf.instance.prior_limit.get_for_nearest_ancestor(cls, prior_tuple.name)
arguments[prior] = GaussianPrior(mean, max(tuples[i][1], width), *limits)
return self.mapper_from_prior_arguments(arguments) | python | def mapper_from_gaussian_tuples(self, tuples, a=None, r=None):
"""
Creates a new model mapper from a list of floats describing the mean values of gaussian priors. The widths \
of the new priors are taken from the width_config. The new gaussian priors must be provided in the same \
order as the priors associated with model.
If a is not None then all priors are created with an absolute width of a.
If r is not None then all priors are created with a relative width of r.
Parameters
----------
r
The relative width to be assigned to gaussian priors
a
The absolute width to be assigned to gaussian priors
tuples
A list of tuples each containing the mean and width of a prior
Returns
-------
mapper: ModelMapper
A new model mapper with all priors replaced by gaussian priors.
"""
prior_tuples = self.prior_tuples_ordered_by_id
prior_class_dict = self.prior_class_dict
arguments = {}
for i, prior_tuple in enumerate(prior_tuples):
prior = prior_tuple.prior
cls = prior_class_dict[prior]
mean = tuples[i][0]
if a is not None and r is not None:
raise exc.PriorException("Width of new priors cannot be both relative and absolute.")
if a is not None:
width_type = "a"
value = a
elif r is not None:
width_type = "r"
value = r
else:
width_type, value = conf.instance.prior_width.get_for_nearest_ancestor(cls, prior_tuple.name)
if width_type == "r":
width = value * mean
elif width_type == "a":
width = value
else:
raise exc.PriorException("Prior widths must be relative 'r' or absolute 'a' e.g. a, 1.0")
if isinstance(prior, GaussianPrior):
limits = (prior.lower_limit, prior.upper_limit)
else:
limits = conf.instance.prior_limit.get_for_nearest_ancestor(cls, prior_tuple.name)
arguments[prior] = GaussianPrior(mean, max(tuples[i][1], width), *limits)
return self.mapper_from_prior_arguments(arguments) | [
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| a9e6144abb08edfc6a6906c4030d7119bf8d3e14 | https://github.com/rhayes777/PyAutoFit/blob/a9e6144abb08edfc6a6906c4030d7119bf8d3e14/autofit/mapper/model_mapper.py#L444-L499 | train |
rhayes777/PyAutoFit | autofit/mapper/model_mapper.py | ModelMapper.info | def info(self):
"""
Use the priors that make up the model_mapper to generate information on each parameter of the overall model.
This information is extracted from each priors *model_info* property.
"""
info = []
for prior_model_name, prior_model in self.prior_model_tuples:
info.append(prior_model.name + '\n')
info.extend([f"{prior_model_name}_{item}" for item in prior_model.info])
return '\n'.join(info) | python | def info(self):
"""
Use the priors that make up the model_mapper to generate information on each parameter of the overall model.
This information is extracted from each priors *model_info* property.
"""
info = []
for prior_model_name, prior_model in self.prior_model_tuples:
info.append(prior_model.name + '\n')
info.extend([f"{prior_model_name}_{item}" for item in prior_model.info])
return '\n'.join(info) | [
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| a9e6144abb08edfc6a6906c4030d7119bf8d3e14 | https://github.com/rhayes777/PyAutoFit/blob/a9e6144abb08edfc6a6906c4030d7119bf8d3e14/autofit/mapper/model_mapper.py#L520-L532 | train |
peterbe/gg | gg/builtins/push/gg_push.py | push | def push(config, force=False):
"""Create push the current branch."""
repo = config.repo
active_branch = repo.active_branch
if active_branch.name == "master":
error_out(
"Can't commit when on the master branch. "
"You really ought to do work in branches."
)
state = read(config.configfile)
if not state.get("FORK_NAME"):
info_out("Can't help you push the commit. Please run: gg config --help")
return 0
try:
repo.remotes[state["FORK_NAME"]]
except IndexError:
error_out("There is no remote called '{}'".format(state["FORK_NAME"]))
destination = repo.remotes[state["FORK_NAME"]]
if force:
pushed, = destination.push(force=True)
info_out(pushed.summary)
else:
pushed, = destination.push()
# Was it rejected?
if (
pushed.flags & git.remote.PushInfo.REJECTED
or pushed.flags & git.remote.PushInfo.REMOTE_REJECTED
):
error_out('The push was rejected ("{}")'.format(pushed.summary), False)
try_force_push = input("Try to force push? [Y/n] ").lower().strip()
if try_force_push not in ("no", "n"):
pushed, = destination.push(force=True)
info_out(pushed.summary)
else:
return 0 | python | def push(config, force=False):
"""Create push the current branch."""
repo = config.repo
active_branch = repo.active_branch
if active_branch.name == "master":
error_out(
"Can't commit when on the master branch. "
"You really ought to do work in branches."
)
state = read(config.configfile)
if not state.get("FORK_NAME"):
info_out("Can't help you push the commit. Please run: gg config --help")
return 0
try:
repo.remotes[state["FORK_NAME"]]
except IndexError:
error_out("There is no remote called '{}'".format(state["FORK_NAME"]))
destination = repo.remotes[state["FORK_NAME"]]
if force:
pushed, = destination.push(force=True)
info_out(pushed.summary)
else:
pushed, = destination.push()
# Was it rejected?
if (
pushed.flags & git.remote.PushInfo.REJECTED
or pushed.flags & git.remote.PushInfo.REMOTE_REJECTED
):
error_out('The push was rejected ("{}")'.format(pushed.summary), False)
try_force_push = input("Try to force push? [Y/n] ").lower().strip()
if try_force_push not in ("no", "n"):
pushed, = destination.push(force=True)
info_out(pushed.summary)
else:
return 0 | [
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| 2aace5bdb4a9b1cb65bea717784edf54c63b7bad | https://github.com/peterbe/gg/blob/2aace5bdb4a9b1cb65bea717784edf54c63b7bad/gg/builtins/push/gg_push.py#L12-L52 | train |
tslight/treepick | treepick/__main__.py | chkpath | def chkpath(path):
"""
Checks if a path exists.
"""
if os.path.exists(path):
return path
else:
msg = "{0} does not exist.".format(path)
raise argparse.ArgumentTypeError(msg) | python | def chkpath(path):
"""
Checks if a path exists.
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| 7adf838900f11e8845e17d8c79bb2b23617aec2c | https://github.com/tslight/treepick/blob/7adf838900f11e8845e17d8c79bb2b23617aec2c/treepick/__main__.py#L14-L22 | train |
geophysics-ubonn/crtomo_tools | src/volt_correct_temperature.py | readin_volt | def readin_volt(filename):
"""Read in measurement data from a volt.dat file and return electrodes and
measured resistance.
"""
with open(filename, 'r') as fid:
content = np.loadtxt(fid, skiprows=1, usecols=[0, 1, 2])
volt = content[:, 2]
elecs = content[:, 0:2]
return elecs, volt | python | def readin_volt(filename):
"""Read in measurement data from a volt.dat file and return electrodes and
measured resistance.
"""
with open(filename, 'r') as fid:
content = np.loadtxt(fid, skiprows=1, usecols=[0, 1, 2])
volt = content[:, 2]
elecs = content[:, 0:2]
return elecs, volt | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/volt_correct_temperature.py#L56-L64 | train |
geophysics-ubonn/crtomo_tools | src/volt_correct_temperature.py | save_volt | def save_volt(elecs, volt, filename):
"""Save the values in volt-format.
"""
# bring data in shape
content = np.column_stack((elecs, volt, np.zeros(len(volt))))
# save datapoints
with open(filename, 'w') as fid:
fid.write('{0}\n'.format(content.shape[0]))
with open(filename, 'ab') as fid:
np.savetxt(fid, np.array(content), fmt='%i %i %f %f') | python | def save_volt(elecs, volt, filename):
"""Save the values in volt-format.
"""
# bring data in shape
content = np.column_stack((elecs, volt, np.zeros(len(volt))))
# save datapoints
with open(filename, 'w') as fid:
fid.write('{0}\n'.format(content.shape[0]))
with open(filename, 'ab') as fid:
np.savetxt(fid, np.array(content), fmt='%i %i %f %f') | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/volt_correct_temperature.py#L90-L100 | train |
geophysics-ubonn/crtomo_tools | src/volt_correct_temperature.py | main | def main():
"""Function to remove temperature effect from field data
"""
options = handle_options()
# read in observed and synthetic data
elecs, d_obs = readin_volt(options.d_obs)
elecs, d_est = readin_volt(options.d_est)
elecs, d_estTC = readin_volt(options.d_estTC)
# calculate corrected data
volt_corr = calc_correction(d_obs,
d_est,
d_estTC,
)
# save data
save_volt(elecs,
volt_corr,
options.output,
) | python | def main():
"""Function to remove temperature effect from field data
"""
options = handle_options()
# read in observed and synthetic data
elecs, d_obs = readin_volt(options.d_obs)
elecs, d_est = readin_volt(options.d_est)
elecs, d_estTC = readin_volt(options.d_estTC)
# calculate corrected data
volt_corr = calc_correction(d_obs,
d_est,
d_estTC,
)
# save data
save_volt(elecs,
volt_corr,
options.output,
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/volt_correct_temperature.py#L103-L121 | train |
Maples7/dict-recursive-update | dict_recursive_update/__init__.py | recursive_update | def recursive_update(default, custom):
'''Return a dict merged from default and custom
>>> recursive_update('a', 'b')
Traceback (most recent call last):
...
TypeError: Params of recursive_update should be dicts
>>> recursive_update({'a': [1]}, {'a': [2], 'c': {'d': {'c': 3}}})
{'a': [2], 'c': {'d': {'c': 3}}}
>>> recursive_update({'a': {'c': 1, 'd': {}}, 'b': 4}, {'b': 5})
{'a': {'c': 1, 'd': {}}, 'b': 5}
>>> recursive_update({'a': {'c': 1, 'd': {}}, 'b': 4}, {'a': 2})
{'a': 2, 'b': 4}
'''
if not isinstance(default, dict) or not isinstance(custom, dict):
raise TypeError('Params of recursive_update should be dicts')
for key in custom:
if isinstance(custom[key], dict) and isinstance(
default.get(key), dict):
default[key] = recursive_update(default[key], custom[key])
else:
default[key] = custom[key]
return default | python | def recursive_update(default, custom):
'''Return a dict merged from default and custom
>>> recursive_update('a', 'b')
Traceback (most recent call last):
...
TypeError: Params of recursive_update should be dicts
>>> recursive_update({'a': [1]}, {'a': [2], 'c': {'d': {'c': 3}}})
{'a': [2], 'c': {'d': {'c': 3}}}
>>> recursive_update({'a': {'c': 1, 'd': {}}, 'b': 4}, {'b': 5})
{'a': {'c': 1, 'd': {}}, 'b': 5}
>>> recursive_update({'a': {'c': 1, 'd': {}}, 'b': 4}, {'a': 2})
{'a': 2, 'b': 4}
'''
if not isinstance(default, dict) or not isinstance(custom, dict):
raise TypeError('Params of recursive_update should be dicts')
for key in custom:
if isinstance(custom[key], dict) and isinstance(
default.get(key), dict):
default[key] = recursive_update(default[key], custom[key])
else:
default[key] = custom[key]
return default | [
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| 07204cdab891ac4123b19fe3fa148c3dd1c93992 | https://github.com/Maples7/dict-recursive-update/blob/07204cdab891ac4123b19fe3fa148c3dd1c93992/dict_recursive_update/__init__.py#L11-L38 | train |
peterbe/gg | gg/builtins/cleanup/gg_cleanup.py | cleanup | def cleanup(config, searchstring, force=False):
"""Deletes a found branch locally and remotely."""
repo = config.repo
branches_ = list(find(repo, searchstring))
if not branches_:
error_out("No branches found")
elif len(branches_) > 1:
error_out(
"More than one branch found.{}".format(
"\n\t".join([""] + [x.name for x in branches_])
)
)
assert len(branches_) == 1
branch_name = branches_[0].name
active_branch = repo.active_branch
if branch_name == active_branch.name:
error_out("Can't clean up the current active branch.")
# branch_name = active_branch.name
upstream_remote = None
fork_remote = None
state = read(config.configfile)
origin_name = state.get("ORIGIN_NAME", "origin")
for remote in repo.remotes:
if remote.name == origin_name:
# remote.pull()
upstream_remote = remote
break
if not upstream_remote:
error_out("No remote called {!r} found".format(origin_name))
# Check out master
repo.heads.master.checkout()
upstream_remote.pull(repo.heads.master)
# Is this one of the merged branches?!
# XXX I don't know how to do this "nativly" with GitPython.
merged_branches = [
x.strip()
for x in repo.git.branch("--merged").splitlines()
if x.strip() and not x.strip().startswith("*")
]
was_merged = branch_name in merged_branches
certain = was_merged or force
if not certain:
# Need to ask the user.
# XXX This is where we could get smart and compare this branch
# with the master.
certain = (
input("Are you certain {} is actually merged? [Y/n] ".format(branch_name))
.lower()
.strip()
!= "n"
)
if not certain:
return 1
if was_merged:
repo.git.branch("-d", branch_name)
else:
repo.git.branch("-D", branch_name)
fork_remote = None
state = read(config.configfile)
for remote in repo.remotes:
if remote.name == state.get("FORK_NAME"):
fork_remote = remote
break
if fork_remote:
fork_remote.push(":" + branch_name)
info_out("Remote branch on fork deleted too.") | python | def cleanup(config, searchstring, force=False):
"""Deletes a found branch locally and remotely."""
repo = config.repo
branches_ = list(find(repo, searchstring))
if not branches_:
error_out("No branches found")
elif len(branches_) > 1:
error_out(
"More than one branch found.{}".format(
"\n\t".join([""] + [x.name for x in branches_])
)
)
assert len(branches_) == 1
branch_name = branches_[0].name
active_branch = repo.active_branch
if branch_name == active_branch.name:
error_out("Can't clean up the current active branch.")
# branch_name = active_branch.name
upstream_remote = None
fork_remote = None
state = read(config.configfile)
origin_name = state.get("ORIGIN_NAME", "origin")
for remote in repo.remotes:
if remote.name == origin_name:
# remote.pull()
upstream_remote = remote
break
if not upstream_remote:
error_out("No remote called {!r} found".format(origin_name))
# Check out master
repo.heads.master.checkout()
upstream_remote.pull(repo.heads.master)
# Is this one of the merged branches?!
# XXX I don't know how to do this "nativly" with GitPython.
merged_branches = [
x.strip()
for x in repo.git.branch("--merged").splitlines()
if x.strip() and not x.strip().startswith("*")
]
was_merged = branch_name in merged_branches
certain = was_merged or force
if not certain:
# Need to ask the user.
# XXX This is where we could get smart and compare this branch
# with the master.
certain = (
input("Are you certain {} is actually merged? [Y/n] ".format(branch_name))
.lower()
.strip()
!= "n"
)
if not certain:
return 1
if was_merged:
repo.git.branch("-d", branch_name)
else:
repo.git.branch("-D", branch_name)
fork_remote = None
state = read(config.configfile)
for remote in repo.remotes:
if remote.name == state.get("FORK_NAME"):
fork_remote = remote
break
if fork_remote:
fork_remote.push(":" + branch_name)
info_out("Remote branch on fork deleted too.") | [
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| 2aace5bdb4a9b1cb65bea717784edf54c63b7bad | https://github.com/peterbe/gg/blob/2aace5bdb4a9b1cb65bea717784edf54c63b7bad/gg/builtins/cleanup/gg_cleanup.py#L13-L84 | train |
geophysics-ubonn/crtomo_tools | src/td_correct_temperature.py | calc_correction | def calc_correction(temp, mag, add=False, T_std=10, m=0.021):
"""Function to add or substract the temperature effect to given data. The
function can be called in python scripts. For application via command line
in a file system use the script td_correct_temperature.py. The data is
taken and given in Ohmm.
rho_std_i = (m * (T_i - 25°) + 1) / (m * (T_std - 25°) + 1) * rho_i
rho_i = (m * (T_std - 25°) + 1) / (m * (T_i - 25°) + 1) * rho_std_i
Hayley (2007)
Parameters:
temp: temperature values corresponding to the individual resistivity
values
mag: resistivity values to be corrected
add: switch for adding instead of substracting the effect
T_std: standard temperature t or from which to correct (default=10°)
m:coeffcient (default=0.021)
"""
if mag.shape[1] == 3:
if add:
data_x = (m * (T_std - 25) + 1) / (m * (temp - 25) + 1) * mag[:, 0]
data_y = (m * (T_std - 25) + 1) / (m * (temp - 25) + 1) * mag[:, 1]
data_z = (m * (T_std - 25) + 1) / (m * (temp - 25) + 1) * mag[:, 2]
return np.column_stack((data_x, data_y, data_z))
else:
data_x = (m * (temp - 25) + 1) / (m * (T_std - 25) + 1) * mag[:, 0]
data_y = (m * (temp - 25) + 1) / (m * (T_std - 25) + 1) * mag[:, 1]
data_z = (m * (temp - 25) + 1) / (m * (T_std - 25) + 1) * mag[:, 2]
return np.column_stack((data_x, data_y, data_z))
else:
if add:
data_i = (m * (T_std - 25) + 1) / (m * (temp - 25) + 1) * mag
return data_i
else:
data_std = (m * (temp - 25) + 1) / (m * (T_std - 25) + 1) * mag
return data_std | python | def calc_correction(temp, mag, add=False, T_std=10, m=0.021):
"""Function to add or substract the temperature effect to given data. The
function can be called in python scripts. For application via command line
in a file system use the script td_correct_temperature.py. The data is
taken and given in Ohmm.
rho_std_i = (m * (T_i - 25°) + 1) / (m * (T_std - 25°) + 1) * rho_i
rho_i = (m * (T_std - 25°) + 1) / (m * (T_i - 25°) + 1) * rho_std_i
Hayley (2007)
Parameters:
temp: temperature values corresponding to the individual resistivity
values
mag: resistivity values to be corrected
add: switch for adding instead of substracting the effect
T_std: standard temperature t or from which to correct (default=10°)
m:coeffcient (default=0.021)
"""
if mag.shape[1] == 3:
if add:
data_x = (m * (T_std - 25) + 1) / (m * (temp - 25) + 1) * mag[:, 0]
data_y = (m * (T_std - 25) + 1) / (m * (temp - 25) + 1) * mag[:, 1]
data_z = (m * (T_std - 25) + 1) / (m * (temp - 25) + 1) * mag[:, 2]
return np.column_stack((data_x, data_y, data_z))
else:
data_x = (m * (temp - 25) + 1) / (m * (T_std - 25) + 1) * mag[:, 0]
data_y = (m * (temp - 25) + 1) / (m * (T_std - 25) + 1) * mag[:, 1]
data_z = (m * (temp - 25) + 1) / (m * (T_std - 25) + 1) * mag[:, 2]
return np.column_stack((data_x, data_y, data_z))
else:
if add:
data_i = (m * (T_std - 25) + 1) / (m * (temp - 25) + 1) * mag
return data_i
else:
data_std = (m * (temp - 25) + 1) / (m * (T_std - 25) + 1) * mag
return data_std | [
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rho_std_i = (m * (T_i - 25°) + 1) / (m * (T_std - 25°) + 1) * rho_i
rho_i = (m * (T_std - 25°) + 1) / (m * (T_i - 25°) + 1) * rho_std_i
Hayley (2007)
Parameters:
temp: temperature values corresponding to the individual resistivity
values
mag: resistivity values to be corrected
add: switch for adding instead of substracting the effect
T_std: standard temperature t or from which to correct (default=10°)
m:coeffcient (default=0.021) | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/td_correct_temperature.py#L137-L173 | train |
geophysics-ubonn/crtomo_tools | src/td_correct_temperature.py | save_mag_to_file | def save_mag_to_file(mag, filename, rhofile):
"""Save the values in rho- or mag-format.
"""
if rhofile:
# bring data in shape
null = np.zeros(len(mag))
if mag.shape[1] == 3:
null = np.column_stack((null, null, null, null))
result = np.column_stack((mag, null))
# save datapoints
with open(filename, 'w') as fid:
fid.write('{0}\n'.format(mag.shape[0]))
with open(filename, 'ab') as fid:
np.savetxt(fid, np.array(result), fmt='%f')
else:
# bring data in shape
with open('inv/rho00.mag', 'r') as fid:
coor = np.loadtxt(fid, skiprows=1, usecols=[0, 1])
# calculated back to log
if mag.shape[1] == 3:
logx = [math.log(d, 10) for d in mag[:, 0]]
logy = [math.log(d, 10) for d in mag[:, 1]]
logz = [math.log(d, 10) for d in mag[:, 2]]
mag_log = np.column_stack((logx, logy, logz))
else:
mag_log = [math.log(d, 10) for d in mag]
content = np.column_stack((coor[:, 0], coor[:, 1], mag_log))
# save datapoints
with open(filename, 'w') as fid:
fid.write('{0}\n'.format(content.shape[0]))
with open(filename, 'ab') as fid:
np.savetxt(fid, np.array(content), fmt='%f') | python | def save_mag_to_file(mag, filename, rhofile):
"""Save the values in rho- or mag-format.
"""
if rhofile:
# bring data in shape
null = np.zeros(len(mag))
if mag.shape[1] == 3:
null = np.column_stack((null, null, null, null))
result = np.column_stack((mag, null))
# save datapoints
with open(filename, 'w') as fid:
fid.write('{0}\n'.format(mag.shape[0]))
with open(filename, 'ab') as fid:
np.savetxt(fid, np.array(result), fmt='%f')
else:
# bring data in shape
with open('inv/rho00.mag', 'r') as fid:
coor = np.loadtxt(fid, skiprows=1, usecols=[0, 1])
# calculated back to log
if mag.shape[1] == 3:
logx = [math.log(d, 10) for d in mag[:, 0]]
logy = [math.log(d, 10) for d in mag[:, 1]]
logz = [math.log(d, 10) for d in mag[:, 2]]
mag_log = np.column_stack((logx, logy, logz))
else:
mag_log = [math.log(d, 10) for d in mag]
content = np.column_stack((coor[:, 0], coor[:, 1], mag_log))
# save datapoints
with open(filename, 'w') as fid:
fid.write('{0}\n'.format(content.shape[0]))
with open(filename, 'ab') as fid:
np.savetxt(fid, np.array(content), fmt='%f') | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/td_correct_temperature.py#L176-L210 | train |
geophysics-ubonn/crtomo_tools | src/td_correct_temperature.py | main | def main():
"""Function to add or substract the temperature effect to data in a tomodir
"""
options = handle_options()
# read in temperature and resistivity data
tempdata = readin_temp(options.temp_file)
magdata = readin_rho(options.filename,
options.rhofile,
aniso=options.aniso)
# calculate corrected data
mag_corr = calc_correction(temp=tempdata,
mag=magdata,
add=options.add,
T_std=options.T_std,
m=options.m,)
# save data
save_mag_to_file(mag_corr,
options.output,
options.rhofile) | python | def main():
"""Function to add or substract the temperature effect to data in a tomodir
"""
options = handle_options()
# read in temperature and resistivity data
tempdata = readin_temp(options.temp_file)
magdata = readin_rho(options.filename,
options.rhofile,
aniso=options.aniso)
# calculate corrected data
mag_corr = calc_correction(temp=tempdata,
mag=magdata,
add=options.add,
T_std=options.T_std,
m=options.m,)
# save data
save_mag_to_file(mag_corr,
options.output,
options.rhofile) | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/td_correct_temperature.py#L213-L232 | train |
lalinsky/mbdata | mbdata/api/utils.py | singular | def singular(plural):
"""
Take a plural English word and turn it into singular
Obviously, this doesn't work in general. It know just enough words to
generate XML tag names for list items. For example, if we have an element
called 'tracks' in the response, it will be serialized as a list without
named items in JSON, but we need names for items in XML, so those will be
called 'track'.
"""
if plural.endswith('ies'):
return plural[:-3] + 'y'
if plural.endswith('s'):
return plural[:-1]
raise ValueError('unknown plural form %r' % (plural,)) | python | def singular(plural):
"""
Take a plural English word and turn it into singular
Obviously, this doesn't work in general. It know just enough words to
generate XML tag names for list items. For example, if we have an element
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if plural.endswith('ies'):
return plural[:-3] + 'y'
if plural.endswith('s'):
return plural[:-1]
raise ValueError('unknown plural form %r' % (plural,)) | [
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| 1ec788834047ced8614ad9763e430afe1d1e65e7 | https://github.com/lalinsky/mbdata/blob/1ec788834047ced8614ad9763e430afe1d1e65e7/mbdata/api/utils.py#L56-L70 | train |
geophysics-ubonn/crtomo_tools | src/sens_center_plot.py | sens_center.plot_single_configuration | def plot_single_configuration(self, config_nr, sens_file):
"""
plot sensitivity distribution with center of mass for
a single configuration. The electrodes used are colored.
Parameters
----------
config_nr: int
number of configuration
sens_file: string, file path
filename to sensitvity file
"""
indices = elem.load_column_file_to_elements_advanced(
sens_file, [2, 3],
False,
False
)
elem.plt_opt.title = ''
elem.plt_opt.reverse = True
elem.plt_opt.cbmin = -1
elem.plt_opt.cbmax = 1
elem.plt_opt.cblabel = r'fill'
elem.plt_opt.xlabel = 'x (m)'
elem.plt_opt.ylabel = 'z (m)'
fig = plt.figure(figsize=(5, 7))
ax = fig.add_subplot(111)
ax, pm, cb = elem.plot_element_data_to_ax(
indices[0],
ax,
scale='asinh',
no_cb=False,
)
ax.scatter(
self.sens_centers[config_nr, 0],
self.sens_centers[config_nr, 1],
marker='*',
s=50,
color='w',
edgecolors='w',
)
self.color_electrodes(config_nr, ax)
# Output
sensf = sens_file.split('sens')[-1]
sensf = sensf.split('.')[0]
out = 'sens_center_' + sensf + '.png'
fig.savefig(out, bbox_inches='tight', dpi=300)
fig.clf()
plt.close(fig) | python | def plot_single_configuration(self, config_nr, sens_file):
"""
plot sensitivity distribution with center of mass for
a single configuration. The electrodes used are colored.
Parameters
----------
config_nr: int
number of configuration
sens_file: string, file path
filename to sensitvity file
"""
indices = elem.load_column_file_to_elements_advanced(
sens_file, [2, 3],
False,
False
)
elem.plt_opt.title = ''
elem.plt_opt.reverse = True
elem.plt_opt.cbmin = -1
elem.plt_opt.cbmax = 1
elem.plt_opt.cblabel = r'fill'
elem.plt_opt.xlabel = 'x (m)'
elem.plt_opt.ylabel = 'z (m)'
fig = plt.figure(figsize=(5, 7))
ax = fig.add_subplot(111)
ax, pm, cb = elem.plot_element_data_to_ax(
indices[0],
ax,
scale='asinh',
no_cb=False,
)
ax.scatter(
self.sens_centers[config_nr, 0],
self.sens_centers[config_nr, 1],
marker='*',
s=50,
color='w',
edgecolors='w',
)
self.color_electrodes(config_nr, ax)
# Output
sensf = sens_file.split('sens')[-1]
sensf = sensf.split('.')[0]
out = 'sens_center_' + sensf + '.png'
fig.savefig(out, bbox_inches='tight', dpi=300)
fig.clf()
plt.close(fig) | [
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Parameters
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config_nr: int
number of configuration
sens_file: string, file path
filename to sensitvity file | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/sens_center_plot.py#L168-L220 | train |
geophysics-ubonn/crtomo_tools | src/sens_center_plot.py | sens_center.plot_sens_center | def plot_sens_center(self, frequency=2):
"""
plot sensitivity center distribution for all configurations in
config.dat. The centers of mass are colored by the data given in
volt_file.
"""
try:
colors = np.loadtxt(self.volt_file, skiprows=1)
except IOError:
print('IOError opening {0}'.format(volt_file))
exit()
# check for 1-dimensionality
if(len(colors.shape) > 1):
print('Artificial or Multi frequency data')
colors = colors[:, frequency].flatten()
colors = colors[~np.isnan(colors)]
elem.load_elem_file(self.elem_file)
elem.load_elec_file(self.elec_file)
nr_elements = len(elem.element_type_list[0])
elem.element_data = np.zeros((nr_elements, 1)) * np.nan
elem.plt_opt.title = ' '
elem.plt_opt.reverse = True
elem.plt_opt.cbmin = -1
elem.plt_opt.cbmax = 1
elem.plt_opt.cblabel = self.cblabel
elem.plt_opt.xlabel = 'x (m)'
elem.plt_opt.ylabel = 'z (m)'
fig = plt.figure(figsize=(5, 7))
ax = fig.add_subplot(111)
ax, pm, cb = elem.plot_element_data_to_ax(0, ax, scale='linear',
no_cb=True)
ax.scatter(self.sens_centers[:, 0], self.sens_centers[:, 1], c=colors,
s=100, edgecolors='none')
cb_pos = mpl_get_cb_bound_next_to_plot(ax)
ax1 = fig.add_axes(cb_pos, frame_on=True)
cmap = mpl.cm.jet_r
norm = mpl.colors.Normalize(vmin=np.nanmin(colors),
vmax=np.nanmax(colors))
mpl.colorbar.ColorbarBase(ax1, cmap=cmap, norm=norm,
orientation='vertical')
fig.savefig(self.output_file, bbox_inches='tight', dpi=300) | python | def plot_sens_center(self, frequency=2):
"""
plot sensitivity center distribution for all configurations in
config.dat. The centers of mass are colored by the data given in
volt_file.
"""
try:
colors = np.loadtxt(self.volt_file, skiprows=1)
except IOError:
print('IOError opening {0}'.format(volt_file))
exit()
# check for 1-dimensionality
if(len(colors.shape) > 1):
print('Artificial or Multi frequency data')
colors = colors[:, frequency].flatten()
colors = colors[~np.isnan(colors)]
elem.load_elem_file(self.elem_file)
elem.load_elec_file(self.elec_file)
nr_elements = len(elem.element_type_list[0])
elem.element_data = np.zeros((nr_elements, 1)) * np.nan
elem.plt_opt.title = ' '
elem.plt_opt.reverse = True
elem.plt_opt.cbmin = -1
elem.plt_opt.cbmax = 1
elem.plt_opt.cblabel = self.cblabel
elem.plt_opt.xlabel = 'x (m)'
elem.plt_opt.ylabel = 'z (m)'
fig = plt.figure(figsize=(5, 7))
ax = fig.add_subplot(111)
ax, pm, cb = elem.plot_element_data_to_ax(0, ax, scale='linear',
no_cb=True)
ax.scatter(self.sens_centers[:, 0], self.sens_centers[:, 1], c=colors,
s=100, edgecolors='none')
cb_pos = mpl_get_cb_bound_next_to_plot(ax)
ax1 = fig.add_axes(cb_pos, frame_on=True)
cmap = mpl.cm.jet_r
norm = mpl.colors.Normalize(vmin=np.nanmin(colors),
vmax=np.nanmax(colors))
mpl.colorbar.ColorbarBase(ax1, cmap=cmap, norm=norm,
orientation='vertical')
fig.savefig(self.output_file, bbox_inches='tight', dpi=300) | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/sens_center_plot.py#L222-L269 | train |
geophysics-ubonn/crtomo_tools | src/sens_center_plot.py | sens_center.color_electrodes | def color_electrodes(self, config_nr, ax):
"""
Color the electrodes used in specific configuration.
Voltage electrodes are yellow, Current electrodes are red ?!
"""
electrodes = np.loadtxt(options.config_file, skiprows=1)
electrodes = self.configs[~np.isnan(self.configs).any(1)]
electrodes = electrodes.astype(int)
conf = []
for dim in range(0, electrodes.shape[1]):
c = electrodes[config_nr, dim]
# c = c.partition('0')
a = np.round(c / 10000) - 1
b = np.mod(c, 10000) - 1
conf.append(a)
conf.append(b)
Ex, Ez = elem.get_electrodes()
color = ['#ffed00', '#ffed00', '#ff0000', '#ff0000']
ax.scatter(Ex[conf], Ez[conf], c=color, marker='s', s=60,
clip_on=False, edgecolors='k') | python | def color_electrodes(self, config_nr, ax):
"""
Color the electrodes used in specific configuration.
Voltage electrodes are yellow, Current electrodes are red ?!
"""
electrodes = np.loadtxt(options.config_file, skiprows=1)
electrodes = self.configs[~np.isnan(self.configs).any(1)]
electrodes = electrodes.astype(int)
conf = []
for dim in range(0, electrodes.shape[1]):
c = electrodes[config_nr, dim]
# c = c.partition('0')
a = np.round(c / 10000) - 1
b = np.mod(c, 10000) - 1
conf.append(a)
conf.append(b)
Ex, Ez = elem.get_electrodes()
color = ['#ffed00', '#ffed00', '#ff0000', '#ff0000']
ax.scatter(Ex[conf], Ez[conf], c=color, marker='s', s=60,
clip_on=False, edgecolors='k') | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/sens_center_plot.py#L271-L291 | train |
geophysics-ubonn/crtomo_tools | src/sens_center_plot.py | sens_center.compute_sens | def compute_sens(self, elem_file, elec_file, configs):
"""
Compute the sensitivities for the given input data.
A CRMod instance is called to create the sensitivity files.
"""
CRMod_config = CRMod.config()
# activate 2D mode and set sink nr
if self.options.sink is not None:
print('2D mode with sink {0}'.format(self.options.sink))
CRMod_config['2D'] = 0
CRMod_config['fictitious_sink'] = 'T'
CRMod_config['sink_node'] = self.options.sink
CRMod_config['write_sens'] = 'T'
CRMod_instance = CRMod.CRMod(CRMod_config)
CRMod_instance.elemfile = elem_file
CRMod_instance.elecfile = elec_file
CRMod_instance.configdata = configs
resistivity = 100
# get number of elements
fid = open(elem_file, 'r')
fid.readline()
elements = int(fid.readline().strip().split()[1])
fid.close()
# create rho.dat file
rhodata = '{0}\n'.format(elements)
for i in range(0, elements):
rhodata += '{0} 0\n'.format(resistivity)
CRMod_instance.rhodata = rhodata
CRMod_instance.run_in_tempdir()
volt_file = CRMod_instance.volt_file
sens_files = CRMod_instance.sens_files
return sens_files, volt_file, CRMod_instance.temp_dir | python | def compute_sens(self, elem_file, elec_file, configs):
"""
Compute the sensitivities for the given input data.
A CRMod instance is called to create the sensitivity files.
"""
CRMod_config = CRMod.config()
# activate 2D mode and set sink nr
if self.options.sink is not None:
print('2D mode with sink {0}'.format(self.options.sink))
CRMod_config['2D'] = 0
CRMod_config['fictitious_sink'] = 'T'
CRMod_config['sink_node'] = self.options.sink
CRMod_config['write_sens'] = 'T'
CRMod_instance = CRMod.CRMod(CRMod_config)
CRMod_instance.elemfile = elem_file
CRMod_instance.elecfile = elec_file
CRMod_instance.configdata = configs
resistivity = 100
# get number of elements
fid = open(elem_file, 'r')
fid.readline()
elements = int(fid.readline().strip().split()[1])
fid.close()
# create rho.dat file
rhodata = '{0}\n'.format(elements)
for i in range(0, elements):
rhodata += '{0} 0\n'.format(resistivity)
CRMod_instance.rhodata = rhodata
CRMod_instance.run_in_tempdir()
volt_file = CRMod_instance.volt_file
sens_files = CRMod_instance.sens_files
return sens_files, volt_file, CRMod_instance.temp_dir | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/sens_center_plot.py#L293-L328 | train |
geophysics-ubonn/crtomo_tools | src/sens_center_plot.py | sens_center.compute_center_of_mass | def compute_center_of_mass(self, filename):
"""
Center of mass is computed using the sensitivity data output from CRMod
Data weights can be applied using command line options
"""
sens = np.loadtxt(filename, skiprows=1)
X = sens[:, 0]
Z = sens[:, 1]
# C = (np.abs(sens[:,2]))# ./ np.max(np.abs(sens[:,2]))
C = sens[:, 2]
x_center = 0
z_center = 0
sens_sum = 0
for i in range(0, C.shape[0]):
# unweighted
if(self.weight == 0):
weight = (C[i])
# abs
if(self.weight == 1):
weight = np.abs(C[i])
# log10
if(self.weight == 2):
weight = np.log10(np.abs(C[i]))
# sqrt
if(self.weight == 3):
weight = np.sqrt(np.abs(C[i]))
x_center += (X[i] * weight)
z_center += (Z[i] * weight)
sens_sum += weight
x_center /= sens_sum
z_center /= sens_sum
return (x_center, z_center) | python | def compute_center_of_mass(self, filename):
"""
Center of mass is computed using the sensitivity data output from CRMod
Data weights can be applied using command line options
"""
sens = np.loadtxt(filename, skiprows=1)
X = sens[:, 0]
Z = sens[:, 1]
# C = (np.abs(sens[:,2]))# ./ np.max(np.abs(sens[:,2]))
C = sens[:, 2]
x_center = 0
z_center = 0
sens_sum = 0
for i in range(0, C.shape[0]):
# unweighted
if(self.weight == 0):
weight = (C[i])
# abs
if(self.weight == 1):
weight = np.abs(C[i])
# log10
if(self.weight == 2):
weight = np.log10(np.abs(C[i]))
# sqrt
if(self.weight == 3):
weight = np.sqrt(np.abs(C[i]))
x_center += (X[i] * weight)
z_center += (Z[i] * weight)
sens_sum += weight
x_center /= sens_sum
z_center /= sens_sum
return (x_center, z_center) | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/sens_center_plot.py#L330-L366 | train |
geophysics-ubonn/crtomo_tools | src/td_init.py | handle_cmd_options | def handle_cmd_options():
'''
Get the options from the command line.
'''
parser = OptionParser()
parser.add_option("-s", "--silent", action="store_true", dest="silent",
help="print any warnings", default=False)
(options, args) = parser.parse_args()
return options, args | python | def handle_cmd_options():
'''
Get the options from the command line.
'''
parser = OptionParser()
parser.add_option("-s", "--silent", action="store_true", dest="silent",
help="print any warnings", default=False)
(options, args) = parser.parse_args()
return options, args | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/td_init.py#L18-L26 | train |
geophysics-ubonn/crtomo_tools | src/td_init.py | move | def move(fname, folder, options):
"""Move file to dir if existing
"""
if os.path.isfile(fname):
shutil.move(fname, folder)
else:
if options.silent is False:
print('{0} missing'.format(fname)) | python | def move(fname, folder, options):
"""Move file to dir if existing
"""
if os.path.isfile(fname):
shutil.move(fname, folder)
else:
if options.silent is False:
print('{0} missing'.format(fname)) | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/td_init.py#L29-L36 | train |
Infinidat/infi.traceback | src/infi/traceback/__init__.py | print_tb | def print_tb(tb, limit=None, file=None):
"""Print up to 'limit' stack trace entries from the traceback 'tb'.
If 'limit' is omitted or None, all entries are printed. If 'file'
is omitted or None, the output goes to sys.stderr; otherwise
'file' should be an open file or file-like object with a write()
method.
"""
if file is None:
file = sys.stderr
if limit is None:
if hasattr(sys, 'tracebacklimit'):
limit = sys.tracebacklimit
file.write('\n'.join(format_tb(tb, limit)) + '\n') | python | def print_tb(tb, limit=None, file=None):
"""Print up to 'limit' stack trace entries from the traceback 'tb'.
If 'limit' is omitted or None, all entries are printed. If 'file'
is omitted or None, the output goes to sys.stderr; otherwise
'file' should be an open file or file-like object with a write()
method.
"""
if file is None:
file = sys.stderr
if limit is None:
if hasattr(sys, 'tracebacklimit'):
limit = sys.tracebacklimit
file.write('\n'.join(format_tb(tb, limit)) + '\n') | [
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Infinidat/infi.traceback | src/infi/traceback/__init__.py | print_exception | def print_exception(etype, value, tb, limit=None, file=None, chain=True):
"""Print exception up to 'limit' stack trace entries from 'tb' to 'file'.
This differs from print_tb() in the following ways: (1) if
traceback is not None, it prints a header "Traceback (most recent
call last):"; (2) it prints the exception type and value after the
stack trace; (3) if type is SyntaxError and value has the
appropriate format, it prints the line where the syntax error
occurred with a caret on the next line indicating the approximate
position of the error.
"""
import traceback
if file is None:
file = sys.stderr
if tb:
file.write('Traceback (most recent call last):\n')
print_tb(tb, limit, file)
lines = traceback.format_exception_only(etype, value)
for line in lines:
file.write(line) | python | def print_exception(etype, value, tb, limit=None, file=None, chain=True):
"""Print exception up to 'limit' stack trace entries from 'tb' to 'file'.
This differs from print_tb() in the following ways: (1) if
traceback is not None, it prints a header "Traceback (most recent
call last):"; (2) it prints the exception type and value after the
stack trace; (3) if type is SyntaxError and value has the
appropriate format, it prints the line where the syntax error
occurred with a caret on the next line indicating the approximate
position of the error.
"""
import traceback
if file is None:
file = sys.stderr
if tb:
file.write('Traceback (most recent call last):\n')
print_tb(tb, limit, file)
lines = traceback.format_exception_only(etype, value)
for line in lines:
file.write(line) | [
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| ae25455ec451c136458d2781fea876964375bf8b | https://github.com/Infinidat/infi.traceback/blob/ae25455ec451c136458d2781fea876964375bf8b/src/infi/traceback/__init__.py#L168-L187 | train |
gofed/gofedlib | gofedlib/go/projectinfo.py | ProjectInfo.construct | def construct(self, data):
"""Construct info about a project from artefact
:param data: golang-project-packages artefact
:type data: json/dict
"""
occurrences = {}
main_occurrences = {}
# occurrences of devel packages
for pkg in data["data"]["dependencies"]:
package = pkg["package"]
for item in pkg["dependencies"]:
dep = item["name"]
if package != ".":
deps = map(lambda l: "%s/%s" % (package, l), item["location"])
else:
deps = item["location"]
if dep not in occurrences:
occurrences[dep] = deps
else:
occurrences[dep] = occurrences[dep] + deps
self.occurrences = occurrences
# occurrences of main packages
for main in data["data"]["main"]:
filename = main["filename"]
for dep in main["dependencies"]:
if dep not in main_occurrences:
main_occurrences[dep] = [filename]
else:
main_occurrences[dep].append(filename)
self.main_occurrences = main_occurrences
# test directories
self.test_directories = sorted(map(lambda l: l["test"], data["data"]["tests"]))
# provided devel packages
self.provided_packages = sorted(data["data"]["packages"])
# imported paths in devel packages
imported_packages = []
imported_native_packages = []
for path in occurrences:
try:
self.ipparser.parse(path)
except ValueError:
continue
if self.ipparser.isNative():
imported_native_packages.append(path)
else:
imported_packages.append(path)
self.imported_packages = sorted(imported_packages)
self.imported_native_packages = sorted(imported_native_packages)
# main packages
self.main_packages = map(lambda l: l["filename"], data["data"]["main"]) | python | def construct(self, data):
"""Construct info about a project from artefact
:param data: golang-project-packages artefact
:type data: json/dict
"""
occurrences = {}
main_occurrences = {}
# occurrences of devel packages
for pkg in data["data"]["dependencies"]:
package = pkg["package"]
for item in pkg["dependencies"]:
dep = item["name"]
if package != ".":
deps = map(lambda l: "%s/%s" % (package, l), item["location"])
else:
deps = item["location"]
if dep not in occurrences:
occurrences[dep] = deps
else:
occurrences[dep] = occurrences[dep] + deps
self.occurrences = occurrences
# occurrences of main packages
for main in data["data"]["main"]:
filename = main["filename"]
for dep in main["dependencies"]:
if dep not in main_occurrences:
main_occurrences[dep] = [filename]
else:
main_occurrences[dep].append(filename)
self.main_occurrences = main_occurrences
# test directories
self.test_directories = sorted(map(lambda l: l["test"], data["data"]["tests"]))
# provided devel packages
self.provided_packages = sorted(data["data"]["packages"])
# imported paths in devel packages
imported_packages = []
imported_native_packages = []
for path in occurrences:
try:
self.ipparser.parse(path)
except ValueError:
continue
if self.ipparser.isNative():
imported_native_packages.append(path)
else:
imported_packages.append(path)
self.imported_packages = sorted(imported_packages)
self.imported_native_packages = sorted(imported_native_packages)
# main packages
self.main_packages = map(lambda l: l["filename"], data["data"]["main"]) | [
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| Construct info about a project from artefact
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| 0674c248fe3d8706f98f912996b65af469f96b10 | https://github.com/gofed/gofedlib/blob/0674c248fe3d8706f98f912996b65af469f96b10/gofedlib/go/projectinfo.py#L43-L103 | train |
NiklasRosenstein/py-bundler | bundler/modules.py | ModuleInfo.join_import_from | def join_import_from(self, import_spec):
"""
Joins a relative import like `from .foo import bar` with this module as
its parent module. If the module is not a root module or package root,
it will be joined with the package root.
"""
if not self.isroot and not self.ispkg:
parent = self.name.rpartition('.')[0]
else:
parent = self.name
return join_import_from(import_spec, parent) | python | def join_import_from(self, import_spec):
"""
Joins a relative import like `from .foo import bar` with this module as
its parent module. If the module is not a root module or package root,
it will be joined with the package root.
"""
if not self.isroot and not self.ispkg:
parent = self.name.rpartition('.')[0]
else:
parent = self.name
return join_import_from(import_spec, parent) | [
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| 80dd6dc971667ba015f7f67481417c45cc757231 | https://github.com/NiklasRosenstein/py-bundler/blob/80dd6dc971667ba015f7f67481417c45cc757231/bundler/modules.py#L80-L91 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/status.py | is_tomodir | def is_tomodir(directory):
"""Check if the supplied directory is a tomodir
Parameters
----------
directory: string
Check if the supplied path is a valid tomodir
Returns
-------
is_tomodir: bool
True if the supplied directory is a tomodir directory
"""
if os.path.isdir(directory):
if(os.path.isdir(directory + "/exe") and
os.path.isdir(directory + "/config") and
os.path.isdir(directory + "/rho") and
os.path.isdir(directory + "/inv") and
os.path.isdir(directory + "/mod")):
return True
else:
return False
else:
return False | python | def is_tomodir(directory):
"""Check if the supplied directory is a tomodir
Parameters
----------
directory: string
Check if the supplied path is a valid tomodir
Returns
-------
is_tomodir: bool
True if the supplied directory is a tomodir directory
"""
if os.path.isdir(directory):
if(os.path.isdir(directory + "/exe") and
os.path.isdir(directory + "/config") and
os.path.isdir(directory + "/rho") and
os.path.isdir(directory + "/inv") and
os.path.isdir(directory + "/mod")):
return True
else:
return False
else:
return False | [
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Check if the supplied path is a valid tomodir
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/status.py#L9-L32 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/status.py | td_is_finished | def td_is_finished(tomodir):
"""Return the state of modeling and inversion for a given tomodir. The
result does not take into account sensitivities or potentials, as
optionally generated by CRMod.
Parameters
----------
tomodir: string
Directory to check
Returns
-------
crmod_is_finished: bool
True if a successful CRMod result is contained in the tomodir
directory.
crtomo_is_finished: bool
True if a successful CRTomo inversion results is contained in the
tomodir directory.
"""
if not is_tomodir(tomodir):
raise Exception('Supplied directory is not a tomodir!')
# crmod finished is determined by:
# config.dat/rho.dat/crmod.cfg are present
# volt.dat is present
if(os.path.isfile(tomodir + os.sep + 'config/config.dat') and
os.path.isfile(tomodir + os.sep + 'rho/rho.dat') and
os.path.isfile(tomodir + os.sep + 'grid/elem.dat') and
os.path.isfile(tomodir + os.sep + 'grid/elec.dat') and
os.path.isfile(tomodir + os.sep + 'exe/crmod.cfg') and
os.path.isfile(tomodir + os.sep + 'mod/volt.dat')):
crmod_is_finished = True
else:
crmod_is_finished = False
# crtomo is finished if
# crtomo.cfg/volt.dat/elem.dat/elec.dat are present
# inv/run.ctr contains the word "CPU" in the last line
if(os.path.isfile(tomodir + os.sep + 'grid/elem.dat') and
os.path.isfile(tomodir + os.sep + 'grid/elec.dat') and
os.path.isfile(tomodir + os.sep + 'exe/crtomo.cfg') and
os.path.isfile(tomodir + os.sep + 'inv/inv.ctr') and
os.path.isfile(tomodir + os.sep + 'inv/run.ctr') and
os.path.isfile(tomodir + os.sep + 'mod/volt.dat')):
with open(tomodir + os.sep + 'inv/run.ctr', 'r') as fid:
lines = fid.readlines()
crtomo_is_finished = False
# check the last 5 lines
for line in lines[-5:]:
test_line = line.strip()
regex = re.compile('CPU')
result = regex.match(test_line)
if result is not None:
crtomo_is_finished = True
else:
crtomo_is_finished = False
return crmod_is_finished, crtomo_is_finished | python | def td_is_finished(tomodir):
"""Return the state of modeling and inversion for a given tomodir. The
result does not take into account sensitivities or potentials, as
optionally generated by CRMod.
Parameters
----------
tomodir: string
Directory to check
Returns
-------
crmod_is_finished: bool
True if a successful CRMod result is contained in the tomodir
directory.
crtomo_is_finished: bool
True if a successful CRTomo inversion results is contained in the
tomodir directory.
"""
if not is_tomodir(tomodir):
raise Exception('Supplied directory is not a tomodir!')
# crmod finished is determined by:
# config.dat/rho.dat/crmod.cfg are present
# volt.dat is present
if(os.path.isfile(tomodir + os.sep + 'config/config.dat') and
os.path.isfile(tomodir + os.sep + 'rho/rho.dat') and
os.path.isfile(tomodir + os.sep + 'grid/elem.dat') and
os.path.isfile(tomodir + os.sep + 'grid/elec.dat') and
os.path.isfile(tomodir + os.sep + 'exe/crmod.cfg') and
os.path.isfile(tomodir + os.sep + 'mod/volt.dat')):
crmod_is_finished = True
else:
crmod_is_finished = False
# crtomo is finished if
# crtomo.cfg/volt.dat/elem.dat/elec.dat are present
# inv/run.ctr contains the word "CPU" in the last line
if(os.path.isfile(tomodir + os.sep + 'grid/elem.dat') and
os.path.isfile(tomodir + os.sep + 'grid/elec.dat') and
os.path.isfile(tomodir + os.sep + 'exe/crtomo.cfg') and
os.path.isfile(tomodir + os.sep + 'inv/inv.ctr') and
os.path.isfile(tomodir + os.sep + 'inv/run.ctr') and
os.path.isfile(tomodir + os.sep + 'mod/volt.dat')):
with open(tomodir + os.sep + 'inv/run.ctr', 'r') as fid:
lines = fid.readlines()
crtomo_is_finished = False
# check the last 5 lines
for line in lines[-5:]:
test_line = line.strip()
regex = re.compile('CPU')
result = regex.match(test_line)
if result is not None:
crtomo_is_finished = True
else:
crtomo_is_finished = False
return crmod_is_finished, crtomo_is_finished | [
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Directory to check
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/status.py#L35-L91 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/status.py | is_sipdir | def is_sipdir(directory):
""" Simple check if the supplied directory is a SIP directory.
Parameters
----------
directory: string
Check if the supplied path is a valid SIP directory
Returns
-------
is_sipdir: bool
True if the supplied directory is a SIP directory
"""
is_sipdir = True
if(not os.path.isfile(directory + os.sep + 'frequencies.dat')):
is_sipdir = False
if(not os.path.isdir(directory + os.sep + 'invmod')):
is_sipdir = False
return is_sipdir | python | def is_sipdir(directory):
""" Simple check if the supplied directory is a SIP directory.
Parameters
----------
directory: string
Check if the supplied path is a valid SIP directory
Returns
-------
is_sipdir: bool
True if the supplied directory is a SIP directory
"""
is_sipdir = True
if(not os.path.isfile(directory + os.sep + 'frequencies.dat')):
is_sipdir = False
if(not os.path.isdir(directory + os.sep + 'invmod')):
is_sipdir = False
return is_sipdir | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/status.py#L94-L116 | train |
geophysics-ubonn/crtomo_tools | lib/crtomo/status.py | sipdir_is_finished | def sipdir_is_finished(sipdir):
"""Return the state of modeling and inversion for a given SIP dir. The
result does not take into account sensitivities or potentials, as
optionally generated by CRMod.
Parameters
----------
sipdir: string
Directory to check
Returns
-------
crmod_is_finished: bool
True if all tomodirs of this SIP directory contain finished modeling
results.
crtomo_is_finished: bool
True if all tomodirs of this SIP directory contain finished inversion
results.
"""
if not is_sipdir(sipdir):
raise Exception('Directory is not a valid SIP directory!')
subdirs_raw = sorted(glob.glob(sipdir + os.sep + 'invmod' + os.sep + '*'))
subdirs = [x for x in subdirs_raw if os.path.isdir(x)]
crmod_finished = True
crtomo_finished = True
for subdir in subdirs:
subcrmod, subcrtomo = td_is_finished(subdir)
if not subcrmod:
crmod_finished = False
if not subcrtomo:
crtomo_finished = False
return crmod_finished, crtomo_finished | python | def sipdir_is_finished(sipdir):
"""Return the state of modeling and inversion for a given SIP dir. The
result does not take into account sensitivities or potentials, as
optionally generated by CRMod.
Parameters
----------
sipdir: string
Directory to check
Returns
-------
crmod_is_finished: bool
True if all tomodirs of this SIP directory contain finished modeling
results.
crtomo_is_finished: bool
True if all tomodirs of this SIP directory contain finished inversion
results.
"""
if not is_sipdir(sipdir):
raise Exception('Directory is not a valid SIP directory!')
subdirs_raw = sorted(glob.glob(sipdir + os.sep + 'invmod' + os.sep + '*'))
subdirs = [x for x in subdirs_raw if os.path.isdir(x)]
crmod_finished = True
crtomo_finished = True
for subdir in subdirs:
subcrmod, subcrtomo = td_is_finished(subdir)
if not subcrmod:
crmod_finished = False
if not subcrtomo:
crtomo_finished = False
return crmod_finished, crtomo_finished | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/lib/crtomo/status.py#L119-L154 | train |
redhat-openstack/python-tripleo-helper | tripleohelper/ovb_undercloud.py | OVBUndercloud.enable_neutron_hack | def enable_neutron_hack(self, os_username, os_password, os_project_id, os_auth_url):
"""Enable the neutron hack on the undercloud.
This script will watch the undercloud and copy any relevant network
configuration in the host OpenStack. This is required to avoid the
firewall limitations (no-spoofing and DHCP restriction).
"""
self.yum_install(['python-neutronclient'])
self.send_file(pkg_data_filename('static', 'ovb_fix_neutron_addr'), '/usr/local/bin/ovb_fix_neutron_addr', unix_mode=0o755)
content = """
[Unit]
Description=OVB neutron hack Service
[Service]
ExecStart=/usr/local/bin/ovb_fix_neutron_addr --os-user {os_username} --os-password {os_password} --os-project-id {os_project_id} --os-auth-url {os_auth_url}
User=root
StandardOutput=kmsg+console
StandardError=inherit
Restart=always
[Install]
WantedBy=multi-user.target
"""
unit = 'ovb_fix_neutron_addr.service'
self.create_file(
'/usr/lib/systemd/system/%s' % unit,
content.format(
os_username=os_username,
os_password=protect_password(os_password),
os_project_id=os_project_id,
os_auth_url=os_auth_url))
self.run('systemctl enable %s' % unit)
self.run('systemctl start %s' % unit) | python | def enable_neutron_hack(self, os_username, os_password, os_project_id, os_auth_url):
"""Enable the neutron hack on the undercloud.
This script will watch the undercloud and copy any relevant network
configuration in the host OpenStack. This is required to avoid the
firewall limitations (no-spoofing and DHCP restriction).
"""
self.yum_install(['python-neutronclient'])
self.send_file(pkg_data_filename('static', 'ovb_fix_neutron_addr'), '/usr/local/bin/ovb_fix_neutron_addr', unix_mode=0o755)
content = """
[Unit]
Description=OVB neutron hack Service
[Service]
ExecStart=/usr/local/bin/ovb_fix_neutron_addr --os-user {os_username} --os-password {os_password} --os-project-id {os_project_id} --os-auth-url {os_auth_url}
User=root
StandardOutput=kmsg+console
StandardError=inherit
Restart=always
[Install]
WantedBy=multi-user.target
"""
unit = 'ovb_fix_neutron_addr.service'
self.create_file(
'/usr/lib/systemd/system/%s' % unit,
content.format(
os_username=os_username,
os_password=protect_password(os_password),
os_project_id=os_project_id,
os_auth_url=os_auth_url))
self.run('systemctl enable %s' % unit)
self.run('systemctl start %s' % unit) | [
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| bfa165538335edb1088170c7a92f097167225c81 | https://github.com/redhat-openstack/python-tripleo-helper/blob/bfa165538335edb1088170c7a92f097167225c81/tripleohelper/ovb_undercloud.py#L96-L126 | train |
redhat-openstack/python-tripleo-helper | tripleohelper/ovb_undercloud.py | OVBUndercloud.patch_ironic_ramdisk | def patch_ironic_ramdisk(self):
"""Clean the disk before flushing the new image.
See: https://bugs.launchpad.net/ironic-lib/+bug/1550604
"""
tmpdir = self.run('mktemp -d')[0].rstrip('\n')
self.run('cd {tmpdir}; zcat /home/stack/ironic-python-agent.initramfs| cpio -id'.format(tmpdir=tmpdir))
self.send_file(pkg_data_filename('static', 'ironic-wipefs.patch'), '/tmp/ironic-wipefs.patch')
self.run('cd {tmpdir}; patch -p0 < /tmp/ironic-wipefs.patch'.format(tmpdir=tmpdir))
self.run('cd {tmpdir}; find . | cpio --create --format=newc > /home/stack/ironic-python-agent.initramfs'.format(tmpdir=tmpdir)) | python | def patch_ironic_ramdisk(self):
"""Clean the disk before flushing the new image.
See: https://bugs.launchpad.net/ironic-lib/+bug/1550604
"""
tmpdir = self.run('mktemp -d')[0].rstrip('\n')
self.run('cd {tmpdir}; zcat /home/stack/ironic-python-agent.initramfs| cpio -id'.format(tmpdir=tmpdir))
self.send_file(pkg_data_filename('static', 'ironic-wipefs.patch'), '/tmp/ironic-wipefs.patch')
self.run('cd {tmpdir}; patch -p0 < /tmp/ironic-wipefs.patch'.format(tmpdir=tmpdir))
self.run('cd {tmpdir}; find . | cpio --create --format=newc > /home/stack/ironic-python-agent.initramfs'.format(tmpdir=tmpdir)) | [
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| bfa165538335edb1088170c7a92f097167225c81 | https://github.com/redhat-openstack/python-tripleo-helper/blob/bfa165538335edb1088170c7a92f097167225c81/tripleohelper/ovb_undercloud.py#L128-L137 | train |
elifiner/termenu | termenu/menu.py | show_menu | def show_menu(title, options, default=None, height=None, width=None, multiselect=False, precolored=False):
"""
Shows an interactive menu in the terminal.
Arguments:
options: list of menu options
default: initial option to highlight
height: maximum height of the menu
width: maximum width of the menu
multiselect: allow multiple items to be selected?
precolored: allow strings with embedded ANSI commands
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* If an option is a 2-tuple, the first item will be displayed and the
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* If menu is cancelled (Esc pressed), returns None.
*
Notes:
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"""
plugins = [FilterPlugin()]
if any(isinstance(opt, OptionGroup) for opt in options):
plugins.append(OptionGroupPlugin())
if title:
plugins.append(TitlePlugin(title))
if precolored:
plugins.append(PrecoloredPlugin())
menu = Termenu(options, default=default, height=height,
width=width, multiselect=multiselect, plugins=plugins)
return menu.show() | python | def show_menu(title, options, default=None, height=None, width=None, multiselect=False, precolored=False):
"""
Shows an interactive menu in the terminal.
Arguments:
options: list of menu options
default: initial option to highlight
height: maximum height of the menu
width: maximum width of the menu
multiselect: allow multiple items to be selected?
precolored: allow strings with embedded ANSI commands
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* If an option is a 2-tuple, the first item will be displayed and the
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* If menu is cancelled (Esc pressed), returns None.
*
Notes:
* You can pass OptionGroup objects to `options` to create sub-headers
in the menu.
"""
plugins = [FilterPlugin()]
if any(isinstance(opt, OptionGroup) for opt in options):
plugins.append(OptionGroupPlugin())
if title:
plugins.append(TitlePlugin(title))
if precolored:
plugins.append(PrecoloredPlugin())
menu = Termenu(options, default=default, height=height,
width=width, multiselect=multiselect, plugins=plugins)
return menu.show() | [
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| a7a57a1b07d8451003ee750704cdf0d904e9e272 | https://github.com/elifiner/termenu/blob/a7a57a1b07d8451003ee750704cdf0d904e9e272/termenu/menu.py#L6-L39 | train |
elifiner/termenu | termenu/menu.py | pluggable | def pluggable(method):
"""
Mark a class method as extendable with plugins.
"""
def wrapped(self, *args, **kwargs):
if hasattr(self, "_plugins"):
# call the last plugin, it may call the previous via self.parent.method
# creating a call call chain
return getattr(self._plugins[-1], method.__name__)(*args, **kwargs)
else:
return method(self, *args, **kwargs)
wrapped.original = method
return wrapped | python | def pluggable(method):
"""
Mark a class method as extendable with plugins.
"""
def wrapped(self, *args, **kwargs):
if hasattr(self, "_plugins"):
# call the last plugin, it may call the previous via self.parent.method
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elifiner/termenu | termenu/menu.py | register_plugin | def register_plugin(host, plugin):
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host._plugins.append(plugin) | python | def register_plugin(host, plugin):
"""
Register a plugin with a host object. Some @pluggable methods in the host
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"""
class OriginalMethods(object):
def __getattr__(self, name):
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NikolayDachev/jadm | lib/paramiko-1.14.1/paramiko/sftp_client.py | SFTPClient.chdir | def chdir(self, path=None):
"""
Change the "current directory" of this SFTP session. Since SFTP
doesn't really have the concept of a current working directory, this is
emulated by Paramiko. Once you use this method to set a working
directory, all operations on this `.SFTPClient` object will be relative
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:param str path: new current working directory
:raises IOError: if the requested path doesn't exist on the server
.. versionadded:: 1.4
"""
if path is None:
self._cwd = None
return
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raise SFTPError(errno.ENOTDIR, "%s: %s" % (os.strerror(errno.ENOTDIR), path))
self._cwd = b(self.normalize(path)) | python | def chdir(self, path=None):
"""
Change the "current directory" of this SFTP session. Since SFTP
doesn't really have the concept of a current working directory, this is
emulated by Paramiko. Once you use this method to set a working
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:param str path: new current working directory
:raises IOError: if the requested path doesn't exist on the server
.. versionadded:: 1.4
"""
if path is None:
self._cwd = None
return
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:param str path: new current working directory
:raises IOError: if the requested path doesn't exist on the server
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| 12bb550445edfcd87506f7cba7a6a35d413c5511 | https://github.com/NikolayDachev/jadm/blob/12bb550445edfcd87506f7cba7a6a35d413c5511/lib/paramiko-1.14.1/paramiko/sftp_client.py#L480-L500 | train |
NikolayDachev/jadm | lib/paramiko-1.14.1/paramiko/message.py | Message.get_int | def get_int(self):
"""
Fetch an int from the stream.
:return: a 32-bit unsigned `int`.
"""
byte = self.get_bytes(1)
if byte == max_byte:
return util.inflate_long(self.get_binary())
byte += self.get_bytes(3)
return struct.unpack('>I', byte)[0] | python | def get_int(self):
"""
Fetch an int from the stream.
:return: a 32-bit unsigned `int`.
"""
byte = self.get_bytes(1)
if byte == max_byte:
return util.inflate_long(self.get_binary())
byte += self.get_bytes(3)
return struct.unpack('>I', byte)[0] | [
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| 12bb550445edfcd87506f7cba7a6a35d413c5511 | https://github.com/NikolayDachev/jadm/blob/12bb550445edfcd87506f7cba7a6a35d413c5511/lib/paramiko-1.14.1/paramiko/message.py#L132-L142 | train |
reorx/torext | torext/log.py | set_logger | def set_logger(name,
level='INFO',
fmt=None,
datefmt=None,
propagate=1,
remove_handlers=False):
"""
This function will clear the previous handlers and set only one handler,
which will only be StreamHandler for the logger.
This function is designed to be able to called multiple times in a context.
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"""
logger = logging.getLogger(name)
logger.setLevel(getattr(logging, level))
logger.propagate = propagate
if remove_handlers:
logger.handlers = []
return
handler = None
for h in logger.handlers:
if isinstance(h, logging.StreamHandler):
# use existing instead of clean and create
handler = h
break
if not handler:
handler = logging.StreamHandler()
logger.addHandler(handler)
formatter_kwgs = {}
for i in ('fmt', 'datefmt'):
if locals()[i] is not None:
formatter_kwgs[i] = locals()[i]
handler.setFormatter(BaseFormatter(**formatter_kwgs)) | python | def set_logger(name,
level='INFO',
fmt=None,
datefmt=None,
propagate=1,
remove_handlers=False):
"""
This function will clear the previous handlers and set only one handler,
which will only be StreamHandler for the logger.
This function is designed to be able to called multiple times in a context.
Note that if a logger has no handlers, it will be added a handler automatically when it is used.
"""
logger = logging.getLogger(name)
logger.setLevel(getattr(logging, level))
logger.propagate = propagate
if remove_handlers:
logger.handlers = []
return
handler = None
for h in logger.handlers:
if isinstance(h, logging.StreamHandler):
# use existing instead of clean and create
handler = h
break
if not handler:
handler = logging.StreamHandler()
logger.addHandler(handler)
formatter_kwgs = {}
for i in ('fmt', 'datefmt'):
if locals()[i] is not None:
formatter_kwgs[i] = locals()[i]
handler.setFormatter(BaseFormatter(**formatter_kwgs)) | [
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| 84c4300ebc7fab0dbd11cf8b020bc7d4d1570171 | https://github.com/reorx/torext/blob/84c4300ebc7fab0dbd11cf8b020bc7d4d1570171/torext/log.py#L152-L188 | train |
reorx/torext | torext/log.py | BaseFormatter.format | def format(self, record):
"""
return log in unicode
"""
self._format_record(record)
record_dict = {}
for k, v in record.__dict__.items():
if isinstance(k, str):
k = decode_(k, 'utf8')
if isinstance(v, str):
v = decode_(v, 'utf8', 'replace')
record_dict[k] = v
if 'color' in self.fmt or 'end_color' in self.fmt:
record_dict['color'], record_dict['end_color'] = _color(record.levelno)
log = self.ufmt % record_dict
if record.exc_text:
if log[-1:] != '\n':
log += '\n'
log += decode_(record.exc_text, 'utf8', 'replace')
log = log.replace('\n', '\n' + self.tab)
return log | python | def format(self, record):
"""
return log in unicode
"""
self._format_record(record)
record_dict = {}
for k, v in record.__dict__.items():
if isinstance(k, str):
k = decode_(k, 'utf8')
if isinstance(v, str):
v = decode_(v, 'utf8', 'replace')
record_dict[k] = v
if 'color' in self.fmt or 'end_color' in self.fmt:
record_dict['color'], record_dict['end_color'] = _color(record.levelno)
log = self.ufmt % record_dict
if record.exc_text:
if log[-1:] != '\n':
log += '\n'
log += decode_(record.exc_text, 'utf8', 'replace')
log = log.replace('\n', '\n' + self.tab)
return log | [
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| 84c4300ebc7fab0dbd11cf8b020bc7d4d1570171 | https://github.com/reorx/torext/blob/84c4300ebc7fab0dbd11cf8b020bc7d4d1570171/torext/log.py#L108-L134 | train |
Riminder/python-riminder-api | riminder/profile.py | Profile.list | def list(self, source_ids=None, seniority="all", stage=None,
date_start="1494539999", date_end=TIMESTAMP_NOW, filter_id=None,
page=1, limit=30, sort_by='ranking', filter_reference=None, order_by=None):
"""
Retreive all profiles that match the query param.
Args:
date_end: <string> REQUIRED (default to timestamp of now)
profiles' last date of reception
date_start: <string> REQUIRED (default to "1494539999")
profiles' first date of reception
filter_id: <string>
limit: <int> (default to 30)
number of fetched profiles/page
page: <int> REQUIRED default to 1
number of the page associated to the pagination
seniority: <string> defaut to "all"
profiles' seniority ("all", "senior", "junior")
sort_by: <string>
source_ids: <array of strings> REQUIRED
stage: <string>
Returns
Retrieve the profiles data as <dict>
"""
query_params = {}
query_params["date_end"] = _validate_timestamp(date_end, "date_end")
query_params["date_start"] = _validate_timestamp(date_start, "date_start")
if filter_id:
query_params["filter_id"] = _validate_filter_id(filter_id)
if filter_reference:
query_params["filter_reference"] = _validate_filter_reference(filter_reference)
query_params["limit"] = _validate_limit(limit)
query_params["page"] = _validate_page(page)
query_params["seniority"] = _validate_seniority(seniority)
query_params["sort_by"] = _validate_sort_by(sort_by)
query_params["source_ids"] = json.dumps(_validate_source_ids(source_ids))
query_params["stage"] = _validate_stage(stage)
query_params["order_by"] = order_by
response = self.client.get("profiles", query_params)
return response.json() | python | def list(self, source_ids=None, seniority="all", stage=None,
date_start="1494539999", date_end=TIMESTAMP_NOW, filter_id=None,
page=1, limit=30, sort_by='ranking', filter_reference=None, order_by=None):
"""
Retreive all profiles that match the query param.
Args:
date_end: <string> REQUIRED (default to timestamp of now)
profiles' last date of reception
date_start: <string> REQUIRED (default to "1494539999")
profiles' first date of reception
filter_id: <string>
limit: <int> (default to 30)
number of fetched profiles/page
page: <int> REQUIRED default to 1
number of the page associated to the pagination
seniority: <string> defaut to "all"
profiles' seniority ("all", "senior", "junior")
sort_by: <string>
source_ids: <array of strings> REQUIRED
stage: <string>
Returns
Retrieve the profiles data as <dict>
"""
query_params = {}
query_params["date_end"] = _validate_timestamp(date_end, "date_end")
query_params["date_start"] = _validate_timestamp(date_start, "date_start")
if filter_id:
query_params["filter_id"] = _validate_filter_id(filter_id)
if filter_reference:
query_params["filter_reference"] = _validate_filter_reference(filter_reference)
query_params["limit"] = _validate_limit(limit)
query_params["page"] = _validate_page(page)
query_params["seniority"] = _validate_seniority(seniority)
query_params["sort_by"] = _validate_sort_by(sort_by)
query_params["source_ids"] = json.dumps(_validate_source_ids(source_ids))
query_params["stage"] = _validate_stage(stage)
query_params["order_by"] = order_by
response = self.client.get("profiles", query_params)
return response.json() | [
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profiles' last date of reception
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profiles' first date of reception
filter_id: <string>
limit: <int> (default to 30)
number of fetched profiles/page
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number of the page associated to the pagination
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| 01279f0ece08cf3d1dd45f76de6d9edf7fafec90 | https://github.com/Riminder/python-riminder-api/blob/01279f0ece08cf3d1dd45f76de6d9edf7fafec90/riminder/profile.py#L68-L110 | train |
Riminder/python-riminder-api | riminder/profile.py | Profile.add | def add(self, source_id=None, file_path=None, profile_reference="",
timestamp_reception=None, training_metadata=[]):
"""
Add a profile resume to a sourced id.
Args:
source_id: <string>
source id
file_path: <string>
local path to resume file
profile_reference: <string> (default to "")
reference to assign to the profile
timestamp_reception: <string>
original date of the application of the profile
Returns
Response that contains code 201 if successful
Other status codes otherwise.
"""
data = {}
data["source_id"] = _validate_source_id(source_id)
data["profile_reference"] = _validate_profile_reference(profile_reference)
data["timestamp_reception"] = _validate_timestamp(timestamp_reception, "timestamp_reception")
data["training_metadata"] = _validate_training_metadata(training_metadata)
files = _get_file_metadata(file_path, profile_reference)
response = None
with open(file_path, 'rb') as in_file:
files = (files[0], in_file, files[2])
response = self.client.post("profile", data=data, files={"file": files})
return response.json() | python | def add(self, source_id=None, file_path=None, profile_reference="",
timestamp_reception=None, training_metadata=[]):
"""
Add a profile resume to a sourced id.
Args:
source_id: <string>
source id
file_path: <string>
local path to resume file
profile_reference: <string> (default to "")
reference to assign to the profile
timestamp_reception: <string>
original date of the application of the profile
Returns
Response that contains code 201 if successful
Other status codes otherwise.
"""
data = {}
data["source_id"] = _validate_source_id(source_id)
data["profile_reference"] = _validate_profile_reference(profile_reference)
data["timestamp_reception"] = _validate_timestamp(timestamp_reception, "timestamp_reception")
data["training_metadata"] = _validate_training_metadata(training_metadata)
files = _get_file_metadata(file_path, profile_reference)
response = None
with open(file_path, 'rb') as in_file:
files = (files[0], in_file, files[2])
response = self.client.post("profile", data=data, files={"file": files})
return response.json() | [
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| Add a profile resume to a sourced id.
Args:
source_id: <string>
source id
file_path: <string>
local path to resume file
profile_reference: <string> (default to "")
reference to assign to the profile
timestamp_reception: <string>
original date of the application of the profile
Returns
Response that contains code 201 if successful
Other status codes otherwise. | [
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| 01279f0ece08cf3d1dd45f76de6d9edf7fafec90 | https://github.com/Riminder/python-riminder-api/blob/01279f0ece08cf3d1dd45f76de6d9edf7fafec90/riminder/profile.py#L112-L142 | train |
Riminder/python-riminder-api | riminder/profile.py | Profile.addList | def addList(self, source_id, dir_path, is_recurcive=False, timestamp_reception=None, training_metadata=[]):
"""Add all profile from a given directory."""
if not path.isdir(dir_path):
raise ValueError(dir_path + ' is not a directory')
files_to_send = _get_files_from_dir(dir_path, is_recurcive)
succeed_upload = {}
failed_upload = {}
for file_path in files_to_send:
try:
resp = self.add(source_id=source_id,
file_path=file_path, profile_reference="",
timestamp_reception=timestamp_reception, training_metadata=training_metadata)
if resp['code'] != 200 and resp['code'] != 201:
failed_upload[file_path] = ValueError('Invalid response: ' + str(resp))
else:
succeed_upload[file_path] = resp
except BaseException as e:
failed_upload[file_path] = e
result = {
'success': succeed_upload,
'fail': failed_upload
}
return result | python | def addList(self, source_id, dir_path, is_recurcive=False, timestamp_reception=None, training_metadata=[]):
"""Add all profile from a given directory."""
if not path.isdir(dir_path):
raise ValueError(dir_path + ' is not a directory')
files_to_send = _get_files_from_dir(dir_path, is_recurcive)
succeed_upload = {}
failed_upload = {}
for file_path in files_to_send:
try:
resp = self.add(source_id=source_id,
file_path=file_path, profile_reference="",
timestamp_reception=timestamp_reception, training_metadata=training_metadata)
if resp['code'] != 200 and resp['code'] != 201:
failed_upload[file_path] = ValueError('Invalid response: ' + str(resp))
else:
succeed_upload[file_path] = resp
except BaseException as e:
failed_upload[file_path] = e
result = {
'success': succeed_upload,
'fail': failed_upload
}
return result | [
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| 01279f0ece08cf3d1dd45f76de6d9edf7fafec90 | https://github.com/Riminder/python-riminder-api/blob/01279f0ece08cf3d1dd45f76de6d9edf7fafec90/riminder/profile.py#L144-L166 | train |
Riminder/python-riminder-api | riminder/profile.py | Profile.get | def get(self, source_id=None, profile_id=None, profile_reference=None):
"""
Retrieve the profile information associated with profile id.
Args:
source_id: <string>
source id
profile_id: <string>
profile id
Returns
profile information
"""
query_params = {}
query_params["source_id"] = _validate_source_id(source_id)
if profile_id:
query_params["profile_id"] = _validate_profile_id(profile_id)
if profile_reference:
query_params["profile_reference"] = _validate_profile_reference(profile_reference)
response = self.client.get('profile', query_params)
return response.json() | python | def get(self, source_id=None, profile_id=None, profile_reference=None):
"""
Retrieve the profile information associated with profile id.
Args:
source_id: <string>
source id
profile_id: <string>
profile id
Returns
profile information
"""
query_params = {}
query_params["source_id"] = _validate_source_id(source_id)
if profile_id:
query_params["profile_id"] = _validate_profile_id(profile_id)
if profile_reference:
query_params["profile_reference"] = _validate_profile_reference(profile_reference)
response = self.client.get('profile', query_params)
return response.json() | [
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Args:
source_id: <string>
source id
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profile id
Returns
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| 01279f0ece08cf3d1dd45f76de6d9edf7fafec90 | https://github.com/Riminder/python-riminder-api/blob/01279f0ece08cf3d1dd45f76de6d9edf7fafec90/riminder/profile.py#L168-L189 | train |
Riminder/python-riminder-api | riminder/profile.py | ProfileStage.set | def set(self, source_id=None, profile_id=None, filter_id=None, stage=None, profile_reference=None, filter_reference=None):
"""
Edit the profile stage given a filter.
Args:
profile_id: <string>
profile id
body params:
source_id: <string>
source id associated to the profile
filter_id: <string>
filter id
stage: <string>
profiles' stage associated to the filter ( null for all, NEW, YES, LATER or NO).
Returns
Response that contains code 201 if successful
Other status codes otherwise.
"""
data = {}
data["source_id"] = _validate_source_id(source_id)
if profile_id:
data["profile_id"] = _validate_profile_id(profile_id)
if filter_id:
data["filter_id"] = _validate_filter_id(filter_id)
if profile_reference:
data["profile_reference"] = _validate_profile_reference(profile_reference)
if filter_reference:
data["filter_reference"] = _validate_filter_reference(filter_reference)
data["stage"] = _validate_stage(stage)
response = self.client.patch('profile/stage', data=data)
return response.json() | python | def set(self, source_id=None, profile_id=None, filter_id=None, stage=None, profile_reference=None, filter_reference=None):
"""
Edit the profile stage given a filter.
Args:
profile_id: <string>
profile id
body params:
source_id: <string>
source id associated to the profile
filter_id: <string>
filter id
stage: <string>
profiles' stage associated to the filter ( null for all, NEW, YES, LATER or NO).
Returns
Response that contains code 201 if successful
Other status codes otherwise.
"""
data = {}
data["source_id"] = _validate_source_id(source_id)
if profile_id:
data["profile_id"] = _validate_profile_id(profile_id)
if filter_id:
data["filter_id"] = _validate_filter_id(filter_id)
if profile_reference:
data["profile_reference"] = _validate_profile_reference(profile_reference)
if filter_reference:
data["filter_reference"] = _validate_filter_reference(filter_reference)
data["stage"] = _validate_stage(stage)
response = self.client.patch('profile/stage', data=data)
return response.json() | [
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Args:
profile_id: <string>
profile id
body params:
source_id: <string>
source id associated to the profile
filter_id: <string>
filter id
stage: <string>
profiles' stage associated to the filter ( null for all, NEW, YES, LATER or NO).
Returns
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Other status codes otherwise. | [
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| 01279f0ece08cf3d1dd45f76de6d9edf7fafec90 | https://github.com/Riminder/python-riminder-api/blob/01279f0ece08cf3d1dd45f76de6d9edf7fafec90/riminder/profile.py#L292-L326 | train |
Riminder/python-riminder-api | riminder/profile.py | ProfileRevealing.get | def get(self, source_id=None, profile_id=None, profile_reference=None, filter_id=None, filter_reference=None):
"""
Retrieve the interpretability information.
Args:
source_id: <string>
source id
profile_id: <string>
profile id
filter_id: <string>
filter id
Returns
interpretability information
"""
query_params = {}
query_params["source_id"] = _validate_source_id(source_id)
if profile_id:
query_params["profile_id"] = _validate_profile_id(profile_id)
if profile_reference:
query_params["profile_reference"] = _validate_profile_reference(profile_reference)
if filter_id:
query_params["filter_id"] = _validate_filter_id(filter_id)
if filter_reference:
query_params["filter_reference"] = _validate_filter_reference(filter_reference)
response = self.client.get('profile/revealing', query_params)
return response | python | def get(self, source_id=None, profile_id=None, profile_reference=None, filter_id=None, filter_reference=None):
"""
Retrieve the interpretability information.
Args:
source_id: <string>
source id
profile_id: <string>
profile id
filter_id: <string>
filter id
Returns
interpretability information
"""
query_params = {}
query_params["source_id"] = _validate_source_id(source_id)
if profile_id:
query_params["profile_id"] = _validate_profile_id(profile_id)
if profile_reference:
query_params["profile_reference"] = _validate_profile_reference(profile_reference)
if filter_id:
query_params["filter_id"] = _validate_filter_id(filter_id)
if filter_reference:
query_params["filter_reference"] = _validate_filter_reference(filter_reference)
response = self.client.get('profile/revealing', query_params)
return response | [
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filter id
Returns
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| 01279f0ece08cf3d1dd45f76de6d9edf7fafec90 | https://github.com/Riminder/python-riminder-api/blob/01279f0ece08cf3d1dd45f76de6d9edf7fafec90/riminder/profile.py#L380-L407 | train |
Riminder/python-riminder-api | riminder/profile.py | ProfileJson.check | def check(self, profile_data, training_metadata=[]):
"""Use the api to check weither the profile_data are valid."""
data = {
"profile_json": _validate_dict(profile_data, "profile_data"),
"training_metadata": _validate_training_metadata(training_metadata),
}
response = self.client.post("profile/json/check", data=data)
return response.json() | python | def check(self, profile_data, training_metadata=[]):
"""Use the api to check weither the profile_data are valid."""
data = {
"profile_json": _validate_dict(profile_data, "profile_data"),
"training_metadata": _validate_training_metadata(training_metadata),
}
response = self.client.post("profile/json/check", data=data)
return response.json() | [
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| 01279f0ece08cf3d1dd45f76de6d9edf7fafec90 | https://github.com/Riminder/python-riminder-api/blob/01279f0ece08cf3d1dd45f76de6d9edf7fafec90/riminder/profile.py#L417-L424 | train |
Riminder/python-riminder-api | riminder/profile.py | ProfileJson.add | def add(self, source_id, profile_data, training_metadata=[], profile_reference=None, timestamp_reception=None):
"""Use the api to add a new profile using profile_data."""
data = {
"source_id": _validate_source_id(source_id),
"profile_json": _validate_dict(profile_data, "profile_data"),
"training_metadata": _validate_training_metadata(training_metadata),
"profile_reference": profile_reference
}
# some enrichement for profile_json
if timestamp_reception is not None:
data['timestamp_reception'] = _validate_timestamp(timestamp_reception, 'timestamp_reception')
response = self.client.post("profile/json", data=data)
return response.json() | python | def add(self, source_id, profile_data, training_metadata=[], profile_reference=None, timestamp_reception=None):
"""Use the api to add a new profile using profile_data."""
data = {
"source_id": _validate_source_id(source_id),
"profile_json": _validate_dict(profile_data, "profile_data"),
"training_metadata": _validate_training_metadata(training_metadata),
"profile_reference": profile_reference
}
# some enrichement for profile_json
if timestamp_reception is not None:
data['timestamp_reception'] = _validate_timestamp(timestamp_reception, 'timestamp_reception')
response = self.client.post("profile/json", data=data)
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| 01279f0ece08cf3d1dd45f76de6d9edf7fafec90 | https://github.com/Riminder/python-riminder-api/blob/01279f0ece08cf3d1dd45f76de6d9edf7fafec90/riminder/profile.py#L426-L440 | train |
kwlzn/blast | blast/scanner.py | DirScanner.md5sum | def md5sum(self, f):
''' md5sums a file, returning the hex digest
Parameters:
- f filename string
'''
m = hashlib.md5()
fh = open(f, 'r')
while 1:
chunk = fh.read(BUF_SIZE)
if not chunk: break
m.update(chunk)
fh.close()
return m.hexdigest() | python | def md5sum(self, f):
''' md5sums a file, returning the hex digest
Parameters:
- f filename string
'''
m = hashlib.md5()
fh = open(f, 'r')
while 1:
chunk = fh.read(BUF_SIZE)
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fh.close()
return m.hexdigest() | [
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kwlzn/blast | blast/scanner.py | DirScanner.iterdupes | def iterdupes(self, compare=None, filt=None):
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'''
if not compare: compare = self.md5sum
seen_siz = {} ## store size -> first seen filename
seen_sum = {} ## store chksum -> first seen filename
size_func = lambda x: os.stat(x).st_size
for (fsize, f) in self.iteritems(want_dirs=False, func=size_func, filt=filt):
if fsize not in seen_siz: ## state 1: no previous size collisions
seen_siz[fsize] = f
continue
else:
if seen_siz[fsize]: ## state 2: defined key => str (initial, unscanned path)
chksum = compare(seen_siz[fsize])
if chksum in seen_sum: yield (chksum, seen_siz[fsize])
else: seen_sum[chksum] = seen_siz[fsize]
seen_siz[fsize] = None
## state 3: defined key => None (already scanned path, no-op)
chksum = compare(f)
if chksum in seen_sum:
## if it's a dupe, check if the first one was ever yielded then yield
if seen_sum[chksum]:
yield (chksum, seen_sum[chksum])
seen_sum[chksum] = None
yield (chksum, f)
else:
## if not, set the initial filename
seen_sum[chksum] = f | python | def iterdupes(self, compare=None, filt=None):
''' streaming item iterator with low overhead duplicate file detection
Parameters:
- compare compare function between files (defaults to md5sum)
'''
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seen_sum = {} ## store chksum -> first seen filename
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if fsize not in seen_siz: ## state 1: no previous size collisions
seen_siz[fsize] = f
continue
else:
if seen_siz[fsize]: ## state 2: defined key => str (initial, unscanned path)
chksum = compare(seen_siz[fsize])
if chksum in seen_sum: yield (chksum, seen_siz[fsize])
else: seen_sum[chksum] = seen_siz[fsize]
seen_siz[fsize] = None
## state 3: defined key => None (already scanned path, no-op)
chksum = compare(f)
if chksum in seen_sum:
## if it's a dupe, check if the first one was ever yielded then yield
if seen_sum[chksum]:
yield (chksum, seen_sum[chksum])
seen_sum[chksum] = None
yield (chksum, f)
else:
## if not, set the initial filename
seen_sum[chksum] = f | [
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| ae18a19182a6884c453bf9b2a3c6386bd3b2655a | https://github.com/kwlzn/blast/blob/ae18a19182a6884c453bf9b2a3c6386bd3b2655a/blast/scanner.py#L71-L102 | train |
gebn/wood | wood/integrations/s3.py | objects_to_root | def objects_to_root(objects: List) -> Root:
"""
Convert a list of s3 ObjectSummaries into a directory tree.
:param objects: The list of objects, e.g. the result of calling
`.objects.all()` on a bucket.
:return: The tree structure, contained within a root node.
"""
def _to_tree(objs: Iterable) -> Dict:
"""
Build a tree structure from a flat list of objects.
:param objs: The raw iterable of S3 `ObjectSummary`s, as returned by a
bucket listing.
:return: The listing as a nested dictionary where keys are directory
and file names. The values of directories will in turn be a
dict. The values of keys representing files will be the
`ObjectSummary` instance.
"""
path_tree = {}
for obj in objs:
is_dir = obj.key.endswith('/')
chunks = [chunk for chunk in obj.key.split('/') if chunk]
chunk_count = len(chunks)
tmp = path_tree
for i, chunk in enumerate(chunks):
is_last_chunk = i == chunk_count - 1
if is_last_chunk and not is_dir:
tmp[chunk] = obj
else:
# must be a directory
if chunk not in tmp:
# it doesn't exist - create it
tmp[chunk] = {}
tmp = tmp[chunk]
return path_tree
def _to_entity(key: str, value: Union[Dict, Any]) -> Entity:
"""
Turn a nested dictionary representing an S3 bucket into the correct
`Entity` object.
:param key: The name of the entity.
:param value: If the entity is a directory, the nested dict
representing its contents. Otherwise, the `ObjectSummary`
instance representing the file.
:return: The entity representing the entity name and value pair.
"""
if isinstance(value, dict):
return Directory(
key,
{key_: _to_entity(key_, value_)
for key_, value_ in value.items()})
return File(pathlib.PurePath(value.key).name, value.size,
value.e_tag.strip('"'))
tree = _to_tree(objects)
return Root({pathlib.PurePath(key).name: _to_entity(key, value)
for key, value in tree.items()}) | python | def objects_to_root(objects: List) -> Root:
"""
Convert a list of s3 ObjectSummaries into a directory tree.
:param objects: The list of objects, e.g. the result of calling
`.objects.all()` on a bucket.
:return: The tree structure, contained within a root node.
"""
def _to_tree(objs: Iterable) -> Dict:
"""
Build a tree structure from a flat list of objects.
:param objs: The raw iterable of S3 `ObjectSummary`s, as returned by a
bucket listing.
:return: The listing as a nested dictionary where keys are directory
and file names. The values of directories will in turn be a
dict. The values of keys representing files will be the
`ObjectSummary` instance.
"""
path_tree = {}
for obj in objs:
is_dir = obj.key.endswith('/')
chunks = [chunk for chunk in obj.key.split('/') if chunk]
chunk_count = len(chunks)
tmp = path_tree
for i, chunk in enumerate(chunks):
is_last_chunk = i == chunk_count - 1
if is_last_chunk and not is_dir:
tmp[chunk] = obj
else:
# must be a directory
if chunk not in tmp:
# it doesn't exist - create it
tmp[chunk] = {}
tmp = tmp[chunk]
return path_tree
def _to_entity(key: str, value: Union[Dict, Any]) -> Entity:
"""
Turn a nested dictionary representing an S3 bucket into the correct
`Entity` object.
:param key: The name of the entity.
:param value: If the entity is a directory, the nested dict
representing its contents. Otherwise, the `ObjectSummary`
instance representing the file.
:return: The entity representing the entity name and value pair.
"""
if isinstance(value, dict):
return Directory(
key,
{key_: _to_entity(key_, value_)
for key_, value_ in value.items()})
return File(pathlib.PurePath(value.key).name, value.size,
value.e_tag.strip('"'))
tree = _to_tree(objects)
return Root({pathlib.PurePath(key).name: _to_entity(key, value)
for key, value in tree.items()}) | [
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| efc71879890dbd2f2d7a0b1a65ed22a0843139dd | https://github.com/gebn/wood/blob/efc71879890dbd2f2d7a0b1a65ed22a0843139dd/wood/integrations/s3.py#L16-L77 | train |
gebn/wood | wood/integrations/s3.py | Syncer._delete | def _delete(self, paths: Iterable[str]) -> None:
"""
Delete a collection of paths from S3.
:param paths: The paths to delete. The prefix will be prepended to each
one.
:raises ClientError: If any request fails.
"""
for chunk in util.chunk(paths, self._MAX_DELETES_PER_REQUEST):
keys = list([self._prefix + key for key in chunk])
logger.info('Deleting %d objects (%s)', len(keys), ', '.join(keys))
response = self._bucket.delete_objects(Delete={
'Objects': [{'Key': key} for key in keys],
'Quiet': True
})
logger.debug('Delete objects response: %s', response) | python | def _delete(self, paths: Iterable[str]) -> None:
"""
Delete a collection of paths from S3.
:param paths: The paths to delete. The prefix will be prepended to each
one.
:raises ClientError: If any request fails.
"""
for chunk in util.chunk(paths, self._MAX_DELETES_PER_REQUEST):
keys = list([self._prefix + key for key in chunk])
logger.info('Deleting %d objects (%s)', len(keys), ', '.join(keys))
response = self._bucket.delete_objects(Delete={
'Objects': [{'Key': key} for key in keys],
'Quiet': True
})
logger.debug('Delete objects response: %s', response) | [
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| efc71879890dbd2f2d7a0b1a65ed22a0843139dd | https://github.com/gebn/wood/blob/efc71879890dbd2f2d7a0b1a65ed22a0843139dd/wood/integrations/s3.py#L101-L116 | train |
gebn/wood | wood/integrations/s3.py | Syncer._upload | def _upload(self, items: Iterable[Tuple[str, str]]) -> None:
"""
Upload a collection of paths to S3.
:param items: An iterable of pairs containing the local path of the
file to upload, and the remote path to upload it to. The
prefix will be appended to each remote path.
"""
for src, key in items:
logger.info(f'Uploading {src} to {key}')
mimetype, _ = mimetypes.guess_type(src)
if mimetype is None:
logger.warning(f'Could not guess MIME type for {src}')
mimetype = 'application/octet-stream'
logger.debug(f'Deduced MIME type: {mimetype}')
self._bucket.upload_file(src, key, ExtraArgs={
'ContentType': mimetype
}) | python | def _upload(self, items: Iterable[Tuple[str, str]]) -> None:
"""
Upload a collection of paths to S3.
:param items: An iterable of pairs containing the local path of the
file to upload, and the remote path to upload it to. The
prefix will be appended to each remote path.
"""
for src, key in items:
logger.info(f'Uploading {src} to {key}')
mimetype, _ = mimetypes.guess_type(src)
if mimetype is None:
logger.warning(f'Could not guess MIME type for {src}')
mimetype = 'application/octet-stream'
logger.debug(f'Deduced MIME type: {mimetype}')
self._bucket.upload_file(src, key, ExtraArgs={
'ContentType': mimetype
}) | [
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| efc71879890dbd2f2d7a0b1a65ed22a0843139dd | https://github.com/gebn/wood/blob/efc71879890dbd2f2d7a0b1a65ed22a0843139dd/wood/integrations/s3.py#L118-L136 | train |
geophysics-ubonn/crtomo_tools | src/grid_rotate.py | rotmat | def rotmat(alpha):
"""Rotate around z-axis
"""
R = np.array(((np.cos(alpha), -np.sin(alpha)),
(np.sin(alpha), np.cos(alpha))))
return R | python | def rotmat(alpha):
"""Rotate around z-axis
"""
R = np.array(((np.cos(alpha), -np.sin(alpha)),
(np.sin(alpha), np.cos(alpha))))
return R | [
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| 27c3e21a557f8df1c12455b96c4c2e00e08a5b4a | https://github.com/geophysics-ubonn/crtomo_tools/blob/27c3e21a557f8df1c12455b96c4c2e00e08a5b4a/src/grid_rotate.py#L37-L43 | train |
edx/edx-celeryutils | celery_utils/logged_task.py | LoggedTask.apply_async | def apply_async(self, args=None, kwargs=None, **options): # pylint: disable=arguments-differ
"""
Emit a log statement when the task is submitted.
"""
result = super(LoggedTask, self).apply_async(args=args, kwargs=kwargs, **options)
log.info('Task {}[{}] submitted with arguments {}, {}'.format(
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kwargs
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return result | python | def apply_async(self, args=None, kwargs=None, **options): # pylint: disable=arguments-differ
"""
Emit a log statement when the task is submitted.
"""
result = super(LoggedTask, self).apply_async(args=args, kwargs=kwargs, **options)
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| d8745f5f0929ad154fad779a19fbefe7f51e9498 | https://github.com/edx/edx-celeryutils/blob/d8745f5f0929ad154fad779a19fbefe7f51e9498/celery_utils/logged_task.py#L22-L33 | train |
edx/edx-celeryutils | celery_utils/logged_task.py | LoggedTask.on_retry | def on_retry(self, exc, task_id, args, kwargs, einfo):
"""
Capture the exception that caused the task to be retried, if any.
"""
super(LoggedTask, self).on_retry(exc, task_id, args, kwargs, einfo)
log.warning('[{}] retried due to {}'.format(task_id, getattr(einfo, 'traceback', None))) | python | def on_retry(self, exc, task_id, args, kwargs, einfo):
"""
Capture the exception that caused the task to be retried, if any.
"""
super(LoggedTask, self).on_retry(exc, task_id, args, kwargs, einfo)
log.warning('[{}] retried due to {}'.format(task_id, getattr(einfo, 'traceback', None))) | [
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| d8745f5f0929ad154fad779a19fbefe7f51e9498 | https://github.com/edx/edx-celeryutils/blob/d8745f5f0929ad154fad779a19fbefe7f51e9498/celery_utils/logged_task.py#L35-L40 | train |
edx/edx-celeryutils | celery_utils/logged_task.py | LoggedTask.on_failure | def on_failure(self, exc, task_id, args, kwargs, einfo):
"""
Capture the exception that caused the task to fail, if any.
"""
log.error('[{}] failed due to {}'.format(task_id, getattr(einfo, 'traceback', None)))
super(LoggedTask, self).on_failure(exc, task_id, args, kwargs, einfo) | python | def on_failure(self, exc, task_id, args, kwargs, einfo):
"""
Capture the exception that caused the task to fail, if any.
"""
log.error('[{}] failed due to {}'.format(task_id, getattr(einfo, 'traceback', None)))
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| d8745f5f0929ad154fad779a19fbefe7f51e9498 | https://github.com/edx/edx-celeryutils/blob/d8745f5f0929ad154fad779a19fbefe7f51e9498/celery_utils/logged_task.py#L42-L47 | train |
hotzenklotz/pybeerxml | pybeerxml/parser.py | Parser.nodes_to_object | def nodes_to_object(self, node, object):
"Map all child nodes to one object's attributes"
for n in list(node):
self.node_to_object(n, object) | python | def nodes_to_object(self, node, object):
"Map all child nodes to one object's attributes"
for n in list(node):
self.node_to_object(n, object) | [
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| e9cf8d6090b1e01e5bbb101e255792b134affbe0 | https://github.com/hotzenklotz/pybeerxml/blob/e9cf8d6090b1e01e5bbb101e255792b134affbe0/pybeerxml/parser.py#L15-L19 | train |
hotzenklotz/pybeerxml | pybeerxml/parser.py | Parser.node_to_object | def node_to_object(self, node, object):
"Map a single node to one object's attributes"
attribute = self.to_lower(node.tag)
# Yield is a protected keyword in Python, so let's rename it
attribute = "_yield" if attribute == "yield" else attribute
try:
valueString = node.text or ""
value = float(valueString)
except ValueError:
value = node.text
try:
setattr(object, attribute, value)
except AttributeError():
sys.stderr.write("Attribute <%s> not supported." % attribute) | python | def node_to_object(self, node, object):
"Map a single node to one object's attributes"
attribute = self.to_lower(node.tag)
# Yield is a protected keyword in Python, so let's rename it
attribute = "_yield" if attribute == "yield" else attribute
try:
valueString = node.text or ""
value = float(valueString)
except ValueError:
value = node.text
try:
setattr(object, attribute, value)
except AttributeError():
sys.stderr.write("Attribute <%s> not supported." % attribute) | [
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| e9cf8d6090b1e01e5bbb101e255792b134affbe0 | https://github.com/hotzenklotz/pybeerxml/blob/e9cf8d6090b1e01e5bbb101e255792b134affbe0/pybeerxml/parser.py#L21-L38 | train |
hotzenklotz/pybeerxml | pybeerxml/parser.py | Parser.parse | def parse(self, xml_file):
"Get a list of parsed recipes from BeerXML input"
recipes = []
with open(xml_file, "rt") as f:
tree = ElementTree.parse(f)
for recipeNode in tree.iter():
if self.to_lower(recipeNode.tag) != "recipe":
continue
recipe = Recipe()
recipes.append(recipe)
for recipeProperty in list(recipeNode):
tag_name = self.to_lower(recipeProperty.tag)
if tag_name == "fermentables":
for fermentable_node in list(recipeProperty):
fermentable = Fermentable()
self.nodes_to_object(fermentable_node, fermentable)
recipe.fermentables.append(fermentable)
elif tag_name == "yeasts":
for yeast_node in list(recipeProperty):
yeast = Yeast()
self.nodes_to_object(yeast_node, yeast)
recipe.yeasts.append(yeast)
elif tag_name == "hops":
for hop_node in list(recipeProperty):
hop = Hop()
self.nodes_to_object(hop_node, hop)
recipe.hops.append(hop)
elif tag_name == "miscs":
for misc_node in list(recipeProperty):
misc = Misc()
self.nodes_to_object(misc_node, misc)
recipe.miscs.append(misc)
elif tag_name == "style":
style = Style()
recipe.style = style
self.nodes_to_object(recipeProperty, style)
elif tag_name == "mash":
for mash_node in list(recipeProperty):
mash = Mash()
recipe.mash = mash
if self.to_lower(mash_node.tag) == "mash_steps":
for mash_step_node in list(mash_node):
mash_step = MashStep()
self.nodes_to_object(mash_step_node, mash_step)
mash.steps.append(mash_step)
else:
self.nodes_to_object(mash_node, mash)
else:
self.node_to_object(recipeProperty, recipe)
return recipes | python | def parse(self, xml_file):
"Get a list of parsed recipes from BeerXML input"
recipes = []
with open(xml_file, "rt") as f:
tree = ElementTree.parse(f)
for recipeNode in tree.iter():
if self.to_lower(recipeNode.tag) != "recipe":
continue
recipe = Recipe()
recipes.append(recipe)
for recipeProperty in list(recipeNode):
tag_name = self.to_lower(recipeProperty.tag)
if tag_name == "fermentables":
for fermentable_node in list(recipeProperty):
fermentable = Fermentable()
self.nodes_to_object(fermentable_node, fermentable)
recipe.fermentables.append(fermentable)
elif tag_name == "yeasts":
for yeast_node in list(recipeProperty):
yeast = Yeast()
self.nodes_to_object(yeast_node, yeast)
recipe.yeasts.append(yeast)
elif tag_name == "hops":
for hop_node in list(recipeProperty):
hop = Hop()
self.nodes_to_object(hop_node, hop)
recipe.hops.append(hop)
elif tag_name == "miscs":
for misc_node in list(recipeProperty):
misc = Misc()
self.nodes_to_object(misc_node, misc)
recipe.miscs.append(misc)
elif tag_name == "style":
style = Style()
recipe.style = style
self.nodes_to_object(recipeProperty, style)
elif tag_name == "mash":
for mash_node in list(recipeProperty):
mash = Mash()
recipe.mash = mash
if self.to_lower(mash_node.tag) == "mash_steps":
for mash_step_node in list(mash_node):
mash_step = MashStep()
self.nodes_to_object(mash_step_node, mash_step)
mash.steps.append(mash_step)
else:
self.nodes_to_object(mash_node, mash)
else:
self.node_to_object(recipeProperty, recipe)
return recipes | [
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| e9cf8d6090b1e01e5bbb101e255792b134affbe0 | https://github.com/hotzenklotz/pybeerxml/blob/e9cf8d6090b1e01e5bbb101e255792b134affbe0/pybeerxml/parser.py#L40-L104 | train |
hotzenklotz/pybeerxml | pybeerxml/parser.py | Parser.to_lower | def to_lower(self, string):
"Helper function to transform strings to lower case"
value = None
try:
value = string.lower()
except AttributeError:
value = ""
finally:
return value | python | def to_lower(self, string):
"Helper function to transform strings to lower case"
value = None
try:
value = string.lower()
except AttributeError:
value = ""
finally:
return value | [
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| e9cf8d6090b1e01e5bbb101e255792b134affbe0 | https://github.com/hotzenklotz/pybeerxml/blob/e9cf8d6090b1e01e5bbb101e255792b134affbe0/pybeerxml/parser.py#L106-L114 | train |
maxzheng/localconfig | localconfig/manager.py | LocalConfig._to_dot_key | def _to_dot_key(cls, section, key=None):
""" Return the section and key in dot notation format. """
if key:
return (NON_ALPHA_NUM.sub('_', section.lower()), NON_ALPHA_NUM.sub('_', key.lower()))
else:
return NON_ALPHA_NUM.sub('_', section.lower()) | python | def _to_dot_key(cls, section, key=None):
""" Return the section and key in dot notation format. """
if key:
return (NON_ALPHA_NUM.sub('_', section.lower()), NON_ALPHA_NUM.sub('_', key.lower()))
else:
return NON_ALPHA_NUM.sub('_', section.lower()) | [
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| 636087f2489295d9dae2693dda8a86e4daa4ff9d | https://github.com/maxzheng/localconfig/blob/636087f2489295d9dae2693dda8a86e4daa4ff9d/localconfig/manager.py#L102-L107 | train |
maxzheng/localconfig | localconfig/manager.py | LocalConfig.save | def save(self, target_file=None, as_template=False):
"""
Save the config
:param str target_file: File to save to. Defaults to `self._last_source` if set
:param bool as_template: Save the config with all keys and sections commented out for user to modify
:raise AttributeError: if target file is not provided and `self._last_source` is not set
"""
self._read_sources()
if not target_file:
if not self._last_source:
raise AttributeError('Target file is required when last source is not set during instantiation')
target_file = self._last_source
output = str(self)
if as_template:
output_tmpl = []
for line in output.split('\n'):
if line and not line.startswith('#'):
line = '# %s' % line
output_tmpl.append(line)
output = '\n'.join(output_tmpl)
with open(target_file, 'w') as fp:
fp.write(output) | python | def save(self, target_file=None, as_template=False):
"""
Save the config
:param str target_file: File to save to. Defaults to `self._last_source` if set
:param bool as_template: Save the config with all keys and sections commented out for user to modify
:raise AttributeError: if target file is not provided and `self._last_source` is not set
"""
self._read_sources()
if not target_file:
if not self._last_source:
raise AttributeError('Target file is required when last source is not set during instantiation')
target_file = self._last_source
output = str(self)
if as_template:
output_tmpl = []
for line in output.split('\n'):
if line and not line.startswith('#'):
line = '# %s' % line
output_tmpl.append(line)
output = '\n'.join(output_tmpl)
with open(target_file, 'w') as fp:
fp.write(output) | [
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| 636087f2489295d9dae2693dda8a86e4daa4ff9d | https://github.com/maxzheng/localconfig/blob/636087f2489295d9dae2693dda8a86e4daa4ff9d/localconfig/manager.py#L203-L229 | train |
maxzheng/localconfig | localconfig/manager.py | LocalConfig._parse_extra | def _parse_extra(self, fp):
""" Parse and store the config comments and create maps for dot notion lookup """
comment = ''
section = ''
fp.seek(0)
for line in fp:
line = line.rstrip()
if not line:
if comment:
comment += '\n'
continue
if line.startswith('#'): # Comment
comment += line + '\n'
continue
if line.startswith('['): # Section
section = line.strip('[]')
self._add_dot_key(section)
if comment:
self._comments[section] = comment.rstrip()
elif CONFIG_KEY_RE.match(line): # Config
key = line.split('=', 1)[0].strip()
self._add_dot_key(section, key)
if comment:
self._comments[(section, key)] = comment.rstrip()
comment = ''
if comment:
self._comments[self.LAST_COMMENT_KEY] = comment | python | def _parse_extra(self, fp):
""" Parse and store the config comments and create maps for dot notion lookup """
comment = ''
section = ''
fp.seek(0)
for line in fp:
line = line.rstrip()
if not line:
if comment:
comment += '\n'
continue
if line.startswith('#'): # Comment
comment += line + '\n'
continue
if line.startswith('['): # Section
section = line.strip('[]')
self._add_dot_key(section)
if comment:
self._comments[section] = comment.rstrip()
elif CONFIG_KEY_RE.match(line): # Config
key = line.split('=', 1)[0].strip()
self._add_dot_key(section, key)
if comment:
self._comments[(section, key)] = comment.rstrip()
comment = ''
if comment:
self._comments[self.LAST_COMMENT_KEY] = comment | [
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| 636087f2489295d9dae2693dda8a86e4daa4ff9d | https://github.com/maxzheng/localconfig/blob/636087f2489295d9dae2693dda8a86e4daa4ff9d/localconfig/manager.py#L231-L265 | train |
maxzheng/localconfig | localconfig/manager.py | LocalConfig._typed_value | def _typed_value(self, value):
""" Transform string value to an actual data type of the same value. """
if value not in self._value_cache:
new_value = value
if is_int(value):
new_value = int(value)
elif is_float(value):
new_value = float(value)
elif is_bool(value):
new_value = to_bool(value)
elif is_none(value):
new_value = None
self._value_cache[value] = new_value
return self._value_cache[value] | python | def _typed_value(self, value):
""" Transform string value to an actual data type of the same value. """
if value not in self._value_cache:
new_value = value
if is_int(value):
new_value = int(value)
elif is_float(value):
new_value = float(value)
elif is_bool(value):
new_value = to_bool(value)
elif is_none(value):
new_value = None
self._value_cache[value] = new_value
return self._value_cache[value] | [
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| 636087f2489295d9dae2693dda8a86e4daa4ff9d | https://github.com/maxzheng/localconfig/blob/636087f2489295d9dae2693dda8a86e4daa4ff9d/localconfig/manager.py#L330-L345 | train |
maxzheng/localconfig | localconfig/manager.py | LocalConfig.add_section | def add_section(self, section, comment=None):
"""
Add a section
:param str section: Section to add
:raise DuplicateSectionError: if section already exist.
"""
self._read_sources()
if self._to_dot_key(section) in self._dot_keys:
raise DuplicateSectionError(section)
self._parser.add_section(section)
self._add_dot_key(section)
if comment:
self._set_comment(section, comment) | python | def add_section(self, section, comment=None):
"""
Add a section
:param str section: Section to add
:raise DuplicateSectionError: if section already exist.
"""
self._read_sources()
if self._to_dot_key(section) in self._dot_keys:
raise DuplicateSectionError(section)
self._parser.add_section(section)
self._add_dot_key(section)
if comment:
self._set_comment(section, comment) | [
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| 636087f2489295d9dae2693dda8a86e4daa4ff9d | https://github.com/maxzheng/localconfig/blob/636087f2489295d9dae2693dda8a86e4daa4ff9d/localconfig/manager.py#L381-L396 | train |
maxzheng/localconfig | localconfig/manager.py | LocalConfig._set_comment | def _set_comment(self, section, comment, key=None):
"""
Set a comment for section or key
:param str section: Section to add comment to
:param str comment: Comment to add
:param str key: Key to add comment to
"""
if '\n' in comment:
comment = '\n# '.join(comment.split('\n'))
comment = '# ' + comment
if key:
self._comments[(section, key)] = comment
else:
self._comments[section] = comment | python | def _set_comment(self, section, comment, key=None):
"""
Set a comment for section or key
:param str section: Section to add comment to
:param str comment: Comment to add
:param str key: Key to add comment to
"""
if '\n' in comment:
comment = '\n# '.join(comment.split('\n'))
comment = '# ' + comment
if key:
self._comments[(section, key)] = comment
else:
self._comments[section] = comment | [
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| 636087f2489295d9dae2693dda8a86e4daa4ff9d | https://github.com/maxzheng/localconfig/blob/636087f2489295d9dae2693dda8a86e4daa4ff9d/localconfig/manager.py#L398-L414 | train |
thiagopbueno/tf-rddlsim | tfrddlsim/policy/random_policy.py | RandomPolicy._sample_actions | def _sample_actions(self,
state: Sequence[tf.Tensor]) -> Tuple[Sequence[tf.Tensor], tf.Tensor, tf.Tensor]:
'''Returns sampled action fluents and tensors related to the sampling.
Args:
state (Sequence[tf.Tensor]): A list of state fluents.
Returns:
Tuple[Sequence[tf.Tensor], tf.Tensor, tf.Tensor]: A tuple with
action fluents, an integer tensor for the number of samples, and
a boolean tensor for checking all action preconditions.
'''
default = self.compiler.compile_default_action(self.batch_size)
bound_constraints = self.compiler.compile_action_bound_constraints(state)
action = self._sample_action(bound_constraints, default)
n, action, checking = self._check_preconditions(state, action, bound_constraints, default)
return action, n, checking | python | def _sample_actions(self,
state: Sequence[tf.Tensor]) -> Tuple[Sequence[tf.Tensor], tf.Tensor, tf.Tensor]:
'''Returns sampled action fluents and tensors related to the sampling.
Args:
state (Sequence[tf.Tensor]): A list of state fluents.
Returns:
Tuple[Sequence[tf.Tensor], tf.Tensor, tf.Tensor]: A tuple with
action fluents, an integer tensor for the number of samples, and
a boolean tensor for checking all action preconditions.
'''
default = self.compiler.compile_default_action(self.batch_size)
bound_constraints = self.compiler.compile_action_bound_constraints(state)
action = self._sample_action(bound_constraints, default)
n, action, checking = self._check_preconditions(state, action, bound_constraints, default)
return action, n, checking | [
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| d7102a0ad37d179dbb23141640254ea383d3b43f | https://github.com/thiagopbueno/tf-rddlsim/blob/d7102a0ad37d179dbb23141640254ea383d3b43f/tfrddlsim/policy/random_policy.py#L70-L86 | train |
thiagopbueno/tf-rddlsim | tfrddlsim/policy/random_policy.py | RandomPolicy._check_preconditions | def _check_preconditions(self,
state: Sequence[tf.Tensor],
action: Sequence[tf.Tensor],
bound_constraints: Dict[str, Constraints],
default: Sequence[tf.Tensor]) -> Tuple[tf.Tensor, Sequence[tf.Tensor], tf.Tensor]:
'''Samples action fluents until all preconditions are satisfied.
Checks action preconditions for the sampled `action` and current `state`,
and iff all preconditions are satisfied it returns the sampled action fluents.
Args:
state (Sequence[tf.Tensor]): A list of state fluents.
action (Sequence[tf.Tensor]): A list of action fluents.
bound_constraints (Dict[str, Tuple[Optional[TensorFluent], Optional[TensorFluent]]]): The bounds for each action fluent.
default (Sequence[tf.Tensor]): The default action fluents.
Returns:
Tuple[tf.Tensor, Sequence[tf.Tensor], tf.Tensor]: A tuple with
an integer tensor corresponding to the number of samples,
action fluents and a boolean tensor for checking all action preconditions.
'''
def condition(i, a, checking):
not_checking = tf.reduce_any(tf.logical_not(checking))
return not_checking
def body(i, a, checking):
new_action = []
new_sampled_action = self._sample_action(bound_constraints, default)
new_preconds_checking = self.compiler.compile_action_preconditions_checking(state, new_sampled_action)
for action_fluent, new_sampled_action_fluent in zip(a, new_sampled_action):
new_action_fluent = tf.where(checking, action_fluent, new_sampled_action_fluent)
new_action.append(new_action_fluent)
new_action = tuple(new_action)
new_checking = tf.logical_or(checking, new_preconds_checking)
return (i + 1, new_action, new_checking)
i0 = tf.constant(0)
preconds_checking = self.compiler.compile_action_preconditions_checking(state, action)
return tf.while_loop(condition, body, loop_vars=[i0, action, preconds_checking]) | python | def _check_preconditions(self,
state: Sequence[tf.Tensor],
action: Sequence[tf.Tensor],
bound_constraints: Dict[str, Constraints],
default: Sequence[tf.Tensor]) -> Tuple[tf.Tensor, Sequence[tf.Tensor], tf.Tensor]:
'''Samples action fluents until all preconditions are satisfied.
Checks action preconditions for the sampled `action` and current `state`,
and iff all preconditions are satisfied it returns the sampled action fluents.
Args:
state (Sequence[tf.Tensor]): A list of state fluents.
action (Sequence[tf.Tensor]): A list of action fluents.
bound_constraints (Dict[str, Tuple[Optional[TensorFluent], Optional[TensorFluent]]]): The bounds for each action fluent.
default (Sequence[tf.Tensor]): The default action fluents.
Returns:
Tuple[tf.Tensor, Sequence[tf.Tensor], tf.Tensor]: A tuple with
an integer tensor corresponding to the number of samples,
action fluents and a boolean tensor for checking all action preconditions.
'''
def condition(i, a, checking):
not_checking = tf.reduce_any(tf.logical_not(checking))
return not_checking
def body(i, a, checking):
new_action = []
new_sampled_action = self._sample_action(bound_constraints, default)
new_preconds_checking = self.compiler.compile_action_preconditions_checking(state, new_sampled_action)
for action_fluent, new_sampled_action_fluent in zip(a, new_sampled_action):
new_action_fluent = tf.where(checking, action_fluent, new_sampled_action_fluent)
new_action.append(new_action_fluent)
new_action = tuple(new_action)
new_checking = tf.logical_or(checking, new_preconds_checking)
return (i + 1, new_action, new_checking)
i0 = tf.constant(0)
preconds_checking = self.compiler.compile_action_preconditions_checking(state, action)
return tf.while_loop(condition, body, loop_vars=[i0, action, preconds_checking]) | [
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action (Sequence[tf.Tensor]): A list of action fluents.
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| d7102a0ad37d179dbb23141640254ea383d3b43f | https://github.com/thiagopbueno/tf-rddlsim/blob/d7102a0ad37d179dbb23141640254ea383d3b43f/tfrddlsim/policy/random_policy.py#L88-L127 | train |
thiagopbueno/tf-rddlsim | tfrddlsim/policy/random_policy.py | RandomPolicy._sample_action | def _sample_action(self,
constraints: Dict[str, Constraints],
default: Sequence[tf.Tensor],
prob: float = 0.3) -> Sequence[tf.Tensor]:
'''Samples action fluents respecting the given bound `constraints`.
With probability `prob` it chooses the action fluent default value,
with probability 1-`prob` it samples the fluent w.r.t. its bounds.
Args:
constraints (Dict[str, Tuple[Optional[TensorFluent], Optional[TensorFluent]]]): The bounds for each action fluent.
default (Sequence[tf.Tensor]): The default action fluents.
prob (float): A probability measure.
Returns:
Sequence[tf.Tensor]: A tuple of action fluents.
'''
ordering = self.compiler.rddl.domain.action_fluent_ordering
dtypes = map(rddl2tf.utils.range_type_to_dtype, self.compiler.rddl.action_range_type)
size = self.compiler.rddl.action_size
action = []
for name, dtype, size, default_value in zip(ordering, dtypes, size, default):
action_fluent = self._sample_action_fluent(name, dtype, size, constraints, default_value, prob)
action.append(action_fluent)
return tuple(action) | python | def _sample_action(self,
constraints: Dict[str, Constraints],
default: Sequence[tf.Tensor],
prob: float = 0.3) -> Sequence[tf.Tensor]:
'''Samples action fluents respecting the given bound `constraints`.
With probability `prob` it chooses the action fluent default value,
with probability 1-`prob` it samples the fluent w.r.t. its bounds.
Args:
constraints (Dict[str, Tuple[Optional[TensorFluent], Optional[TensorFluent]]]): The bounds for each action fluent.
default (Sequence[tf.Tensor]): The default action fluents.
prob (float): A probability measure.
Returns:
Sequence[tf.Tensor]: A tuple of action fluents.
'''
ordering = self.compiler.rddl.domain.action_fluent_ordering
dtypes = map(rddl2tf.utils.range_type_to_dtype, self.compiler.rddl.action_range_type)
size = self.compiler.rddl.action_size
action = []
for name, dtype, size, default_value in zip(ordering, dtypes, size, default):
action_fluent = self._sample_action_fluent(name, dtype, size, constraints, default_value, prob)
action.append(action_fluent)
return tuple(action) | [
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Args:
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default (Sequence[tf.Tensor]): The default action fluents.
prob (float): A probability measure.
Returns:
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| d7102a0ad37d179dbb23141640254ea383d3b43f | https://github.com/thiagopbueno/tf-rddlsim/blob/d7102a0ad37d179dbb23141640254ea383d3b43f/tfrddlsim/policy/random_policy.py#L129-L155 | train |
thiagopbueno/tf-rddlsim | tfrddlsim/policy/random_policy.py | RandomPolicy._sample_action_fluent | def _sample_action_fluent(self,
name: str,
dtype: tf.DType,
size: Sequence[int],
constraints: Dict[str, Constraints],
default_value: tf.Tensor,
prob: float) -> tf.Tensor:
'''Samples the action fluent with given `name`, `dtype`, and `size`.
With probability `prob` it chooses the action fluent `default_value`,
with probability 1-`prob` it samples the fluent w.r.t. its `constraints`.
Args:
name (str): The name of the action fluent.
dtype (tf.DType): The data type of the action fluent.
size (Sequence[int]): The size and shape of the action fluent.
constraints (Dict[str, Tuple[Optional[TensorFluent], Optional[TensorFluent]]]): The bounds for each action fluent.
default_value (tf.Tensor): The default value for the action fluent.
prob (float): A probability measure.
Returns:
tf.Tensor: A tensor for sampling the action fluent.
'''
shape = [self.batch_size] + list(size)
if dtype == tf.float32:
bounds = constraints.get(name)
if bounds is None:
low, high = -self.MAX_REAL_VALUE, self.MAX_REAL_VALUE
dist = tf.distributions.Uniform(low=low, high=high)
sampled_fluent = dist.sample(shape)
else:
low, high = bounds
batch = (low is not None and low.batch) or (high is not None and high.batch)
low = tf.cast(low.tensor, tf.float32) if low is not None else -self.MAX_REAL_VALUE
high = tf.cast(high.tensor, tf.float32) if high is not None else self.MAX_REAL_VALUE
dist = tf.distributions.Uniform(low=low, high=high)
if batch:
sampled_fluent = dist.sample()
elif isinstance(low, tf.Tensor) or isinstance(high, tf.Tensor):
if (low+high).shape.as_list() == list(size):
sampled_fluent = dist.sample([self.batch_size])
else:
raise ValueError('bounds are not compatible with action fluent.')
else:
sampled_fluent = dist.sample(shape)
elif dtype == tf.int32:
logits = [1.0] * self.MAX_INT_VALUE
dist = tf.distributions.Categorical(logits=logits, dtype=tf.int32)
sampled_fluent = dist.sample(shape)
elif dtype == tf.bool:
probs = 0.5
dist = tf.distributions.Bernoulli(probs=probs, dtype=tf.bool)
sampled_fluent = dist.sample(shape)
select_default = tf.distributions.Bernoulli(prob, dtype=tf.bool).sample(self.batch_size)
action_fluent = tf.where(select_default, default_value, sampled_fluent)
return action_fluent | python | def _sample_action_fluent(self,
name: str,
dtype: tf.DType,
size: Sequence[int],
constraints: Dict[str, Constraints],
default_value: tf.Tensor,
prob: float) -> tf.Tensor:
'''Samples the action fluent with given `name`, `dtype`, and `size`.
With probability `prob` it chooses the action fluent `default_value`,
with probability 1-`prob` it samples the fluent w.r.t. its `constraints`.
Args:
name (str): The name of the action fluent.
dtype (tf.DType): The data type of the action fluent.
size (Sequence[int]): The size and shape of the action fluent.
constraints (Dict[str, Tuple[Optional[TensorFluent], Optional[TensorFluent]]]): The bounds for each action fluent.
default_value (tf.Tensor): The default value for the action fluent.
prob (float): A probability measure.
Returns:
tf.Tensor: A tensor for sampling the action fluent.
'''
shape = [self.batch_size] + list(size)
if dtype == tf.float32:
bounds = constraints.get(name)
if bounds is None:
low, high = -self.MAX_REAL_VALUE, self.MAX_REAL_VALUE
dist = tf.distributions.Uniform(low=low, high=high)
sampled_fluent = dist.sample(shape)
else:
low, high = bounds
batch = (low is not None and low.batch) or (high is not None and high.batch)
low = tf.cast(low.tensor, tf.float32) if low is not None else -self.MAX_REAL_VALUE
high = tf.cast(high.tensor, tf.float32) if high is not None else self.MAX_REAL_VALUE
dist = tf.distributions.Uniform(low=low, high=high)
if batch:
sampled_fluent = dist.sample()
elif isinstance(low, tf.Tensor) or isinstance(high, tf.Tensor):
if (low+high).shape.as_list() == list(size):
sampled_fluent = dist.sample([self.batch_size])
else:
raise ValueError('bounds are not compatible with action fluent.')
else:
sampled_fluent = dist.sample(shape)
elif dtype == tf.int32:
logits = [1.0] * self.MAX_INT_VALUE
dist = tf.distributions.Categorical(logits=logits, dtype=tf.int32)
sampled_fluent = dist.sample(shape)
elif dtype == tf.bool:
probs = 0.5
dist = tf.distributions.Bernoulli(probs=probs, dtype=tf.bool)
sampled_fluent = dist.sample(shape)
select_default = tf.distributions.Bernoulli(prob, dtype=tf.bool).sample(self.batch_size)
action_fluent = tf.where(select_default, default_value, sampled_fluent)
return action_fluent | [
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With probability `prob` it chooses the action fluent `default_value`,
with probability 1-`prob` it samples the fluent w.r.t. its `constraints`.
Args:
name (str): The name of the action fluent.
dtype (tf.DType): The data type of the action fluent.
size (Sequence[int]): The size and shape of the action fluent.
constraints (Dict[str, Tuple[Optional[TensorFluent], Optional[TensorFluent]]]): The bounds for each action fluent.
default_value (tf.Tensor): The default value for the action fluent.
prob (float): A probability measure.
Returns:
tf.Tensor: A tensor for sampling the action fluent. | [
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| d7102a0ad37d179dbb23141640254ea383d3b43f | https://github.com/thiagopbueno/tf-rddlsim/blob/d7102a0ad37d179dbb23141640254ea383d3b43f/tfrddlsim/policy/random_policy.py#L157-L215 | train |
Nic30/hwtGraph | hwtGraph/elk/fromHwt/convertor.py | UnitToLNode | def UnitToLNode(u: Unit, node: Optional[LNode]=None,
toL: Optional[dict]=None,
optimizations=[]) -> LNode:
"""
Build LNode instance from Unit instance
:attention: unit has to be synthesized
"""
if toL is None:
toL = {}
if node is None:
root = LNode(name=u._name, originObj=u, node2lnode=toL)
else:
root = node
stmPorts = {}
# {RtlSignal: NetCtx}
netCtx = NetCtxs(root)
# create subunits
for su in u._units:
n = root.addNode(name=su._name, originObj=su)
UnitToLNode(su, n, toL, optimizations)
# create subunits from statements
for stm in u._ctx.statements:
n = addStmAsLNode(root, stm, stmPorts, netCtx)
# create ports for this unit
for intf in u._interfaces:
addPort(root, intf)
# render content of statements
for stm in u._ctx.statements:
n = toL.get(stm, None)
if n is not None:
if isinstance(n, VirtualLNode):
# statement is not in wrap and does not need any port context
p = None
else:
# statement is in wrap and needs a port context
# to resolve port connections to wrap
p = stmPorts[n]
r = StatementRenderer(n, toL, p, netCtx)
r.renderContent()
# connect nets inside this unit
for s in u._ctx.signals:
if not s.hidden:
net, _ = netCtx.getDefault(s)
for e in s.endpoints:
if isinstance(e, PortItem):
net.addEndpoint(toL[e])
for d in s.drivers:
if isinstance(d, PortItem):
net.addDriver(toL[d])
netCtx.applyConnections(root)
for opt in optimizations:
opt(root)
isRootOfWholeGraph = root.parent is None
if not isRootOfWholeGraph:
for intf in u._interfaces:
# connect my external port to port on my container on parent
# also override toL to use this new port
ext_p = toL[originObjOfPort(intf)].parentNode
nodePort = addPortToLNode(root, intf)
# connect this node which represents port to port of this node
if intf._direction == INTF_DIRECTION.SLAVE:
src = nodePort
dst = ext_p.addPort("", PortType.INPUT, PortSide.WEST)
else:
src = ext_p.addPort("", PortType.OUTPUT, PortSide.EAST)
dst = nodePort
root.addEdge(src, dst, name=repr(intf), originObj=intf)
return root | python | def UnitToLNode(u: Unit, node: Optional[LNode]=None,
toL: Optional[dict]=None,
optimizations=[]) -> LNode:
"""
Build LNode instance from Unit instance
:attention: unit has to be synthesized
"""
if toL is None:
toL = {}
if node is None:
root = LNode(name=u._name, originObj=u, node2lnode=toL)
else:
root = node
stmPorts = {}
# {RtlSignal: NetCtx}
netCtx = NetCtxs(root)
# create subunits
for su in u._units:
n = root.addNode(name=su._name, originObj=su)
UnitToLNode(su, n, toL, optimizations)
# create subunits from statements
for stm in u._ctx.statements:
n = addStmAsLNode(root, stm, stmPorts, netCtx)
# create ports for this unit
for intf in u._interfaces:
addPort(root, intf)
# render content of statements
for stm in u._ctx.statements:
n = toL.get(stm, None)
if n is not None:
if isinstance(n, VirtualLNode):
# statement is not in wrap and does not need any port context
p = None
else:
# statement is in wrap and needs a port context
# to resolve port connections to wrap
p = stmPorts[n]
r = StatementRenderer(n, toL, p, netCtx)
r.renderContent()
# connect nets inside this unit
for s in u._ctx.signals:
if not s.hidden:
net, _ = netCtx.getDefault(s)
for e in s.endpoints:
if isinstance(e, PortItem):
net.addEndpoint(toL[e])
for d in s.drivers:
if isinstance(d, PortItem):
net.addDriver(toL[d])
netCtx.applyConnections(root)
for opt in optimizations:
opt(root)
isRootOfWholeGraph = root.parent is None
if not isRootOfWholeGraph:
for intf in u._interfaces:
# connect my external port to port on my container on parent
# also override toL to use this new port
ext_p = toL[originObjOfPort(intf)].parentNode
nodePort = addPortToLNode(root, intf)
# connect this node which represents port to port of this node
if intf._direction == INTF_DIRECTION.SLAVE:
src = nodePort
dst = ext_p.addPort("", PortType.INPUT, PortSide.WEST)
else:
src = ext_p.addPort("", PortType.OUTPUT, PortSide.EAST)
dst = nodePort
root.addEdge(src, dst, name=repr(intf), originObj=intf)
return root | [
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:attention: unit has to be synthesized | [
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| 6b7d4fdd759f263a0fdd2736f02f123e44e4354f | https://github.com/Nic30/hwtGraph/blob/6b7d4fdd759f263a0fdd2736f02f123e44e4354f/hwtGraph/elk/fromHwt/convertor.py#L20-L102 | train |
redhat-openstack/python-tripleo-helper | tripleohelper/host0.py | Host0.configure | def configure(self, rhsm=None, repositories=None):
"""This method will configure the host0 and run the hypervisor."""
if rhsm is not None:
self.rhsm_register(rhsm)
if repositories is not None:
self.enable_repositories(repositories)
self.create_stack_user()
self.deploy_hypervisor() | python | def configure(self, rhsm=None, repositories=None):
"""This method will configure the host0 and run the hypervisor."""
if rhsm is not None:
self.rhsm_register(rhsm)
if repositories is not None:
self.enable_repositories(repositories)
self.create_stack_user()
self.deploy_hypervisor() | [
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| bfa165538335edb1088170c7a92f097167225c81 | https://github.com/redhat-openstack/python-tripleo-helper/blob/bfa165538335edb1088170c7a92f097167225c81/tripleohelper/host0.py#L35-L42 | train |
redhat-openstack/python-tripleo-helper | tripleohelper/host0.py | Host0.deploy_hypervisor | def deploy_hypervisor(self):
"""Install the libvirtd and instack-undercloud packages.
"""
self.yum_install(['libvirt-daemon-driver-nwfilter', 'libvirt-client', 'libvirt-daemon-config-network', 'libvirt-daemon-driver-nodedev', 'libvirt-daemon-kvm', 'libvirt-python', 'libvirt-daemon-config-nwfilter', 'libvirt-glib', 'libvirt-daemon', 'libvirt-daemon-driver-storage', 'libvirt', 'libvirt-daemon-driver-network', 'libvirt-devel', 'libvirt-gobject', 'libvirt-daemon-driver-secret', 'libvirt-daemon-driver-qemu', 'libvirt-daemon-driver-interface', 'libguestfs-tools', 'virt-install', 'genisoimage', 'openstack-tripleo', 'instack-undercloud'])
self.run('sed -i "s,#auth_unix_rw,auth_unix_rw," /etc/libvirt/libvirtd.conf')
self.run('systemctl start libvirtd')
self.run('systemctl status libvirtd')
self.install_base_packages()
self.clean_system()
self.yum_update() | python | def deploy_hypervisor(self):
"""Install the libvirtd and instack-undercloud packages.
"""
self.yum_install(['libvirt-daemon-driver-nwfilter', 'libvirt-client', 'libvirt-daemon-config-network', 'libvirt-daemon-driver-nodedev', 'libvirt-daemon-kvm', 'libvirt-python', 'libvirt-daemon-config-nwfilter', 'libvirt-glib', 'libvirt-daemon', 'libvirt-daemon-driver-storage', 'libvirt', 'libvirt-daemon-driver-network', 'libvirt-devel', 'libvirt-gobject', 'libvirt-daemon-driver-secret', 'libvirt-daemon-driver-qemu', 'libvirt-daemon-driver-interface', 'libguestfs-tools', 'virt-install', 'genisoimage', 'openstack-tripleo', 'instack-undercloud'])
self.run('sed -i "s,#auth_unix_rw,auth_unix_rw," /etc/libvirt/libvirtd.conf')
self.run('systemctl start libvirtd')
self.run('systemctl status libvirtd')
self.install_base_packages()
self.clean_system()
self.yum_update() | [
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| bfa165538335edb1088170c7a92f097167225c81 | https://github.com/redhat-openstack/python-tripleo-helper/blob/bfa165538335edb1088170c7a92f097167225c81/tripleohelper/host0.py#L44-L54 | train |
redhat-openstack/python-tripleo-helper | tripleohelper/host0.py | Host0.build_undercloud_on_libvirt | def build_undercloud_on_libvirt(self, image_path,
rhsm=None, repositories=[]):
"""Build the Undercloud by using instack-virt-setup script."""
self.run('sysctl net.ipv4.ip_forward=1')
self.fetch_image(path=image_path, dest='/home/stack/guest_image.qcow2',
user='stack')
# NOTE(Gonéri): this is a hack for our OpenStack, the MTU of its outgoing route
# is 1400 and libvirt do not provide a mechanism to adjust the guests MTU.
self.run("LIBGUESTFS_BACKEND=direct virt-customize -a /home/stack/guest_image.qcow2 --run-command 'echo MTU=\"1400\" >> /etc/sysconfig/network-scripts/ifcfg-eth0'")
env = Environment()
env.loader = FileSystemLoader(pkg_data_filename('template'))
template = env.get_template('virt-setup-env.j2')
self.run('mkdir -p /home/stack/DIB', user='stack')
self.run('cp -v /etc/yum.repos.d/*.repo /home/stack/DIB', user='stack')
# NOTE(Gonéri): Hack to be sure DIB won't complain because of missing gpg files
# self.run('sed -i "s,gpgcheck=1,gpgcheck=0," /home/stack/DIB/*.repo', user='stack')
dib_yum_repo_conf = self.run('find /home/stack/DIB -type f', user='stack')[0].split()
virt_setup_template = {
'dib_yum_repo_conf': dib_yum_repo_conf,
'node': {
'count': 2,
'mem': 6144,
'cpu': 2
},
'undercloud_node_mem': 8192,
'guest_image_name': '/home/stack/guest_image.qcow2'
}
if rhsm is not None:
virt_setup_template['rhsm'] = {
'login': rhsm.get('login'),
'password': rhsm.get('password', os.environ.get('RHN_PW')),
'pool_id': rhsm.get('pool_id', ''),
'repositories': [i['name'] for i in repositories if i['type'] == 'rhsm_channel']
}
virt_setup_env = template.render(virt_setup_template)
self.create_file('virt-setup-env', virt_setup_env, user='stack')
self.run('virsh destroy instack', ignore_error=True)
self.run('virsh undefine instack --remove-all-storage', ignore_error=True)
self.run('source virt-setup-env; instack-virt-setup', user='stack')
undercloud_ip = self.run(
'/sbin/ip n | grep $(tripleo get-vm-mac instack) | awk \'{print $1;}\'',
user='stack')[0]
assert undercloud_ip, 'undercloud should have an IP'
undercloud = Undercloud(hostname=undercloud_ip,
via_ip=self.hostname,
user='root',
key_filename=self._key_filename)
return undercloud | python | def build_undercloud_on_libvirt(self, image_path,
rhsm=None, repositories=[]):
"""Build the Undercloud by using instack-virt-setup script."""
self.run('sysctl net.ipv4.ip_forward=1')
self.fetch_image(path=image_path, dest='/home/stack/guest_image.qcow2',
user='stack')
# NOTE(Gonéri): this is a hack for our OpenStack, the MTU of its outgoing route
# is 1400 and libvirt do not provide a mechanism to adjust the guests MTU.
self.run("LIBGUESTFS_BACKEND=direct virt-customize -a /home/stack/guest_image.qcow2 --run-command 'echo MTU=\"1400\" >> /etc/sysconfig/network-scripts/ifcfg-eth0'")
env = Environment()
env.loader = FileSystemLoader(pkg_data_filename('template'))
template = env.get_template('virt-setup-env.j2')
self.run('mkdir -p /home/stack/DIB', user='stack')
self.run('cp -v /etc/yum.repos.d/*.repo /home/stack/DIB', user='stack')
# NOTE(Gonéri): Hack to be sure DIB won't complain because of missing gpg files
# self.run('sed -i "s,gpgcheck=1,gpgcheck=0," /home/stack/DIB/*.repo', user='stack')
dib_yum_repo_conf = self.run('find /home/stack/DIB -type f', user='stack')[0].split()
virt_setup_template = {
'dib_yum_repo_conf': dib_yum_repo_conf,
'node': {
'count': 2,
'mem': 6144,
'cpu': 2
},
'undercloud_node_mem': 8192,
'guest_image_name': '/home/stack/guest_image.qcow2'
}
if rhsm is not None:
virt_setup_template['rhsm'] = {
'login': rhsm.get('login'),
'password': rhsm.get('password', os.environ.get('RHN_PW')),
'pool_id': rhsm.get('pool_id', ''),
'repositories': [i['name'] for i in repositories if i['type'] == 'rhsm_channel']
}
virt_setup_env = template.render(virt_setup_template)
self.create_file('virt-setup-env', virt_setup_env, user='stack')
self.run('virsh destroy instack', ignore_error=True)
self.run('virsh undefine instack --remove-all-storage', ignore_error=True)
self.run('source virt-setup-env; instack-virt-setup', user='stack')
undercloud_ip = self.run(
'/sbin/ip n | grep $(tripleo get-vm-mac instack) | awk \'{print $1;}\'',
user='stack')[0]
assert undercloud_ip, 'undercloud should have an IP'
undercloud = Undercloud(hostname=undercloud_ip,
via_ip=self.hostname,
user='root',
key_filename=self._key_filename)
return undercloud | [
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| bfa165538335edb1088170c7a92f097167225c81 | https://github.com/redhat-openstack/python-tripleo-helper/blob/bfa165538335edb1088170c7a92f097167225c81/tripleohelper/host0.py#L56-L105 | train |
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