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visu_coupe/main.py

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+# Import data
+import time
+import numpy as np
+from skimage import io
+import plotly.graph_objects as go
+from scipy.ndimage import uniform_filter1d
+from scipy.signal import savgol_filter
+from scipy import *
+from scipy.signal import *
+from util import *
+"""
+vol = io.imread("https://s3.amazonaws.com/assets.datacamp.com/blog_assets/attention-mri.tif")
+volume = vol.T
+r, c = volume[0].shape
+"""
+
+# Import data
+dossier = "Dataset/Shear_Wave_Rot00_CSV_Data"
+fichiers_selectionnes= fichiers_selectionnes = ['Shear_x001-x101_y{:03d}_Rot00.csv'.format(i) for i in range(10, 62)]
+print(fichiers_selectionnes)
+
+pre_volume= np.array(lire_fichier_csv(dossier,fichiers_selectionnes))
+pre_traitement = abs(hilbert(pre_volume))
+
+traitement = savgol_filter(pre_traitement, window_length=50, polyorder=5)
+
+volume = traitement[:, ::10, :]
+#volume = np.load('Dataset/3D_Dataset_All_Wave_PY_Data/3D_Dataset_shear_Wave_Rot00.npy')
+r, c = volume[0].shape
+# Define the number of frames based on the depth of the 3D volume
+nb_frames = volume.shape[0]
+
+# Define the z-scale based on the number of frames
+z_scale = 6.7 / nb_frames
+
+#custom_colorscale = [(0, 'blue'), (0.5, 'cyan'), (1, 'red')]
+
+fig = go.Figure(frames=[go.Frame(data=go.Surface(
+    z=(z_scale * nb_frames - k * z_scale) * np.ones((r, c)),
+    surfacecolor=np.flipud(volume[nb_frames - 1 - k]),
+    cmin=0, cmax=20000,
+    colorscale='Jet'
+    ),
+    name=str(k) # you need to name the frame for the animation to behave properly
+    )
+    for k in range(nb_frames)])
+
+# Add data to be displayed before animation starts
+fig.add_trace(go.Surface(
+    z=z_scale * nb_frames * np.ones((r, c)),
+    surfacecolor=np.flipud(volume[nb_frames - 1]),
+    colorscale='Jet',
+    cmin=-20000, cmax=20000,
+    colorbar=dict(thickness=20, ticklen=4)
+    ))
+
+def frame_args(duration):
+    return {
+            "frame": {"duration": duration},
+            "mode": "immediate",
+            "fromcurrent": True,
+            "transition": {"duration": duration, "easing": "linear"},
+        }
+
+sliders = [
+            {
+                "pad": {"b": 10, "t": 60},
+                "len": 0.9,
+                "x": 0.1,
+                "y": 0,
+                "steps": [
+                    {
+                        "args": [[f.name], frame_args(0)],
+                        "label": str(k),
+                        "method": "animate",
+                    }
+                    for k, f in enumerate(fig.frames)
+                ],
+            }
+        ]
+
+# Layout
+fig.update_layout(
+         title='Slices in volumetric data',
+         width=600,
+         height=600,
+         scene=dict(
+                    zaxis=dict(range=[-0.1, z_scale * nb_frames], autorange=False),
+                    aspectratio=dict(x=1, y=1, z=1),
+                    ),
+         updatemenus = [
+            {
+                "buttons": [
+                    {
+                        "args": [None, frame_args(50)],
+                        "label": "▶", # play symbol
+                        "method": "animate",
+                    },
+                    {
+                        "args": [[None], frame_args(0)],
+                        "label": "◼", # pause symbol
+                        "method": "animate",
+                    },
+                ],
+                "direction": "left",
+                "pad": {"r": 10, "t": 70},
+                "type": "buttons",
+                "x": 0.1,
+                "y": 0,
+            }
+         ],
+         sliders=sliders
+)
+
+fig.show()

visu_coupe/util.py

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+import csv
+import os
+
+def lire_un_fichier_csv(data):
+    tableau_2D = []
+    tab = []
+    with open(data, "r") as csv_file:
+        csv_reader = csv.reader(csv_file, delimiter=',')
+        for ligne in csv_reader:
+            tableau_2D.append(ligne)
+    for i in range(len(tableau_2D[0])):
+        ligne = []
+        for j in range(len(tableau_2D)):
+            ligne.append(float(tableau_2D[j][i]))
+        tab.append(ligne)
+    return tab
+
+def lire_fichier_csv(data,fichier):
+    resultat=[]
+    tableau=[]
+    for i in fichier:
+        tableau=lire_un_fichier_csv(os.path.join(data,i))
+        resultat.append(tableau)
+    return resultat