qcdash refactoring started

qcdash/app.py

@@ -12,10 +12,12 @@ import numpy as np
 from dash import Dash, Input, Output, State, callback, ctx, dash_table, dcc, html
 from dash.dash_table.Format import Align, Format, Scheme
 
-from quacc import plot
-from quacc.evaluation.estimators import CE, _renames
-from quacc.evaluation.report import CompReport, DatasetReport
-from quacc.evaluation.stats import wilcoxon
+from quacc.experiments.report import Report
+from quacc.experiments.util import get_acc_name
+from quacc.legacy.evaluation.estimators import CE, _renames
+from quacc.legacy.evaluation.report import CompReport, DatasetReport
+from quacc.legacy.evaluation.stats import wilcoxon
+from quacc.plot.plotly import plot_delta, plot_diagonal, plot_shift
 
 valid_plot_modes = defaultdict(lambda: CompReport._default_modes)
 valid_plot_modes["avg"] = DatasetReport._default_dr_modes
@@ -74,29 +76,61 @@ def get_datasets(root: str | Path) -> List[DatasetReport]:
     return {str(drp.parent): load_dataset(drp) for drp in dr_paths}
 
 
-def get_fig(dr: DatasetReport, metric, estimators, view, mode, backend=None):
-    _backend = backend or plot.get_backend("plotly")
-    estimators = CE.name[estimators]
+def get_fig(rep: Report, dataset, metric, estimators, view, mode):
     match (view, mode):
-        case ("avg", _):
-            return dr.get_plots(
-                mode=mode,
-                metric=metric,
-                estimators=estimators,
-                conf="plotly",
-                save_fig=False,
-                backend=_backend,
+        case ("avg", "diagonal"):
+            true_accs, estim_accs = rep.diagonal_plot_data(
+                dataset_name=dataset,
+                method_names=estimators,
+                acc_name=metric,
+            )
+            return plot_diagonal(
+                method_names=estimators,
+                true_accs=true_accs,
+                estim_accs=estim_accs,
+                measure_name=metric,
+            )
+        case ("avg", "delta_train"):
+            prevs, acc_errs = rep.delta_train_plot_data(
+                dataset_name=dataset,
+                method_names=estimators,
+                acc_name=metric,
+            )
+            return plot_delta(
+                method_names=estimators,
+                prevs=prevs,
+                acc_errs=acc_errs,
+                measure_name=metric,
+                prev_name="Test",
+            )
+        case ("avg", "stdev_train"):
+            prevs, acc_errs, stdevs = rep.delta_train_plot_data(
+                dataset_name=dataset,
+                method_names=estimators,
+                acc_name=metric,
+                stdev=True,
+            )
+            return plot_delta(
+                method_names=estimators,
+                prevs=prevs,
+                acc_errs=acc_errs,
+                measure_name=metric,
+                prev_name="Test",
+                stdevs=stdevs,
+            )
+        case ("avg", "shift"):
+            prevs, acc_errs, counts = rep.shift_plot_data(
+                dataset_name=dataset, method_names=estimators, acc_name=metric
+            )
+            return plot_shift(
+                method_names=estimators,
+                prevs=prevs,
+                acc_errs=acc_errs,
+                measure_name=metric,
+                counts=counts,
             )
         case (_, _):
-            cr = dr.crs[[_get_prev_str(c.train_prev) for c in dr.crs].index(view)]
-            return cr.get_plots(
-                mode=mode,
-                metric=metric,
-                estimators=estimators,
-                conf="plotly",
-                save_fig=False,
-                backend=_backend,
-            )
+            return None
 
 
 def get_table(dr: DatasetReport, metric, estimators, view, mode):