Merge pull request #267 from uriahf/jules/ty-fixes-322255806096583053

Pass ty check and update AGENTS.md

Author: uriahf

AGENTS.md

@@ -67,3 +67,11 @@ Before committing, please ensure that the pre-commit hooks pass. You can run the
 ## Documentation
 
 The documentation for this project is built using `quartodoc`. The documentation is automatically built and deployed via GitHub Actions. There is no need to build the documentation manually.
+
+## Type Checking
+
+This project uses `ty` for type checking. To check for type errors, run the following command:
+
+```bash
+uv run ty check src tests
+```

src/rtichoke/calibration/calibration.py

@@ -206,13 +206,14 @@ def _create_plotly_curve_from_calibration_curve_list_times(
     num_traces_per_horizon = 1 + 2 * len(calibration_curve_list["reference_group_keys"])
 
     for i, horizon in enumerate(calibration_curve_list["fixed_time_horizons"]):
+        visibility = [False] * (num_traces_per_horizon * len(calibration_curve_list["fixed_time_horizons"]))
+        for j in range(num_traces_per_horizon):
+            visibility[i * num_traces_per_horizon + j] = True
         step = dict(
             method="restyle",
-            args=[{"visible": [False] * (num_traces_per_horizon * len(calibration_curve_list["fixed_time_horizons"]))}],
+            args=[{"visible": visibility}],
             label=str(horizon),
         )
-        for j in range(num_traces_per_horizon):
-            step["args"][0]["visible"][i * num_traces_per_horizon + j] = True
         steps.append(step)
 
     sliders = [dict(
@@ -726,7 +727,7 @@ def _add_hover_text_to_calibration_data(
     deciles_dat: pl.DataFrame,
     smooth_dat: pl.DataFrame,
     performance_type: str,
-) -> (pl.DataFrame, pl.DataFrame):
+) -> tuple[pl.DataFrame, pl.DataFrame]:
     """Adds hover text to the deciles and smooth dataframes."""
     if performance_type != "one model":
         deciles_dat = deciles_dat.with_columns(

src/rtichoke/helpers/plotly_helper_functions.py

@@ -681,6 +681,15 @@ def _htext(title: pl.Expr) -> pl.Expr:
             (pl.col("x") >= min_p_threshold) & (pl.col("x") <= max_p_threshold)
         )
 
+    return pl.DataFrame(
+        schema={
+            "reference_group": pl.Utf8,
+            "x": pl.Float64,
+            "y": pl.Float64,
+            "text": pl.Utf8,
+        }
+    )
+
 
 def create_non_interactive_curve_polars(
     performance_data_ready_for_curve, reference_group_color, reference_group
@@ -1157,7 +1166,7 @@ def _add_hover_text_to_performance_data(
     )
 
     return performance_data.with_columns(
-        [pl.col(pl.FLOAT_DTYPES).round(3), hover_text_expr.alias("text")]
+        [pl.col(pl.Float64).round(3), hover_text_expr.alias("text")]
     )
 
 

src/rtichoke/helpers/sandbox_observable_helpers.py

@@ -152,7 +152,7 @@ def transform_group(group: pl.DataFrame, by: float) -> pl.DataFrame:
 
             labels = [f"{x:.{decimals}f}" for x in np.linspace(by, 1.0, q)]
 
-            strata_labels = np.array([labels[i] for i in bin_idx], dtype=object)
+            strata_labels = np.array(labels)[bin_idx]
 
             columns_to_add.append(
                 pl.Series("strata_ppcr", strata_labels).cast(pl.Enum(labels))