status so far

docs/examples/09a_model_lna/09a_model_lna.py

@@ -16,21 +16,30 @@
 
 
 # +
-import pandas as pd
-
-data = pd.read_csv("data/example_dc_response.csv")
-
-data[data["driver_b_v_set"] == 1.6]
-data["driver_b_v_set"].unique()
+# import pandas as pd
+
+# data = pd.read_csv("data/example_dc_response.csv")
+
+# data[data["driver_b_v_set"] == 1.6]
+# data["driver_b_v_set"].unique()
+# opp = data[["driver_b_v_set"]].drop_duplicates()
+# for index, operating_point in opp.iterrows():
+#     print(index)
+#     print(operating_point)
+#     a = data[(data[["driver_b_v_set"]] == operating_point).all(axis=1)]
+# print(a)
 # -
 
-dc_sweep = pe.extract_signal_data_from_csv(
+dc_sweep = pe.extract_dc_sweeps_from_operating_point_csv(
     file_path="data/example_dc_response.csv",
     sourcemeter_voltage_current_signal_name_pairs=[
         ("driver_a_v", "driver_a_i"),
         ("driver_b_v", "driver_b_i"),
     ],
     multimeter_signals=["measurement_a_v"],
+    unique_operating_point_columns=["driver_b_v_set"],
 )
 
-pe.visual.plot_dc_sweep(dc_sweep=dc_sweep)
+pe.visual.plot_dc_sweep(dc_sweep=dc_sweep[0])
+
+pe.visual.plot_dc_sweeps(dc_sweep_collection=dc_sweep)

piel/experimental/__init__.py

@@ -14,6 +14,8 @@
     construct_multimeter_sweep_signal_from_dataframe,
     construct_sourcemeter_sweep_signal_from_dataframe,
     extract_signal_data_from_csv,
+    extract_signal_data_from_dataframe,
+    extract_dc_sweeps_from_operating_point_csv,
 )
 from .measurements.data.propagation import (
     extract_propagation_delay_from_measurement,

piel/experimental/measurements/data/dc.py

@@ -9,6 +9,7 @@
 from ...types import (
     SourcemeterSweepMeasurementData,
     DCSweepMeasurementData,
+    DCSweepMeasurementDataCollection,
     MultimeterSweepVoltageMeasurementData,
     SourcemeterVoltageCurrentSignalNamePair,
 )
@@ -61,6 +62,26 @@ def construct_multimeter_sweep_signal_from_csv(
     signal_type: QuantityTypesDC = "voltage",
     **kwargs,
 ) -> MultimeterSweepVoltageMeasurementData:
+    """
+    Construct a multimeter sweep signal from a CSV file.
+
+    Parameters
+    ----------
+
+    file_path : PathTypes
+        The path to the CSV file.
+    signal_name : str
+        The name of the signal.
+    signal_type : QuantityTypesDC
+        The type of signal.
+    **kwargs
+
+    Returns
+    -------
+
+    MultimeterSweepVoltageMeasurementData
+        The multimeter sweep signal
+    """
     file = return_path(file_path)
     dataframe = pd.read_csv(file)
 
@@ -84,6 +105,26 @@ def construct_multimeter_sweep_signal_from_dataframe(
     signal_kwargs: dict = None,
     **kwargs,
 ) -> MultimeterSweepVoltageMeasurementData:
+    """
+    Construct a multimeter sweep signal from a dataframe.
+
+    Parameters
+    ----------
+
+    dataframe : pd.DataFrame
+        The dataframe containing the multimeter sweep signal data.
+    signal_name : str
+        The name of the signal.
+    signal_kwargs : dict
+        Additional keyword arguments.
+    **kwargs
+
+    Returns
+    -------
+
+    MultimeterSweepVoltageMeasurementData
+        The multimeter sweep signal
+    """
     if signal_kwargs is None:
         signal_kwargs = {}
 
@@ -94,17 +135,35 @@ def construct_multimeter_sweep_signal_from_dataframe(
     return MultimeterSweepVoltageMeasurementData(signal=signal, **kwargs)
 
 
-def extract_signal_data_from_csv(
-    file_path: PathTypes,
+def extract_signal_data_from_dataframe(
+    dataframe: pd.DataFrame,
     sourcemeter_voltage_current_signal_name_pairs: list[
         SourcemeterVoltageCurrentSignalNamePair
     ],
     multimeter_signals: list[str],
     **kwargs,
 ) -> DCSweepMeasurementData:
-    file = return_path(file_path)
-    dataframe = pd.read_csv(file)
+    """
+    Extract DC sweep data from a dataframe.
+
+    Parameters
+    ----------
 
+    dataframe : pd.DataFrame
+        The dataframe containing the DC sweep data.
+    sourcemeter_voltage_current_signal_name_pairs : list[SourcemeterVoltageCurrentSignalNamePair]
+        The pairs of sourcemeter voltage and current signal names.
+    multimeter_signals : list[str]
+        The multimeter signals.
+    **kwargs
+        Additional keyword arguments.
+
+    Returns
+    -------
+
+    DCSweepMeasurementData
+        The DC sweep data.
+    """
     # Iterate through the sourcemeter signals and create the sourcemeter sweep signals
     sourcemeter_sweep_signals = []
 
@@ -134,3 +193,103 @@ def extract_signal_data_from_csv(
         outputs=multimeter_sweep_signals,
         **kwargs,
     )
+
+
+def extract_signal_data_from_csv(
+    file_path: PathTypes,
+    sourcemeter_voltage_current_signal_name_pairs: list[
+        SourcemeterVoltageCurrentSignalNamePair
+    ],
+    multimeter_signals: list[str],
+    **kwargs,
+) -> DCSweepMeasurementData:
+    """
+    Extract DC sweep data from a CSV file.
+
+    Parameters
+    ----------
+    file_path : PathTypes
+        The path to the CSV file.
+    sourcemeter_voltage_current_signal_name_pairs : list[SourcemeterVoltageCurrentSignalNamePair]
+        The pairs of sourcemeter voltage and current signal names.
+    multimeter_signals : list[str]
+        The multimeter signals.
+    **kwargs
+        Additional keyword arguments.
+
+    Returns
+    -------
+
+    DCSweepMeasurementData
+        The DC sweep data.
+    """
+    file = return_path(file_path)
+    dataframe = pd.read_csv(file)
+    return extract_signal_data_from_dataframe(
+        dataframe=dataframe,
+        sourcemeter_voltage_current_signal_name_pairs=sourcemeter_voltage_current_signal_name_pairs,
+        multimeter_signals=multimeter_signals,
+        **kwargs,
+    )
+
+
+def extract_dc_sweeps_from_operating_point_csv(
+    file_path: PathTypes,
+    sourcemeter_voltage_current_signal_name_pairs: list[
+        SourcemeterVoltageCurrentSignalNamePair
+    ],
+    multimeter_signals: list[str],
+    unique_operating_point_columns: list[str],
+    **kwargs,
+) -> DCSweepMeasurementDataCollection:
+    """
+    Extract DC sweep data from a full operating point CSV file. The operating point CSV file contains the DC sweep data
+    for multiple operating points. The unique operating point columns are used to extract the unique operating points
+    from the CSV file. The DC sweep data is then extracted for each unique operating point. The DC sweep data is
+    returned as a DCMeasurementDataCollection. The DCMeasurementDataCollection is a list of DCMeasurementDataTypes.
+
+    Parameters
+    ----------
+
+    file_path : PathTypes
+        The path to the operating point CSV file.
+    sourcemeter_voltage_current_signal_name_pairs : list[SourcemeterVoltageCurrentSignalNamePair]
+        The pairs of sourcemeter voltage and current signal names.
+    multimeter_signals : list[str]
+        The multimeter signals.
+    unique_operating_point_columns : list[str]
+        The unique operating point columns.
+    **kwargs
+        Additional keyword arguments.
+
+    Returns
+    -------
+    DCMeasurementDataCollection
+        The DC sweep data collection.
+    """
+    file = return_path(file_path)
+    dataframe = pd.read_csv(file)
+
+    # Extract the unique operating points
+    unique_operating_points = dataframe[
+        unique_operating_point_columns
+    ].drop_duplicates()
+
+    # Iterate through the unique operating points and extract the DC sweep data
+    dc_sweep_data = []
+
+    for _, operating_point in unique_operating_points.iterrows():
+        operating_point_data = dataframe[
+            (dataframe[unique_operating_point_columns] == operating_point).all(axis=1)
+        ]
+
+        dc_sweep = extract_signal_data_from_dataframe(
+            dataframe=operating_point_data,
+            sourcemeter_voltage_current_signal_name_pairs=sourcemeter_voltage_current_signal_name_pairs,
+            multimeter_signals=multimeter_signals,
+            **kwargs,
+        )
+
+        dc_sweep_data.append(dc_sweep)
+
+    return dc_sweep_data

piel/experimental/types/__init__.py

@@ -28,6 +28,8 @@
 
 from .measurements.data.dc import (
     DCSweepMeasurementData,
+    DCSweepMeasurementDataCollection,
+    DCMeasurementDataCollection,
     MultimeterSweepVoltageMeasurementData,
     SourcemeterSweepMeasurementData,
 )

piel/experimental/types/measurements/data/dc.py

@@ -22,9 +22,14 @@ class DCSweepMeasurementData(MeasurementData):
     """
 
 
+DCSweepMeasurementDataCollection = list[DCSweepMeasurementData]
+
 DCMeasurementDataTypes = (
     DCSweepMeasurementData
     | MultimeterSweepVoltageMeasurementData
     | SourcemeterSweepMeasurementData
 )
-DCMeasurementDataCollection = list[DCMeasurementDataTypes]
+
+DCMeasurementDataCollection = (
+    list[DCMeasurementDataTypes] | DCSweepMeasurementDataCollection
+)

piel/experimental/visual/__init__.py

@@ -1,4 +1,4 @@
-from .dc import plot_dc_sweep
+from .dc import plot_dc_sweep, plot_dc_sweeps
 from .propagation import (
     plot_signal_propagation_measurements,
     plot_signal_propagation_signals,

piel/experimental/visual/dc.py

@@ -1,8 +1,8 @@
-from ..types import DCSweepMeasurementData
-import matplotlib.pyplot as plt
+from ..types import DCSweepMeasurementData, DCSweepMeasurementDataCollection
+from ...visual import create_plot_containers, save
 
 
-def plot_dc_sweep(dc_sweep: DCSweepMeasurementData):
+def plot_dc_sweep(dc_sweep: DCSweepMeasurementData, **kwargs) -> tuple:
     """
     Plot a DC sweep measurement.
 
@@ -11,7 +11,33 @@ def plot_dc_sweep(dc_sweep: DCSweepMeasurementData):
     dc_sweep : DCMeasurementDataTypes
         The DC sweep measurement data to plot.
     """
-    plt.plot(
+    fig, axs = create_plot_containers(container_list=[dc_sweep])
+
+    axs[0].plot(
         # dc_sweep.inputs[0].signal.signal_instances[0].values
         dc_sweep.outputs[0].signal.signal_instances[0].values,
     )
+
+    if kwargs["path"]:
+        save(fig, **kwargs)
+
+    return fig, axs
+
+
+def plot_dc_sweeps(
+    dc_sweep_collection: DCSweepMeasurementDataCollection, **kwargs
+) -> tuple:
+    fig, axs = create_plot_containers(
+        container_list=dc_sweep_collection, axes_structure="overlay"
+    )
+
+    for dc_sweep_i in dc_sweep_collection:
+        axs[0].plot(
+            dc_sweep_i.inputs[0].signal.signal_instances[0].values,
+            dc_sweep_i.outputs[0].signal.signal_instances[0].values,
+        )
+
+    if kwargs["path"]:
+        save(fig, **kwargs)
+
+    return fig, axs

piel/visual/plot/position.py

@@ -23,7 +23,7 @@ def create_axes_per_figure(rows: int = 1, columns: int = 1, **kwargs) -> tuple:
     """
     fig, axs = plt.subplots(rows, columns, **kwargs)
 
-    if rows == 1 and columns == 1:
+    if (rows == 1) and (columns == 1):
         # We always want this to be an array so we can compose easily with the rest of the code.
         axs = [axs]
 
@@ -57,6 +57,7 @@ def list_to_separate_plots(
 
 def list_to_overlayed_plots(container_list: list, **kwargs) -> tuple:
     fig, axs = create_axes_per_figure(rows=1, columns=1, **kwargs)
+    return fig, axs
 
 
 def create_plot_containers(