Feature/issue 166/multiple metrics (#233)

* orchestrator input changes

* loop over metric

* names to function calls.

* multipule metrics, pal

* multiple metrics, pal working fix for orchestrator

* cli fix

* revert bug check change

* threshold change

* threshold parsing.

* cli str fix.

* working tests

* documentation.

* post-merge fixes.

* Json error

* ruff error

* reverting old test change.

* typer error

* mypy errors

* test for typer error.

* removing validation.

* removing redundant test causing error.

* multiple metrics tests for cli and orchestrator.

* extra test for missmatch error.

* review changes.

* mypy error demands tuple unpacking

Author: frey-perez

src/wristpy/core/cli.py

@@ -62,6 +62,36 @@ def version_check(version: bool) -> None:
         raise typer.Exit()
 
 
+def _parse_thresholds(thresholds: list[str]) -> list[tuple[float, float, float]]:
+    """Parse the threshold strings into a list of tuples.
+
+    Args:
+        thresholds: List of threshold strings, each containing three space-separated
+            floats.
+
+    Returns:
+        List of tuple float triplets containing the parsed threshold values.
+
+    Raises:
+        typer.BadParameter: If any threshold triplet does not contain exactly three
+            floats
+        typer.BadParameter: If threshold format is invalid or values cannot be parsed.
+    """
+    parsed = []
+    for triplet_str in thresholds:
+        parts = triplet_str.strip().split()
+        if len(parts) != 3:
+            raise typer.BadParameter(
+                f"Threshold triplet must have exactly 3 floats: {triplet_str}"
+            )
+        try:
+            values = [float(part) for part in parts]
+        except ValueError:
+            raise typer.BadParameter(f"Invalid float in threshold: {triplet_str}")
+        parsed.append((values[0], values[1], values[2]))
+    return parsed
+
+
 @app.command()
 def main(
     input: pathlib.Path = typer.Argument(
@@ -87,22 +117,24 @@ def main(
         "Must choose one of 'none', 'ggir', or 'gradient'.",
         case_sensitive=False,
     ),
-    activity_metric: ActivityMetric = typer.Option(
-        ActivityMetric.enmo,
+    activity_metric: list[ActivityMetric] = typer.Option(
+        [ActivityMetric.enmo],
         "-a",
         "--activity-metric",
-        help="Metric used for physical activity categorization. "
-        "Choose from 'enmo', 'mad', 'ag_count', or 'mims'.  ",
+        help="Metric(s) used for physical activity categorization. "
+        "Choose from 'enmo', 'mad', 'ag_count', or 'mims'. "
+        "Use multiple times for multiple metrics: '-a enmo -a mad' etc.",
         case_sensitive=False,
     ),
-    thresholds: tuple[float, float, float] = typer.Option(
+    # Typer does not support list[tuple[...]]
+    thresholds: list[str] = typer.Option(
         None,
         "-t",
         "--thresholds",
         help="Provide three thresholds for light, moderate, and vigorous activity. "
-        "Exactly three values must be >= 0, given in ascending order, "
-        "and separated by a space. (e.g. '-t 0.1 1.0 1.5').",
-        min=0,
+        "One threshold set per activity metric, in the same order as metrics. "
+        "Format: three space-separated values >= 0 in ascending order. "
+        "Example: -t '0.1 1.0 1.5' or -a enmo -a mad -t '0.1 1.0 1.5' -t '0.2 2.0 3.0'",
     ),
     nonwear_algorithm: list[NonwearAlgorithms] = typer.Option(
         [NonwearAlgorithms.ggir],
@@ -146,6 +178,8 @@ def main(
     logger.setLevel(log_level)
 
     nonwear_algorithms = [algo.value for algo in nonwear_algorithm]
+    activity_metrics = [metric.value for metric in activity_metric]
+    parsed_thresholds = _parse_thresholds(thresholds) if thresholds else None
     calibrator_value = None if calibrator == Calibrator.none else calibrator.value
 
     logger.debug("Running wristpy. arguments given: %s", locals())
@@ -154,8 +188,8 @@ def main(
             input=input,
             output=output,
             calibrator=calibrator_value,
-            activity_metric=activity_metric.value,
-            thresholds=None if thresholds is None else thresholds,
+            activity_metric=activity_metrics,  # type: ignore[arg-type] # Covered by ActivityMetric Enum class
+            thresholds=parsed_thresholds,
             epoch_length=epoch_length,
             nonwear_algorithm=nonwear_algorithms,  # type: ignore[arg-type] # Covered by NonwearAlgorithm Enum class
             verbosity=log_level,

src/wristpy/core/computations.py

@@ -14,6 +14,7 @@ def _moving(
     *,
     centered: bool = False,
     continuous: bool = False,
+    name: str | None = None,
 ) -> models.Measurement:
     """Internal handler of rolling window functions.
 
@@ -24,6 +25,7 @@ def _moving(
         centered: If true, centers the window. Defaults to False.
         continuous: If true, applies the window to every measurement. If false,
             groups measurements into chunks of epoch_length. Defaults to False.
+        name: The name of the Measurement object.
 
     Returns:
         The measurement with the rolling function applied to it.
@@ -54,25 +56,26 @@ def _moving(
             .agg(aggregator())
         )
 
-    return models.Measurement.from_data_frame(aggregated_df.collect())
+    return models.Measurement.from_data_frame(aggregated_df.collect(), name=name)
 
 
 def moving_mean(
-    array: models.Measurement, epoch_length: float = 5
+    array: models.Measurement, epoch_length: float = 5, name: str | None = None
 ) -> models.Measurement:
     """Calculate the moving mean of the sensor data in array.
 
     Args:
         array: The Measurement object with the sensor data we want to take the mean of
         epoch_length: The length, in seconds, of the window.
+        name: The name of the Measurement object.
 
     Returns:
         The moving mean of the array in a new Measurement instance.
 
     Raises:
         ValueError: If the epoch length is not an integer or is less than 1.
     """
-    return _moving(array, epoch_length, "mean")
+    return _moving(array, epoch_length, "mean", name=name)
 
 
 def moving_std(

src/wristpy/core/models.py

@@ -16,18 +16,23 @@
 class Measurement(BaseModel):
     """A single measurement of a sensor and its corresponding time."""
 
+    name: str | None = None
     measurements: np.ndarray
     time: pl.Series
 
     @classmethod
-    def from_data_frame(cls, data_frame: pl.DataFrame) -> "Measurement":
+    def from_data_frame(
+        cls, data_frame: pl.DataFrame, name: str | None = None
+    ) -> "Measurement":
         """Creates a measurement from a Polars DataFrame.
 
         Args:
             data_frame: The Polars DataFrame, must have a time column. All
                 non-time columns will be used as the 'measurements' input.
+            name: Optional name describing the type of measurement.
         """
         return Measurement(
+            name=name,
             measurements=data_frame.drop("time").to_numpy().squeeze(),
             time=data_frame["time"],
         )