File size: 5,089 Bytes
5ad11ec |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 |
from reports.BrightnessReport import BrightnessReport
from reports.DecodabilityReport import DecodabilityReport
from reports.MaskedBrightnessReport import MaskedBrightnessReport
from reports.FocusReport import FocusReport
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
import pandas as pd
# Brightness report worker-------
def generate_brightness_reports(image_stack_file,coord_info,out_file,fov,z):
#This was necessary to prototype on OSX...consider removing in the future after testing
import multiprocessing
job = multiprocessing.Process(target=brightness_worker,args=(image_stack_file,coord_info,out_file,fov,z))
job.start()
#brightness_worker(image_stack_file,coord_info,out_file,fov,fovs)
def brightness_worker(image_stack_file,coord_info,out_file,fov,z):
br = BrightnessReport(image_stack_file,coord_info,fov,z)
br.set_pdf(PdfPages(filename=out_file))
br.preview_images()
br.brightness_infov_z()
br.brightness_on_images()
br.contrast_heatmap()
br.closePdf()
# Masked Brightness report worker-------
def generate_masked_brightness_reports(image_stack_file,coord_info,out_file,fov,z,mask_stack):
#This was necessary to prototype on OSX...consider removing in the future after testing
import multiprocessing
job = multiprocessing.Process(target=masked_brightness_worker,args=(image_stack_file,mask_stack,coord_info,out_file,fov,z))
job.start()
def masked_brightness_worker(image_stack_file,mask_stack,coord_info,out_file,fov,z):
mbr = MaskedBrightnessReport(image_stack_file,mask_stack,coord_info,fov,z)
mbr.set_pdf(PdfPages(filename=out_file))
mbr.preview_images()
mbr.brightness_infov_z()
mbr.brightness_on_images()
mbr.contrast_heatmap()
mbr.closePdf()
# Decodability Report worker --------
def generate_decodability_reports(image_stack_file,coord_info,out_file,codebook_file,data_org_file,fov,z,out_detection_stats,):
#This was necessary to prototype on OSX...consider removing in the future after testing
import multiprocessing
job = multiprocessing.Process(target=decodability_worker,args=(image_stack_file,coord_info,out_file,codebook_file,data_org_file,fov,z,out_detection_stats))
job.start()
def decodability_worker(image_stack_file,coord_info,out_file,codebook_file,data_org_file,fov,z,out_detection_stats):
dr = DecodabilityReport(image_stack_file,coord_info,codebook_file,data_org_file,fov,z,out_detection_stats)
dr.set_pdf(PdfPages(filename=out_file))
dr.make_bit_imgs()
dr.make_decodability_hists()
dr.closePdf()
# Focus report worker-------
def generate_focus_reports(image_stack_file,coord_info,out_file,out_csv,fov):
#This was necessary to prototype on OSX...consider removing in the future after testing
import multiprocessing
job = multiprocessing.Process(target=focus_worker,args=(image_stack_file,coord_info,out_file,out_csv,fov))
job.start()
# focus_worker(image_stack_file,coord_info,out_file,out_csv,fov,fovs)
def focus_worker(image_stack_file,coord_info,out_file,out_csv,fov):
fr = FocusReport(image_stack_file,coord_info,fov,out_csv)
fr.set_pdf(PdfPages(filename=out_file))
fr.f_measure_report()
fr.closePdf()
# Compile reports----------------
def compile_focus_report(file_list:list,output,irs,wvs):
full_df = pd.DataFrame()
for fl in file_list:
test = pd.read_csv(fl)
full_df = full_df.append(test,ignore_index=True)
full_df.to_csv(output)
if not isinstance(irs,list):
irs = list(irs)
report_pdf = PdfPages(filename = output)
compiled_matrix = np.zeros((
len(file_list), # length of fovs
len(wvs),
len(irs)
))
for iir, ir in enumerate(irs):#for each ir
for iwv, wv in enumerate(wvs):#for each wv
data = full_df[["FOV",str(wv)]][(full_df["IR"]==int(ir))] #extract the FOVs...assume stuff is ordered
data = data.to_numpy() # FOV x 2
compiled_matrix[:,iwv,iir] = data[:,1] #this is the z
#ax[iir].plot("FOV",str(wv),data=data)
#x:FOV y:z spy:IR
f,ax = plt.subplots(nrows = len(wvs),ncols = 1,sharex=True,sharey=True,figsize=(8,len(irs)*4))
if not isinstance(ax,np.ndarray):
ax = np.array(ax)
for iwv, wv in enumerate(wvs):#for each wv
ax[iwv].imshow(compiled_matrix[:,iwv,:])
ax[iwv].set_xticks(np.arange(len(irs)), irs)
ax[iwv].set_yticks(np.arange(len(file_list)), np.arange(len(file_list)))
ax[iwv].set_ylabel("FOVS ")
ax[iwv].set_xlabel("Imaging Round")
plt.setp(ax[iwv].get_xticklabels(), rotation=45, ha="right", rotation_mode="anchor")
for iir in range(len(irs)):
for ifl in range(len(file_list)):
text = ax[iwv].text(iir, ifl, int(compiled_matrix[ifl,iwv, iir]), ha="center", va="center", color="w")
ax[iwv].set_title(f"Wavelength: {wv} nm")
report_pdf.savefig()
report_pdf.close()
|