theme updated
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@ -1,290 +0,0 @@
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import argparse
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import os
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from pathlib import Path
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import panel as pn
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import param
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from quacc.evaluation.estimators import CE
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from quacc.evaluation.report import DatasetReport
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pn.extension(design="bootstrap")
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def create_cr_plots(
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dr: DatasetReport,
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mode="delta",
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metric="acc",
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estimators=None,
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prev=None,
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):
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idx = [round(cr.train_prev[1] * 100) for cr in dr.crs].index(prev)
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cr = dr.crs[idx]
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estimators = CE.name[estimators]
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_dpi = 112
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return pn.pane.Matplotlib(
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cr.get_plots(
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mode=mode,
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metric=metric,
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estimators=estimators,
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conf="panel",
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return_fig=True,
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),
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tight=True,
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format="png",
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sizing_mode="scale_height",
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# sizing_mode="scale_both",
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)
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def create_avg_plots(
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dr: DatasetReport,
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mode="delta",
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metric="acc",
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estimators=None,
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prev=None,
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):
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estimators = CE.name[estimators]
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return pn.pane.Matplotlib(
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dr.get_plots(
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mode=mode,
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metric=metric,
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estimators=estimators,
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conf="panel",
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return_fig=True,
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),
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tight=True,
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format="png",
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sizing_mode="scale_height",
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# sizing_mode="scale_both",
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)
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def build_cr_tab(dr: DatasetReport):
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_data = dr.data()
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_metrics = _data.columns.unique(0)
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_estimators = _data.columns.unique(1)
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valid_metrics = [m for m in _metrics if not m.endswith("_score")]
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metric_widget = pn.widgets.Select(
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name="metric",
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value="acc",
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options=valid_metrics,
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align="center",
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)
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valid_estimators = [e for e in _estimators if e != "ref"]
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estimators_widget = pn.widgets.CheckButtonGroup(
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name="estimators",
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options=valid_estimators,
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value=valid_estimators,
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button_style="outline",
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button_type="primary",
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align="center",
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orientation="vertical",
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sizing_mode="scale_width",
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)
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valid_plot_modes = ["delta", "delta_stdev", "diagonal", "shift"]
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plot_mode_widget = pn.widgets.RadioButtonGroup(
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name="mode",
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value=valid_plot_modes[0],
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options=valid_plot_modes,
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button_style="outline",
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button_type="primary",
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align="center",
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orientation="vertical",
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sizing_mode="scale_width",
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)
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valid_prevs = [round(cr.train_prev[1] * 100) for cr in dr.crs]
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prevs_widget = pn.widgets.RadioButtonGroup(
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name="train prevalence",
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value=valid_prevs[0],
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options=valid_prevs,
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button_style="outline",
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button_type="primary",
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align="center",
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orientation="vertical",
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)
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plot_pane = pn.bind(
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create_cr_plots,
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dr=dr,
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mode=plot_mode_widget,
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metric=metric_widget,
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estimators=estimators_widget,
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prev=prevs_widget,
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)
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return pn.Row(
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pn.Spacer(width=20),
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pn.Column(
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metric_widget,
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pn.Row(
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prevs_widget,
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plot_mode_widget,
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),
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estimators_widget,
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align="center",
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),
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pn.Spacer(sizing_mode="scale_width"),
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plot_pane,
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)
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def build_avg_tab(dr: DatasetReport):
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_data = dr.data()
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_metrics = _data.columns.unique(0)
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_estimators = _data.columns.unique(1)
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valid_metrics = [m for m in _metrics if not m.endswith("_score")]
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metric_widget = pn.widgets.Select(
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name="metric",
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value="acc",
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options=valid_metrics,
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align="center",
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)
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valid_estimators = [e for e in _estimators if e != "ref"]
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estimators_widget = pn.widgets.CheckButtonGroup(
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name="estimators",
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options=valid_estimators,
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value=valid_estimators,
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button_style="outline",
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button_type="primary",
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align="center",
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orientation="vertical",
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sizing_mode="scale_width",
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)
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valid_plot_modes = [
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"delta_train",
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"stdev_train",
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"delta_test",
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"stdev_test",
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"shift",
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]
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plot_mode_widget = pn.widgets.RadioButtonGroup(
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name="mode",
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value=valid_plot_modes[0],
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options=valid_plot_modes,
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button_style="outline",
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button_type="primary",
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align="center",
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orientation="vertical",
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sizing_mode="scale_width",
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)
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plot_pane = pn.bind(
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create_avg_plots,
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dr=dr,
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mode=plot_mode_widget,
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metric=metric_widget,
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estimators=estimators_widget,
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)
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return pn.Row(
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pn.Spacer(width=20),
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pn.Column(
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metric_widget,
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plot_mode_widget,
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estimators_widget,
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align="center",
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),
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pn.Spacer(sizing_mode="scale_width"),
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plot_pane,
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)
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def build_dataset(dataset_path: Path):
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dr: DatasetReport = DatasetReport.unpickle(dataset_path)
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prevs_tab = ("train prevs.", build_cr_tab(dr))
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avg_tab = ("avg", build_avg_tab(dr))
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app = pn.Tabs(objects=[avg_tab, prevs_tab], dynamic=False)
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app.servable()
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return app
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def explore_datasets(root: Path | str):
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if isinstance(root, str):
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root = Path(root)
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if root.name == "plot":
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return []
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if not root.exists():
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return []
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drs = []
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for f in os.listdir(root):
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if (root / f).is_dir():
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drs += explore_datasets(root / f)
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elif f == f"{root.name}.pickle":
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drs.append((root, build_dataset(root / f)))
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# drs.append((str(root),))
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return drs
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class PlotSelector(param.Parameterized):
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metric = param.Selector(objects=["acc", "f1"])
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view = param.Selector(objects=["train prevs", "avg"])
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def plot_selector_widget():
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return pn.Param(
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PlotSelector.param,
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widgets={
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"metric": pn.widgets.Select,
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"view": pn.widgets.Select,
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},
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)
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def serve(address="localhost"):
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# app = build_dataset(Path("output/rcv1_CCAT_9prevs/rcv1_CCAT_9prevs.pickle"))
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__base_path = "output"
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__tabs = sorted(
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explore_datasets(__base_path), key=lambda t: (len(t[0].parts), t[0])
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)
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__tabs = [(str(p.relative_to(Path(__base_path))), d) for (p, d) in __tabs]
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if len(__tabs) > 0:
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app = pn.Tabs(
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objects=__tabs,
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tabs_location="left",
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dynamic=False,
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)
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else:
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app = pn.Column(
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pn.pane.Str("No Dataset Found", styles={"font-size": "24pt"}),
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align="center",
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)
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__port = 33420
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__allowed = [address]
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if address == "localhost":
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__allowed.append("127.0.0.1")
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pn.serve(
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app,
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autoreload=True,
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port=__port,
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show=False,
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address=address,
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websocket_origin=[f"{_a}:{__port}" for _a in __allowed],
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)
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def run():
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--address",
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action="store",
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dest="address",
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default="localhost",
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)
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args = parser.parse_args()
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serve(address=args.address)
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@ -1,10 +1,11 @@
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import argparse
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import panel as pn
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from panel.theme.fast import FastDarkTheme, FastDefaultTheme
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from qcpanel.viewer import QuaccTestViewer
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# pn.config.design = pn.theme.Bootstrap
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# pn.config.design = Fast
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# pn.config.theme = "dark"
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pn.config.notifications = True
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],
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main=[pn.Column(qtv.get_plot, sizing_mode="stretch_both")],
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modal=[qtv.modal_pane],
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theme=pn.theme.DarkTheme,
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theme_toggle=False,
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# theme=FastDefaultTheme,
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theme_toggle=True,
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)
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app.servable()
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