feat: Separate GUI callbacks for improved code readability
chore: Updated save/open function
This commit is contained in:
@ -29,3 +29,9 @@
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* Ajout des GNG
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* Ajout de config.json pour éditer la configuration de l'application plus facilement
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* Ajustement des callback pour éviter les bugs
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* Séparation des callbacks de la GUI pour faciliter la lecture du code
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## V4.1
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* Ajustement de la fonction d'enregistrement et d'ouverture des datasets
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* Ajout d'un bouton de sauvegarde pour les datasets filtrés
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@ -1,3 +1,18 @@
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# Test
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# 3D App
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Ceci est un test
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## Pages description
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**Home page**: On the home page, you will have the A-Scan, the two B-Scan and he 3D Plot. You can view them in fullscreen by clicking the fullscreen button on the top right of the card.
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**A-Scan filters**: On this page, you can apply filters on the dataset with custom values and see the difference with the raw dataset on the A-Scan graph.
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**GNG**: The GNG page is to reconstruct default of the dataset by neural network.
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## Navbar description
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**Settings**: Open the settings modal taht allows you to change the sampling values, if the filters must be applied on the entire dataset and the usage of real values of the dataset
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**Open**: Open a dataset present in `Dataset/saves` folder (only .npy files)
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**Save**: Save the current dataset in `Dataset/saves` folder
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313
3D_app/callbacks/ascan.py
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313
3D_app/callbacks/ascan.py
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@ -0,0 +1,313 @@
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from re import I
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from dash import callback, Input, Output, State
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from selection_filtre import switch_case
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import plotly.graph_objects as go
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import plotly.express as px
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from Bscan_Cscan_trait import Cscant, Bscant
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from util import lire_fichier_csv
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import numpy as np
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# on définit le dossier et les fichiers à lire
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dossier = "Dataset/Shear_Wave_Rot00_CSV_Data"
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fichiers_selectionnes = [
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"Shear_x001-x101_y{:03d}_Rot00.csv".format(i) for i in range(10, 13)
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]
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# on lit les fichiers et on les met dans un tableau
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pre_volume = np.array(lire_fichier_csv(dossier, fichiers_selectionnes))
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volume = pre_volume[:, :, :]
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data_traits = volume
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dim_x, dim_y, dim_z = volume.shape
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X, Y, Z = np.mgrid[0:dim_x, 0:dim_y, 0:dim_z]
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def get_callbacks():
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@callback(
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Output("store-filters", "data"),
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Input("button-validate-filter", "n_clicks"),
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[
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State("select-ascan-filter1", "value"),
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State("select-ascan-filter2", "value"),
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State("select-ascan-filter3", "value"),
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State("input-ascan-solo-fs", "value"),
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State("input-ascan-solo-cutoff", "value"),
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State("input-ascan-solo-order", "value"),
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State("input-ascan-solo-windowsize", "value"),
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State("input-ascan-solo-fs-2", "value"),
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State("input-ascan-solo-cutoff-2", "value"),
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State("input-ascan-solo-order-2", "value"),
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State("input-ascan-solo-windowsize-2", "value"),
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],
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)
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def store_settings(
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clicks,
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select_filtre_1,
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select_filtre_2,
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select_filtre_3,
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fs_filtre_1,
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cutoff_filtre_1,
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order_filtre_1,
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windowsize_filtre_1,
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fs_filtre_2,
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cutoff_filtre_2,
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order_filtre_2,
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windowsize_filtre_2,
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):
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if clicks:
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return {
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"select_filtre_1": select_filtre_1,
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"select_filtre_2": select_filtre_2,
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"select_filtre_3": select_filtre_3,
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"fs_filtre_1": fs_filtre_1,
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"cutoff_filtre_1": cutoff_filtre_1,
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"order_filtre_1": order_filtre_1,
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"windowsize_filtre_1": windowsize_filtre_1,
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"fs_filtre_2": fs_filtre_2,
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"cutoff_filtre_2": cutoff_filtre_2,
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"order_filtre_2": order_filtre_2,
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"windowsize_filtre_2": windowsize_filtre_2,
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}
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# callback to update filter values
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@callback(
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[
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Output("input-ascan-solo-fs", "disabled"),
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Output("input-ascan-solo-cutoff", "disabled"),
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Output("input-ascan-solo-order", "disabled"),
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Output("input-ascan-solo-windowsize", "disabled"),
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Output("input-ascan-solo-fs-2", "disabled"),
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Output("input-ascan-solo-cutoff-2", "disabled"),
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Output("input-ascan-solo-order-2", "disabled"),
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Output("input-ascan-solo-windowsize-2", "disabled"),
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],
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[
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Input("select-ascan-filter2", "value"),
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Input("select-ascan-filter3", "value"),
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],
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)
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def update_filter_values(select_filtre_1, select_filtre_2):
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fs_1 = True
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cutoff_1 = True
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ordre_1 = True
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windowsize_1 = True
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fs_2 = True
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cutoff_2 = True
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ordre_2 = True
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windowsize_2 = True
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if int(select_filtre_1) == 3:
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fs_1 = False
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cutoff_1 = False
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ordre_1 = False
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if int(select_filtre_2) == 3:
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fs_2 = False
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cutoff_2 = False
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ordre_2 = False
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if int(select_filtre_1) in (4, 5, 6, 7):
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windowsize_1 = False
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if int(select_filtre_2) in (4, 5, 6, 7):
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windowsize_2 = False
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return [
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fs_1,
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cutoff_1,
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ordre_1,
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windowsize_1,
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fs_2,
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cutoff_2,
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ordre_2,
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windowsize_2,
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]
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# callback to update the heatmap
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@callback(
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[
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Output("heatmap-ascan-solo", "figure"),
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Output("heatmap-bscan-solo", "figure"),
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Output("heatmap-fft-solo", "figure"),
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Output("loading", "children"),
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],
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[
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Input("layer-slider-ascan-solo-x", "value"),
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Input("layer-slider-ascan-solo-y", "value"),
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Input("layer-slider-ascan-solo-z", "value"),
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Input("button-validate-filter", "n_clicks"),
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],
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[
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State("select-ascan-filter1", "value"),
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State("select-ascan-filter2", "value"),
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State("select-ascan-filter3", "value"),
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State("input-ascan-solo-fs", "value"),
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State("input-ascan-solo-cutoff", "value"),
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State("input-ascan-solo-order", "value"),
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State("input-ascan-solo-windowsize", "value"),
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State("input-ascan-solo-fs-2", "value"),
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State("input-ascan-solo-cutoff-2", "value"),
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State("input-ascan-solo-order-2", "value"),
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State("input-ascan-solo-windowsize-2", "value"),
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],
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)
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def update_heatmap_ascan(
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select_ascan_x,
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select_ascan_y,
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select_ascan_z,
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n_clicks,
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selec_transforme_hilbert,
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select_filtre_1,
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select_filtre_2,
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fs_filtre_1,
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cutoff_filtre_1,
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order_filtre_1,
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windowsize_filtre_1,
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fs_filtre_2,
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cutoff_filtre_2,
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order_filtre_2,
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windowsize_filtre_2,
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):
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print("debut du traitement")
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data_avec_traitement = volume[
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int(select_ascan_y) - 1,
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select_ascan_z[0] : select_ascan_z[1],
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int(select_ascan_x) - 1,
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]
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data_sans_traitement = volume[
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int(select_ascan_y) - 1,
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select_ascan_z[0] : select_ascan_z[1],
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int(select_ascan_x) - 1,
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]
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data_avec_traitement = switch_case(
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data_avec_traitement, int(selec_transforme_hilbert)
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)
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data_sans_traitement = switch_case(
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data_sans_traitement, int(selec_transforme_hilbert)
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)
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data_avec_traitement = switch_case(
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data_avec_traitement,
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int(select_filtre_1),
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float(fs_filtre_1),
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float(cutoff_filtre_1),
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int(order_filtre_1),
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int(windowsize_filtre_1),
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)
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data_avec_traitement = switch_case(
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data_avec_traitement,
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int(select_filtre_2),
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float(fs_filtre_2),
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float(cutoff_filtre_2),
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int(order_filtre_2),
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int(windowsize_filtre_2),
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)
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print("fin du traitement")
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bouton = "Apply"
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if n_clicks != None:
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data_traits = Cscant(
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volume,
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int(selec_transforme_hilbert),
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int(select_filtre_1),
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int(select_filtre_2),
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float(fs_filtre_1),
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float(cutoff_filtre_1),
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int(order_filtre_1),
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int(windowsize_filtre_1),
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float(fs_filtre_2),
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float(cutoff_filtre_2),
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int(order_filtre_2),
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int(windowsize_filtre_2),
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)
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bouton = "Apply"
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fig = px.line(title="A-scan")
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new_trace = go.Scatter(y=data_avec_traitement, mode="lines", name="Ascan trait")
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fig.add_trace(new_trace)
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new_trace = go.Scatter(
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y=data_sans_traitement, mode="lines", name="Ascan (hilbert)"
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)
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fig.add_trace(new_trace)
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fig.update_layout(xaxis_title="Indix", yaxis_title="Amplitude")
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data_bscan = Bscant(
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volume[select_ascan_y - 1, select_ascan_z[0] : select_ascan_z[1], :],
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int(selec_transforme_hilbert),
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int(select_filtre_1),
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int(select_filtre_2),
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float(fs_filtre_1),
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float(cutoff_filtre_1),
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int(order_filtre_1),
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int(windowsize_filtre_1),
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float(fs_filtre_2),
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float(cutoff_filtre_2),
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int(order_filtre_2),
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int(windowsize_filtre_2),
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)
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fig2 = px.imshow(
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data_bscan,
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color_continuous_scale="Jet",
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aspect="auto",
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title="B-scan XZ",
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)
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fig2.update_layout(xaxis_title="Z", yaxis_title=" X")
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data_sans_traitement_fft = np.fft.fft(
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volume[
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int(select_ascan_y) - 1,
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select_ascan_z[0] : select_ascan_z[1],
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int(select_ascan_x) - 1,
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]
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)
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fig3 = px.line(title="FFT")
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trace3 = go.Scatter(
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y=np.abs(data_sans_traitement_fft), mode="lines", name=" FFT "
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)
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fig3.add_trace(trace3)
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fig3.update_layout(
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xaxis_title="FFT indix", yaxis_title="FFT of signal (Mangnitude)"
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)
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return [fig, fig2, fig3, bouton]
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@callback(
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[
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Output("select-ascan-filter1", "value"),
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Output("select-ascan-filter2", "value"),
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Output("select-ascan-filter3", "value"),
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Output("input-ascan-solo-fs", "value"),
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Output("input-ascan-solo-cutoff", "value"),
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Output("input-ascan-solo-order", "value"),
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Output("input-ascan-solo-windowsize", "value"),
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Output("input-ascan-solo-fs-2", "value"),
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Output("input-ascan-solo-cutoff-2", "value"),
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Output("input-ascan-solo-order-2", "value"),
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Output("input-ascan-solo-windowsize-2", "value"),
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],
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Input("store-filters", "data"),
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)
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def load_filters(data):
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if data:
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return [
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data["select_filtre_1"],
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data["select_filtre_2"],
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data["select_filtre_3"],
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data["fs_filtre_1"],
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data["cutoff_filtre_1"],
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data["order_filtre_1"],
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data["windowsize_filtre_1"],
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data["fs_filtre_2"],
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data["cutoff_filtre_2"],
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data["order_filtre_2"],
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data["windowsize_filtre_2"],
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]
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return [1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1]
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@callback(
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[Output("modal-ascan-solo", "is_open"), Output("save-toast", "is_open", allow_duplicate=True)],
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[Input("save-ascan-solo", "n_clicks"), Input("button-save-data", "n_clicks")],
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[State("modal-ascan-solo", "is_open"), State("input-save-ascan", "value")],
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prevent_initial_call=True,
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)
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def toggle_modal(n1, n2, is_open, filename):
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if n1:
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np.save(f"Dataset/saves/{filename}.npy", data_traits)
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return [not is_open, True]
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elif n2:
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return [not is_open, False]
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return [is_open, False]
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82
3D_app/callbacks/gng.py
Normal file
82
3D_app/callbacks/gng.py
Normal file
@ -0,0 +1,82 @@
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from dash import callback_context as ctx
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from dash import callback, Output, Input
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import numpy as np
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import plotly.graph_objects as go
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from GNG_3D import *
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from pages.ascan import data_traits
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def get_callbacks():
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@callback(
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[Output("gng-graph", "figure")],
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[
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Input("generate-gng", "n_clicks"),
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Input("seuil", "value"),
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Input("max_neurons", "value"),
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Input("Iterations", "value"),
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Input("Max_of_age", "value"),
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Input("eb", "value"),
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Input("en", "value"),
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Input("alpha", "value"),
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Input("beta", "value"),
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Input("l", "value"),
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],
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)
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def generate_gng(n_clicks, seuil, max_neurons, max_iter, max_age, eb, en, alpha, beta, l):
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global clics
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if n_clicks:
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data=np.array(data_traits)
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fig = go.Figure()
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size_data=np.shape(data)
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x1=[]
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x2=[]
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x3=[]
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x4=[]
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for i in range(0,size_data[0]):
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res=data[i,:,:]
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res=position_point_espace(data=res,seuil=200,y=i)
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res = np.array(res)
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x1.append(res)
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gng = GrowingNeuralGas(int(max_neurons),int(max_iter),int(max_age), float(eb), float(en), float(alpha), float(beta),int(l), res)
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gng_graph = gng.learn()
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neuron_positions = np.array([vertex['weight'] for vertex in gng_graph.vs])
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neuron_edge= np.array([(edge.source, edge.target) for edge in gng_graph.es])
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for edge in gng_graph.es:
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src, tgt = edge.source, edge.target
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src_pos, tgt_pos = gng_graph.vs[src]['weight'], gng_graph.vs[tgt]['weight']
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x3.append(src_pos)
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x4.append(tgt_pos)
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x2.append(neuron_positions)
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res=np.vstack(x1)
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neuron_positions=np.vstack(x2)
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src_pos=np.vstack(x3)
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tgt_pos=np.vstack(x4)
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fig.add_trace(go.Scatter3d(
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x=res[:, 0],
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y=res[:, 1],
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z=res[:, 2],
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mode='markers',
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marker=dict(size=1, color=res[:, 3], colorscale='Viridis', opacity=0.5),
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name='Data'
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))
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fig.add_trace(go.Scatter3d(
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x=neuron_positions[:, 0],
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y=neuron_positions[:, 1],
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z=neuron_positions[:, 2],
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mode='markers',
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marker=dict(size=4, color=neuron_positions[:,3]),
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name='Neurons'
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))
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for src, tgt in zip(src_pos, tgt_pos):
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fig.add_trace(go.Scatter3d(
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x=[src[0], tgt[0]],
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y=[src[1], tgt[1]],
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z=[src[2], tgt[2]],
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mode='lines',
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line=dict(color="black", width=1),
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showlegend=False,
|
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))
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clics = n_clicks
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return [fig]
|
||||
return [go.Figure().update_layout(title="No data", showlegend=False).update_xaxes(visible=False).update_yaxes(visible=False)]
|
||||
532
3D_app/callbacks/home.py
Normal file
532
3D_app/callbacks/home.py
Normal file
@ -0,0 +1,532 @@
|
||||
from dash import State, Output, Input, callback
|
||||
import dash
|
||||
import numpy as np
|
||||
import plotly.graph_objects as go
|
||||
import plotly.express as px
|
||||
from os.path import join
|
||||
from util import lire_fichier_csv
|
||||
from selection_filtre import switch_case
|
||||
|
||||
# on définit le dossier et les fichiers à lire
|
||||
dossier = "Dataset/Shear_transform"
|
||||
fichiers_selectionnes = [
|
||||
"Shear_x001-x101_y{:03d}_Rot00_transform.csv".format(i) for i in range(10, 14)
|
||||
]
|
||||
|
||||
# valeurs d'échantillonage
|
||||
echantillonage_x = 1
|
||||
echantillonage_y = 32
|
||||
echantillonage_z = 1
|
||||
|
||||
pre_volume = np.array(lire_fichier_csv(dossier, fichiers_selectionnes))
|
||||
volume = pre_volume[::echantillonage_x, ::echantillonage_y, ::echantillonage_z]
|
||||
dim_x, dim_y, dim_z = volume.shape
|
||||
|
||||
X, Y, Z = np.mgrid[0:dim_x, 0:dim_y, 0:dim_z]
|
||||
|
||||
|
||||
def get_callbacks():
|
||||
@callback(
|
||||
[Output("3dplot", "figure"), Output("fade-3dplot", "is_in")],
|
||||
[
|
||||
Input("iso-slider", "value"),
|
||||
Input("y-slider", "value"),
|
||||
Input("store-settings", "data"),
|
||||
],
|
||||
[dash.dependencies.State("fade-3dplot", "is_in")],
|
||||
)
|
||||
def update_3dplot(iso_value, y_values, settings, is_in):
|
||||
if settings["use_real_values"]:
|
||||
y_min, y_max = y_values
|
||||
selected_volume = volume[0:dim_x, int(y_min) : int(y_max), 0:dim_z]
|
||||
X, Y, Z = [
|
||||
np.load("Dataset/npy/{}-values.npy".format(i)) for i in ["x", "y", "z"]
|
||||
]
|
||||
else:
|
||||
y_min, y_max = y_values
|
||||
selected_volume = volume[0:dim_x, int(y_min) : int(y_max), 0:dim_z]
|
||||
X, Y, Z = np.mgrid[
|
||||
0 : selected_volume.shape[0],
|
||||
0 : selected_volume.shape[1],
|
||||
0 : selected_volume.shape[2],
|
||||
]
|
||||
|
||||
fig = go.Figure(
|
||||
data=go.Volume(
|
||||
x=X.flatten(),
|
||||
y=Y.flatten(),
|
||||
z=Z.flatten(),
|
||||
value=selected_volume.flatten(),
|
||||
isomin=iso_value,
|
||||
isomax=selected_volume.max(),
|
||||
opacity=0.1,
|
||||
surface_count=20,
|
||||
colorscale="Jet",
|
||||
)
|
||||
)
|
||||
|
||||
return [fig, True]
|
||||
|
||||
# callback pour le plot 3D en plein écran
|
||||
@callback(
|
||||
Output("3dplot-fullscreen", "figure"),
|
||||
[
|
||||
Input("iso-slider-fullscreen", "value"),
|
||||
Input("y-slider-fullscreen", "value"),
|
||||
],
|
||||
)
|
||||
def update_3dplot_fullscreen(iso_value, y_values):
|
||||
y_min, y_max = y_values
|
||||
selected_volume = volume[0:dim_x, int(y_min) : int(y_max), 0:dim_z]
|
||||
X, Y, Z = np.mgrid[
|
||||
0 : selected_volume.shape[0],
|
||||
0 : selected_volume.shape[1],
|
||||
0 : selected_volume.shape[2],
|
||||
]
|
||||
|
||||
fig = go.Figure(
|
||||
data=go.Volume(
|
||||
x=X.flatten(),
|
||||
y=Y.flatten(),
|
||||
z=Z.flatten(),
|
||||
value=selected_volume.flatten(),
|
||||
isomin=iso_value,
|
||||
isomax=selected_volume.max(),
|
||||
opacity=0.1,
|
||||
surface_count=20,
|
||||
colorscale="Jet",
|
||||
)
|
||||
)
|
||||
|
||||
return fig
|
||||
|
||||
# callback pour le A-scan
|
||||
@callback(
|
||||
[Output("heatmap-ascan", "figure"), Output("fade-ascan", "is_in")],
|
||||
[
|
||||
Input("layer-slider-bscan-zx", "value"),
|
||||
Input("layer-slider-bscan-xy", "value"),
|
||||
],
|
||||
[dash.dependencies.State("fade-ascan", "is_in")],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_heatmap_ascan(layer, layer1, is_in):
|
||||
fig = px.line(y=volume[layer - 1, :, layer1], title="A-scan")
|
||||
|
||||
return [fig, True]
|
||||
|
||||
# callback pour le A-scan en plein écran
|
||||
@callback(
|
||||
Output("heatmap-ascan-fullscreen", "figure"),
|
||||
Input("layer-slider-ascan-fullscreen", "value"),
|
||||
)
|
||||
def update_heatmap_ascan_fullscreen(layer):
|
||||
fig = px.line(y=volume[layer - 1, :, 5], title="A-scan")
|
||||
return fig
|
||||
|
||||
# callback pour les B-scan XY
|
||||
@callback(
|
||||
[
|
||||
Output("heatmap-bscan-zx", "figure"),
|
||||
Output("store-bscan-zx-layer", "data"),
|
||||
Output("fade-bscan-xy", "is_in"),
|
||||
],
|
||||
[Input("layer-slider-bscan-zx", "value")],
|
||||
[dash.dependencies.State("fade-bscan-zx", "is_in")],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_heatmap_bscan_zx(layer, is_in):
|
||||
fig = px.imshow(
|
||||
volume[layer - 1, :, :],
|
||||
color_continuous_scale="Jet",
|
||||
aspect="auto",
|
||||
title="B-scan ZX",
|
||||
)
|
||||
|
||||
return [fig, layer, True]
|
||||
|
||||
# callback pour les B-scan ZX en plein écran
|
||||
@callback(
|
||||
Output("heatmap-bscan-zx-fullscreen", "figure"),
|
||||
Input("layer-slider-bscan-zx-fullscreen", "value"),
|
||||
)
|
||||
def update_heatmap_bscan_zx_fullscreen(layer):
|
||||
fig = px.imshow(
|
||||
volume[layer - 1, :, :],
|
||||
color_continuous_scale="Jet",
|
||||
aspect="auto",
|
||||
title="B-scan ZX",
|
||||
)
|
||||
|
||||
return fig
|
||||
|
||||
# callback pour les B-scan ZX
|
||||
@callback(
|
||||
[
|
||||
Output("heatmap-bscan-xy", "figure"),
|
||||
Output("store-bscan-xy-layer", "data"),
|
||||
Output("fade-bscan-zx", "is_in"),
|
||||
],
|
||||
[Input("layer-slider-bscan-xy", "value")],
|
||||
[dash.dependencies.State("fade-bscan-xy", "is_in")],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_heatmap_bscan_xy(layer, is_in):
|
||||
fig = go.Figure(data=go.Heatmap(z=volume[:, :, layer], colorscale="Jet"))
|
||||
fig.update_layout(title="B-scan XY")
|
||||
|
||||
return [fig, layer, True]
|
||||
|
||||
# callback pour les B-scan ZX en plein écran
|
||||
@callback(
|
||||
Output("heatmap-bscan-xy-fullscreen", "figure"),
|
||||
Input("layer-slider-bscan-xy-fullscreen", "value"),
|
||||
)
|
||||
def update_heatmap_bscan_xy_fullscreen(layer):
|
||||
fig = go.Figure(data=go.Heatmap(z=volume[:, :, layer], colorscale="Jet"))
|
||||
fig.update_layout(title="B-scan XY")
|
||||
|
||||
return fig
|
||||
|
||||
# callback pour le plein écran du plot 3D
|
||||
@callback(
|
||||
Output("modal-3dplot", "is_open"),
|
||||
[Input("fullscreen-button-3dplot", "n_clicks")],
|
||||
[dash.dependencies.State("modal-3dplot", "is_open")],
|
||||
)
|
||||
def toggle_fullscreen_3dplot(n1, is_open):
|
||||
if n1:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
# callback pour le plein écran du A-scan
|
||||
@callback(
|
||||
Output("modal-ascan", "is_open"),
|
||||
[Input("fullscreen-button-ascan", "n_clicks")],
|
||||
[dash.dependencies.State("modal-ascan", "is_open")],
|
||||
)
|
||||
def toggle_fullscreen_ascan(n1, is_open):
|
||||
if n1:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
# callback pour le plein écran du B-scan XY
|
||||
@callback(
|
||||
Output("modal-bscan-xy", "is_open"),
|
||||
[Input("fullscreen-button-bscan-xy", "n_clicks")],
|
||||
[dash.dependencies.State("modal-bscan-xy", "is_open")],
|
||||
)
|
||||
def toggle_fullscreen_bscan_xy(n1, is_open):
|
||||
if n1:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
# callback pour le plein écran du B-scan ZX
|
||||
@callback(
|
||||
Output("modal-bscan-zx", "is_open"),
|
||||
[Input("fullscreen-button-bscan-zx", "n_clicks")],
|
||||
[dash.dependencies.State("modal-bscan-zx", "is_open")],
|
||||
)
|
||||
def toggle_fullscreen_bscan_zx(n1, is_open):
|
||||
if n1:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("3dplot", "clickData"),
|
||||
Output("layer-slider-bscan-xy", "value"),
|
||||
Output("layer-slider-bscan-zx", "value"),
|
||||
],
|
||||
Input("3dplot", "clickData"),
|
||||
)
|
||||
def display_3dplot_click_data(clickData):
|
||||
if clickData is None:
|
||||
return [None, 1, 1]
|
||||
|
||||
bscan_xy = clickData["points"][0]["z"]
|
||||
bscan_zx = clickData["points"][0]["x"]
|
||||
return [clickData, bscan_xy, bscan_zx]
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("heatmap-bscan-xy", "clickData"),
|
||||
Output("layer-slider-bscan-zx", "value", allow_duplicate=True),
|
||||
],
|
||||
[Input("heatmap-bscan-xy", "clickData")],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def display_bscan_xy_click_data(clickData):
|
||||
if clickData is None:
|
||||
return [None, 1]
|
||||
|
||||
bscan_zx = clickData["points"][0]["y"]
|
||||
return [clickData, bscan_zx]
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("heatmap-bscan-zx", "clickData"),
|
||||
Output("layer-slider-bscan-xy", "value", allow_duplicate=True),
|
||||
],
|
||||
[Input("heatmap-bscan-zx", "clickData")],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def display_bscan_zx_click_data(clickData):
|
||||
if clickData is None:
|
||||
return [None, 0]
|
||||
|
||||
bscan_xy = clickData["points"][0]["x"]
|
||||
return [clickData, bscan_xy]
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("heatmap-bscan-xy", "figure", allow_duplicate=True),
|
||||
Output("heatmap-bscan-zx", "figure", allow_duplicate=True),
|
||||
Output("heatmap-ascan", "figure", allow_duplicate=True),
|
||||
],
|
||||
[Input("store-bscan-xy-layer", "data"), Input("store-bscan-zx-layer", "data")],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_bscan_layers(bscan_xy, bscan_zx):
|
||||
fig = go.Figure(data=go.Heatmap(z=volume[:, :, bscan_xy], colorscale="Jet"))
|
||||
fig.add_shape(
|
||||
type="line",
|
||||
x0=0 - 1,
|
||||
y0=bscan_zx,
|
||||
x1=dim_y,
|
||||
y1=bscan_zx,
|
||||
line=dict(color="white", width=1),
|
||||
)
|
||||
fig.update_layout(title="B-scan XY")
|
||||
|
||||
fig2 = px.imshow(
|
||||
volume[bscan_zx - 1, :, :],
|
||||
color_continuous_scale="Jet",
|
||||
aspect="auto",
|
||||
title="B-scan ZX",
|
||||
)
|
||||
fig2.add_shape(
|
||||
type="line",
|
||||
x0=bscan_xy,
|
||||
y0=0,
|
||||
x1=bscan_xy,
|
||||
y1=dim_y,
|
||||
line=dict(color="white", width=1),
|
||||
)
|
||||
|
||||
fig3 = px.line(y=volume[bscan_zx - 1, :, bscan_xy], title="A-scan")
|
||||
|
||||
return [fig, fig2, fig3]
|
||||
|
||||
@callback(
|
||||
[Output("store-settings", "data"), Output("settings-apply", "n_clicks")],
|
||||
[
|
||||
Input("settings-apply", "n_clicks"),
|
||||
],
|
||||
[
|
||||
State("use-real-values", "value"),
|
||||
State("apply-filters-everywhere", "value"),
|
||||
State("echantillonage-x", "value"),
|
||||
State("echantillonage-y", "value"),
|
||||
State("echantillonage-z", "value"),
|
||||
],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_settings(
|
||||
clicks,
|
||||
use_real_values,
|
||||
apply_filters,
|
||||
echantillonage_x_value,
|
||||
echantillonage_y_value,
|
||||
echantillonage_z_value,
|
||||
):
|
||||
if clicks != None and clicks == 1:
|
||||
return [
|
||||
{
|
||||
"use_real_values": use_real_values,
|
||||
"use_filters": apply_filters,
|
||||
"echantillonage_x": echantillonage_x_value,
|
||||
"echantillonage_y": echantillonage_y_value,
|
||||
"echantillonage_z": echantillonage_z_value,
|
||||
},
|
||||
0,
|
||||
]
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("layer-slider-bscan-zx", "max"),
|
||||
Output("layer-slider-bscan-zx", "marks"),
|
||||
Output("layer-slider-bscan-xy", "max"),
|
||||
Output("layer-slider-bscan-xy", "marks"),
|
||||
Output("iso-slider", "min"),
|
||||
Output("iso-slider", "max"),
|
||||
Output("iso-slider", "marks"),
|
||||
Output("y-slider", "max"),
|
||||
Output("y-slider", "marks"),
|
||||
Output("layer-slider-ascan-fullscreen", "max"),
|
||||
Output("layer-slider-ascan-fullscreen", "marks"),
|
||||
Output("layer-slider-bscan-xy-fullscreen", "max"),
|
||||
Output("layer-slider-bscan-xy-fullscreen", "marks"),
|
||||
Output("layer-slider-bscan-zx-fullscreen", "max"),
|
||||
Output("layer-slider-bscan-zx-fullscreen", "marks"),
|
||||
Output("iso-slider-fullscreen", "min"),
|
||||
Output("iso-slider-fullscreen", "max"),
|
||||
Output("iso-slider-fullscreen", "marks"),
|
||||
Output("y-slider-fullscreen", "max"),
|
||||
Output("y-slider-fullscreen", "marks"),
|
||||
Output("settings-spinner", "children"),
|
||||
],
|
||||
Input("store-settings", "data"),
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def redef_data(data):
|
||||
global volume, pre_volume, dim_x, dim_y, dim_z, X, Y, Z
|
||||
volume = pre_volume[
|
||||
:: data["echantillonage_x"],
|
||||
:: data["echantillonage_y"],
|
||||
:: data["echantillonage_z"],
|
||||
]
|
||||
dim_x, dim_y, dim_z = volume.shape
|
||||
X, Y, Z = np.mgrid[0:dim_x, 0:dim_y, 0:dim_z]
|
||||
|
||||
return [
|
||||
dim_x - 1,
|
||||
{str(i): str(i) for i in range(0, dim_x, max(1, int(dim_x / 20)))},
|
||||
dim_z - 1,
|
||||
{str(i): str(i) for i in range(1, dim_z + 1, max(1, int(dim_z / 20)))},
|
||||
volume.min(),
|
||||
volume.max() / 2,
|
||||
{
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
int(volume.min()),
|
||||
int(volume.max() / 2) + 1,
|
||||
int((volume.max() / 2 - volume.min()) / 10),
|
||||
)
|
||||
},
|
||||
dim_y,
|
||||
{str(i): str(i) for i in range(0, int(dim_y) + 1, max(1, int(dim_y / 20)))},
|
||||
dim_x - 1,
|
||||
{str(i): str(i) for i in range(0, dim_x, max(1, int(dim_x / 20)))},
|
||||
dim_x - 1,
|
||||
{str(i): str(i) for i in range(0, dim_x, max(1, int(dim_x / 20)))},
|
||||
dim_z - 1,
|
||||
{str(i): str(i) for i in range(1, dim_z + 1, max(1, int(dim_z / 20)))},
|
||||
volume.min(),
|
||||
volume.max() / 2,
|
||||
{
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
int(volume.min()),
|
||||
int(volume.max() / 2) + 1,
|
||||
int((volume.max() / 2 - volume.min()) / 10),
|
||||
)
|
||||
},
|
||||
dim_y,
|
||||
{str(i): str(i) for i in range(0, int(dim_y) + 1, max(1, int(dim_y / 20)))},
|
||||
"Apply",
|
||||
]
|
||||
|
||||
@callback(
|
||||
Output("store-filters", "data", allow_duplicate=True),
|
||||
[Input("store-filters", "data"), Input("store-settings", "data")],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def apply_filters(data, settings):
|
||||
global volume, pre_volume
|
||||
if settings["use_filters"]:
|
||||
select_filtre_1 = data["select_filtre_2"]
|
||||
select_filtre_2 = data["select_filtre_3"]
|
||||
fs_filtre_1 = data["fs_filtre_1"]
|
||||
cutoff_filtre_1 = data["cutoff_filtre_1"]
|
||||
order_filtre_1 = data["order_filtre_1"]
|
||||
windowsize_filtre_1 = data["windowsize_filtre_1"]
|
||||
fs_filtre_2 = data["fs_filtre_2"]
|
||||
cutoff_filtre_2 = data["cutoff_filtre_2"]
|
||||
order_filtre_2 = data["order_filtre_2"]
|
||||
windowsize_filtre_2 = data["windowsize_filtre_2"]
|
||||
selec_transforme_hilbert = data["select_filtre_1"]
|
||||
|
||||
volume = pre_volume[
|
||||
:: settings["echantillonage_x"],
|
||||
:: settings["echantillonage_y"],
|
||||
:: settings["echantillonage_z"],
|
||||
]
|
||||
|
||||
data_avec_traitement = switch_case(volume, int(selec_transforme_hilbert))
|
||||
|
||||
data_avec_traitement = switch_case(
|
||||
data_avec_traitement,
|
||||
int(select_filtre_1),
|
||||
int(fs_filtre_1),
|
||||
int(cutoff_filtre_1),
|
||||
int(order_filtre_1),
|
||||
int(windowsize_filtre_1),
|
||||
)
|
||||
data_avec_traitement = switch_case(
|
||||
data_avec_traitement,
|
||||
int(select_filtre_2),
|
||||
int(fs_filtre_2),
|
||||
int(cutoff_filtre_2),
|
||||
int(order_filtre_2),
|
||||
int(windowsize_filtre_2),
|
||||
)
|
||||
volume = data_avec_traitement
|
||||
redef_data(settings)
|
||||
else:
|
||||
volume = pre_volume[
|
||||
:: settings["echantillonage_x"],
|
||||
:: settings["echantillonage_y"],
|
||||
:: settings["echantillonage_z"],
|
||||
]
|
||||
return data
|
||||
|
||||
@callback(
|
||||
Output("store-files", "data", allow_duplicate=True),
|
||||
Input("store-files", "data"),
|
||||
State("store-settings", "data"),
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_files(data, settings):
|
||||
global pre_volume, volume, dim_x, dim_y, dim_z, X, Y, Z
|
||||
if data is None or data == "":
|
||||
return None
|
||||
|
||||
# Charger le nouveau volume
|
||||
pre_volume = np.load(join("Dataset/saves", data))
|
||||
print("New volume loaded:", pre_volume.shape)
|
||||
|
||||
# Appliquer les nouveaux paramètres d'échantillonnage
|
||||
volume = pre_volume[
|
||||
::settings["echantillonage_x"],
|
||||
::settings["echantillonage_y"],
|
||||
::settings["echantillonage_z"],
|
||||
]
|
||||
dim_x, dim_y, dim_z = volume.shape
|
||||
X, Y, Z = np.mgrid[0:dim_x, 0:dim_y, 0:dim_z]
|
||||
print("Volume updated with new dimensions:", volume.shape)
|
||||
|
||||
# Mettre à jour les graphiques
|
||||
update_3dplot(0, [0, dim_y // 2], settings, False)
|
||||
update_heatmap_ascan(0, 0, False)
|
||||
update_heatmap_bscan_zx(0, False)
|
||||
update_heatmap_bscan_xy(0, False)
|
||||
|
||||
return None
|
||||
|
||||
@callback(
|
||||
Output("save-toast", "is_open"),
|
||||
Input("save-save", "n_clicks"),
|
||||
[
|
||||
State("save-input", "value"),
|
||||
State("save-format", "value"),
|
||||
],
|
||||
)
|
||||
def save_data(n_clicks, filename, format):
|
||||
if n_clicks is None:
|
||||
return False
|
||||
if format == "raw":
|
||||
np.save(join("Dataset/saves", filename), pre_volume)
|
||||
else:
|
||||
np.save(join("Dataset/saves", filename), volume)
|
||||
return True
|
||||
120
3D_app/callbacks/main.py
Normal file
120
3D_app/callbacks/main.py
Normal file
@ -0,0 +1,120 @@
|
||||
from dash import Input, Output, State, ALL, callback
|
||||
import dash
|
||||
from os import listdir
|
||||
from os.path import isfile, join
|
||||
import dash_bootstrap_components as dbc
|
||||
|
||||
def get_callbacks():
|
||||
# callback pour le modal
|
||||
@callback(
|
||||
Output("modal", "is_open"),
|
||||
[Input("howto-open", "n_clicks"), Input("howto-close", "n_clicks")],
|
||||
[dash.dependencies.State("modal", "is_open")],
|
||||
)
|
||||
def toggle_modal(n1, n2, is_open):
|
||||
if n1 or n2:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
@callback(
|
||||
Output("settings-modal", "is_open"),
|
||||
[Input("settings-open", "n_clicks"), Input("settings-close", "n_clicks")],
|
||||
[dash.dependencies.State("settings-modal", "is_open")],
|
||||
)
|
||||
def toggle_settings(n1, n2, is_open):
|
||||
if n1 or n2:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
# callback pour le navmenu
|
||||
@callback(
|
||||
Output("offcanvas-menu", "is_open"),
|
||||
[Input("navbar-toggler", "n_clicks")],
|
||||
[dash.dependencies.State("offcanvas-menu", "is_open")],
|
||||
)
|
||||
def toggle_offcanvas(n, is_open):
|
||||
if n:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
@callback(
|
||||
Output("open-modal", "is_open"),
|
||||
[Input("open-button", "n_clicks"), Input("open-close", "n_clicks")],
|
||||
[dash.dependencies.State("open-modal", "is_open")],
|
||||
)
|
||||
def toggle_open(n1, n2, is_open):
|
||||
if n1 or n2:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
@callback(
|
||||
Output("save-modal", "is_open"),
|
||||
[
|
||||
Input("save-button", "n_clicks"),
|
||||
Input("save-close", "n_clicks"),
|
||||
Input("save-save", "n_clicks"),
|
||||
],
|
||||
[dash.dependencies.State("save-modal", "is_open")],
|
||||
)
|
||||
def toggle_save(n1, n2, n3, is_open):
|
||||
if n1 or n2 or n3:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
@callback(
|
||||
Output("file-list", "children"),
|
||||
[Input("open-refresh", "n_clicks")],
|
||||
)
|
||||
def refresh_files(n):
|
||||
files = listdir("Dataset/saves")
|
||||
return [
|
||||
dbc.ListGroupItem(
|
||||
f"{file}",
|
||||
action=True,
|
||||
style={"cursor": "pointer"},
|
||||
id={"type": "file-item", "index": i},
|
||||
)
|
||||
for i, file in enumerate(files)
|
||||
if isfile(join("Dataset/saves", file))
|
||||
]
|
||||
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("open-modal", "is_open", allow_duplicate=True),
|
||||
Output("store-files", "data"),
|
||||
],
|
||||
Input({"type": "file-item", "index": ALL}, "n_clicks"),
|
||||
State({"type": "file-item", "index": ALL}, "children"),
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def open_file(n, filenames):
|
||||
ctx = dash.callback_context
|
||||
if not ctx.triggered or all(click is None for click in n):
|
||||
return [None, ""]
|
||||
file_index = ctx.triggered[0]["prop_id"].split(".")[0]
|
||||
file_index = eval(file_index)
|
||||
filename = filenames[file_index["index"]]
|
||||
return [False, filename]
|
||||
|
||||
|
||||
@callback(
|
||||
Output("save-format", "options"),
|
||||
[Input("store-filters", "data")],
|
||||
)
|
||||
def update_save_format(filters):
|
||||
if filters != {}:
|
||||
return [
|
||||
{"label": "Save raw dataset", "value": "raw"},
|
||||
{"label": "Save filtered dataset", "value": "filt"},
|
||||
]
|
||||
return [
|
||||
{"label": "Save raw dataset", "value": "raw"},
|
||||
{"label": "Save filtered dataset", "value": "filt", "disabled": True},
|
||||
]
|
||||
|
||||
121
3D_app/main.py
121
3D_app/main.py
@ -1,11 +1,11 @@
|
||||
import dash
|
||||
from dash import dcc, html, ALL, DiskcacheManager
|
||||
from dash.dependencies import Input, Output, State
|
||||
import dash_bootstrap_components as dbc
|
||||
from os import listdir, mkdir, getenv
|
||||
from os import listdir, mkdir
|
||||
from os.path import isfile, join
|
||||
import diskcache
|
||||
from json import load
|
||||
from callbacks.main import *
|
||||
|
||||
|
||||
# on crée l'application
|
||||
@ -373,121 +373,8 @@ app.layout = dbc.Container(
|
||||
fluid=True,
|
||||
)
|
||||
|
||||
|
||||
# callback pour le modal
|
||||
@app.callback(
|
||||
Output("modal", "is_open"),
|
||||
[Input("howto-open", "n_clicks"), Input("howto-close", "n_clicks")],
|
||||
[dash.dependencies.State("modal", "is_open")],
|
||||
)
|
||||
def toggle_modal(n1, n2, is_open):
|
||||
if n1 or n2:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
@app.callback(
|
||||
Output("settings-modal", "is_open"),
|
||||
[Input("settings-open", "n_clicks"), Input("settings-close", "n_clicks")],
|
||||
[dash.dependencies.State("settings-modal", "is_open")],
|
||||
)
|
||||
def toggle_settings(n1, n2, is_open):
|
||||
if n1 or n2:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
# callback pour le navmenu
|
||||
@app.callback(
|
||||
Output("offcanvas-menu", "is_open"),
|
||||
[Input("navbar-toggler", "n_clicks")],
|
||||
[dash.dependencies.State("offcanvas-menu", "is_open")],
|
||||
)
|
||||
def toggle_offcanvas(n, is_open):
|
||||
if n:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
@app.callback(
|
||||
Output("open-modal", "is_open"),
|
||||
[Input("open-button", "n_clicks"), Input("open-close", "n_clicks")],
|
||||
[dash.dependencies.State("open-modal", "is_open")],
|
||||
)
|
||||
def toggle_open(n1, n2, is_open):
|
||||
if n1 or n2:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
@app.callback(
|
||||
Output("save-modal", "is_open"),
|
||||
[
|
||||
Input("save-button", "n_clicks"),
|
||||
Input("save-close", "n_clicks"),
|
||||
Input("save-save", "n_clicks"),
|
||||
],
|
||||
[dash.dependencies.State("save-modal", "is_open")],
|
||||
)
|
||||
def toggle_save(n1, n2, n3, is_open):
|
||||
if n1 or n2 or n3:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
@app.callback(
|
||||
Output("file-list", "children"),
|
||||
[Input("open-refresh", "n_clicks")],
|
||||
)
|
||||
def refresh_files(n):
|
||||
files = listdir("Dataset/saves")
|
||||
return [
|
||||
dbc.ListGroupItem(
|
||||
f"{file}",
|
||||
action=True,
|
||||
style={"cursor": "pointer"},
|
||||
id={"type": "file-item", "index": i},
|
||||
)
|
||||
for i, file in enumerate(files)
|
||||
if isfile(join("Dataset/saves", file))
|
||||
]
|
||||
|
||||
|
||||
@app.callback(
|
||||
[
|
||||
Output("open-modal", "is_open", allow_duplicate=True),
|
||||
Output("store-files", "data"),
|
||||
],
|
||||
Input({"type": "file-item", "index": ALL}, "n_clicks"),
|
||||
State({"type": "file-item", "index": ALL}, "children"),
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def open_file(n, filenames):
|
||||
ctx = dash.callback_context
|
||||
if not ctx.triggered or all(click is None for click in n):
|
||||
return [None, ""]
|
||||
file_index = ctx.triggered[0]["prop_id"].split(".")[0]
|
||||
file_index = eval(file_index)
|
||||
filename = filenames[file_index["index"]]
|
||||
return [False, filename]
|
||||
|
||||
|
||||
@app.callback(
|
||||
Output("save-format", "options"),
|
||||
[Input("store-filters", "data")],
|
||||
)
|
||||
def update_save_format(filters):
|
||||
if filters != {}:
|
||||
return [
|
||||
{"label": "Save raw dataset", "value": "raw"},
|
||||
{"label": "Save filtered dataset", "value": "filt"},
|
||||
]
|
||||
return [
|
||||
{"label": "Save raw dataset", "value": "raw"},
|
||||
{"label": "Save filtered dataset", "value": "filt", "disabled": True},
|
||||
]
|
||||
|
||||
get_callbacks()
|
||||
|
||||
# on lance l'application
|
||||
if __name__ == "__main__":
|
||||
app.run(debug=config["debug"] or False, port=config["port"] or "8051", threaded=True)
|
||||
app.run(debug=config["debug"] or False, port=config["port"] or "8051", threaded=True)
|
||||
@ -9,10 +9,15 @@ from util import *
|
||||
from filtrage import *
|
||||
from selection_filtre import *
|
||||
from Bscan_Cscan_trait import *
|
||||
from callbacks.ascan import get_callbacks
|
||||
|
||||
|
||||
dash.register_page(
|
||||
__name__, path="/ascan", title="A-Scan filters", name="A-Scan filters"
|
||||
__name__,
|
||||
path="/ascan",
|
||||
title="A-Scan filters",
|
||||
name="A-Scan filters",
|
||||
description="Apply filters on the dataset",
|
||||
)
|
||||
|
||||
# on définit le dossier et les fichiers à lire
|
||||
@ -26,7 +31,7 @@ pre_volume = np.array(lire_fichier_csv(dossier, fichiers_selectionnes))
|
||||
volume = pre_volume[:, :, :]
|
||||
data_traits = volume
|
||||
dim_x, dim_y, dim_z = volume.shape
|
||||
click=None
|
||||
click = None
|
||||
X, Y, Z = np.mgrid[0:dim_x, 0:dim_y, 0:dim_z]
|
||||
# on définit le thème de l'application
|
||||
pio.templates.default = "plotly_dark"
|
||||
@ -43,6 +48,25 @@ configAScan = {
|
||||
}
|
||||
layout = html.Div(
|
||||
[
|
||||
dbc.Modal(
|
||||
[
|
||||
dbc.ModalHeader("Save data"),
|
||||
dbc.ModalBody(
|
||||
dbc.Input(
|
||||
id="input-save-ascan", placeholder="Filename", type="text"
|
||||
),
|
||||
),
|
||||
dbc.ModalFooter(
|
||||
[
|
||||
dbc.Button("Save", id="save-ascan-solo", className="ml-auto"),
|
||||
dbc.Button("Close", id="close-ascan-solo", className="ml-auto"),
|
||||
]
|
||||
),
|
||||
],
|
||||
id="modal-ascan-solo",
|
||||
centered=True,
|
||||
is_open=False,
|
||||
),
|
||||
dbc.Row(
|
||||
[
|
||||
dbc.Col(
|
||||
@ -50,29 +74,29 @@ layout = html.Div(
|
||||
dbc.Select(
|
||||
id="select-ascan-filter1",
|
||||
options=[
|
||||
{"label": "transformer du Hilbert", "value": "1"},
|
||||
{"label": "Transformer du Hilbert", "value": "1"},
|
||||
],
|
||||
value=1,
|
||||
style={"margin-bottom": "15px"},
|
||||
),
|
||||
],
|
||||
width=2,
|
||||
width=3,
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Select(
|
||||
id="select-ascan-filter2",
|
||||
options=[
|
||||
{"label": "sans filtre ", "value": "2"},
|
||||
{"label": "filtre passe bas ", "value": "3"},
|
||||
{"label": "filtre de moyenne mobile", "value": "4"},
|
||||
{"label": "filtre adaptatif (wiener)", "value": "5"},
|
||||
{"label": "No filter ", "value": "2"},
|
||||
{"label": "Filtre passe bas ", "value": "3"},
|
||||
{"label": "Filtre de moyenne mobile", "value": "4"},
|
||||
{"label": "Filtre adaptatif (wiener)", "value": "5"},
|
||||
{
|
||||
"label": "filtre à réponse impulsionnelle infinie",
|
||||
"label": "Filtre à réponse impulsionnelle infinie",
|
||||
"value": "6",
|
||||
},
|
||||
{
|
||||
"label": "filtre à réponse impulsionnelle finie",
|
||||
"label": "Filtre à réponse impulsionnelle finie",
|
||||
"value": "7",
|
||||
},
|
||||
],
|
||||
@ -80,23 +104,23 @@ layout = html.Div(
|
||||
style={"margin-bottom": "15px"},
|
||||
),
|
||||
],
|
||||
width=2,
|
||||
width=3,
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Select(
|
||||
id="select-ascan-filter3",
|
||||
options=[
|
||||
{"label": "sans filtre ", "value": "2"},
|
||||
{"label": "filtre passe bas ", "value": "3"},
|
||||
{"label": "filtre de moyenne mobile", "value": "4"},
|
||||
{"label": "filtre adaptatif (wiener)", "value": "5"},
|
||||
{"label": "No filter ", "value": "2"},
|
||||
{"label": "Filtre passe bas ", "value": "3"},
|
||||
{"label": "Filtre de moyenne mobile", "value": "4"},
|
||||
{"label": "Filtre adaptatif (wiener)", "value": "5"},
|
||||
{
|
||||
"label": "filtre à réponse impulsionnelle infinie",
|
||||
"label": "Filtre à réponse impulsionnelle infinie",
|
||||
"value": "6",
|
||||
},
|
||||
{
|
||||
"label": "filtre à réponse impulsionnelle finie",
|
||||
"label": "Filtre à réponse impulsionnelle finie",
|
||||
"value": "7",
|
||||
},
|
||||
],
|
||||
@ -104,12 +128,12 @@ layout = html.Div(
|
||||
style={"margin-bottom": "15px"},
|
||||
),
|
||||
],
|
||||
width=2,
|
||||
width=3,
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Label(
|
||||
"apply the filters",
|
||||
"Apply the filters",
|
||||
style={"marginRight": "5px"},
|
||||
),
|
||||
dbc.Button(
|
||||
@ -132,26 +156,26 @@ layout = html.Div(
|
||||
dbc.Button(
|
||||
id="button-save-data",
|
||||
children=dbc.Spinner(
|
||||
html.Div("save", id="save"), show_initially=False
|
||||
html.Div("Save", id="save"), show_initially=False
|
||||
),
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
],
|
||||
width=2,
|
||||
width=1,
|
||||
),
|
||||
]
|
||||
),
|
||||
dbc.Row(
|
||||
[
|
||||
dbc.Col(
|
||||
[html.Br(), html.B(" paramètre du 1er filtre ")],
|
||||
[html.Br(), html.B("Parameters of the 1st filter")],
|
||||
width=2,
|
||||
style={"textAlign": "center"},
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Label("Fs ", html_for="Fs "),
|
||||
dbc.Label("Fs", html_for="Fs "),
|
||||
dbc.Input(
|
||||
id="input-ascan-solo-fs",
|
||||
type="number",
|
||||
@ -164,11 +188,11 @@ layout = html.Div(
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Label("cut off ", html_for="cut off"),
|
||||
dbc.Label("Cut off", html_for="cut off"),
|
||||
dbc.Input(
|
||||
id="input-ascan-solo-cutoff",
|
||||
type="number",
|
||||
placeholder="cut_off",
|
||||
placeholder="Cut off",
|
||||
value=1,
|
||||
step=0.1,
|
||||
),
|
||||
@ -177,11 +201,11 @@ layout = html.Div(
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Label("order ", html_for="order"),
|
||||
dbc.Label("Order", html_for="order"),
|
||||
dbc.Input(
|
||||
id="input-ascan-solo-order",
|
||||
type="number",
|
||||
placeholder="order",
|
||||
placeholder="Order",
|
||||
value=1,
|
||||
step=1,
|
||||
),
|
||||
@ -190,11 +214,11 @@ layout = html.Div(
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Label("window size ", html_for="window size"),
|
||||
dbc.Label("Window size", html_for="window size"),
|
||||
dbc.Input(
|
||||
id="input-ascan-solo-windowsize",
|
||||
type="number",
|
||||
placeholder="window_size",
|
||||
placeholder="Window size",
|
||||
value=1,
|
||||
step=1,
|
||||
),
|
||||
@ -202,13 +226,13 @@ layout = html.Div(
|
||||
width=1,
|
||||
),
|
||||
dbc.Col(
|
||||
[html.Br(), html.B(" paramètre du 2e filtre ")],
|
||||
[html.Br(), html.B("Parameters of the 2nd filter")],
|
||||
width=2,
|
||||
style={"textAlign": "center"},
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Label("Fs ", html_for="Fs "),
|
||||
dbc.Label("Fs", html_for="Fs "),
|
||||
dbc.Input(
|
||||
id="input-ascan-solo-fs-2",
|
||||
type="number",
|
||||
@ -221,11 +245,11 @@ layout = html.Div(
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Label("cut off ", html_for="cut off"),
|
||||
dbc.Label("Cut off", html_for="cut off"),
|
||||
dbc.Input(
|
||||
id="input-ascan-solo-cutoff-2",
|
||||
type="number",
|
||||
placeholder="cut_off",
|
||||
placeholder="Cut off",
|
||||
value=1,
|
||||
step=0.1,
|
||||
),
|
||||
@ -234,11 +258,11 @@ layout = html.Div(
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Label("order ", html_for="order"),
|
||||
dbc.Label("Order", html_for="order"),
|
||||
dbc.Input(
|
||||
id="input-ascan-solo-order-2",
|
||||
type="number",
|
||||
placeholder="order",
|
||||
placeholder="Order",
|
||||
value=1,
|
||||
step=1,
|
||||
),
|
||||
@ -247,11 +271,11 @@ layout = html.Div(
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Label("window size ", html_for="window size"),
|
||||
dbc.Label("Window size", html_for="window size"),
|
||||
dbc.Input(
|
||||
id="input-ascan-solo-windowsize-2",
|
||||
type="number",
|
||||
placeholder="window_size",
|
||||
placeholder="Window size",
|
||||
value=1,
|
||||
step=1,
|
||||
),
|
||||
@ -325,267 +349,4 @@ layout = html.Div(
|
||||
style={"padding": "20px"},
|
||||
)
|
||||
|
||||
@callback(
|
||||
Output("store-filters", "data"),
|
||||
[
|
||||
Input("select-ascan-filter1", "value"),
|
||||
Input("select-ascan-filter2", "value"),
|
||||
Input("select-ascan-filter3", "value"),
|
||||
Input("input-ascan-solo-fs", "value"),
|
||||
Input("input-ascan-solo-cutoff", "value"),
|
||||
Input("input-ascan-solo-order", "value"),
|
||||
Input("input-ascan-solo-windowsize", "value"),
|
||||
Input("input-ascan-solo-fs-2", "value"),
|
||||
Input("input-ascan-solo-cutoff-2", "value"),
|
||||
Input("input-ascan-solo-order-2", "value"),
|
||||
Input("input-ascan-solo-windowsize-2", "value"),
|
||||
],
|
||||
)
|
||||
def store_settings(
|
||||
select_filtre_1,
|
||||
select_filtre_2,
|
||||
select_filtre_3,
|
||||
fs_filtre_1,
|
||||
cutoff_filtre_1,
|
||||
order_filtre_1,
|
||||
windowsize_filtre_1,
|
||||
fs_filtre_2,
|
||||
cutoff_filtre_2,
|
||||
order_filtre_2,
|
||||
windowsize_filtre_2,
|
||||
):
|
||||
return {
|
||||
"select_filtre_1": select_filtre_1,
|
||||
"select_filtre_2": select_filtre_2,
|
||||
"select_filtre_3": select_filtre_3,
|
||||
"fs_filtre_1": fs_filtre_1,
|
||||
"cutoff_filtre_1": cutoff_filtre_1,
|
||||
"order_filtre_1": order_filtre_1,
|
||||
"windowsize_filtre_1": windowsize_filtre_1,
|
||||
"fs_filtre_2": fs_filtre_2,
|
||||
"cutoff_filtre_2": cutoff_filtre_2,
|
||||
"order_filtre_2": order_filtre_2,
|
||||
"windowsize_filtre_2": windowsize_filtre_2,
|
||||
}
|
||||
|
||||
|
||||
# callback to update filter values
|
||||
@callback(
|
||||
[
|
||||
Output("input-ascan-solo-fs", "disabled"),
|
||||
Output("input-ascan-solo-cutoff", "disabled"),
|
||||
Output("input-ascan-solo-order", "disabled"),
|
||||
Output("input-ascan-solo-windowsize", "disabled"),
|
||||
Output("input-ascan-solo-fs-2", "disabled"),
|
||||
Output("input-ascan-solo-cutoff-2", "disabled"),
|
||||
Output("input-ascan-solo-order-2", "disabled"),
|
||||
Output("input-ascan-solo-windowsize-2", "disabled"),
|
||||
],
|
||||
[
|
||||
Input("select-ascan-filter2", "value"),
|
||||
Input("select-ascan-filter3", "value"),
|
||||
],
|
||||
)
|
||||
def update_filter_values(select_filtre_1, select_filtre_2):
|
||||
fs_1 = True
|
||||
cutoff_1 = True
|
||||
ordre_1 = True
|
||||
windowsize_1 = True
|
||||
fs_2 = True
|
||||
cutoff_2 = True
|
||||
ordre_2 = True
|
||||
windowsize_2 = True
|
||||
if int(select_filtre_1) == 3:
|
||||
fs_1 = False
|
||||
cutoff_1 = False
|
||||
ordre_1 = False
|
||||
if int(select_filtre_2) == 3:
|
||||
fs_2 = False
|
||||
cutoff_2 = False
|
||||
ordre_2 = False
|
||||
if int(select_filtre_1) in (4, 5, 6, 7):
|
||||
windowsize_1 = False
|
||||
if int(select_filtre_2) in (4, 5, 6, 7):
|
||||
windowsize_2 = False
|
||||
return [
|
||||
fs_1,
|
||||
cutoff_1,
|
||||
ordre_1,
|
||||
windowsize_1,
|
||||
fs_2,
|
||||
cutoff_2,
|
||||
ordre_2,
|
||||
windowsize_2,
|
||||
]
|
||||
|
||||
|
||||
|
||||
@callback(
|
||||
Output("loading", "children"),
|
||||
Input("button-validate-filter", "n_clicks"),
|
||||
[
|
||||
State("select-ascan-filter1", "value"),
|
||||
State("select-ascan-filter2", "value"),
|
||||
State("select-ascan-filter3", "value"),
|
||||
State("input-ascan-solo-fs", "value"),
|
||||
State("input-ascan-solo-cutoff", "value"),
|
||||
State("input-ascan-solo-order", "value"),
|
||||
State("input-ascan-solo-windowsize", "value"),
|
||||
State("input-ascan-solo-fs-2", "value"),
|
||||
State("input-ascan-solo-cutoff-2", "value"),
|
||||
State("input-ascan-solo-order-2", "value"),
|
||||
State("input-ascan-solo-windowsize-2", "value"),
|
||||
]
|
||||
)
|
||||
def load_button(n_clicks,
|
||||
selec_transforme_hilbert,
|
||||
select_filtre_1,select_filtre_2,
|
||||
fs_filtre_1,cutoff_filtre_1,
|
||||
order_filtre_1,windowsize_filtre_1,
|
||||
fs_filtre_2,cutoff_filtre_2,order_filtre_2,windowsize_filtre_2,
|
||||
):
|
||||
bouton = "Valider"
|
||||
global data_traits,click
|
||||
if n_clicks != click:
|
||||
data_traits=Cscant(data_input=data_traits,
|
||||
sel1=int(selec_transforme_hilbert),sel2=int(select_filtre_1),
|
||||
sel3=int(select_filtre_2),
|
||||
fs_1=int(fs_filtre_1),cut_off_1=float(cutoff_filtre_1),
|
||||
order_1=int(order_filtre_1),window_size_1=int(windowsize_filtre_1),
|
||||
fs_2=int(fs_filtre_2),cut_off_2=float(cutoff_filtre_2),
|
||||
order_2=int(order_filtre_2),window_size2=int(windowsize_filtre_2))
|
||||
bouton = "Valider"
|
||||
click=n_clicks
|
||||
return bouton
|
||||
|
||||
|
||||
@callback(
|
||||
Output("save", "children"),
|
||||
Input("button-save-data","n_clicks"),
|
||||
)
|
||||
def save_data(n_clicks):
|
||||
bouton = "save"
|
||||
global data_traits
|
||||
if n_clicks!=None:
|
||||
np.save('Dataset/saves/datat.npy',data_traits)
|
||||
bouton = "save"
|
||||
return bouton
|
||||
|
||||
|
||||
# callback to update the heatmap
|
||||
@callback(
|
||||
[
|
||||
Output("heatmap-ascan-solo", "figure"),
|
||||
Output("heatmap-bscan-solo", "figure"),
|
||||
Output("heatmap-fft-solo", "figure"),
|
||||
],
|
||||
[
|
||||
Input("layer-slider-ascan-solo-x", "value"),
|
||||
Input("layer-slider-ascan-solo-y", "value"),
|
||||
Input("layer-slider-ascan-solo-z", "value"),
|
||||
Input("button-validate-filter", "n_clicks"),
|
||||
],
|
||||
[
|
||||
State("select-ascan-filter1", "value"),
|
||||
State("select-ascan-filter2", "value"),
|
||||
State("select-ascan-filter3", "value"),
|
||||
State("input-ascan-solo-fs", "value"),
|
||||
State("input-ascan-solo-cutoff", "value"),
|
||||
State("input-ascan-solo-order", "value"),
|
||||
State("input-ascan-solo-windowsize", "value"),
|
||||
State("input-ascan-solo-fs-2", "value"),
|
||||
State("input-ascan-solo-cutoff-2", "value"),
|
||||
State("input-ascan-solo-order-2", "value"),
|
||||
State("input-ascan-solo-windowsize-2", "value"),
|
||||
]
|
||||
)
|
||||
def update_heatmap_ascan(
|
||||
select_ascan_x,
|
||||
select_ascan_y,
|
||||
select_ascan_z,
|
||||
n_clicks,
|
||||
selec_transforme_hilbert,
|
||||
select_filtre_1,
|
||||
select_filtre_2,
|
||||
fs_filtre_1,
|
||||
cutoff_filtre_1,
|
||||
order_filtre_1,
|
||||
windowsize_filtre_1,
|
||||
fs_filtre_2,
|
||||
cutoff_filtre_2,
|
||||
order_filtre_2,
|
||||
windowsize_filtre_2,
|
||||
):
|
||||
# TODO: implement the filter
|
||||
|
||||
print("debut du traitement")
|
||||
data_avec_traitement = volume[
|
||||
int(select_ascan_y) - 1,
|
||||
select_ascan_z[0] : select_ascan_z[1],
|
||||
int(select_ascan_x) - 1,
|
||||
]
|
||||
data_sans_traitement = volume[
|
||||
int(select_ascan_y) - 1,
|
||||
select_ascan_z[0] : select_ascan_z[1],
|
||||
int(select_ascan_x) - 1,
|
||||
]
|
||||
|
||||
data_avec_traitement = switch_case(
|
||||
data_avec_traitement, int(selec_transforme_hilbert)
|
||||
)
|
||||
data_sans_traitement = switch_case(
|
||||
data_sans_traitement, int(selec_transforme_hilbert)
|
||||
)
|
||||
|
||||
data_avec_traitement = switch_case(
|
||||
data_avec_traitement,
|
||||
int(select_filtre_1),
|
||||
float(fs_filtre_1),
|
||||
float(cutoff_filtre_1),
|
||||
int(order_filtre_1),
|
||||
int(windowsize_filtre_1),
|
||||
)
|
||||
data_avec_traitement = switch_case(
|
||||
data_avec_traitement,
|
||||
int(select_filtre_2),
|
||||
float(fs_filtre_2),
|
||||
float(cutoff_filtre_2),
|
||||
int(order_filtre_2),
|
||||
int(windowsize_filtre_2),
|
||||
)
|
||||
print("fin du traitement")
|
||||
|
||||
fig = px.line(title="A-scan")
|
||||
new_trace = go.Scatter(y=data_avec_traitement, mode="lines", name=" Ascan trait ")
|
||||
fig.add_trace(new_trace)
|
||||
new_trace = go.Scatter(
|
||||
y=data_sans_traitement, mode="lines", name=" Ascan (hilbert) "
|
||||
)
|
||||
fig.add_trace(new_trace)
|
||||
fig.update_layout(xaxis_title="indix", yaxis_title="amplitude")
|
||||
|
||||
|
||||
data_bscan=Bscant(volume[select_ascan_y - 1, select_ascan_z[0] : select_ascan_z[1], :],int(selec_transforme_hilbert),int(select_filtre_1),int(select_filtre_2),float(fs_filtre_1),
|
||||
float(cutoff_filtre_1),int(order_filtre_1),int(windowsize_filtre_1),float(fs_filtre_2),float(cutoff_filtre_2),int(order_filtre_2),int(windowsize_filtre_2),)
|
||||
|
||||
fig2 = px.imshow(
|
||||
data_bscan,
|
||||
color_continuous_scale="Jet",
|
||||
aspect="auto",
|
||||
title="B-scan XZ",
|
||||
)
|
||||
fig2.update_layout(xaxis_title="Z", yaxis_title=" X")
|
||||
data_sans_traitement_fft = np.fft.fft(
|
||||
volume[
|
||||
int(select_ascan_y) - 1,
|
||||
int(select_ascan_z[0]) : int(select_ascan_z[1]),
|
||||
int(select_ascan_x) - 1,
|
||||
]
|
||||
)
|
||||
fig3 = px.line(title="FFT")
|
||||
trace3 = go.Scatter(y=np.abs(data_sans_traitement_fft[int(select_ascan_z[0]) :int(int(select_ascan_z[1])/2)]), mode="lines", name=" FFT ")
|
||||
fig3.add_trace(trace3)
|
||||
fig3.update_layout(
|
||||
xaxis_title="FFT indix", yaxis_title="FFT of signal (Mangnitude)"
|
||||
)
|
||||
return [fig, fig2, fig3]
|
||||
get_callbacks()
|
||||
|
||||
@ -1,18 +1,11 @@
|
||||
import dash
|
||||
import plotly.graph_objects as go
|
||||
from dash import html, dcc, callback, Input, Output
|
||||
from dash import html, dcc
|
||||
import dash_bootstrap_components as dbc
|
||||
import numpy as np
|
||||
from GNG_3D import *
|
||||
from sklearn import datasets as sk
|
||||
from pages.ascan import data_traits
|
||||
from callbacks.gng import get_callbacks
|
||||
|
||||
|
||||
dash.register_page(__name__, path="/gng", title="GNG", name="GNG")
|
||||
dash.register_page(__name__, path="/gng", title="GNG", name="GNG", description="Growing Neural Gas")
|
||||
|
||||
clics = None
|
||||
|
||||
# Create and fit the GNG model
|
||||
|
||||
layout = html.Div(
|
||||
[
|
||||
@ -138,76 +131,4 @@ layout = html.Div(
|
||||
)
|
||||
|
||||
|
||||
@callback(
|
||||
[Output("gng-graph", "figure")],
|
||||
[
|
||||
Input("generate-gng", "n_clicks"),
|
||||
Input("seuil", "value"),
|
||||
Input("max_neurons", "value"),
|
||||
Input("Iterations", "value"),
|
||||
Input("Max_of_age", "value"),
|
||||
Input("eb", "value"),
|
||||
Input("en", "value"),
|
||||
Input("alpha", "value"),
|
||||
Input("beta", "value"),
|
||||
Input("l", "value"),
|
||||
],
|
||||
)
|
||||
def generate_gng(n_clicks, seuil, max_neurons, max_iter, max_age, eb, en, alpha, beta, l):
|
||||
|
||||
global clics
|
||||
if n_clicks != clics:
|
||||
data=np.array(data_traits)
|
||||
fig = go.Figure()
|
||||
size_data=np.shape(data)
|
||||
x1=[]
|
||||
x2=[]
|
||||
x3=[]
|
||||
x4=[]
|
||||
for i in range(0,size_data[0]):
|
||||
res=data[i,:,:]
|
||||
res=position_point_espace(data=res,seuil=200,y=i)
|
||||
res = np.array(res)
|
||||
x1.append(res)
|
||||
gng = GrowingNeuralGas(int(max_neurons),int(max_iter),int(max_age), float(eb), float(en), float(alpha), float(beta),int(l), res)
|
||||
gng_graph = gng.learn()
|
||||
neuron_positions = np.array([vertex['weight'] for vertex in gng_graph.vs])
|
||||
neuron_edge= np.array([(edge.source, edge.target) for edge in gng_graph.es])
|
||||
for edge in gng_graph.es:
|
||||
src, tgt = edge.source, edge.target
|
||||
src_pos, tgt_pos = gng_graph.vs[src]['weight'], gng_graph.vs[tgt]['weight']
|
||||
x3.append(src_pos)
|
||||
x4.append(tgt_pos)
|
||||
|
||||
x2.append(neuron_positions)
|
||||
res=np.vstack(x1)
|
||||
neuron_positions=np.vstack(x2)
|
||||
src_pos=np.vstack(x3)
|
||||
tgt_pos=np.vstack(x4)
|
||||
fig.add_trace(go.Scatter3d(
|
||||
x=res[:, 0],
|
||||
y=res[:, 1],
|
||||
z=res[:, 2],
|
||||
mode='markers',
|
||||
marker=dict(size=1, color=res[:, 3], colorscale='Viridis', opacity=0.5),
|
||||
name='Data'
|
||||
))
|
||||
fig.add_trace(go.Scatter3d(
|
||||
x=neuron_positions[:, 0],
|
||||
y=neuron_positions[:, 1],
|
||||
z=neuron_positions[:, 2],
|
||||
mode='markers',
|
||||
marker=dict(size=4, color=neuron_positions[:,3]),
|
||||
name='Neurons'
|
||||
))
|
||||
for src, tgt in zip(src_pos, tgt_pos):
|
||||
fig.add_trace(go.Scatter3d(
|
||||
x=[src[0], tgt[0]],
|
||||
y=[src[1], tgt[1]],
|
||||
z=[src[2], tgt[2]],
|
||||
mode='lines',
|
||||
line=dict(color="black", width=1),
|
||||
showlegend=False,
|
||||
))
|
||||
clics = n_clicks
|
||||
return [fig]
|
||||
get_callbacks()
|
||||
@ -1,19 +1,27 @@
|
||||
import dash
|
||||
from dash import html, callback, Input, Output, dcc, State, DiskcacheManager
|
||||
from dash import html, dcc, DiskcacheManager
|
||||
import dash_bootstrap_components as dbc
|
||||
import plotly.graph_objects as go
|
||||
import numpy as np
|
||||
import plotly.express as px
|
||||
import plotly.io as pio
|
||||
from util import *
|
||||
from selection_filtre import *
|
||||
from os.path import join
|
||||
import diskcache
|
||||
from pages.ascan import data_traits, pre_volume
|
||||
from callbacks.home import get_callbacks
|
||||
from pages.ascan import pre_volume
|
||||
|
||||
dash.register_page(__name__, path="/", description="The home page of the web app")
|
||||
|
||||
# on définit le dossier et les fichiers à lire
|
||||
dossier = "Dataset/Shear_transform"
|
||||
fichiers_selectionnes = [
|
||||
"Shear_x001-x101_y{:03d}_Rot00_transform.csv".format(i) for i in range(10, 14)
|
||||
]
|
||||
|
||||
dash.register_page(__name__, path="/")
|
||||
cache = diskcache.Cache("./cache")
|
||||
background_callback_manager = DiskcacheManager(cache)
|
||||
|
||||
# on charge le fichier numpy
|
||||
# fichiers = np.load("Dataset/npy/export.npy")
|
||||
|
||||
# valeurs d'échantillonage
|
||||
echantillonage_x = 1
|
||||
@ -97,26 +105,22 @@ mesh_card = dbc.Fade(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
html.Div(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"3D Plot",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
width="4",
|
||||
html.H2(
|
||||
"3D Plot",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-3dplot",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-3dplot",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
],
|
||||
style={"display": "flex", "justifyContent": "space-between"},
|
||||
),
|
||||
dcc.Graph(
|
||||
id="3dplot",
|
||||
@ -215,26 +219,22 @@ Ascan_card = dbc.Fade(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
html.Div(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"A-scan",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
width="4",
|
||||
html.H2(
|
||||
"A-scan",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-ascan",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-ascan",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
],
|
||||
style={"display": "flex", "justifyContent": "space-between"},
|
||||
),
|
||||
dcc.Graph(
|
||||
id="heatmap-ascan",
|
||||
@ -286,26 +286,22 @@ Bscan_card_xy = dbc.Fade(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
html.Div(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"B-scan ZX",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
width="4",
|
||||
html.H2(
|
||||
"B-scan ZX",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-bscan-zx",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-bscan-zx",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
],
|
||||
style={"display": "flex", "justifyContent": "space-between"},
|
||||
),
|
||||
dcc.Graph(
|
||||
id="heatmap-bscan-zx",
|
||||
@ -367,26 +363,22 @@ Bscan_card_zx = dbc.Fade(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
html.Div(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"B-scan XY",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
width="4",
|
||||
html.H2(
|
||||
"B-scan XY",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-bscan-xy",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-bscan-xy",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
],
|
||||
style={"display": "flex", "justifyContent": "space-between"},
|
||||
),
|
||||
dcc.Graph(
|
||||
id="heatmap-bscan-xy",
|
||||
@ -457,483 +449,4 @@ layout = html.Div(
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
# on défini les callbacks
|
||||
# callback pour le plot 3D
|
||||
@callback(
|
||||
[Output("3dplot", "figure")],
|
||||
[
|
||||
Input("iso-slider", "value"),
|
||||
Input("y-slider", "value"),
|
||||
Input("store-settings", "data"),
|
||||
],
|
||||
[dash.dependencies.State("fade-3dplot", "is_in")],
|
||||
running=[
|
||||
(Output("fade-3dplot", "is_in"), False, True),
|
||||
],
|
||||
)
|
||||
### a revoir###
|
||||
def update_3dplot(iso_value, y_values, settings, is_in):
|
||||
if settings["use_real_values"]:
|
||||
y_min, y_max = y_values
|
||||
selected_volume = volume[0:dim_x, int(y_min) : int(y_max), 0:dim_z]
|
||||
X, Y, Z = [
|
||||
np.load("Dataset/npy/{}-values.npy".format(i)) for i in ["x", "y", "z"]
|
||||
]
|
||||
else:
|
||||
y_min, y_max = y_values
|
||||
selected_volume = volume[0:dim_x, int(y_min) : int(y_max), 0:dim_z]
|
||||
X, Y, Z = np.mgrid[
|
||||
0 : selected_volume.shape[0],
|
||||
0 : selected_volume.shape[1],
|
||||
0 : selected_volume.shape[2],
|
||||
]
|
||||
|
||||
fig = go.Figure(
|
||||
data=go.Volume(
|
||||
x=X.flatten(),
|
||||
y=Y.flatten(),
|
||||
z=Z.flatten(),
|
||||
value=selected_volume.flatten(),
|
||||
isomin=iso_value,
|
||||
isomax=selected_volume.max(),
|
||||
opacity=0.1,
|
||||
surface_count=20,
|
||||
colorscale="Jet",
|
||||
)
|
||||
)
|
||||
|
||||
return [fig]
|
||||
|
||||
|
||||
# callback pour le plot 3D en plein écran
|
||||
@callback(
|
||||
Output("3dplot-fullscreen", "figure"),
|
||||
[Input("iso-slider-fullscreen", "value"), Input("y-slider-fullscreen", "value")],
|
||||
)
|
||||
### à revoir ###
|
||||
def update_3dplot_fullscreen(iso_value, y_values):
|
||||
y_min, y_max = y_values
|
||||
selected_volume = volume[0:dim_x, int(y_min) : int(y_max), 0:dim_z]
|
||||
X, Y, Z = np.mgrid[
|
||||
0 : selected_volume.shape[0],
|
||||
0 : selected_volume.shape[1],
|
||||
0 : selected_volume.shape[2],
|
||||
]
|
||||
|
||||
fig = go.Figure(
|
||||
data=go.Volume(
|
||||
x=X.flatten(),
|
||||
y=Y.flatten(),
|
||||
z=Z.flatten(),
|
||||
value=selected_volume.flatten(),
|
||||
isomin=iso_value,
|
||||
isomax=selected_volume.max(),
|
||||
opacity=0.1,
|
||||
surface_count=20,
|
||||
colorscale="Jet",
|
||||
)
|
||||
)
|
||||
|
||||
return fig
|
||||
|
||||
|
||||
# callback pour le A-scan
|
||||
@callback(
|
||||
[Output("heatmap-ascan", "figure")],
|
||||
[Input("layer-slider-bscan-zx", "value"), Input("layer-slider-bscan-xy", "value")],
|
||||
[dash.dependencies.State("fade-ascan", "is_in")],
|
||||
running=[
|
||||
(Output("fade-ascan", "is_in"), False, True),
|
||||
],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_heatmap_ascan(layer, layer1, is_in):
|
||||
fig = px.line(y=volume[layer - 1, :, layer1], title="A-scan")
|
||||
|
||||
return [fig]
|
||||
|
||||
|
||||
# callback pour le A-scan en plein écran
|
||||
@callback(
|
||||
Output("heatmap-ascan-fullscreen", "figure"),
|
||||
Input("layer-slider-ascan-fullscreen", "value"),
|
||||
)
|
||||
def update_heatmap_ascan_fullscreen(layer):
|
||||
fig = px.line(y=volume[layer - 1, :, 5], title="A-scan")
|
||||
return fig
|
||||
|
||||
|
||||
# callback pour les B-scan XY
|
||||
@callback(
|
||||
[
|
||||
Output("heatmap-bscan-zx", "figure"),
|
||||
Output("store-bscan-zx-layer", "data"),
|
||||
],
|
||||
[Input("layer-slider-bscan-zx", "value")],
|
||||
[dash.dependencies.State("fade-bscan-zx", "is_in")],
|
||||
running=[
|
||||
(Output("fade-bscan-xy", "is_in"), False, True),
|
||||
],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_heatmap_bscan_zx(layer, is_in):
|
||||
fig = px.imshow(
|
||||
volume[layer - 1, :, :],
|
||||
color_continuous_scale="Jet",
|
||||
aspect="auto",
|
||||
title="B-scan ZX",
|
||||
)
|
||||
|
||||
return [fig, layer]
|
||||
|
||||
|
||||
# callback pour les B-scan ZX en plein écran
|
||||
@callback(
|
||||
Output("heatmap-bscan-zx-fullscreen", "figure"),
|
||||
Input("layer-slider-bscan-zx-fullscreen", "value"),
|
||||
)
|
||||
def update_heatmap_bscan_zx_fullscreen(layer):
|
||||
fig = px.imshow(
|
||||
volume[layer - 1, :, :],
|
||||
color_continuous_scale="Jet",
|
||||
aspect="auto",
|
||||
title="B-scan ZX",
|
||||
)
|
||||
|
||||
return fig
|
||||
|
||||
|
||||
# callback pour les B-scan ZX
|
||||
@callback(
|
||||
[Output("heatmap-bscan-xy", "figure"), Output("store-bscan-xy-layer", "data")],
|
||||
[Input("layer-slider-bscan-xy", "value")],
|
||||
[dash.dependencies.State("fade-bscan-xy", "is_in")],
|
||||
running=[
|
||||
(Output("fade-bscan-zx", "is_in"), False, True),
|
||||
],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_heatmap_bscan_xy(layer, is_in):
|
||||
fig = go.Figure(data=go.Heatmap(z=volume[:, :, layer], colorscale="Jet"))
|
||||
fig.update_layout(title="B-scan XY")
|
||||
|
||||
return [fig, layer]
|
||||
|
||||
|
||||
# callback pour les B-scan ZX en plein écran
|
||||
@callback(
|
||||
Output("heatmap-bscan-xy-fullscreen", "figure"),
|
||||
Input("layer-slider-bscan-xy-fullscreen", "value"),
|
||||
)
|
||||
def update_heatmap_bscan_xy_fullscreen(layer):
|
||||
fig = go.Figure(data=go.Heatmap(z=volume[:, :, layer], colorscale="Jet"))
|
||||
fig.update_layout(title="B-scan XY")
|
||||
|
||||
return fig
|
||||
|
||||
|
||||
# callback pour le plein écran du plot 3D
|
||||
@callback(
|
||||
Output("modal-3dplot", "is_open"),
|
||||
[Input("fullscreen-button-3dplot", "n_clicks")],
|
||||
[dash.dependencies.State("modal-3dplot", "is_open")],
|
||||
)
|
||||
def toggle_fullscreen_3dplot(n1, is_open):
|
||||
if n1:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
# callback pour le plein écran du A-scan
|
||||
@callback(
|
||||
Output("modal-ascan", "is_open"),
|
||||
[Input("fullscreen-button-ascan", "n_clicks")],
|
||||
[dash.dependencies.State("modal-ascan", "is_open")],
|
||||
)
|
||||
def toggle_fullscreen_ascan(n1, is_open):
|
||||
if n1:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
# callback pour le plein écran du B-scan XY
|
||||
@callback(
|
||||
Output("modal-bscan-xy", "is_open"),
|
||||
[Input("fullscreen-button-bscan-xy", "n_clicks")],
|
||||
[dash.dependencies.State("modal-bscan-xy", "is_open")],
|
||||
)
|
||||
def toggle_fullscreen_bscan_xy(n1, is_open):
|
||||
if n1:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
# callback pour le plein écran du B-scan ZX
|
||||
@callback(
|
||||
Output("modal-bscan-zx", "is_open"),
|
||||
[Input("fullscreen-button-bscan-zx", "n_clicks")],
|
||||
[dash.dependencies.State("modal-bscan-zx", "is_open")],
|
||||
)
|
||||
def toggle_fullscreen_bscan_zx(n1, is_open):
|
||||
if n1:
|
||||
return not is_open
|
||||
return is_open
|
||||
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("3dplot", "clickData"),
|
||||
Output("layer-slider-bscan-xy", "value"),
|
||||
Output("layer-slider-bscan-zx", "value"),
|
||||
],
|
||||
Input("3dplot", "clickData"),
|
||||
)
|
||||
def display_3dplot_click_data(clickData):
|
||||
if clickData is None:
|
||||
return [None, 1, 1]
|
||||
|
||||
bscan_xy = clickData["points"][0]["z"]
|
||||
bscan_zx = clickData["points"][0]["x"]
|
||||
return [clickData, bscan_xy, bscan_zx]
|
||||
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("heatmap-bscan-xy", "clickData"),
|
||||
Output("layer-slider-bscan-zx", "value", allow_duplicate=True),
|
||||
],
|
||||
[Input("heatmap-bscan-xy", "clickData")],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def display_bscan_xy_click_data(clickData):
|
||||
if clickData is None:
|
||||
return [None, 1]
|
||||
|
||||
bscan_zx = clickData["points"][0]["y"]
|
||||
return [clickData, bscan_zx]
|
||||
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("heatmap-bscan-zx", "clickData"),
|
||||
Output("layer-slider-bscan-xy", "value", allow_duplicate=True),
|
||||
],
|
||||
[Input("heatmap-bscan-zx", "clickData")],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def display_bscan_zx_click_data(clickData):
|
||||
if clickData is None:
|
||||
return [None, 0]
|
||||
|
||||
bscan_xy = clickData["points"][0]["x"]
|
||||
return [clickData, bscan_xy]
|
||||
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("heatmap-bscan-xy", "figure", allow_duplicate=True),
|
||||
Output("heatmap-bscan-zx", "figure", allow_duplicate=True),
|
||||
Output("heatmap-ascan", "figure", allow_duplicate=True),
|
||||
],
|
||||
[Input("store-bscan-xy-layer", "data"), Input("store-bscan-zx-layer", "data")],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_bscan_layers(bscan_xy, bscan_zx):
|
||||
fig = go.Figure(data=go.Heatmap(z=volume[:, :, bscan_xy], colorscale="Jet"))
|
||||
fig.add_shape(
|
||||
type="line",
|
||||
x0=0 - 1,
|
||||
y0=bscan_zx,
|
||||
x1=dim_y,
|
||||
y1=bscan_zx,
|
||||
line=dict(color="white", width=1),
|
||||
)
|
||||
fig.update_layout(title="B-scan XY")
|
||||
|
||||
fig2 = px.imshow(
|
||||
volume[bscan_zx - 1, :, :],
|
||||
color_continuous_scale="Jet",
|
||||
aspect="auto",
|
||||
title="B-scan ZX",
|
||||
)
|
||||
fig2.add_shape(
|
||||
type="line",
|
||||
x0=bscan_xy,
|
||||
y0=0,
|
||||
x1=bscan_xy,
|
||||
y1=dim_y,
|
||||
line=dict(color="white", width=1),
|
||||
)
|
||||
|
||||
fig3 = px.line(y=volume[bscan_zx - 1, :, bscan_xy], title="A-scan")
|
||||
|
||||
return [fig, fig2, fig3]
|
||||
|
||||
|
||||
@callback(
|
||||
[Output("store-settings", "data"), Output("settings-apply", "n_clicks")],
|
||||
[
|
||||
Input("settings-apply", "n_clicks"),
|
||||
],
|
||||
[
|
||||
State("use-real-values", "value"),
|
||||
State("apply-filters-everywhere", "value"),
|
||||
State("echantillonage-x", "value"),
|
||||
State("echantillonage-y", "value"),
|
||||
State("echantillonage-z", "value"),
|
||||
],
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_settings(
|
||||
clicks,
|
||||
use_real_values,
|
||||
apply_filters,
|
||||
echantillonage_x_value,
|
||||
echantillonage_y_value,
|
||||
echantillonage_z_value,
|
||||
):
|
||||
if clicks != None and clicks == 1:
|
||||
return [
|
||||
{
|
||||
"use_real_values": use_real_values,
|
||||
"use_filters": apply_filters,
|
||||
"echantillonage_x": echantillonage_x_value,
|
||||
"echantillonage_y": echantillonage_y_value,
|
||||
"echantillonage_z": echantillonage_z_value,
|
||||
},
|
||||
0,
|
||||
]
|
||||
|
||||
|
||||
@callback(
|
||||
[
|
||||
Output("layer-slider-bscan-zx", "max"),
|
||||
Output("layer-slider-bscan-zx", "marks"),
|
||||
Output("layer-slider-bscan-xy", "max"),
|
||||
Output("layer-slider-bscan-xy", "marks"),
|
||||
Output("iso-slider", "min"),
|
||||
Output("iso-slider", "max"),
|
||||
Output("iso-slider", "marks"),
|
||||
Output("y-slider", "max"),
|
||||
Output("y-slider", "marks"),
|
||||
Output("settings-spinner", "children"),
|
||||
],
|
||||
Input("store-settings", "data"),
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def redef_data(data):
|
||||
global volume, dim_x, dim_y, dim_z, X, Y, Z
|
||||
volume = pre_volume[
|
||||
:: data["echantillonage_x"],
|
||||
:: data["echantillonage_y"],
|
||||
:: data["echantillonage_z"],
|
||||
]
|
||||
dim_x, dim_y, dim_z = volume.shape
|
||||
X, Y, Z = np.mgrid[0:dim_x, 0:dim_y, 0:dim_z]
|
||||
|
||||
return [
|
||||
dim_x - 1,
|
||||
{str(i): str(i) for i in range(0, dim_x, max(1, int(dim_x / 20)))},
|
||||
dim_z - 1,
|
||||
{str(i): str(i) for i in range(1, dim_z + 1, max(1, int(dim_z / 20)))},
|
||||
volume.min(),
|
||||
volume.max() / 2,
|
||||
{
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
int(volume.min()),
|
||||
int(volume.max() / 2) + 1,
|
||||
int((volume.max() / 2 - volume.min()) / 10),
|
||||
)
|
||||
},
|
||||
dim_y,
|
||||
{str(i): str(i) for i in range(0, int(dim_y) + 1, max(1, int(dim_y / 20)))},
|
||||
"Apply",
|
||||
]
|
||||
|
||||
"""
|
||||
@callback(
|
||||
[Input("store-filters", "data"), Input("store-settings", "data")],
|
||||
)
|
||||
def apply_filters(data, settings):
|
||||
global volume
|
||||
if settings["use_filters"]:
|
||||
select_filtre_1 = data["select_filtre_2"]
|
||||
select_filtre_2 = data["select_filtre_3"]
|
||||
fs_filtre_1 = data["fs_filtre_1"]
|
||||
cutoff_filtre_1 = data["cutoff_filtre_1"]
|
||||
order_filtre_1 = data["order_filtre_1"]
|
||||
windowsize_filtre_1 = data["windowsize_filtre_1"]
|
||||
fs_filtre_2 = data["fs_filtre_2"]
|
||||
cutoff_filtre_2 = data["cutoff_filtre_2"]
|
||||
order_filtre_2 = data["order_filtre_2"]
|
||||
windowsize_filtre_2 = data["windowsize_filtre_2"]
|
||||
selec_transforme_hilbert = data["select_filtre_1"]
|
||||
|
||||
volume = pre_volume[
|
||||
:: settings["echantillonage_x"],
|
||||
:: settings["echantillonage_y"],
|
||||
:: settings["echantillonage_z"],
|
||||
]
|
||||
|
||||
data_avec_traitement = switch_case(volume, int(selec_transforme_hilbert))
|
||||
|
||||
data_avec_traitement = switch_case(
|
||||
data_avec_traitement,
|
||||
int(select_filtre_1),
|
||||
int(fs_filtre_1),
|
||||
int(cutoff_filtre_1),
|
||||
int(order_filtre_1),
|
||||
int(windowsize_filtre_1),
|
||||
)
|
||||
data_avec_traitement = switch_case(
|
||||
data_avec_traitement,
|
||||
int(select_filtre_2),
|
||||
int(fs_filtre_2),
|
||||
int(cutoff_filtre_2),
|
||||
int(order_filtre_2),
|
||||
int(windowsize_filtre_2),
|
||||
)
|
||||
volume = data_avec_traitement
|
||||
else:
|
||||
volume = pre_volume[
|
||||
:: settings["echantillonage_x"],
|
||||
:: settings["echantillonage_y"],
|
||||
:: settings["echantillonage_z"],
|
||||
]
|
||||
return None
|
||||
"""
|
||||
|
||||
@callback(
|
||||
Output("store-files", "data", allow_duplicate=True),
|
||||
Input("store-files", "data"),
|
||||
State("store-settings", "data"),
|
||||
prevent_initial_call=True,
|
||||
)
|
||||
def update_files(data, settings):
|
||||
global pre_volume, volume, dim_x, dim_y, dim_z, X, Y, Z
|
||||
if data is None or data == "":
|
||||
return None
|
||||
|
||||
# Charger le nouveau volume
|
||||
pre_volume = np.load(join("Dataset/saves", data))
|
||||
print("New volume loaded:", pre_volume.shape)
|
||||
|
||||
# Appliquer les nouveaux paramètres d'échantillonnage
|
||||
volume = pre_volume[
|
||||
::settings["echantillonage_x"],
|
||||
::settings["echantillonage_y"],
|
||||
::settings["echantillonage_z"],
|
||||
]
|
||||
dim_x, dim_y, dim_z = volume.shape
|
||||
X, Y, Z = np.mgrid[0:dim_x, 0:dim_y, 0:dim_z]
|
||||
print("Volume updated with new dimensions:", volume.shape)
|
||||
|
||||
# Mettre à jour les graphiques
|
||||
update_3dplot(0, [0, dim_y // 2], settings, False)
|
||||
update_heatmap_ascan(0, 0, False)
|
||||
update_heatmap_bscan_zx(0, False)
|
||||
update_heatmap_bscan_xy(0, False)
|
||||
|
||||
return None
|
||||
get_callbacks()
|
||||
Reference in New Issue
Block a user