"""Create reference files."""

import logging
import os

import numpy as np
import xarray as xr
from rich.logging import RichHandler
from ruamel.yaml import YAML

import mvcm.spectral_tests as tst

_LOG_FORMAT = "%(message)s"
logging.basicConfig(level="NOTSET", datefmt="[%X]", format=_LOG_FORMAT, handlers=[RichHandler()])
logger = logging.getLogger(__name__)

_scene_list = [
    "Land_Day",
    "Land_Day_Coast",
    "Land_Day_Desert",
    "Land_Day_Desert_Coast",
    "Ocean_Day",
    "Ocean_Night",
    "Polar_Day_Ocean",
    "Polar_Night_Ocean",
    "Polar_Day_Land",
    "Polar_Day_Coast",
    "Polar_Day_Desert",
    "Polar_Day_Desert_Coast",
    "Polar_Day_Snow",
    "Land_Night",
    "Polar_Night_Land",
    "Polar_Night_Snow",
    "Day_Snow",
    "Night_Snow",
]


_threshold_file = "/home/pveglio/mvcm/tests/fixtures/thresholds.mvcm.snpp.v0.0.1.yaml"
_test_path = "/ships19/hercules/pveglio/mvcm_git_tests"


def main() -> None:
    """Create reference file."""
    with open(_threshold_file) as f:
        text = f.read()
    thresholds = YAML(typ="safe").load(text)

    output_dict: dict = {}

    for scene_name in _scene_list:
        logger.info(f"Running tests for {scene_name} \n")

        if os.path.isfile(f"{_test_path}/ref_confidence_{scene_name}.nc"):
            logger.info(f"Skipping {scene_name}, file already exists")
            continue

        if not os.path.isfile(f"{_test_path}/test_scene_{scene_name}.nc"):
            logger.info(f"Skipping {scene_name}, test file not present in {_test_path}")
            continue

        viirs_data = xr.open_dataset(f"{_test_path}/test_scene_{scene_name}.nc")

        bits = {
            "test": np.zeros(viirs_data.M15.shape, dtype=np.int8),
            "qa": np.zeros(viirs_data.M15.shape, dtype=np.int8),
        }

        if np.all(viirs_data[scene_name].values == 0):
            logger.info("Skipping, no pixels in scene.")
            continue

        my_scene = tst.CloudTests(data=viirs_data, scene_name=scene_name, thresholds=thresholds)  # type: ignore

        # 11um Test
        logger.info(f"Running 11um test for {scene_name}")
        confidence, bits = my_scene.test_11um("M15", np.ones(viirs_data.M15.shape), bits)
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape, confidence, bits, output_dict, "11um"
        )

        # surface_temperature_test() is not performed right now

        # SST Test
        logger.info(f"Running SST test for {scene_name} \n")
        confidence, bits = my_scene.sst_test("M15", "M16", np.ones(viirs_data.M15.shape), bits)
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape, confidence, bits, output_dict, "sst"
        )

        # 8.6 - 11 um Test
        logger.info(f"Running 8.6 - 11 um test for {scene_name} \n")
        confidence, bits = my_scene.bt_diff_86_11um("M14-M15", np.ones(viirs_data.M15.shape), bits)
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape, confidence, bits, output_dict, "86_11um_diff"
        )

        # 11 - 12um Test
        logger.info(f"Running 11 - 12um test for {scene_name} \n")
        confidence, bits = my_scene.test_11_12um_diff(
            "M15-M16", np.ones(viirs_data.M15.shape), bits
        )
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape, confidence, bits, output_dict, "11_12um_diff"
        )

        # 11um Variability Test
        logger.info(f"Running 11um variability test for {scene_name} \n")
        confidence, bits = my_scene.variability_11um_test(
            "M15", np.ones(viirs_data.M15.shape), bits
        )
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape,
            confidence,
            bits,
            output_dict,
            "variability_11um",
        )

        # 11 - 4um Test Ocean
        logger.info(f"Running 11 - 4um test for {scene_name} \n")
        confidence, bits = my_scene.bt_difference_11_4um_test_ocean(
            "M15-M12", np.ones(viirs_data.M15.shape), bits
        )
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape, confidence, bits, output_dict, "11_4um_ocean"
        )

        # 11 - 4um Test Land
        # confidence, bits = my_scene.bt_difference_11_4um_test_land(
        #     "M15-M12", np.ones(viirs_data.M15.shape), bits
        # )
        # bits, output_dict = update_and_clean(
        #     viirs_data.M15.shape, confidence, bits, output_dict, "11_4um_land"
        # )

        # 11 - 4um Oceanic Stratus Test
        logger.info(f"Running 11 - 4um Oceanic Stratus test for {scene_name} \n")
        confidence, bits = my_scene.oceanic_stratus_11_4um_test(
            "M15-M12", np.ones(viirs_data.M15.shape), bits
        )
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape,
            confidence,
            bits,
            output_dict,
            "oceanic_stratus_11_4um",
        )

        # NIR Reflectance Test
        logger.info(f"Running nir reflectance test for {scene_name} \n")
        confidence, bits = my_scene.nir_reflectance_test("M07", np.ones(viirs_data.M15.shape), bits)
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape,
            confidence,
            bits,
            output_dict,
            "nir_reflectance",
        )

        # Vis/NIR Ratio test
        logger.info(f"Running vis/nir ratio test for {scene_name} \n")
        confidence, bits = my_scene.vis_nir_ratio_test(
            "M07-M05ratio", np.ones(viirs_data.M15.shape), bits
        )
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape, confidence, bits, output_dict, "vis_nir_ratio"
        )

        # 1.6 - 2.1um Test
        logger.info(f"Running 1.6 - 2.1um test for {scene_name} \n")
        confidence, bits = my_scene.test_16_21um_reflectance(
            "M10", np.ones(viirs_data.M15.shape), bits
        )
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape,
            confidence,
            bits,
            output_dict,
            "16_21um_reflectance",
        )

        # Visible Reflectance Test
        logger.info(f"Running visible reflectance test for {scene_name} \n")
        confidence, bits = my_scene.visible_reflectance_test(
            "M05", np.ones(viirs_data.M15.shape), bits
        )
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape, confidence, bits, output_dict, "vis_refl"
        )

        # GEMI Test
        logger.info(f"Running GEMI test for {scene_name} \n")
        confidence, bits = my_scene.gemi_test("GEMI", np.ones(viirs_data.M15.shape), bits)
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape, confidence, bits, output_dict, "gemi"
        )

        # 1.38 High Clouds Test
        logger.info(f"Running 1.38um high clouds test for {scene_name} \n")
        confidence, bits = my_scene.test_1_38um_high_clouds(
            "M09", np.ones(viirs_data.M15.shape), bits
        )
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape, confidence, bits, output_dict, "high_clouds"
        )

        # 4 -12um Thin Cirrus Test
        logger.info(f"Running 4-12um thin cirrus test for {scene_name} \n")
        confidence, bits = my_scene.thin_cirrus_4_12um_BTD_test(
            "M13-M16", np.ones(viirs_data.M15.shape), bits
        )
        bits, output_dict = update_and_clean(
            viirs_data.M15.shape, confidence, bits, output_dict, "thin_cirrus"
        )

        logger.info(f"Saving reference file for scene {scene_name} \n")

        output = xr.Dataset.from_dict(output_dict)
        output.to_netcdf(f"{_test_path}/ref_confidence_{scene_name}.nc")


def update_and_clean(
    shape: tuple, confidence: np.ndarray, bits: dict, output_dict: dict, test_name: str
) -> tuple[dict, dict]:
    """Update and clean output dictionary."""
    output_dict[f"confidence_{test_name}"] = {"dims": ("x", "y"), "data": confidence}
    output_dict[f"qa_bit_{test_name}"] = {"dims": ("x", "y"), "data": bits["qa"]}
    output_dict[f"test_bit_{test_name}"] = {"dims": ("x", "y"), "data": bits["test"]}

    bits = {
        "test": np.zeros(shape, dtype=np.int8),
        "qa": np.zeros(shape, dtype=np.int8),
    }

    return bits, output_dict


if __name__ == "__main__":
    main()