feat: Add settings modal to main.py
This commit is contained in:
@ -24,13 +24,40 @@ modal_overlay = dbc.Modal(
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size="lg",
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)
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modal_settings = dbc.Modal(
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[
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dbc.ModalHeader("Settings"),
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dbc.ModalBody(
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[
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dbc.Switch(
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id="use-real-values",
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label="Use real values",
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value=False,
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className="me-2",
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),
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dbc.Input(
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id="echantillonage-x",
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type="number",
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placeholder="Echantillonage X",
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style={"width": "100px"},
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),
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]
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),
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dbc.ModalFooter(
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dbc.Button("Close", id="settings-close", className="settings-bn"),
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),
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],
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id="settings-modal",
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size="lg",
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)
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# on défini les boutons de la navbar
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button_gh = dbc.Button(
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"Learn more",
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id="howto-open",
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outline=True,
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color="secondary",
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style={"textTransform": "none"},
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style={"textTransform": "none", "marginRight": "10px"},
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)
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button_howto = dbc.Button(
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@ -42,6 +69,14 @@ button_howto = dbc.Button(
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style={"textTransform": "none", "marginRight": "10px"},
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)
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button_settings = dbc.Button(
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"Settings",
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outline=True,
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color="success",
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id="settings-open",
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style={"textTransform": "none"},
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)
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navmenu = html.Div(
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dbc.Offcanvas(
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dbc.ListGroup(
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@ -121,7 +156,7 @@ nav_bar = dbc.Navbar(
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[
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dbc.Collapse(
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dbc.Nav(
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[dbc.NavItem(button_howto), dbc.NavItem(button_gh)],
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[dbc.NavItem(button_howto), dbc.NavItem(button_gh), dbc.NavItem(button_settings)],
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className="ml-auto",
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navbar=True,
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),
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@ -132,6 +167,7 @@ nav_bar = dbc.Navbar(
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align="right",
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),
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modal_overlay,
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modal_settings,
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navmenu,
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],
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align="center",
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@ -162,6 +198,16 @@ def toggle_modal(n1, n2, is_open):
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return not is_open
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return is_open
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@app.callback(
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Output("settings-modal", "is_open"),
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[Input("settings-open", "n_clicks"), Input("settings-close", "n_clicks")],
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[dash.dependencies.State("settings-modal", "is_open")],
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)
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def toggle_settings(n1, n2, is_open):
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if n1 or n2:
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return not is_open
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return is_open
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# callback pour le navmenu
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@app.callback(
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@ -10,18 +10,20 @@ from filtrage import *
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from selection_filtre import *
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dash.register_page(__name__, path="/ascan", title='A-Scan filters', name='A-Scan filters')
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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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# 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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@ -52,7 +54,8 @@ layout = html.Div(
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value=1,
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style={"margin-bottom": "15px"},
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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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@ -63,13 +66,20 @@ 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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{"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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"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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],
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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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width=3,
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),
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dbc.Col(
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[
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@ -80,14 +90,20 @@ 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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{"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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"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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],
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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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width=3,
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),
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dbc.Col(
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[
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@ -98,165 +114,203 @@ 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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],
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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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[
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dbc.Col(
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dcc.Graph(
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id="heatmap-ascan-solo",
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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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width=8,
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),
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dbc.Col(
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dcc.Graph(
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id="heatmap-bscan-solo",
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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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width=4,
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),
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]
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),
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dcc.Graph(
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id="heatmap-ascan-solo",
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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-x",
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min=1,
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max=dim_z,
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max=dim_z - 1,
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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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marks={str(i): str(i) for i in range(1, dim_z + 1, max(1, int(dim_z / 20)))},
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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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min=0,
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max=dim_x - 1,
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value=0,
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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+1,1)
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},
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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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),
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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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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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),
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],
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width=3,
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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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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"),
|
||||
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(
|
||||
id="input-ascan-solo-order-2",
|
||||
type="number",
|
||||
placeholder="order",
|
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value=1,
|
||||
step=1,
|
||||
style={"marginTop": "15px"},
|
||||
),
|
||||
],
|
||||
width=3,
|
||||
),
|
||||
dbc.Col(
|
||||
[
|
||||
dbc.Label("window size ", html_for="window size"),
|
||||
dbc.Input(
|
||||
id="input-ascan-solo-windowsize-2",
|
||||
type="number",
|
||||
placeholder="window_size",
|
||||
value=1,
|
||||
step=1,
|
||||
style={"marginTop": "15px"},
|
||||
),
|
||||
],
|
||||
width=3,
|
||||
),
|
||||
]),
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||||
],
|
||||
|
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style={"padding": "20px"},
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)
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# callback to update filter values
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@callback(
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[
|
||||
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"),
|
||||
],
|
||||
[
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||||
Input("select-ascan-filter2", "value"),
|
||||
Input("select-ascan-filter3", "value"),
|
||||
],
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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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# callback to update the heatmap
|
||||
@callback(
|
||||
Output("heatmap-ascan-solo", "figure"),
|
||||
[Output("heatmap-ascan-solo", "figure"), Output("heatmap-bscan-solo", "figure")],
|
||||
[
|
||||
Input("select-ascan-filter1", "value"),
|
||||
Input("select-ascan-filter2", "value"),
|
||||
@ -274,25 +328,81 @@ layout = html.Div(
|
||||
Input("input-ascan-solo-windowsize-2", "value"),
|
||||
],
|
||||
)
|
||||
|
||||
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):
|
||||
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,
|
||||
):
|
||||
# TODO: implement the filter
|
||||
print("debut du traitement")
|
||||
data_avec_traitement=volume[int(select_ascan_y)-1,:,int(select_ascan_x)-1]
|
||||
data_sans_traitement=volume[int(select_ascan_y)-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))
|
||||
data_avec_traitement = volume[int(select_ascan_y) - 1, :, int(select_ascan_x) - 1]
|
||||
data_sans_traitement = volume[int(select_ascan_y) - 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")
|
||||
if(n_clicks!=None):
|
||||
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 ')
|
||||
if n_clicks != None:
|
||||
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)
|
||||
return fig
|
||||
|
||||
fig2 = px.imshow(
|
||||
volume[select_ascan_y - 1, :, :],
|
||||
color_continuous_scale="Jet",
|
||||
aspect="auto",
|
||||
title="B-scan ZX",
|
||||
)
|
||||
|
||||
return [fig, fig2]
|
||||
|
||||
@ -16,7 +16,7 @@ fichiers_selectionnes = [
|
||||
]
|
||||
|
||||
# on charge le fichier numpy
|
||||
fichiers = np.load("Dataset/npy/export.npy")
|
||||
# fichiers = np.load("Dataset/npy/export.npy")
|
||||
|
||||
# valeurs d'échantillonage
|
||||
echantillonage_x = 1
|
||||
@ -96,347 +96,354 @@ configBScanZX = {
|
||||
|
||||
# on crée les cartes
|
||||
# carte pour le plot 3D
|
||||
mesh_card = dbc.Card(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"3D Plot",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
width="4",
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-3dplot",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
),
|
||||
],
|
||||
),
|
||||
dcc.Graph(
|
||||
id="3dplot",
|
||||
figure=fig,
|
||||
config=config3DPlot,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 3D plotly figure
|
||||
dcc.Slider(
|
||||
id="iso-slider",
|
||||
min=volume.min(),
|
||||
max=volume.max() / 2,
|
||||
value=volume.min(),
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
int(volume.min()),
|
||||
int(volume.max() / 2) + 1,
|
||||
int((volume.max() / 2 - volume.min()) / 10),
|
||||
)
|
||||
},
|
||||
step=1,
|
||||
),
|
||||
dcc.RangeSlider(
|
||||
id="y-slider",
|
||||
min=0,
|
||||
max=dim_y,
|
||||
value=[0, dim_y / 2],
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(0, int(dim_y) + 1, max(1, int(dim_y / 20)))
|
||||
},
|
||||
step=1,
|
||||
),
|
||||
dbc.Modal(
|
||||
[
|
||||
dbc.ModalHeader(dbc.ModalTitle("3D Plot")),
|
||||
dbc.ModalBody(
|
||||
[
|
||||
dcc.Graph(
|
||||
id="3dplot-fullscreen",
|
||||
figure=fig,
|
||||
config=config3DPlot,
|
||||
style={"marginBottom": "15px", "height": "90%"},
|
||||
), # 'fig' is your 3D plotly figure
|
||||
dcc.Slider(
|
||||
id="iso-slider-fullscreen",
|
||||
min=volume.min(),
|
||||
max=volume.max() / 2,
|
||||
value=volume.min(),
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
int(volume.min()),
|
||||
int(volume.max() / 2) + 1,
|
||||
int((volume.max() / 2 - volume.min()) / 20),
|
||||
)
|
||||
},
|
||||
step=1,
|
||||
mesh_card = dbc.Fade(
|
||||
dbc.Card(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"3D Plot",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
dcc.RangeSlider(
|
||||
id="y-slider-fullscreen",
|
||||
min=0,
|
||||
max=dim_y,
|
||||
value=[0, dim_y / 2],
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
0, int(dim_y) + 1, max(1, int(dim_y / 50))
|
||||
)
|
||||
},
|
||||
step=1,
|
||||
width="4",
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-3dplot",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
]
|
||||
),
|
||||
],
|
||||
id="modal-3dplot",
|
||||
fullscreen=True,
|
||||
),
|
||||
]
|
||||
)
|
||||
]
|
||||
),
|
||||
],
|
||||
),
|
||||
dcc.Graph(
|
||||
id="3dplot",
|
||||
figure=fig,
|
||||
config=config3DPlot,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 3D plotly figure
|
||||
dcc.Slider(
|
||||
id="iso-slider",
|
||||
min=volume.min(),
|
||||
max=volume.max() / 2,
|
||||
value=volume.min(),
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
int(volume.min()),
|
||||
int(volume.max() / 2) + 1,
|
||||
int((volume.max() / 2 - volume.min()) / 10),
|
||||
)
|
||||
},
|
||||
step=1,
|
||||
),
|
||||
dcc.RangeSlider(
|
||||
id="y-slider",
|
||||
min=0,
|
||||
max=dim_y,
|
||||
value=[0, dim_y / 2],
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(0, int(dim_y) + 1, max(1, int(dim_y / 20)))
|
||||
},
|
||||
step=1,
|
||||
),
|
||||
dbc.Modal(
|
||||
[
|
||||
dbc.ModalHeader(dbc.ModalTitle("3D Plot")),
|
||||
dbc.ModalBody(
|
||||
[
|
||||
dcc.Graph(
|
||||
id="3dplot-fullscreen",
|
||||
figure=fig,
|
||||
config=config3DPlot,
|
||||
style={"marginBottom": "15px", "height": "90%"},
|
||||
), # 'fig' is your 3D plotly figure
|
||||
dcc.Slider(
|
||||
id="iso-slider-fullscreen",
|
||||
min=volume.min(),
|
||||
max=volume.max() / 2,
|
||||
value=volume.min(),
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
int(volume.min()),
|
||||
int(volume.max() / 2) + 1,
|
||||
int(
|
||||
(volume.max() / 2 - volume.min())
|
||||
/ 20
|
||||
),
|
||||
)
|
||||
},
|
||||
step=1,
|
||||
),
|
||||
dcc.RangeSlider(
|
||||
id="y-slider-fullscreen",
|
||||
min=0,
|
||||
max=dim_y,
|
||||
value=[0, dim_y / 2],
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
0,
|
||||
int(dim_y) + 1,
|
||||
max(1, int(dim_y / 50)),
|
||||
)
|
||||
},
|
||||
step=1,
|
||||
),
|
||||
]
|
||||
),
|
||||
],
|
||||
id="modal-3dplot",
|
||||
fullscreen=True,
|
||||
),
|
||||
]
|
||||
)
|
||||
]
|
||||
),
|
||||
id="fade-3dplot",
|
||||
is_in=False,
|
||||
appear=False,
|
||||
)
|
||||
|
||||
# carte pour le A-scan
|
||||
Ascan_card = dbc.Card(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"A-scan",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
width="4",
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-ascan",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
),
|
||||
],
|
||||
),
|
||||
dcc.Graph(
|
||||
id="heatmap-ascan",
|
||||
config=configAScan,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-ascan",
|
||||
min=0,
|
||||
max=dim_x - 1,
|
||||
value=0,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i) for i in range(0, dim_x, max(1, int(dim_x / 20)))
|
||||
},
|
||||
),
|
||||
dcc.Slider(
|
||||
id="ascan-slider",
|
||||
min=1,
|
||||
max=dim_z - 1,
|
||||
value=0,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i) for i in range(1, dim_z, max(1, int(dim_z / 20)))
|
||||
},
|
||||
),
|
||||
dbc.Modal(
|
||||
[
|
||||
dbc.ModalHeader(dbc.ModalTitle("A-Scan")),
|
||||
dbc.ModalBody(
|
||||
[
|
||||
dcc.Graph(
|
||||
id="heatmap-ascan-fullscreen",
|
||||
config=configAScan,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-ascan-fullscreen",
|
||||
min=0,
|
||||
max=dim_x,
|
||||
value=0,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
0, dim_x, max(1, int(dim_x / 50))
|
||||
)
|
||||
},
|
||||
Ascan_card = dbc.Fade(
|
||||
dbc.Card(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"A-scan",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
]
|
||||
),
|
||||
],
|
||||
id="modal-ascan",
|
||||
fullscreen=True,
|
||||
),
|
||||
]
|
||||
)
|
||||
]
|
||||
width="4",
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-ascan",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
),
|
||||
],
|
||||
),
|
||||
dcc.Graph(
|
||||
id="heatmap-ascan",
|
||||
config=configAScan,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dbc.Modal(
|
||||
[
|
||||
dbc.ModalHeader(dbc.ModalTitle("A-Scan")),
|
||||
dbc.ModalBody(
|
||||
[
|
||||
dcc.Graph(
|
||||
id="heatmap-ascan-fullscreen",
|
||||
config=configAScan,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-ascan-fullscreen",
|
||||
min=0,
|
||||
max=dim_x,
|
||||
value=0,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
0, dim_x, max(1, int(dim_x / 50))
|
||||
)
|
||||
},
|
||||
),
|
||||
]
|
||||
),
|
||||
],
|
||||
id="modal-ascan",
|
||||
fullscreen=True,
|
||||
),
|
||||
],
|
||||
style={"height": "599px"},
|
||||
)
|
||||
],
|
||||
),
|
||||
id="fade-ascan",
|
||||
is_in=False,
|
||||
appear=False,
|
||||
)
|
||||
|
||||
# carte pour le B-scan ZX
|
||||
Bscan_card_xy = dbc.Card(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"B-scan ZX",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
width="4",
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-bscan-zx",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
),
|
||||
],
|
||||
),
|
||||
dcc.Graph(
|
||||
id="heatmap-bscan-zx",
|
||||
config=configBScanZX,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-bscan-zx",
|
||||
min=0,
|
||||
max=dim_x - 1,
|
||||
value=0,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i) for i in range(0, dim_x, max(1, int(dim_x / 20)))
|
||||
},
|
||||
),
|
||||
dbc.Modal(
|
||||
[
|
||||
dbc.ModalHeader(dbc.ModalTitle("B-Scan ZX")),
|
||||
dbc.ModalBody(
|
||||
[
|
||||
dcc.Graph(
|
||||
id="heatmap-bscan-zx-fullscreen",
|
||||
config=configBScanXY,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-bscan-zx-fullscreen",
|
||||
min=0,
|
||||
max=dim_x,
|
||||
value=0,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
0, dim_x + 1, max(1, int(dim_x / 50))
|
||||
)
|
||||
},
|
||||
Bscan_card_xy = dbc.Fade(
|
||||
dbc.Card(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"B-scan ZX",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
]
|
||||
),
|
||||
],
|
||||
id="modal-bscan-zx",
|
||||
fullscreen=True,
|
||||
),
|
||||
]
|
||||
)
|
||||
]
|
||||
width="4",
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-bscan-zx",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
),
|
||||
],
|
||||
),
|
||||
dcc.Graph(
|
||||
id="heatmap-bscan-zx",
|
||||
config=configBScanZX,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-bscan-zx",
|
||||
min=0,
|
||||
max=dim_x - 1,
|
||||
value=0,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(0, dim_x, max(1, int(dim_x / 20)))
|
||||
},
|
||||
),
|
||||
dbc.Modal(
|
||||
[
|
||||
dbc.ModalHeader(dbc.ModalTitle("B-Scan ZX")),
|
||||
dbc.ModalBody(
|
||||
[
|
||||
dcc.Graph(
|
||||
id="heatmap-bscan-zx-fullscreen",
|
||||
config=configBScanXY,
|
||||
style={"marginBottom": "15px", "height": "90%"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-bscan-zx-fullscreen",
|
||||
min=0,
|
||||
max=dim_x,
|
||||
value=0,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
0, dim_x + 1, max(1, int(dim_x / 50))
|
||||
)
|
||||
},
|
||||
),
|
||||
]
|
||||
),
|
||||
],
|
||||
id="modal-bscan-zx",
|
||||
fullscreen=True,
|
||||
),
|
||||
]
|
||||
)
|
||||
]
|
||||
),
|
||||
id="fade-bscan-zx",
|
||||
is_in=False,
|
||||
appear=False,
|
||||
)
|
||||
|
||||
# carte pour le B-scan ZX
|
||||
Bscan_card_zx = dbc.Card(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"B-scan XY",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
width="4",
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-bscan-xy",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
),
|
||||
],
|
||||
),
|
||||
dcc.Graph(
|
||||
id="heatmap-bscan-xy",
|
||||
config=configBScanXY,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-bscan-xy",
|
||||
min=1,
|
||||
max=dim_z - 1,
|
||||
value=1,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(1, dim_z + 1, max(1, int(dim_z / 20)))
|
||||
},
|
||||
),
|
||||
dbc.Modal(
|
||||
[
|
||||
dbc.ModalHeader(dbc.ModalTitle("B-Scan XY")),
|
||||
dbc.ModalBody(
|
||||
[
|
||||
dcc.Graph(
|
||||
id="heatmap-bscan-xy-fullscreen",
|
||||
config=configBScanXY,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-bscan-xy-fullscreen",
|
||||
min=1,
|
||||
max=dim_z - 1,
|
||||
value=1,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
1, dim_z + 1, max(1, int(dim_z / 50))
|
||||
)
|
||||
},
|
||||
Bscan_card_zx = dbc.Fade(
|
||||
dbc.Card(
|
||||
[
|
||||
dbc.CardBody(
|
||||
[
|
||||
dbc.Row(
|
||||
[
|
||||
dbc.Col(
|
||||
html.H2(
|
||||
"B-scan XY",
|
||||
className="card-title",
|
||||
style={"textAlign": "left"},
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
id="modal-bscan-xy",
|
||||
fullscreen=True,
|
||||
),
|
||||
]
|
||||
)
|
||||
]
|
||||
width="4",
|
||||
),
|
||||
dbc.Col(
|
||||
dbc.Button(
|
||||
html.I(className="bi bi-arrows-fullscreen"),
|
||||
id="fullscreen-button-bscan-xy",
|
||||
className="mb-3",
|
||||
color="primary",
|
||||
style={"marginBottom": "15px"},
|
||||
),
|
||||
),
|
||||
],
|
||||
),
|
||||
dcc.Graph(
|
||||
id="heatmap-bscan-xy",
|
||||
config=configBScanXY,
|
||||
style={"marginBottom": "15px"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-bscan-xy",
|
||||
min=1,
|
||||
max=dim_z - 1,
|
||||
value=1,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(1, dim_z + 1, max(1, int(dim_z / 20)))
|
||||
},
|
||||
),
|
||||
dbc.Modal(
|
||||
[
|
||||
dbc.ModalHeader(dbc.ModalTitle("B-Scan XY")),
|
||||
dbc.ModalBody(
|
||||
[
|
||||
dcc.Graph(
|
||||
id="heatmap-bscan-xy-fullscreen",
|
||||
config=configBScanXY,
|
||||
style={"marginBottom": "15px", "height": "90%"},
|
||||
), # 'fig' is your 2D plotly figure
|
||||
dcc.Slider(
|
||||
id="layer-slider-bscan-xy-fullscreen",
|
||||
min=1,
|
||||
max=dim_z - 1,
|
||||
value=1,
|
||||
step=1,
|
||||
marks={
|
||||
str(i): str(i)
|
||||
for i in range(
|
||||
1, dim_z + 1, max(1, int(dim_z / 50))
|
||||
)
|
||||
},
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
id="modal-bscan-xy",
|
||||
fullscreen=True,
|
||||
),
|
||||
]
|
||||
)
|
||||
]
|
||||
),
|
||||
id="fade-bscan-xy",
|
||||
is_in=False,
|
||||
appear=False,
|
||||
)
|
||||
|
||||
layout = html.Div(
|
||||
@ -451,6 +458,7 @@ layout = html.Div(
|
||||
),
|
||||
dcc.Store(id="store-bscan-xy-layer", data=1),
|
||||
dcc.Store(id="store-bscan-zx-layer", data=0),
|
||||
dcc.Store(id="store-settings", data={"use_real_values": False, "echantillonage_x": 1, "echantillonage_y": 32, "echantillonage_z": 1}),
|
||||
]
|
||||
)
|
||||
|
||||
@ -458,17 +466,29 @@ layout = html.Div(
|
||||
# on défini les callbacks
|
||||
# callback pour le plot 3D
|
||||
@callback(
|
||||
Output("3dplot", "figure"),
|
||||
[Input("iso-slider", "value"), Input("y-slider", "value")],
|
||||
[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):
|
||||
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],
|
||||
]
|
||||
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(
|
||||
@ -484,7 +504,7 @@ def update_3dplot(iso_value, y_values):
|
||||
)
|
||||
)
|
||||
|
||||
return fig
|
||||
return [fig, True]
|
||||
|
||||
|
||||
# callback pour le plot 3D en plein écran
|
||||
@ -520,12 +540,18 @@ def update_3dplot_fullscreen(iso_value, y_values):
|
||||
|
||||
# callback pour le A-scan
|
||||
@callback(
|
||||
Output("heatmap-ascan", "figure"),
|
||||
Input("layer-slider-ascan", "value"),
|
||||
[
|
||||
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):
|
||||
fig = px.line(y=volume[layer - 1, :, 5], title="A-scan")
|
||||
return fig
|
||||
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
|
||||
@ -543,11 +569,13 @@ def update_heatmap_ascan_fullscreen(layer):
|
||||
[
|
||||
Output("heatmap-bscan-zx", "figure"),
|
||||
Output("store-bscan-zx-layer", "data"),
|
||||
Output("fade-bscan-zx", "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):
|
||||
def update_heatmap_bscan_zx(layer, is_in):
|
||||
fig = px.imshow(
|
||||
volume[layer - 1, :, :],
|
||||
color_continuous_scale="Jet",
|
||||
@ -555,7 +583,7 @@ def update_heatmap_bscan_zx(layer):
|
||||
title="B-scan ZX",
|
||||
)
|
||||
|
||||
return [fig, layer]
|
||||
return [fig, layer, True]
|
||||
|
||||
|
||||
# callback pour les B-scan ZX en plein écran
|
||||
@ -576,14 +604,20 @@ def update_heatmap_bscan_zx_fullscreen(layer):
|
||||
|
||||
# callback pour les B-scan ZX
|
||||
@callback(
|
||||
[Output("heatmap-bscan-xy", "figure"), Output("store-bscan-xy-layer", "data")],
|
||||
[
|
||||
Output("heatmap-bscan-xy", "figure"),
|
||||
Output("store-bscan-xy-layer", "data"),
|
||||
Output("fade-bscan-xy", "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):
|
||||
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]
|
||||
return [fig, layer, True]
|
||||
|
||||
|
||||
# callback pour les B-scan ZX en plein écran
|
||||
@ -593,6 +627,7 @@ def update_heatmap_bscan_xy(layer):
|
||||
)
|
||||
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
|
||||
|
||||
@ -688,14 +723,18 @@ def display_bscan_xy_click_data(clickData):
|
||||
)
|
||||
def display_bscan_zx_click_data(clickData):
|
||||
if clickData is None:
|
||||
return [None, 1]
|
||||
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-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,
|
||||
)
|
||||
@ -703,12 +742,13 @@ 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,
|
||||
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, :, :],
|
||||
@ -725,4 +765,14 @@ def update_bscan_layers(bscan_xy, bscan_zx):
|
||||
line=dict(color="white", width=1),
|
||||
)
|
||||
|
||||
return [fig, fig2]
|
||||
fig3 = px.line(y=volume[bscan_zx - 1, :, bscan_xy], title="A-scan")
|
||||
|
||||
return [fig, fig2, fig3]
|
||||
|
||||
|
||||
@callback(
|
||||
Output("store-settings", "data"),
|
||||
[Input("use-real-values", "value")],
|
||||
)
|
||||
def update_settings(use_real_values):
|
||||
return {"use_real_values": use_real_values}
|
||||
|
||||
Reference in New Issue
Block a user