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yalmansour1998
@ -10,20 +10,18 @@ from filtrage import *
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from selection_filtre import *
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dash.register_page(
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__name__, path="/ascan", title="A-Scan filters", name="A-Scan filters"
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)
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dash.register_page(__name__, path="/ascan", title='A-Scan filters', name='A-Scan filters')
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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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"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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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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@ -66,14 +64,8 @@ layout = html.Div(
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{"label": "filtre passe bas ", "value": "3"},
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{"label": "filtre de moyenne mobile", "value": "4"},
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{"label": "filtre adaptatif (wiener)", "value": "5"},
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{
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"label": "filtre à réponse impulsionnelle infinie",
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"value": "6",
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},
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{
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"label": "filtre à réponse impulsionnelle finie",
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"value": "7",
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},
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{"label": "filtre à réponse impulsionnelle infinie", "value": "6"},
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{"label": "filtre à réponse impulsionnelle finie", "value": "7"},
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],
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value=2,
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style={"margin-bottom": "15px"},
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@ -90,18 +82,13 @@ layout = html.Div(
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{"label": "filtre passe bas ", "value": "3"},
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{"label": "filtre de moyenne mobile", "value": "4"},
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{"label": "filtre adaptatif (wiener)", "value": "5"},
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{
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"label": "filtre à réponse impulsionnelle infinie",
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"value": "6",
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},
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{
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"label": "filtre à réponse impulsionnelle finie",
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"value": "7",
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},
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{"label": "filtre à réponse impulsionnelle infinie", "value": "6"},
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{"label": "filtre à réponse impulsionnelle finie", "value": "7"},
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],
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value=2,
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style={"margin-bottom": "15px"},
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),
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],
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width=3,
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),
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@ -114,9 +101,11 @@ layout = html.Div(
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color="primary",
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style={"marginBottom": "15px"},
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),
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],
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width=3,
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),
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]
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),
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dbc.Row(
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@ -143,147 +132,156 @@ layout = html.Div(
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dcc.Slider(
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id="layer-slider-ascan-solo-x",
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min=1,
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max=dim_z - 1,
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max=dim_z,
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value=1,
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step=1,
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marks={str(i): str(i) for i in range(1, dim_z + 1, max(1, int(dim_z / 20)))},
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marks={
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str(i): str(i) for i in range(1, dim_z+1,1)
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},
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),
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dbc.Label("y"),
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dcc.Slider(
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id="layer-slider-ascan-solo-y",
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min=0,
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max=dim_x - 1,
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value=0,
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min=1,
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max=dim_x,
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value=1,
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step=1,
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marks={str(i): str(i) for i in range(0, dim_x + 1, max(1, int(dim_x / 20)))},
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marks={
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str(i): str(i) for i in range(1, dim_x+1,1)
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},
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),
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dbc.Label("z"),
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dcc.RangeSlider(
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id="layer-slider-ascan-solo-z",
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min=1,
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max=dim_y,
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value=[dim_y/dim_y,dim_y],
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step=1,
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marks={
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str(i): str(i) for i in range(1, dim_y+1,1)
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},
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),
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dbc.Row(
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[
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dbc.Row(
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[
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dbc.Label(" paramètre du 1er filtre ", html_for="Fs "),
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dbc.Col(
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[
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dbc.Label("Fs ", html_for="Fs "),
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dbc.Input(
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id="input-ascan-solo-fs",
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type="number",
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placeholder="Fs",
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value=1,
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step=0.1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("cut off ", html_for="cut off"),
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dbc.Input(
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id="input-ascan-solo-cutoff",
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type="number",
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placeholder="cut_off",
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value=1,
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step=0.1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("order ", html_for="order"),
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dbc.Input(
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id="input-ascan-solo-order",
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type="number",
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placeholder="order",
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value=1,
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step=1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("window size ", html_for="window size"),
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dbc.Input(
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id="input-ascan-solo-windowsize",
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type="number",
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placeholder="window_size",
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value=1,
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step=1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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]
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dbc.Label(" paramètre du 1er filtre ", html_for="Fs "),
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dbc.Col(
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[
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dbc.Label("Fs ", html_for="Fs "),
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dbc.Input(
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id="input-ascan-solo-fs",
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type="number",
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placeholder="Fs",
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value=1,
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step=0.1,
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style={"marginTop": "15px"},
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),
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dbc.Row(
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[
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dbc.Label("paramètre de 2eme filtre ", html_for="Fs "),
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dbc.Col(
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[
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dbc.Label("Fs ", html_for="Fs "),
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dbc.Input(
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id="input-ascan-solo-fs-2",
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type="number",
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placeholder="Fs",
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value=1,
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step=0.1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("cut off ", html_for="cut off"),
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dbc.Input(
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id="input-ascan-solo-cutoff-2",
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type="number",
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placeholder="cut_off",
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value=1,
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step=0.1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("order ", html_for="order"),
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dbc.Input(
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id="input-ascan-solo-order-2",
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type="number",
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placeholder="order",
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value=1,
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step=1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("window size ", html_for="window size"),
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dbc.Input(
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id="input-ascan-solo-windowsize-2",
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type="number",
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placeholder="window_size",
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value=1,
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step=1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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]
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),
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]
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("cut off ", html_for="cut off"),
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dbc.Input(
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id="input-ascan-solo-cutoff",
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type="number",
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placeholder="cut_off",
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value=1,
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step=0.1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("order ", html_for="order"),
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dbc.Input(
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id="input-ascan-solo-order",
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type="number",
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placeholder="order",
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value=1,
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step=1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("window size ", html_for="window size"),
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dbc.Input(
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id="input-ascan-solo-windowsize",
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type="number",
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placeholder="window_size",
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value=1,
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step=1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),]),
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dbc.Row(
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[
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dbc.Label("paramètre de 2eme filtre ", html_for="Fs "),
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dbc.Col(
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[
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dbc.Label("Fs ", html_for="Fs "),
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dbc.Input(
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id="input-ascan-solo-fs-2",
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type="number",
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placeholder="Fs",
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value=1,
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step=0.1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("cut off ", html_for="cut off"),
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dbc.Input(
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id="input-ascan-solo-cutoff-2",
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type="number",
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placeholder="cut_off",
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value=1,
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step=0.1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("order ", html_for="order"),
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dbc.Input(
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id="input-ascan-solo-order-2",
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type="number",
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placeholder="order",
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value=1,
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step=1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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dbc.Col(
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[
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dbc.Label("window size ", html_for="window size"),
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dbc.Input(
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id="input-ascan-solo-windowsize-2",
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type="number",
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placeholder="window_size",
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value=1,
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step=1,
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style={"marginTop": "15px"},
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),
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],
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width=3,
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),
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]),
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],
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style={"padding": "20px"},
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)
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@ -305,7 +303,19 @@ layout = html.Div(
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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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return [select_filtre_1 == 2, select_filtre_1 == 2, select_filtre_1 == 2, select_filtre_1 == 2, select_filtre_2 == 2, select_filtre_2 == 2, select_filtre_2 == 2, select_filtre_2 == 2]
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fs_1=True;cutoff_1=True;ordre_1=True;windowsize_1=True
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fs_2=True;cutoff_2=True;ordre_2=True;windowsize_2=True
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if (int(select_filtre_1)==3):
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fs_1=False;cutoff_1=False;ordre_1=False
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if(int(select_filtre_2)==3):
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fs_2=False;cutoff_2=False;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 [fs_1, cutoff_1, ordre_1, windowsize_1, fs_2, cutoff_2, ordre_2, windowsize_2]
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# callback to update the heatmap
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@ -317,6 +327,7 @@ def update_filter_values(select_filtre_1, select_filtre_2):
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Input("select-ascan-filter3", "value"),
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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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Input("input-ascan-solo-fs", "value"),
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Input("input-ascan-solo-cutoff", "value"),
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@ -328,81 +339,36 @@ def update_filter_values(select_filtre_1, select_filtre_2):
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Input("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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selec_transforme_hilbert,
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select_filtre_1,
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select_filtre_2,
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select_ascan_x,
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select_ascan_y,
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n_clicks,
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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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def update_heatmap_ascan(selec_transforme_hilbert,select_filtre_1,select_filtre_2,select_ascan_x,select_ascan_y,select_ascan_z,n_clicks,fs_filtre_1,cutoff_filtre_1,order_filtre_1,windowsize_filtre_1,fs_filtre_2,cutoff_filtre_2,order_filtre_2,windowsize_filtre_2):
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# TODO: implement the filter
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print("debut du traitement")
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data_avec_traitement = volume[int(select_ascan_y) - 1, :, int(select_ascan_x) - 1]
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data_sans_traitement = volume[int(select_ascan_y) - 1, :, int(select_ascan_x) - 1]
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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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data_avec_traitement=volume[int(select_ascan_y)-1,select_ascan_z[0]:select_ascan_z[1],int(select_ascan_x)-1]
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data_sans_traitement=volume[int(select_ascan_y)-1,select_ascan_z[0]:select_ascan_z[1],int(select_ascan_x)-1]
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data_avec_traitement=switch_case(data_avec_traitement,int(selec_transforme_hilbert))
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data_sans_traitement=switch_case(data_sans_traitement,int(selec_transforme_hilbert))
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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))
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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))
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print("fin du traitement")
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if n_clicks != None:
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data_traits = switch_case(data_traits, int(selec_transforme_hilbert))
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data_traits = switch_case(
|
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data_traits,
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int(select_filtre_1),
|
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float(fs_filtre_1),
|
||||
float(cutoff_filtre_1),
|
||||
int(order_filtre_1),
|
||||
int(windowsize_filtre_1),
|
||||
)
|
||||
data_traits = switch_case(
|
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data_traits,
|
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int(select_filtre_2),
|
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float(fs_filtre_2),
|
||||
float(cutoff_filtre_2),
|
||||
int(order_filtre_2),
|
||||
int(windowsize_filtre_2),
|
||||
)
|
||||
fig = px.line(title="A-scan")
|
||||
new_trace = go.Scatter(y=data_avec_traitement, mode="lines", name=" Ascan trait ")
|
||||
if(n_clicks!=None):
|
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data_traits=switch_case(data_traits,int(selec_transforme_hilbert))
|
||||
data_traits=switch_case(data_traits,int(select_filtre_1),float(fs_filtre_1),float(cutoff_filtre_1),int(order_filtre_1),int(windowsize_filtre_1))
|
||||
data_traits=switch_case(data_traits,int(select_filtre_2),float(fs_filtre_2),float(cutoff_filtre_2),int(order_filtre_2),int(windowsize_filtre_2))
|
||||
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) "
|
||||
)
|
||||
new_trace = go.Scatter(y=data_sans_traitement, mode='lines', name=' Ascan (hilbert) ')
|
||||
fig.add_trace(new_trace)
|
||||
|
||||
data_bscan=switch_case(volume[select_ascan_y - 1, select_ascan_z[0]:select_ascan_z[1], :],int(selec_transforme_hilbert))
|
||||
data_bscan=switch_case(data_bscan,int(select_filtre_1),float(fs_filtre_1),float(cutoff_filtre_1),int(order_filtre_1),int(windowsize_filtre_1))
|
||||
data_bscan=switch_case(data_bscan,int(select_filtre_2),float(fs_filtre_2),float(cutoff_filtre_2),int(order_filtre_2),int(windowsize_filtre_2))
|
||||
fig2 = px.imshow(
|
||||
volume[select_ascan_y - 1, :, :],
|
||||
data_bscan,
|
||||
color_continuous_scale="Jet",
|
||||
aspect="auto",
|
||||
title="B-scan ZX",
|
||||
)
|
||||
|
||||
return [fig, fig2]
|
||||
|
||||
return [fig, fig2]
|
||||
Reference in New Issue
Block a user