panel refactored
This commit is contained in:
Lorenzo Volpi
parent
e69e8381e3
commit
2aa77d9e19
149
qcpanel/util.py
149
qcpanel/util.py
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@ -13,7 +13,7 @@ valid_plot_modes = defaultdict(lambda: CompReport._default_modes)
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valid_plot_modes["avg"] = DatasetReport._default_dr_modes
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def create_plots(
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def create_plot(
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dr: DatasetReport,
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mode="delta",
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metric="acc",
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@ -24,28 +24,7 @@ def create_plots(
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estimators = CE.name[estimators]
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if mode is None:
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mode = valid_plot_modes[plot_view][0]
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_dpi = 112
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match (plot_view, mode):
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case ("avg", "train_table"):
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_data = (
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dr.data(metric=metric, estimators=estimators).groupby(level=1).mean()
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)
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return pn.pane.DataFrame(_data, align="center") if not _data.empty else None
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case ("avg", "test_table"):
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_data = (
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dr.data(metric=metric, estimators=estimators).groupby(level=0).mean()
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)
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return pn.pane.DataFrame(_data, align="center") if not _data.empty else None
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case ("avg", "shift_table"):
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_data = (
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dr.shift_data(metric=metric, estimators=estimators)
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.groupby(level=0)
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.mean()
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)
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return pn.pane.DataFrame(_data, align="center") if not _data.empty else None
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case ("avg", "stats_table"):
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_data = wilcoxon(dr, metric=metric, estimators=estimators)
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return pn.pane.DataFrame(_data, align="center") if not _data.empty else None
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case ("avg", _ as plot_mode):
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_plot = dr.get_plots(
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mode=mode,
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@ -54,36 +33,6 @@ def create_plots(
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conf="panel",
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save_fig=False,
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)
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return (
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pn.pane.Matplotlib(
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_plot,
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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=_plot_sizing_mode,
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# sizing_mode="scale_both",
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)
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if _plot is not None
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else None
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)
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case (_, "train_table"):
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cr = dr.crs[_prevs.index(int(plot_view))]
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_data = (
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cr.data(metric=metric, estimators=estimators).groupby(level=0).mean()
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)
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return pn.pane.DataFrame(_data, align="center") if not _data.empty else None
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case (_, "shift_table"):
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cr = dr.crs[_prevs.index(int(plot_view))]
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_data = (
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cr.shift_data(metric=metric, estimators=estimators)
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.groupby(level=0)
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.mean()
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)
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return pn.pane.DataFrame(_data, align="center") if not _data.empty else None
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case (_, "stats_table"):
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cr = dr.crs[_prevs.index(int(plot_view))]
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_data = wilcoxon(cr, metric=metric, estimators=estimators)
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return pn.pane.DataFrame(_data, align="center") if not _data.empty else None
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case (_, _ as plot_mode):
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cr = dr.crs[_prevs.index(int(plot_view))]
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_plot = cr.get_plots(
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@ -93,18 +42,92 @@ def create_plots(
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conf="panel",
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save_fig=False,
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)
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return (
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pn.pane.Matplotlib(
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_plot,
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tight=True,
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format="png",
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sizing_mode=_plot_sizing_mode,
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# sizing_mode="scale_height",
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# sizing_mode="scale_both",
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)
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if _plot is not None
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else None
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if _plot is None:
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return None
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return pn.pane.Matplotlib(
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_plot,
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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=_plot_sizing_mode,
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styles=dict(margin="0"),
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# sizing_mode="scale_both",
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)
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def create_table(
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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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plot_view=None,
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):
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_prevs = [round(cr.train_prev[1] * 100) for cr in dr.crs]
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estimators = CE.name[estimators]
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if mode is None:
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mode = valid_plot_modes[plot_view][0]
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match (plot_view, mode):
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case ("avg", "train_table"):
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_data = (
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dr.data(metric=metric, estimators=estimators).groupby(level=1).mean()
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)
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case ("avg", "test_table"):
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_data = (
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dr.data(metric=metric, estimators=estimators).groupby(level=0).mean()
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)
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case ("avg", "shift_table"):
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_data = (
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dr.shift_data(metric=metric, estimators=estimators)
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.groupby(level=0)
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.mean()
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)
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case ("avg", "stats_table"):
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_data = wilcoxon(dr, metric=metric, estimators=estimators)
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case (_, "train_table"):
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cr = dr.crs[_prevs.index(int(plot_view))]
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_data = (
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cr.data(metric=metric, estimators=estimators).groupby(level=0).mean()
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)
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case (_, "shift_table"):
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cr = dr.crs[_prevs.index(int(plot_view))]
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_data = (
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cr.shift_data(metric=metric, estimators=estimators)
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.groupby(level=0)
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.mean()
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)
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case (_, "stats_table"):
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cr = dr.crs[_prevs.index(int(plot_view))]
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_data = wilcoxon(cr, metric=metric, estimators=estimators)
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return (
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pn.Column(
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pn.pane.DataFrame(
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_data,
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align="center",
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float_format=lambda v: f"{v:6e}",
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styles={"font-size-adjust": "0.62"},
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),
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sizing_mode="stretch_both",
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# scroll=True,
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)
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if not _data.empty
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else None
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)
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def create_result(
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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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plot_view=None,
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):
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match mode:
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case m if m.endswith("table"):
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return create_table(dr, mode, metric, estimators, plot_view)
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case _:
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return create_plot(dr, mode, metric, estimators, plot_view)
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def explore_datasets(root: Path | str):
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@ -6,7 +6,7 @@ import pandas as pd
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import panel as pn
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import param
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from qcpanel.util import create_plots, explore_datasets, valid_plot_modes
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from qcpanel.util import create_result, explore_datasets, valid_plot_modes
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from quacc.evaluation.estimators import CE
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from quacc.evaluation.report import DatasetReport
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@ -365,7 +365,7 @@ class QuaccTestViewer(param.Parameterized):
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self.plot_pane = __svg
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else:
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_dr = self.datasets_[self.dataset]
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__plot = create_plots(
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__plot = create_result(
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_dr,
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mode=self.mode,
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metric=self.metric,
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