"""
    This file is part of MSS.

    :copyright: Copyright 2021-2022 by the MSS team, see AUTHORS.
    :license: APACHE-2.0, see LICENSE for details.

    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.
    You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

    Unless required by applicable law or agreed to in writing, software
    distributed under the License is distributed on an "AS IS" BASIS,
    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    See the License for the specific language governing permissions and
    limitations under the License.
"""

import warnings
import matplotlib
import matplotlib.pyplot as plt
import mpl_toolkits.axes_grid1.inset_locator
from matplotlib import patheffects
import numpy as np
from mslib.mswms.mpl_vsec import AbstractVerticalSectionStyle
from mslib.mswms.utils import Targets, get_style_parameters, get_cbar_label_format, make_cbar_labels_readable
from mslib.utils import thermolib
from mslib.utils.units import convert_to

class VS_VerticalVelocityStyle_01(AbstractVerticalSectionStyle):
    """
    Vertical sections of vertical velocity.
    """

    name = "VS_W01"
    title = "Vertical Velocity (cm/s) Vertical Section"
    abstract = "Veertical velocity (cm/s) with temperature (K) and potential temperature (K)"

    # Variables with the highest number of dimensions first (otherwise
    # MFDatasetCommonDims will throw an exception)!
    required_datafields = [
        ("ml", "air_pressure", "Pa"),
        ("ml", "air_temperature", "K"),
        ("ml", "lagrangian_tendency_of_air_pressure", "Pa/s")]

    def _prepare_datafields(self):
        """
        Computes potential temperature from pressure and temperature if
        it has not been passed as a data field. Also computes vertical
        velocity in cm/s.
        """
        self.data['air_potential_temperature'] = thermolib.pot_temp(
            self.data['air_pressure'], self.data['air_temperature'])
        self.data["upward_wind"] = convert_to(
            thermolib.omega_to_w(self.data["lagrangian_tendency_of_air_pressure"],
                                 self.data['air_pressure'], self.data["air_temperature"]),
            "m/s", "cm/s")

    def _plot_style(self):
        """
        Make a vertical velocity vertical section with temperature/potential
        temperature overlay.
        """
        ax = self.ax
        curtain_p = self.data["air_pressure"]
        curtain_t = self.data["air_temperature"]
        curtain_pt = self.data["air_potential_temperature"]
        curtain_w = self.data["upward_wind"]

        # Contour spacing for temperature lines.
        delta_t = 2 if (np.log(self.p_bot) - np.log(self.p_top)) < 2.2 else 4
        delta_pt = 5 if (np.log(self.p_bot) - np.log(self.p_top)) < 2.2 else 10

        upward_contours = np.arange(-42, 46, 4)

        # Filled contour plot of relative humidity.
        # INFO on COLORMAPS:
        #    http://matplotlib.sourceforge.net/examples/pylab_examples/show_colormaps.html
        cs = ax.contourf(self.horizontal_coordinate, curtain_p, curtain_w,
                         upward_contours, cmap=plt.cm.bwr)
        # Contour line plot of relative humidity.
        ax.contour(self.horizontal_coordinate, curtain_p, curtain_w, [2],
                   colors="red", linestyles="solid", linewidths=0.5)
        ax.contour(self.horizontal_coordinate, curtain_p, curtain_w, [-2],
                   colors="blue", linestyles="solid", linewidths=0.5)
        # Contour line plot of temperature.
        cs_t = ax.contour(self.horizontal_coordinate,
                          curtain_p, curtain_t, np.arange(236, 330, delta_t),
                          colors='green', linestyles='solid', linewidths=1)
        ax.clabel(cs_t, fontsize=8, fmt='%.0f')
        cs_t = ax.contour(self.horizontal_coordinate,
                          curtain_p, curtain_t, [234],
                          colors='green', linestyles='solid', linewidths=2)
        ax.clabel(cs_t, fontsize=8, fmt='%.0f')
        cs_t = ax.contour(self.horizontal_coordinate,
                          curtain_p, curtain_t, np.arange(160, 232, delta_t),
                          colors='green', linestyles='dashed', linewidths=1)
        ax.clabel(cs_t, fontsize=8, fmt='%.0f')
        # Contour line plot of potential temperature.
        cs_pt = ax.contour(self.horizontal_coordinate, curtain_p, curtain_pt,
                           np.arange(200, 700, delta_pt), colors='grey',
                           linestyles='solid', linewidths=1)
        ax.clabel(cs_pt, fontsize=8, fmt='%.0f')

        # Pressure decreases with index, i.e. orography is stored at the
        # zero-p-index (data field is flipped in mss_plot_driver.py if
        # pressure increases with index).
        self._latlon_logp_setup(orography=curtain_p[0, :])
        self.add_colorbar(cs, "Vertical velocity (cm/s)")