Merge branch 'dev' into 'main'

hdf5 conversion

See merge request !2

.gitignore

+*.hdf5
+plots
+.ipynb_checkpoints/
+__pycache__/
+

functions.py

+import matplotlib.pyplot as plt
+import matplotlib as mpl
+import numpy as np
+
+
+def plt_ExampleImage(image, model_title='ML Model', save_title='ML_model', mode='comp', draw_3D=False, n=1):
+
+    #print(image.shape)
+    #data[B,Z,X,Y]
+    
+    cmap = mpl.cm.viridis
+    cmap.set_bad('white',1.)
+    
+    
+    #image = tf_logscale_rev_np(np.reshape(image,(1,30,30)))+1.0
+    
+    for k in range(n):
+        figExIm = plt.figure(figsize=(6,6))
+        axExIm1 = figExIm.add_subplot(1,1,1)
+        image1 = np.sum(image[k], axis=0)#+1.0
+        masked_array1 = np.ma.array(image1, mask=(image1==0.0))
+        im1 = axExIm1.imshow(masked_array1, filternorm=False, interpolation='none', cmap = cmap, vmin=0.001, vmax=1000,
+                           norm=mpl.colors.LogNorm(), origin='lower')
+        figExIm.patch.set_facecolor('white')
+        axExIm1.title.set_text(model_title + ' {:d}'.format(k))
+        axExIm1.set_xlabel('y [cells]', family='serif')
+        axExIm1.set_ylabel('x [cells]', family='serif')
+        figExIm.colorbar(im1)
+        plt.savefig('./' + save_title+"_CollapseZ_{:d}.png".format(k))
+
+        figExIm = plt.figure(figsize=(6,6))
+        axExIm2 = figExIm.add_subplot(1,1,1)    
+        image2 = np.sum(image[k], axis=1)#+1.0
+        masked_array2 = np.ma.array(image2, mask=(image2==0.0))
+        im2 = axExIm2.imshow(masked_array2, filternorm=False, interpolation='none', cmap = cmap, vmin=0.001, vmax=1000,
+                           norm=mpl.colors.LogNorm(), origin='lower') 
+        figExIm.patch.set_facecolor('white')
+        axExIm2.title.set_text(model_title + ' {:d}'.format(k))
+        axExIm2.set_xlabel('y [cells]', family='serif')
+        axExIm2.set_ylabel('z [layers]', family='serif')
+        figExIm.colorbar(im2)
+        plt.savefig('./' + save_title+"_CollapseX_{:d}.png".format(k))
+
+        figExIm = plt.figure(figsize=(6,6))
+        axExIm3 = figExIm.add_subplot(1,1,1)
+        image3 = np.sum(image[k], axis=2)#+1.0
+        masked_array3 = np.ma.array(image3, mask=(image3==0.0))
+        im3 = axExIm3.imshow(masked_array3, filternorm=False, interpolation='none', cmap = cmap, vmin=0.001, vmax=1000,
+                           norm=mpl.colors.LogNorm(), origin='lower')
+        figExIm.patch.set_facecolor('white')
+        axExIm3.title.set_text(model_title + ' {:d}'.format(k))
+        axExIm3.set_xlabel('x [cells]', family='serif')
+        axExIm3.set_ylabel('z [layers]', family='serif')
+        figExIm.colorbar(im3)
+        plt.savefig('./' + save_title+"_CollapseY_{:d}.png".format(k))
+
+    #print(np.min(image))
+    
+
+    figExIm = plt.figure(figsize=(6,6))
+    axExIm1 = figExIm.add_subplot(1,1,1)
+    image1 = np.mean(np.sum(image, axis=1), axis=0)#+1.0
+    masked_array1 = np.ma.array(image1, mask=(image1==0.0))
+    im1 = axExIm1.imshow(masked_array1, filternorm=False, interpolation='none', cmap = cmap, vmin=0.001, vmax=1000,
+                       norm=mpl.colors.LogNorm(), origin='lower')
+    figExIm.patch.set_facecolor('white')
+    axExIm1.title.set_text(model_title + 'overlay')
+    axExIm1.set_xlabel('y [cells]', family='serif')
+    axExIm1.set_ylabel('x [cells]', family='serif')
+    figExIm.colorbar(im1)
+    plt.savefig('./' + save_title+"_CollapseZSum.png")
+
+    figExIm = plt.figure(figsize=(6,6))
+    axExIm2 = figExIm.add_subplot(1,1,1)    
+    image2 = np.mean(np.sum(image, axis=2), axis=0)#+1.0
+    masked_array2 = np.ma.array(image2, mask=(image2==0.0))
+    im2 = axExIm2.imshow(masked_array2, filternorm=False, interpolation='none', cmap = cmap, vmin=0.001, vmax=1000,
+                       norm=mpl.colors.LogNorm(), origin='lower') 
+    figExIm.patch.set_facecolor('white')
+    axExIm2.title.set_text(model_title + 'overlay')
+    axExIm2.set_xlabel('y [cells]', family='serif')
+    axExIm2.set_ylabel('z [layers]', family='serif')
+    figExIm.colorbar(im2)
+    plt.savefig('./' + save_title+"__CollapseXSum.png")
+   
+    figExIm = plt.figure(figsize=(6,6))
+    axExIm3 = figExIm.add_subplot(1,1,1)    
+    image3 = np.mean(np.sum(image, axis=3), axis=0)#+1.0
+    masked_array3 = np.ma.array(image3, mask=(image3==0.0))
+    im3 = axExIm3.imshow(masked_array3, filternorm=False, interpolation='none', cmap = cmap, vmin=0.001, vmax=1000,
+                       norm=mpl.colors.LogNorm(), origin='lower')
+    figExIm.patch.set_facecolor('white')
+    axExIm3.title.set_text(model_title + 'overlay')
+    axExIm3.set_xlabel('x [cells]', family='serif')
+    axExIm3.set_ylabel('z [layers]', family='serif')
+    figExIm.colorbar(im3)
+    plt.savefig('./' + save_title+"_CollapseYSum.png")
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