311 lines
10 KiB
Python
311 lines
10 KiB
Python
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 qcpanel.util import build_plot, explore_datasets, valid_plot_modes
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from quacc.evaluation.comp import CE
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from quacc.evaluation.report import DatasetReport
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class QuaccTestViewer(param.Parameterized):
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dataset = param.Selector()
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metric = param.Selector()
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estimators = param.ListSelector()
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plot_view = param.Selector()
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mode = param.Selector()
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modal_estimators = param.ListSelector()
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modal_plot_view = param.ListSelector()
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modal_mode_prev = param.ListSelector(
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objects=valid_plot_modes[0], default=valid_plot_modes[0]
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)
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modal_mode_avg = param.ListSelector(
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objects=valid_plot_modes["avg"], default=valid_plot_modes["avg"]
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)
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param_pane = param.Parameter()
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plot_pane = param.Parameter()
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modal_pane = param.Parameter()
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def __init__(self, **params):
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super().__init__(**params)
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self.__setup_watchers()
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self.update_datasets()
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# self._update_on_dataset()
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self.__create_param_pane()
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self.__create_modal_pane()
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def __save_callback(self, event):
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_home = Path("output")
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_save_input_val = self.save_input.value_input
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_config = "default" if len(_save_input_val) == 0 else _save_input_val
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base_path = _home / self.dataset / _config
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os.makedirs(base_path, exist_ok=True)
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base_plot = base_path / "plot"
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os.makedirs(base_plot, exist_ok=True)
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l_dr = self.datasets_[self.dataset]
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res = l_dr.to_md(
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conf=_config,
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metric=self.metric,
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estimators=CE.name[self.modal_estimators],
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dr_modes=self.modal_mode_avg,
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cr_modes=self.modal_mode_prev,
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cr_prevs=self.modal_plot_view,
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plot_path=base_plot,
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)
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with open(base_path / f"{self.metric}.md", "w") as f:
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f.write(res)
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pn.state.notifications.success(f'"{_config}" successfully saved')
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def __create_param_pane(self):
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self.dataset_widget = pn.Param(
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self,
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show_name=False,
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parameters=["dataset"],
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widgets={"dataset": {"widget_type": pn.widgets.Select}},
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)
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self.metric_widget = pn.Param(
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self,
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show_name=False,
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parameters=["metric"],
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widgets={"metric": {"widget_type": pn.widgets.Select}},
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)
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self.estimators_widgets = pn.Param(
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self,
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show_name=False,
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parameters=["estimators"],
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widgets={
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"estimators": {
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"widget_type": pn.widgets.CheckButtonGroup,
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"orientation": "vertical",
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"sizing_mode": "scale_width",
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"button_type": "primary",
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"button_style": "outline",
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}
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},
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)
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self.plot_view_widget = pn.Param(
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self,
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show_name=False,
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parameters=["plot_view"],
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widgets={
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"plot_view": {
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"widget_type": pn.widgets.RadioButtonGroup,
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"orientation": "vertical",
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"button_type": "primary",
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"button_style": "outline",
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}
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},
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)
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self.mode_widget = pn.Param(
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self,
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show_name=False,
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parameters=["mode"],
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widgets={
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"mode": {
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"widget_type": pn.widgets.RadioButtonGroup,
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"orientation": "vertical",
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"sizing_mode": "scale_width",
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"button_type": "primary",
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"button_style": "outline",
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}
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},
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align="center",
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)
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self.param_pane = pn.Column(
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self.dataset_widget,
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self.metric_widget,
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pn.Row(
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self.plot_view_widget,
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self.mode_widget,
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),
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self.estimators_widgets,
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)
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def __create_modal_pane(self):
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self.modal_estimators_widgets = pn.Param(
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self,
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show_name=False,
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parameters=["modal_estimators"],
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widgets={
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"modal_estimators": {
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"widget_type": pn.widgets.CheckButtonGroup,
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"orientation": "vertical",
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"sizing_mode": "scale_width",
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"button_type": "primary",
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"button_style": "outline",
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}
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},
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)
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self.modal_plot_view_widget = pn.Param(
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self,
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show_name=False,
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parameters=["modal_plot_view"],
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widgets={
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"modal_plot_view": {
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"widget_type": pn.widgets.CheckButtonGroup,
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"orientation": "vertical",
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"button_type": "primary",
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"button_style": "outline",
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}
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},
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)
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self.modal_mode_prev_widget = pn.Param(
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self,
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show_name=False,
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parameters=["modal_mode_prev"],
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widgets={
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"modal_mode_prev": {
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"widget_type": pn.widgets.CheckButtonGroup,
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"orientation": "vertical",
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"sizing_mode": "scale_width",
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"button_type": "primary",
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"button_style": "outline",
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}
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},
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align="center",
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)
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self.modal_mode_avg_widget = pn.Param(
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self,
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show_name=False,
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parameters=["modal_mode_avg"],
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widgets={
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"modal_mode_avg": {
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"widget_type": pn.widgets.CheckButtonGroup,
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"orientation": "vertical",
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"sizing_mode": "scale_width",
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"button_type": "primary",
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"button_style": "outline",
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}
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},
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align="center",
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)
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self.save_input = pn.widgets.TextInput(
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name="Configuration Name", placeholder="default", sizing_mode="scale_width"
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)
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self.save_button = pn.widgets.Button(
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name="Save",
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sizing_mode="scale_width",
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button_style="solid",
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button_type="success",
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)
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self.save_button.on_click(self.__save_callback)
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_title_styles = {
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"font-size": "14pt",
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"font-weight": "bold",
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}
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self.modal_pane = pn.Column(
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pn.Column(
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pn.pane.Str("Avg. configuration", styles=_title_styles),
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self.modal_mode_avg_widget,
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pn.pane.Str("Train prevs. configuration", styles=_title_styles),
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pn.Row(
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self.modal_plot_view_widget,
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self.modal_mode_prev_widget,
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),
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pn.pane.Str("Estimators configuration", styles=_title_styles),
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self.modal_estimators_widgets,
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self.save_input,
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self.save_button,
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pn.Spacer(height=20),
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width=450,
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align="center",
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scroll=True,
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),
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sizing_mode="stretch_both",
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)
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def update_datasets(self):
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__base_path = "output"
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dataset_paths = sorted(
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explore_datasets(__base_path), key=lambda t: (-len(t.parts), t)
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)
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self.datasets_ = {
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str(dp.parent.relative_to(Path(__base_path))): DatasetReport.unpickle(dp)
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for dp in dataset_paths
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}
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self.available_datasets = list(self.datasets_.keys())
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self.param["dataset"].objects = self.available_datasets
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self.dataset = self.available_datasets[0]
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def __setup_watchers(self):
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self.param.watch(
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self._update_on_dataset,
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["dataset"],
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queued=True,
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precedence=0,
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)
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self.param.watch(self._update_on_view, ["plot_view"], queued=True, precedence=1)
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self.param.watch(
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self._update_plot,
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["dataset", "metric", "estimators", "plot_view", "mode"],
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# ["metric", "estimators", "mode"],
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onlychanged=False,
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precedence=2,
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)
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self.param.watch(
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self._update_on_estimators,
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["estimators"],
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queued=True,
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precedence=3,
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)
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def _update_on_dataset(self, *events):
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l_dr = self.datasets_[self.dataset]
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l_data = l_dr.data()
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l_metrics = l_data.columns.unique(0)
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l_estimators = l_data.columns.unique(1)
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l_valid_estimators = [e for e in l_estimators if e != "ref"]
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l_valid_metrics = [m for m in l_metrics if not m.endswith("_score")]
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l_valid_views = [str(round(cr.train_prev[1] * 100)) for cr in l_dr.crs]
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self.param["metric"].objects = l_valid_metrics
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self.metric = l_valid_metrics[0]
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self.param["estimators"].objects = l_valid_estimators
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self.estimators = l_valid_estimators
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self.param["plot_view"].objects = ["avg"] + l_valid_views
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self.plot_view = "avg"
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self.param["mode"].objects = valid_plot_modes["avg"]
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self.mode = valid_plot_modes["avg"][0]
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self.param["modal_estimators"].objects = l_valid_estimators
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self.modal_estimators = []
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self.param["modal_plot_view"].objects = l_valid_views
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self.modal_plot_view = l_valid_views.copy()
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def _update_on_view(self, *events):
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self.param["mode"].objects = valid_plot_modes[self.plot_view]
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self.mode = valid_plot_modes[self.plot_view][0]
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def _update_on_estimators(self, *events):
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self.modal_estimators = self.estimators.copy()
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def _update_plot(self, *events):
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self.plot_pane = build_plot(
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datasets=self.datasets_,
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dst=self.dataset,
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metric=self.metric,
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estimators=self.estimators,
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view=self.plot_view,
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mode=self.mode,
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)
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def get_plot(self):
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return self.plot_pane
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def get_param_pane(self):
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return self.param_pane
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