"""Find nodata value of datasets."""

import click
import numpy as np
import rasterio
from scipy.stats import mode

from rio_alpha.utils import (
    _convert_rgb,
    _compute_continuous,
    _debug_mode,
    _search_image_edge,
    _evaluate_count,
)


def discover_ndv(rgb_orig, debug, verbose):
    """Returns nodata value by calculating mode of RGB array

    Parameters
    ----------
    rgb_orig: ndarray
              array of input pixels of shape (rows, cols, depth)
    debug: Boolean
           Enables matplotlib & printing of figures
    verbose: Boolean
             Prints extra information, like competing candidate values


    Returns
    -------
    list of nodata value candidates or empty string if none found

    """
    rgb_mod, rgb_mod_flat = _convert_rgb(rgb_orig)
    # Full image mode bincount
    mode_vals = mode(rgb_mod_flat)
    candidate_original = [int((mode_vals[0])[0, i]) for i in range(3)]

    # Find continuous values in RGB array
    candidate_continuous, arr = _compute_continuous(rgb_mod, 1)

    # If debug mode, print histograms & be verbose
    if debug:
        click.echo("Original image ndv candidate: %s" % (str(candidate_original)))
        click.echo("Filtered image ndv candidate: %s" % (str(candidate_continuous)))
        outplot = "/tmp/hist_plot.png"
        _debug_mode(rgb_mod_flat, arr, outplot)

    # Compare ndv candidates from full & squished image
    candidate_list = [
        i for i, j in zip(candidate_original, candidate_continuous) if i == j
    ]

    # If candidates from original & filtered images match exactly,
    # print value & exit
    if len(candidate_list) == 3:
        return candidate_list

    # If candidates do not match exactly, continue vetting process
    # by searching image edge for frequency of each candidate
    elif len(candidate_list) < 3:
        if verbose:
            click.echo(
                "Competing ndv candidates...searching "
                "image collar for value frequency. "
                "Candidate list: %s" % str(candidate_list)
            )

        count_img_edge_full, count_img_edge_continuous = _search_image_edge(
            rgb_mod, candidate_original, candidate_continuous
        )

        if verbose:
            for candidate in (candidate_original, candidate_continuous):
                click.echo(
                    "Candidate value: %s "
                    "Candidate count: %s "
                    "Continuous count: %s"
                    % (
                        str(candidate),
                        str(count_img_edge_full),
                        str(count_img_edge_continuous),
                    )
                )

        output = _evaluate_count(
            count_img_edge_full, count_img_edge_continuous, verbose
        )

        return output

    else:
        raise ValueError("Invalid candidate list {!r}".format(candidate_list))


def determine_nodata(src_path, user_nodata, discovery, debug, verbose):
    """Worker function for determining nodata

    Parameters
    ----------
    src_path: string
    user_nodata: string/integer
                 User supplies the nodata value,
                 input a single value or a string of list
    discovery: Boolean
               determines nodata if alpha channel does not exist
               or internal ndv does not exist
    debug: Boolean
           Enables matplotlib & printing of figures
    verbose: Boolean
             Prints extra information, like competing candidate values


    Returns
    -------
    nodata value: string
                  string(int) or stringified array of values of
                  len == the number of bands.
                  For example, string([int(ndv), int(ndv), int(ndv)])
    """

    if user_nodata:
        return user_nodata

    with rasterio.open(src_path, "r") as src:
        count = src.count

        if count == 4:
            return "alpha"
        else:
            nodata = src.nodata
            if nodata is None:
                if discovery:
                    data = np.rollaxis(src.read(), 0, 3)
                    candidates = discover_ndv(data, debug, verbose)
                    if len(candidates) != 3:
                        return ""
                    else:
                        return "[{}, {}, {}]".format(*candidates)
                else:
                    return ""
            else:
                return "%s" % (str(int(nodata)))

"""Find nodata value of datasets."""

import click
import numpy as np
import rasterio
from scipy.stats import mode

from rio_alpha.utils import (
    _convert_rgb,
    _compute_continuous,
    _debug_mode,
    _search_image_edge,
    _evaluate_count,
)


def discover_ndv(rgb_orig, debug, verbose):
    """Returns nodata value by calculating mode of RGB array

    Parameters
    ----------
    rgb_orig: ndarray
              array of input pixels of shape (rows, cols, depth)
    debug: Boolean
           Enables matplotlib & printing of figures
    verbose: Boolean
             Prints extra information, like competing candidate values


    Returns
    -------
    list of nodata value candidates or empty string if none found

    """
    rgb_mod, rgb_mod_flat = _convert_rgb(rgb_orig)
    # Full image mode bincount
    mode_vals = mode(rgb_mod_flat)
    candidate_original = [int((mode_vals[0])[0, i]) for i in range(3)]

    # Find continuous values in RGB array
    candidate_continuous, arr = _compute_continuous(rgb_mod, 1)

    # If debug mode, print histograms & be verbose
    if debug:
        click.echo("Original image ndv candidate: %s" % (str(candidate_original)))
        click.echo("Filtered image ndv candidate: %s" % (str(candidate_continuous)))
        outplot = "/tmp/hist_plot.png"
        _debug_mode(rgb_mod_flat, arr, outplot)

    # Compare ndv candidates from full & squished image
    candidate_list = [
        i for i, j in zip(candidate_original, candidate_continuous) if i == j
    ]

    # If candidates from original & filtered images match exactly,
    # print value & exit
    if len(candidate_list) == 3:
        return candidate_list

    # If candidates do not match exactly, continue vetting process
    # by searching image edge for frequency of each candidate
    elif len(candidate_list) < 3:
        if verbose:
            click.echo(
                "Competing ndv candidates...searching "
                "image collar for value frequency. "
                "Candidate list: %s" % str(candidate_list)
            )

        count_img_edge_full, count_img_edge_continuous = _search_image_edge(
            rgb_mod, candidate_original, candidate_continuous
        )

        if verbose:
            for candidate in (candidate_original, candidate_continuous):
                click.echo(
                    "Candidate value: %s "
                    "Candidate count: %s "
                    "Continuous count: %s"
                    % (
                        str(candidate),
                        str(count_img_edge_full),
                        str(count_img_edge_continuous),
                    )
                )

        output = _evaluate_count(
            count_img_edge_full, count_img_edge_continuous, verbose
        )

        return output

    else:
        raise ValueError("Invalid candidate list {!r}".format(candidate_list))


def determine_nodata(src_path, user_nodata, discovery, debug, verbose):
    """Worker function for determining nodata

    Parameters
    ----------
    src_path: string
    user_nodata: string/integer
                 User supplies the nodata value,
                 input a single value or a string of list
    discovery: Boolean
               determines nodata if alpha channel does not exist
               or internal ndv does not exist
    debug: Boolean
           Enables matplotlib & printing of figures
    verbose: Boolean
             Prints extra information, like competing candidate values


    Returns
    -------
    nodata value: string
                  string(int) or stringified array of values of
                  len == the number of bands.
                  For example, string([int(ndv), int(ndv), int(ndv)])
    """

    if user_nodata:
        return user_nodata

    with rasterio.open(src_path, "r") as src:
        count = src.count

        if count == 4:
            return "alpha"
        else:
            nodata = src.nodata
            if nodata is None:
                if discovery:
                    data = np.rollaxis(src.read(), 0, 3)
                    candidates = discover_ndv(data, debug, verbose)
                    if len(candidates) != 3:
                        return ""
                    else:
                        return "[{}, {}, {}]".format(*candidates)
                else:
                    return ""
            else:
                return "%s" % (str(int(nodata)))

Find nodata value of datasets. Returns nodata value by calculating mode of RGB array      Parameters     ----------     rgb_orig: ndarray               array of input pixels of shape (rows, cols, depth)     debug: Boolean            Enables matplotlib & printing of figures     verbose: Boolean              Prints extra information, like competing candidate values       Returns     -------     list of nodata value candidates or empty string if none found # Full image mode bincount # Find continuous values in RGB array # If debug mode, print histograms & be verbose # Compare ndv candidates from full & squished image # If candidates from original & filtered images match exactly, # print value & exit # If candidates do not match exactly, continue vetting process # by searching image edge for frequency of each candidate Worker function for determining nodata      Parameters     ----------     src_path: string     user_nodata: string/integer                  User supplies the nodata value,                  input a single value or a string of list     discovery: Boolean                determines nodata if alpha channel does not exist                or internal ndv does not exist     debug: Boolean            Enables matplotlib & printing of figures     verbose: Boolean              Prints extra information, like competing candidate values       Returns     -------     nodata value: string                   string(int) or stringified array of values of                   len == the number of bands.                   For example, string([int(ndv), int(ndv), int(ndv)])