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yalmansour1998
@ -15,12 +15,13 @@ dash.register_page(__name__, path="/ascan", title='A-Scan filters', name='A-Scan
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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, 11)
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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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@ -65,7 +66,7 @@ layout = html.Div(
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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=3,
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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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@ -85,10 +86,12 @@ layout = html.Div(
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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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),
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dbc.Col(
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[
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dbc.Label("applique les filtres selections sur tous les data"),
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dbc.Button(
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id="button-validate-filter",
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children="Valider",
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@ -104,24 +107,39 @@ layout = html.Div(
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config=configAScan,
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style={"marginBottom": "15px"},
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), # 'fig' is your 2D plotly figure
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dbc.Label("x"),
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dcc.Slider(
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id="layer-slider-ascan-solo",
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id="layer-slider-ascan-solo-x",
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min=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={
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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=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={
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str(i): str(i) for i in range(1, dim_x + 1, max(1, int(dim_x / 20)))
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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.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.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=200,
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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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@ -130,12 +148,12 @@ layout = html.Div(
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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.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=3,
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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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@ -144,12 +162,12 @@ layout = html.Div(
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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.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=2,
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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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@ -158,19 +176,80 @@ layout = html.Div(
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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.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=21,
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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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@ -182,33 +261,37 @@ layout = html.Div(
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Input("select-ascan-filter1", "value"),
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Input("select-ascan-filter2", "value"),
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Input("select-ascan-filter3", "value"),
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Input("layer-slider-ascan-solo", "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("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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Input("input-ascan-solo-order", "value"),
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Input("input-ascan-solo-windowsize", "value"),
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Input("input-ascan-solo-fs-2", "value"),
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Input("input-ascan-solo-cutoff-2", "value"),
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Input("input-ascan-solo-order-2", "value"),
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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(value1,value2,value3,value,n_clicks,fs,cutoff,order,windowsize):
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def update_heatmap_ascan(selec_transforme_hilbert,select_filtre_1,select_filtre_2,select_ascan_x,select_ascan_y,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[0,:,1]
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data_sans_traitement=volume[0,:,1]
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data_avec_traitement=switch_case(data_avec_traitement,value1)
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data_sans_traitement=switch_case(data_sans_traitement,value1)
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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(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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print(fs,cutoff,order,windowsize,value2,value3)
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data_avec_traitement=switch_case(data_avec_traitement,value2,fs,cutoff,order,windowsize)
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data_avec_traitement=switch_case(data_avec_traitement,value3,fs,cutoff,order,windowsize)
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#data_avec_traitement=switch_case(data_avec_traitement,3,200,3,2,21)
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#data_avec_traitement=switch_case(data_avec_traitement,2,200,3,2,21)
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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(data_traits,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_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))
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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 traits ')
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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(y=data_sans_traitement, mode='lines', name=' Ascan (hilbert) ')
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fig.add_trace(new_trace)
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