import csv
import logging
from pathlib import Path
from typing import Union

import click
import numpy as np

from blender import Blender, Blend
from blender.catalog import blend2cat, CATALOG_HEADER


def save_img(blend: Blend, idx: int, prefix: str, outdir: Union[Path, str] = ".") -> None:
    np.save(f"{outdir}/{prefix}_blend_{idx:06d}.npy", blend.img)
    np.save(f"{outdir}/{prefix}_blend_seg_{idx:06d}.npy", blend.segmap)


def create_image_set(blender: Blender, n_blends: int, outdir: Path,
                     test_set: bool = False) -> None:
    """
    Use a Blender instance to output stamps of blended galaxies and
    their associated segmentation mask, plus a catalog of these sources.

    Parameters
    ----------
    blender:
        the Blender instance
    n_blends:
        number of desired images
    outdir:
        output directory
    test_set: default False
        switch between the training and testing galaxy split

    """
    prefix = "test" if test_set else "train"

    outcat = outdir / f"{prefix}_catalogue.csv"

    with open(outcat, "w") as f:
        output = csv.writer(f)
        output.writerow(CATALOG_HEADER)

        msg = f"Producing {prefix} blended images"
        with click.progressbar(range(n_blends), label=msg) as bar:
            for blend_id in bar:
                blend = blender.next_blend(from_test=test_set)
                while blend is None:
                    blend = blender.next_blend(from_test=test_set)
                output.writerow(blend2cat(blend, blend_id))
                save_img(blend, blend_id, prefix, outdir)


@click.command("produce")
@click.option(
    "-n",
    "--n_blends",
    type=int,
    default=100,
    show_default=True,
    help="Number of blends to produce",
)
@click.option(
    "--mag_low",
    type=float,
    default=0,
    show_default=True,
    help="Lowest galaxy magnitude",
)
@click.option(
    "--mag_high",
    type=float,
    default=100,
    show_default=True,
    help="Highest galaxy magnitude",
)
@click.option(
    "--mag_diff",
    type=float,
    default=2,
    show_default=True,
    help="Top magnitude difference between galaxies",
)
@click.option(
    "--rad_diff",
    type=float,
    default=4,
    show_default=True,
    help="Top distance between galaxies as a fraction of radius",
)
@click.option(
    "-t",
    "--test_ratio",
    type=float,
    default=0.2,
    show_default=True,
    help="Ratio of the input galaxies used only for the test set",
)
@click.option(
    "-e",
    "--excluded_type",
    type=click.Choice(["irr", "disk", "sph", "sphd"]),
    multiple=True,
    help="Excluded galaxy types",
)
@click.option(
    "-d",
    "--datapath",
              type=click.Path(exists=True),
    default="./data",
    show_default=True,
    help="Path to data files",
)
@click.option(
    "-s",
    "--seed",
    type=int,
    default=42,
    show_default=True,
    help="Random seed",
)
def main(n_blends, excluded_type, mag_low, mag_high, mag_diff, rad_diff,
         test_ratio, datapath, seed):
    """
    Produce stamps of CANDELS blended galaxies with their individual masks
    """
    # Define the various paths and create directories
    cwd = Path.cwd()
    datapath = cwd / datapath
    input_stamps = datapath / "candels_img.npy"
    input_segmaps = datapath / "candels_seg.npy"
    input_catalog = datapath / "candels_cat.csv"

    outdir = cwd / f"output-s_{seed}-n_{n_blends}"
    if not outdir.exists():
        outdir.mkdir()
    outlog = outdir / "candels-blender.log"

    logging.basicConfig(
        filename=outlog,
        level=logging.INFO,
        format="%(asctime)s [ %(levelname)s ] : %(message)s",
    )

    blender = Blender(
        input_stamps,
        input_segmaps,
        input_catalog,
        train_test_ratio=test_ratio,
        magdiff=mag_diff,
        raddiff=rad_diff,
        seed=seed,
    )

    logger = logging.getLogger(__name__)
    logger.info(
        "\n"
        "Configuration\n"
        "=============\n"
        f"Number of blends: {n_blends}\n"
        f"Seed: {seed}\n"
        "\n"
        "Catalog cuts\n"
        "------------\n"
        f"Excluded galaxy types: {excluded_type}\n"
        f"Lowest magnitude: {mag_low}\n"
        f"Highest magnitude: {mag_high}\n"
        "\n"
        "Blend properties\n"
        "----------------\n"
        f"Top difference in magnitude between galaxies: {mag_diff}\n"
        f"Top distance between galaxies as a fraction of radius: {rad_diff}\n"
    )

    # Apply cuts to the galaxy catalog
    click.echo(
        f"Selecting galaxies in the magnitude range {mag_low} < m < {mag_high}"
    )
    blender.make_cut(blender.cat.mag > mag_low)
    blender.make_cut(blender.cat.mag < mag_high)
    for galtype in set(excluded_type):
        click.echo(f"Excluding {galtype} galaxies")
        blender.make_cut(blender.cat.galtype != galtype)

    click.echo(
        f"After the cuts, there are {blender.n_gal} individual galaxies "
        "left in the catalog."
    )

    # Compute the train/test splits
    n_test = int(test_ratio * n_blends)
    n_train = n_blends - n_test

    create_image_set(blender, n_train, outdir)
    create_image_set(blender, n_test, outdir, test_set=True)

    click.echo(message=f"Images stored in {outdir}")


if __name__ == "__main__":
    main()  # pylint: disable=no-value-for-parameter

import csv
import logging
from pathlib import Path
from typing import Union

import click
import numpy as np

from blender import Blender, Blend
from blender.catalog import blend2cat, CATALOG_HEADER


def save_img(blend: Blend, idx: int, prefix: str, outdir: Union[Path, str] = ".") -> None:
    np.save(f"{outdir}/{prefix}_blend_{idx:06d}.npy", blend.img)
    np.save(f"{outdir}/{prefix}_blend_seg_{idx:06d}.npy", blend.segmap)


def create_image_set(blender: Blender, n_blends: int, outdir: Path,
                     test_set: bool = False) -> None:
    """
    Use a Blender instance to output stamps of blended galaxies and
    their associated segmentation mask, plus a catalog of these sources.

    Parameters
    ----------
    blender:
        the Blender instance
    n_blends:
        number of desired images
    outdir:
        output directory
    test_set: default False
        switch between the training and testing galaxy split

    """
    prefix = "test" if test_set else "train"

    outcat = outdir / f"{prefix}_catalogue.csv"

    with open(outcat, "w") as f:
        output = csv.writer(f)
        output.writerow(CATALOG_HEADER)

        msg = f"Producing {prefix} blended images"
        with click.progressbar(range(n_blends), label=msg) as bar:
            for blend_id in bar:
                blend = blender.next_blend(from_test=test_set)
                while blend is None:
                    blend = blender.next_blend(from_test=test_set)
                output.writerow(blend2cat(blend, blend_id))
                save_img(blend, blend_id, prefix, outdir)


@click.command("produce")
@click.option(
    "-n",
    "--n_blends",
    type=int,
    default=100,
    show_default=True,
    help="Number of blends to produce",
)
@click.option(
    "--mag_low",
    type=float,
    default=0,
    show_default=True,
    help="Lowest galaxy magnitude",
)
@click.option(
    "--mag_high",
    type=float,
    default=100,
    show_default=True,
    help="Highest galaxy magnitude",
)
@click.option(
    "--mag_diff",
    type=float,
    default=2,
    show_default=True,
    help="Top magnitude difference between galaxies",
)
@click.option(
    "--rad_diff",
    type=float,
    default=4,
    show_default=True,
    help="Top distance between galaxies as a fraction of radius",
)
@click.option(
    "-t",
    "--test_ratio",
    type=float,
    default=0.2,
    show_default=True,
    help="Ratio of the input galaxies used only for the test set",
)
@click.option(
    "-e",
    "--excluded_type",
    type=click.Choice(["irr", "disk", "sph", "sphd"]),
    multiple=True,
    help="Excluded galaxy types",
)
@click.option(
    "-d",
    "--datapath",
              type=click.Path(exists=True),
    default="./data",
    show_default=True,
    help="Path to data files",
)
@click.option(
    "-s",
    "--seed",
    type=int,
    default=42,
    show_default=True,
    help="Random seed",
)
def main(n_blends, excluded_type, mag_low, mag_high, mag_diff, rad_diff,
         test_ratio, datapath, seed):
    """
    Produce stamps of CANDELS blended galaxies with their individual masks
    """
    # Define the various paths and create directories
    cwd = Path.cwd()
    datapath = cwd / datapath
    input_stamps = datapath / "candels_img.npy"
    input_segmaps = datapath / "candels_seg.npy"
    input_catalog = datapath / "candels_cat.csv"

    outdir = cwd / f"output-s_{seed}-n_{n_blends}"
    if not outdir.exists():
        outdir.mkdir()
    outlog = outdir / "candels-blender.log"

    logging.basicConfig(
        filename=outlog,
        level=logging.INFO,
        format="%(asctime)s [ %(levelname)s ] : %(message)s",
    )

    blender = Blender(
        input_stamps,
        input_segmaps,
        input_catalog,
        train_test_ratio=test_ratio,
        magdiff=mag_diff,
        raddiff=rad_diff,
        seed=seed,
    )

    logger = logging.getLogger(__name__)
    logger.info(
        "\n"
        "Configuration\n"
        "=============\n"
        f"Number of blends: {n_blends}\n"
        f"Seed: {seed}\n"
        "\n"
        "Catalog cuts\n"
        "------------\n"
        f"Excluded galaxy types: {excluded_type}\n"
        f"Lowest magnitude: {mag_low}\n"
        f"Highest magnitude: {mag_high}\n"
        "\n"
        "Blend properties\n"
        "----------------\n"
        f"Top difference in magnitude between galaxies: {mag_diff}\n"
        f"Top distance between galaxies as a fraction of radius: {rad_diff}\n"
    )

    # Apply cuts to the galaxy catalog
    click.echo(
        f"Selecting galaxies in the magnitude range {mag_low} < m < {mag_high}"
    )
    blender.make_cut(blender.cat.mag > mag_low)
    blender.make_cut(blender.cat.mag < mag_high)
    for galtype in set(excluded_type):
        click.echo(f"Excluding {galtype} galaxies")
        blender.make_cut(blender.cat.galtype != galtype)

    click.echo(
        f"After the cuts, there are {blender.n_gal} individual galaxies "
        "left in the catalog."
    )

    # Compute the train/test splits
    n_test = int(test_ratio * n_blends)
    n_train = n_blends - n_test

    create_image_set(blender, n_train, outdir)
    create_image_set(blender, n_test, outdir, test_set=True)

    click.echo(message=f"Images stored in {outdir}")


if __name__ == "__main__":
    main()  # pylint: disable=no-value-for-parameter

Use a Blender instance to output stamps of blended galaxies and     their associated segmentation mask, plus a catalog of these sources.      Parameters     ----------     blender:         the Blender instance     n_blends:         number of desired images     outdir:         output directory     test_set: default False         switch between the training and testing galaxy split Produce stamps of CANDELS blended galaxies with their individual masks # Define the various paths and create directories # Apply cuts to the galaxy catalog # Compute the train/test splits # pylint: disable=no-value-for-parameter