Add from_dataframe method to Measurement to create multidim measurement from a DataFrame.

This also adds some symmetry with the existing to_dataframe method.

PiperOrigin-RevId: 722726903

Author: glados-verma

openhtf/core/measurements.py

@@ -480,6 +480,35 @@ def to_dataframe(self, columns: Any = None) -> Any:
 
     return dataframe
 
+  def from_dataframe(self, dataframe: Any, metric_column: str) -> None:
+    """Convert a pandas DataFrame to a multi-dim measurement.
+
+    Args:
+      dataframe: A pandas DataFrame. Dimensions for this multi-dim measurement
+        need to match columns in the DataFrame (can be multi-index).
+      metric_column: The column name of the metric to be measured.
+
+    Raises:
+      TypeError: If this measurement is not dimensioned.
+      ValueError: If dataframe is missing dimensions.
+    """
+    if not isinstance(self._measured_value, DimensionedMeasuredValue):
+      raise TypeError(
+          'Only a dimensioned measurement can be set from a DataFrame'
+      )
+    dimension_labels = [d.name for d in self.dimensions]
+    dimensioned_df = dataframe.reset_index()
+    try:
+      dimensioned_df.set_index(dimension_labels, inplace=True)
+    except KeyError as e:
+      raise ValueError('DataFrame is missing dimensions') from e
+    if metric_column not in dimensioned_df.columns:
+      raise ValueError(
+          f'DataFrame does not have a column named {metric_column}'
+      )
+    for row_dimensions, row_metrics in dimensioned_df.iterrows():
+      self.measured_value[row_dimensions] = row_metrics[metric_column]
+
 
 @attr.s(slots=True)
 class MeasuredValue(object):

test/core/measurements_test.py

@@ -25,6 +25,7 @@
 from openhtf.core import measurements
 from examples import all_the_things
 from openhtf.util import test as htf_test
+import pandas
 
 # Fields that are considered 'volatile' for record comparison.
 _VOLATILE_FIELDS = {
@@ -231,14 +232,19 @@ def test_to_dataframe__no_pandas(self):
     with self.assertRaises(RuntimeError):
       self.test_to_dataframe(units=True)
 
-  def test_to_dataframe(self, units=True):
+  def _make_multidim_measurement(self, units=''):
     measurement = htf.Measurement('test_multidim')
     measurement.with_dimensions('ms', 'assembly', htf.Dimension('my_zone'))
+    if units:
+      measurement.with_units(units)
+    return measurement
 
+  def test_to_dataframe(self, units=True):
     if units:
-      measurement.with_units('°C')
+      measurement = self._make_multidim_measurement('°C')
       measure_column_name = 'degree Celsius'
     else:
+      measurement = self._make_multidim_measurement()
       measure_column_name = 'value'
 
     for t in range(5):
@@ -260,6 +266,100 @@ def test_to_dataframe(self, units=True):
   def test_to_dataframe__no_units(self):
     self.test_to_dataframe(units=False)
 
+  def _multidim_testdata(self):
+    return {
+        'ms': [1, 2, 3],
+        'assembly': ['A', 'B', 'C'],
+        'my_zone': ['X', 'Y', 'Z'],
+        'degree_celsius': [10, 20, 30],
+    }
+
+  def test_from_dataframe_raises_if_dimensions_missing_in_dataframe(self):
+    measurement = self._make_multidim_measurement('°C')
+    source_data = self._multidim_testdata()
+    del source_data['assembly']
+    with self.assertRaisesRegex(
+        ValueError, 'DataFrame is missing dimensions'
+    ) as cm:
+      measurement.from_dataframe(
+          pandas.DataFrame(source_data),
+          metric_column='degree_celsius',
+      )
+    with self.assertRaisesRegex(
+        KeyError, r"None of \['assembly'\] are in the columns"
+    ):
+      raise cm.exception.__cause__
+
+  def test_from_dataframe_raises_if_metric_missing_in_dataframe(self):
+    measurement = self._make_multidim_measurement('°C')
+    source_data = self._multidim_testdata()
+    del source_data['degree_celsius']
+    with self.assertRaisesRegex(
+        ValueError, 'DataFrame does not have a column named degree_celsius'
+    ):
+      measurement.from_dataframe(
+          pandas.DataFrame(source_data),
+          metric_column='degree_celsius',
+      )
+
+  def _assert_multidim_measurement_matches_testdata(self, measurement):
+    self.assertEqual(measurement.measured_value[(1, 'A', 'X')], 10)
+    self.assertEqual(measurement.measured_value[(2, 'B', 'Y')], 20)
+    self.assertEqual(measurement.measured_value[(3, 'C', 'Z')], 30)
+    pandas.testing.assert_frame_equal(
+        measurement.to_dataframe().rename(
+            columns={
+                'ms': 'ms',
+                'assembly': 'assembly',
+                'my_zone': 'my_zone',
+                # The metric column name comes from the unit.
+                'degree Celsius': 'degree_celsius',
+            }
+        ),
+        pandas.DataFrame(self._multidim_testdata()),
+    )
+
+  def test_from_flat_dataframe(self):
+    measurement = self._make_multidim_measurement('°C')
+    source_dataframe = pandas.DataFrame(self._multidim_testdata())
+    measurement.from_dataframe(source_dataframe, metric_column='degree_celsius')
+    measurement.outcome = measurements.Outcome.PASS
+    self._assert_multidim_measurement_matches_testdata(measurement)
+
+  def test_from_dataframe_with_multiindex_dataframe(self):
+    measurement = self._make_multidim_measurement('°C')
+    source_dataframe = pandas.DataFrame(self._multidim_testdata()).set_index(
+        ['ms', 'assembly', 'my_zone']
+    )
+    measurement.from_dataframe(source_dataframe, metric_column='degree_celsius')
+    measurement.outcome = measurements.Outcome.PASS
+    self._assert_multidim_measurement_matches_testdata(measurement)
+
+  def test_from_dataframe_ignores_extra_columns(self):
+    measurement = self._make_multidim_measurement('°C')
+    source_data = self._multidim_testdata()
+    source_data['degrees_fahrenheit'] = [11, 21, 31]
+    source_dataframe = pandas.DataFrame(source_data)
+    measurement.from_dataframe(source_dataframe, metric_column='degree_celsius')
+    measurement.outcome = measurements.Outcome.PASS
+    self._assert_multidim_measurement_matches_testdata(measurement)
+
+  def test_from_dataframe_with_duplicate_dimensions_overwrites(self):
+    """Verifies multi-dim measurement overwrite with duplicate dimensions."""
+    measurement = self._make_multidim_measurement('°C')
+    source_dataframe = pandas.DataFrame({
+        'ms': [1, 2, 3, 1],
+        'assembly': ['A', 'B', 'C', 'A'],
+        'my_zone': ['X', 'Y', 'Z', 'X'],
+        'degree_celsius': [10, 20, 30, 11],
+    })
+    measurement.from_dataframe(source_dataframe, metric_column='degree_celsius')
+    measurement.outcome = measurements.Outcome.PASS
+    # Overwritten value.
+    self.assertEqual(measurement.measured_value[(1, 'A', 'X')], 11)
+    self.assertEqual(measurement.measured_value[(2, 'B', 'Y')], 20)
+    self.assertEqual(measurement.measured_value[(3, 'C', 'Z')], 30)
+
   def test_bad_validator(self):
     measurement = htf.Measurement('bad_measure')
     measurement.with_dimensions('a')