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davidbhrdavidbhr
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Clean up comments & add SaveExcel / Saenopy option
1 parent c9c0a8e commit 344a441

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Lines changed: 32 additions & 39 deletions

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‎CompactionAnalyzer/CompactionFunctions.py‎

Lines changed: 32 additions & 39 deletions
Original file line numberDiff line numberDiff line change
@@ -260,7 +260,8 @@ def StuctureAnalysisMain(fiber_list,
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manual_segmention = False , # segmentation of mask by manual clicking the cell outline
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plotting = True , # creates and saves individual figures additionally to the excel files
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dpi = 200 , # resolution of figures
263-
SaveNumpy = False , # saves numpy arrays for later analysis - can create large data files
263+
SaveNumpy = True , # saves numpy arrays for later analysis
264+
SaveExcel = True , # saves Excel files for later analysis
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norm1=1,norm2 = 99 , # contrast spreading for input images between norm1- and norm2-percentile; values below norm1-percentile are set to zero and
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# values above norm2-percentile are set to 1
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### use norm1= 0,norm2 = 100 if no contras enhancement desired
@@ -270,7 +271,13 @@ def StuctureAnalysisMain(fiber_list,
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segmention_min_area = 1000, # small bjects below this px-area are removed during cell segmentation
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load_segmentation = False, # if True enter the path of the segementation.npy - file in path_seg
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path_seg = None, # to load a mask
273-
ignore_cell_outline=False): # if True the cell area is not set to nan and orientation are calculted everywhere - still the cell center is calculated from segmention
274+
ignore_cell_outline=False, # if True the cell area is not set to nan and orientation are calculted everywhere - still the cell center is calculated from segmention
275+
276+
277+
mode_saenopy=False): # only used for the Saenopy Version to return data files directly after single run
278+
279+
280+
274281
"""
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Main analysis
276283
@@ -491,7 +498,8 @@ def StuctureAnalysisMain(fiber_list,
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results_total['Orientation (weighted by intensity and coherency)'].append(cos_dev_total3)
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excel_total = pd.DataFrame.from_dict(results_total)
494-
excel_total.to_excel(os.path.join(out_list[n],"results_total.xlsx"))
501+
if SaveExcel:
502+
excel_total.to_excel(os.path.join(out_list[n],"results_total.xlsx"))
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"""
@@ -546,14 +554,18 @@ def StuctureAnalysisMain(fiber_list,
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# create excel sheet with results for angle analysis
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excel_angles= pd.DataFrame.from_dict(results_angle)
549-
excel_angles.to_excel(os.path.join(out_list[n],"results_angles.xlsx"))
550-
557+
if SaveExcel:
558+
excel_angles.to_excel(os.path.join(out_list[n],"results_angles.xlsx"))
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560+
552561
"""
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Distance Evaluation
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"""
555564

556-
# initialize result dictionary
565+
566+
# def distance_analysis(shells,shell_width,dist_surface,scale,angle_dev, ori, orientation_dev, weight_image,im_fiber_g):
567+
568+
# initialize result dictionary
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results_distance = {'Shell_mid (px)': [], 'Shell_mid (µm)': [], 'Intensity (accumulated)': [],
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'Intensity (individual)': [], 'Intensity Norm (individual)': [],
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'Intensity Norm (accumulated)': [], 'Angle (accumulated)': [], 'Angle (individual)': [], 'Angle (individual-weightInt)': [],
@@ -565,7 +577,7 @@ def StuctureAnalysisMain(fiber_list,
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'Angle disttocenter (accumulated)': [], 'Angle disttocenter (individual)': [],
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'Orientation disttocenter (accumulated)': [], 'Orientation disttocenter (individual)': [],
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'Angle disttocenter (individual)': []
568-
}
580+
}
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mask_shells = {'Mask_shell': [], 'Mask_shell_center': [] }
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# shell distances
@@ -598,7 +610,7 @@ def StuctureAnalysisMain(fiber_list,
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results_distance['Orientation (individual-weightInt)'].append(np.nanmean(orientation_dev[mask_shell]*ori[mask_shell]*weight_image[mask_shell]/np.nanmean(ori[mask_shell]*weight_image[mask_shell]) ))
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600612

601-
# mean intensity
613+
# mean intensity
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results_distance['Intensity (accumulated)'].append(np.nanmean(im_fiber_g[mask_shell_lower])) # accumulation of lower shells
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results_distance['Intensity (individual)'].append(np.nanmean(im_fiber_g[mask_shell]) ) # exclusively in certain shell
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@@ -632,7 +644,8 @@ def StuctureAnalysisMain(fiber_list,
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results_distance['Intensity Norm disttocenter (accumulated)'].extend(list(norm_accum_int_c) )
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# create excel sheet with results for angle analysis
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excel_distance = pd.DataFrame.from_dict(results_distance)
635-
excel_distance.to_excel(os.path.join(out_list[n],"results_distance.xlsx"))
647+
if SaveExcel:
648+
excel_distance.to_excel(os.path.join(out_list[n],"results_distance.xlsx"))
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638651

@@ -661,11 +674,11 @@ def StuctureAnalysisMain(fiber_list,
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#np.save(os.path.join(numpy_out, "mask_surface_shells.npy"),mask_shells['Mask_shell'])
662675
#np.save(os.path.join(numpy_out, "mask_spherical_shells.npy"),mask_shells['Mask_shell_center'])
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664-
# check the shapes --> everything is the same format
665-
# print(segmention["mask"][edge:-edge,edge:-edge].shape)
666-
# print(orientation_dev.shape)
667-
# print(normalize(im_fiber_n[edge:-edge,edge:-edge]).shape)
668-
# print(angle_no_reference.shape)
677+
# check the shapes --> everything is the same format
678+
# print(segmention["mask"][edge:-edge,edge:-edge].shape)
679+
# print(orientation_dev.shape)
680+
# print(normalize(im_fiber_n[edge:-edge,edge:-edge]).shape)
681+
# print(angle_no_reference.shape)
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671684
"""
@@ -682,25 +695,7 @@ def StuctureAnalysisMain(fiber_list,
682695
plot_angle_dev(angle_map = orientation_dev, vmin=-1,vmax=1,
683696
vec0=min_evec[:,:,0] ,vec1=min_evec[:,:,1] ,coherency_map=ori,
684697
path_png= os.path.join(figures,"Orientation.png"),label="Orientation",dpi=dpi,cmap="coolwarm")
685-
# plot orientation and angle deviation maps together with orientation structure
686-
# plot_angle_dev(angle_map = angle_dev, vmin=0,vmax=90,
687-
# vec0=min_evec[:,:,0] ,vec1=min_evec[:,:,1] ,coherency_map=ori,
688-
# path_png= os.path.join(figures,"Angle_deviation.png"),label="Angle Deviation",dpi=dpi,cmap="viridis_r")
689-
690-
# # do not show the weighted ones here, as only the mean has the same range again and here angles can be smaller/large
691-
# plot_angle_dev(angle_map = angle_dev_weighted2,
692-
# vec0=min_evec[:,:,0] ,vec1=min_evec[:,:,1] ,coherency_map=ori,
693-
# path_png= os.path.join(figures,"Angle_deviation_weighted.png"),label="Angle Deviation",dpi=dpi,cmap="viridis_r")
694-
# plot_angle_dev(angle_map = orientation_dev_weighted2 ,
695-
# vec0=min_evec[:,:,0] ,vec1=min_evec[:,:,1] ,coherency_map=ori,
696-
# path_png= os.path.join(figures,"Orientation_weighted.png"),label="Orientation",dpi=dpi,cmap="viridis")
697-
698-
# # pure coherency and pure orientation
699-
# plot_coherency(ori,path_png= os.path.join(figures,"coherency_noquiver.png"),
700-
# label="Coherency",vmin=0,vmax=1,cmap="turbo",dpi=dpi)
701-
# plot_coherency(orientation_dev,
702-
# path_png= os.path.join(figures,"Orientation_noquiver.png"),
703-
# label="Orientation",vmin=-1,vmax=1,cmap="coolwarm",dpi=dpi)
698+
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705700

706701
if cell_list == None:
@@ -726,8 +721,6 @@ def StuctureAnalysisMain(fiber_list,
726721
orientation_dev, cmap_angle="coolwarm",
727722
path_png= os.path.join(figures,"Orientation_overlay.png"),
728723
label="Orientation",dpi=dpi,
729-
# ,cmap_cell="Greys_r",cmap_fiber="Greys_r", ### use default values here
730-
# cmap_angle="viridis", alpha_ori =0.8, alpha_cell = 0.4, alpha_fiber = 0.4,
731724
omin=-1, omax=1,scale=scale)
732725

733726
else:
@@ -771,7 +764,6 @@ def StuctureAnalysisMain(fiber_list,
771764

772765

773766
plt.close("all")
774-
775767

776768
# Polar plots
777769
plot_polar(results_angle['Angles Plotting'], results_angle['Coherency (weighted by intensity)'],
@@ -807,7 +799,6 @@ def StuctureAnalysisMain(fiber_list,
807799
path_png=os.path.join(figures,"fiber_structure.png"),dpi=dpi ,scale=scale)
808800

809801

810-
811802
plt.close("all")
812803
### DISTANCE PLOTS
813804
# plot shells - deactived as it consumes a lot of time
@@ -825,8 +816,10 @@ def StuctureAnalysisMain(fiber_list,
825816
plot_cell(im_cell_n, path_png=os.path.join(figures,"cell-raw.png"), scale=scale, dpi=dpi)
826817
plot_cell(normalize(im_fiber_n[edge:-edge,edge:-edge]), path_png=os.path.join(figures,"fiber-raw.png"), scale=scale, dpi=dpi)
827818

828-
plt.close("all")
829-
819+
plt.close("all")
820+
821+
if mode_saenopy == True: # only evaluates a single item at each call and returns the arrays
822+
return excel_total, excel_angles, excel_distance
830823
return
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