Instantiate TimeSeries from a csv file

floris/wind_data.py

@@ -2692,6 +2692,53 @@ def to_WindTIRose(
             self.heterogeneous_map,
         )
 
+    @staticmethod
+    def read_csv(
+        file_path: str,
+        ws_col: str = "wind_speeds",
+        wd_col: str = "wind_directions",
+        ti_col_or_value: str | float = "turbulence_intensities",
+        value_col: str | None = None,
+        sep: str = ",",
+    ) -> TimeSeries:
+        """
+        Reads a CSV file and returns a TimeSeries object.
+
+        Args:
+            file_path (str): Path to the CSV file.
+            ws_col (str, optional): Column name for wind speeds. Defaults to "wind_speeds".
+            wd_col (str, optional): Column name for wind directions. Defaults to "wind_directions".
+            ti_col_or_value (str | float, optional): Column name for turbulence intensities
+                or a single float value. Defaults to "turbulence_intensities".
+            value_col (str | None, optional): Column name for values. Defaults to None.
+            sep (str, optional): Separator used in the CSV file. Defaults to ",".
+
+        Returns:
+            TimeSeries: A TimeSeries object populated with data from the CSV file.
+        """
+        df = pd.read_csv(file_path, sep=sep)
+
+        wind_speeds = df[ws_col].to_numpy()
+        wind_directions = df[wd_col].to_numpy()
+
+        if isinstance(ti_col_or_value, str):
+            turbulence_intensities = df[ti_col_or_value].to_numpy()
+        else:
+            turbulence_intensities = ti_col_or_value
+
+        if value_col is not None:
+            values = df[value_col].to_numpy()
+        else:
+            values = None
+
+        return TimeSeries(
+            wind_directions=wind_directions,
+            wind_speeds=wind_speeds,
+            turbulence_intensities=turbulence_intensities,
+            values=values,
+        )
+
+
 
 class WindRoseWRG(WindDataBase):
     """

tests/wind_data_integration_test.py

@@ -1,7 +1,9 @@
 import copy
+import os
 from pathlib import Path
 
 import numpy as np
+import pandas as pd
 import pytest
 
 from floris import (
@@ -63,6 +65,82 @@ def test_time_series_instantiation():
             wind_directions, wind_speeds, turbulence_intensities=np.array([0.06, 0.07, 0.08, 0.09])
         )
 
+def test_time_series_read_csv():
+
+    df_test = pd.DataFrame(
+        {
+            "Wind Direction": [270, 280, 290],
+            "Wind Speed": [5, 6, 7],
+            "Turbulence Intensity": [0.06, 0.07, 0.08],
+            "Other Column": [1, 2, 3],
+        }
+    )
+
+    csv_path = TEST_DATA / "test_time_series.csv"
+    df_test.to_csv(csv_path, index=False)
+
+    time_series = TimeSeries.read_csv(
+        csv_path,
+        ws_col="Wind Speed",
+        wd_col="Wind Direction",
+        ti_col_or_value="Turbulence Intensity",
+    )
+
+    assert isinstance(time_series, TimeSeries)
+    assert np.allclose(time_series.wind_directions, df_test["Wind Direction"].values)
+
+    # Test with fixed TI value
+    time_series = TimeSeries.read_csv(
+        csv_path,
+        ws_col="Wind Speed",
+        wd_col="Wind Direction",
+        ti_col_or_value=0.05,
+    )
+
+    assert isinstance(time_series, TimeSeries)
+    assert np.allclose(time_series.turbulence_intensities, 0.05)
+
+    # Test with invalid column raises error
+    with pytest.raises(KeyError):
+        TimeSeries.read_csv(
+            csv_path,
+            ws_col="Wind Speed",
+            wd_col="Wind Direction",
+            ti_col_or_value="Nonexistent Column",
+        )
+
+    # Test that unspecified column raises error
+    with pytest.raises(KeyError):
+        TimeSeries.read_csv(
+            csv_path,
+            ws_col="Wind Speed",
+            wd_col="Wind Direction",
+        )
+
+    # Test with default column names, default column separator
+    df_test_2 = pd.DataFrame(
+        {
+            "wind_directions": [270, 280, 290],
+            "wind_speeds": [5, 6, 7],
+            "turbulence_intensities": [0.06, 0.07, 0.08],
+            "other_column": [1, 2, 3],
+        }
+    )
+    df_test_2.to_csv(csv_path, index=True, sep=" ")
+
+    time_series = TimeSeries.read_csv(csv_path, value_col="other_column", sep=" ")
+    assert isinstance(time_series, TimeSeries)
+    assert np.allclose(time_series.wind_speeds, df_test_2["wind_speeds"].values)
+    assert np.allclose(time_series.values, df_test_2["other_column"].values)
+
+    # Test error if default column names are used but a column is missing
+    df_test_3 = df_test_2.drop(columns=["turbulence_intensities"])
+    df_test_3.to_csv(csv_path, index=True, sep=" ")
+
+    with pytest.raises(KeyError):
+        TimeSeries.read_csv(csv_path)
+
+    os.remove(csv_path)
 
 def test_wind_rose_init():
     """