"""
Parse TSWCs from CSV
======================

This example shows how to parse a Time Series Wind Climate (TSWC) from a .csv file.

"""

# %%
# Prepare Sample Data
# ------------------------
# First, we need to prepare the sample data. This is done by creating a
# DataFrame with the wind speed and direction data.

import tempfile
import numpy as np
import pandas as pd
import windkit as wk


size = 8760  # 1 year of hourly data

df = pd.DataFrame(
    {
        "wspd_50": np.random.uniform(5, 15, size=size),  # Wind speed in m/s
        "wdir_50": np.random.uniform(0, 360, size=size),  # Wind direction in degrees
    },
    index=pd.date_range("2023-01-01", periods=size, freq="h"),
)
df.index.name = "time"  # Set the index name to 'time'
print(df.head())

# %%
# Save to .csv
# ------------------------
# We save the DataFrame to a .csv file in the temporary directory.

with tempfile.TemporaryDirectory() as tmpdir:
    df.to_csv(f"{tmpdir}/sample_tswc.csv", index=True)

    # %%
    # Parse .csv to TSWC
    # ------------------------
    # Now, we can parse the CSV file to create a Time Series Wind Climate (TSWC) object using
    # the :py:func:`read_tswc` function. We have to specify the spatial coordinate system (CRS),
    # coordinates for the west-east and south-north axes,
    # the time column, and the height to columns mapping. In this case, we assume that the
    # wind speed and direction data are at a height of 50 meters, and we map them accordingly.

    tswc = wk.read_tswc(
        f"{tmpdir}/sample_tswc.csv",
        west_east=0.0,
        south_north=0.0,
        crs=4326,
        time_col=0,
        height_to_columns={50: ["wspd_50", "wdir_50"]},
    )

    print(tswc)

# %%
# Alternatively, we can also use the :py:func:`tswc_from_dataframe` function to parse a
# DataFrame directly into a TSWC object. This is useful if you already have the data in a
# DataFrame format and do not need to read it from a file.

tswc_from_df = wk.tswc_from_dataframe(
    df,
    west_east=0.0,
    south_north=0.0,
    crs=4326,
    height_to_columns={50: ["wspd_50", "wdir_50"]},
)
print(tswc_from_df)