<filename>dival/util/plot.py<gh_stars>10-100
# -*- coding: utf-8 -*-
"""Provides utility functions for visualization."""
from warnings import warn
from math import ceil
import matplotlib.pyplot as plt
# import mpl_toolkits.axes_grid.axes_size as Size
# from mpl_toolkits.axes_grid import Divider
import numpy as np


def plot_image(x, fig=None, ax=None, **kwargs):
    """Plot image using matplotlib's :meth:`imshow` method.

    Parameters
    ----------
    x : array-like or PIL image
        The image data. For further information see `imshow documentation
        <https://matplotlib.org/api/_as_gen/matplotlib.pyplot.imshow.html>`_.
    fig : :class:`matplotlib.figure.Figure`, optional
        The figure to plot the image in. If ``fig is None``, but `ax` is given,
        it is retrieved from `ax`. If both ``fig is None`` and ``ax is None``,
        a new figure is created.
    ax : :class:`matplotlib.axes.Axes`, optional
        The axes to plot the image in. If `None`, an axes object is created
        in `fig`.
    kwargs : dict, optional
        Keyword arguments passed to ``ax.imshow``.

    Returns
    -------
    im : :class:`matplotlib.image.AxesImage`
        The image that was plotted.
    ax : :class:`matplotlib.axes.Axes`
        The axes the image was plotted in.
    """
    if fig is None:
        if ax is None:
            fig = plt.figure()
        else:
            fig = ax.get_figure()
    if ax is None:
        ax = fig.add_subplot(111)
    kwargs.setdefault('cmap', 'gray')
    xticks = kwargs.pop('xticks', None)
    yticks = kwargs.pop('yticks', None)
    if xticks is not None:
        ax.set_xticks(xticks)
    if yticks is not None:
        ax.set_yticks(yticks)
    im = ax.imshow(np.asarray(x).T, **kwargs)
    return im, ax


def plot_images(x_list, nrows=1, ncols=-1, fig=None, vrange='equal',
                cbar='auto', rect=None, fig_size=None, **kwargs):
    """Plot multiple images using matplotlib's :meth:`imshow` method in
    subplots.

    Parameters
    ----------
    x_list : sequence of (array-like or PIL image)
        List of the image data. For further information see `imshow
        documentation
        <https://matplotlib.org/api/_as_gen/matplotlib.pyplot.imshow.html>`_.
    nrows : int, optional
        The number of subplot rows (the default is 1). If -1, it is computed by
        ``ceil(len(x_list)/ncols)``, or set to 1 if `ncols` is not given.
    ncols : int, optional
        The number of subplot columns. If -1, it is computed by
        ``ceil(len(x_list)/nrows)`` (default). If both `nrows` and `ncols` are
        given, the value of `ncols` is ignored.
    vrange : {``'equal'``, ``'individual'``} or [list of ](float, float),\
             optional
        Value ranges for the colors of the images.
        If a string is passed, the range is auto-computed:

            ``'equal'``
                The same colors are used for all images.
            ``'individual'``
                The colors differ between the images.

        If a tuple of floats is passed, it is used for all images.
        If a list of tuples of floats is passed, each tuple is used for one
        image.
    cbar : {``'one'``, ``'many'``, ``'auto'``, ``'none'``}, optional
        Colorbar option.
        If ``cbar=='one'``, one colorbar is shown. Only possible if the value
        ranges used for the colors (cf. `vrange`) are the same for all images.
        If ``cbar=='many'``, a colorbar is shown for every image.
        If ``cbar=='auto'``, either ``'one'`` or ``'many'`` is chosen,
        depending on whether `vrange` is equal for all images.
        If ``cbar=='none'``, no colorbars are shown.
    fig : :class:`matplotlib.figure.Figure`, optional
        The figure to plot the images in. If `None`, a new figure is created.
    kwargs : dict, optional
        Keyword arguments passed to `plot_image`, which in turn passes them to
        ``imshow``.

    Returns
    -------
    im : ndarray of :class:`matplotlib.image.AxesImage`
        The images that were plotted.
    ax : ndarray of :class:`matplotlib.axes.Axes`
        The axes the images were plotted in.
    """
    try:
        x_list = list(x_list)
    except TypeError:
        raise TypeError('x_list must be iterable. Pass a sequence or use '
                        '`plot_image` to plot single images.')
    for i in range(len(x_list)):
        x_list[i] = np.asarray(x_list[i])
    if fig is None:
        fig = plt.figure()
    if nrows is None or nrows == -1:
        if ncols is None or ncols == -1:
            nrows = 1
        else:
            nrows = ceil(len(x_list)/ncols)
    ncols = ceil(len(x_list)/nrows)
    if rect is None:
        rect = [0.1, 0.1, 0.8, 0.8]
    if fig_size is not None:
        fig.set_size_inches(fig_size)
    if isinstance(vrange, str):
        if vrange == 'equal':
            vrange_ = [(min((np.min(x) for x in x_list)),
                        max((np.max(x) for x in x_list)))] * len(x_list)
            VRANGE_EQUAL = True
        elif vrange == 'individual':
            vrange_ = [(np.min(x), np.max(x)) for x in x_list]
            VRANGE_EQUAL = False
        else:
            raise ValueError("`vrange` must be 'equal' or 'individual'")
    elif isinstance(vrange, tuple) and len(vrange) == 2:
        vrange_ = [vrange] * len(x_list)
        VRANGE_EQUAL = True
    else:
        vrange_ = vrange
        VRANGE_EQUAL = False
    if not VRANGE_EQUAL:
        if cbar == 'one':
            warn("cannot use cbar='one' when vrange is not equal for all"
                 "images, falling back to cbar='many'")
        if cbar != 'none':
            cbar = 'many'
    elif cbar == 'auto':
        cbar = 'one'
    ax = fig.subplots(nrows, ncols)
    if isinstance(ax, plt.Axes):
        ax = np.atleast_1d(ax)
    im = np.empty(ax.shape, dtype=object)
    for i, (x, ax_, v) in enumerate(zip(x_list, ax.flat, vrange_)):
        im_, _ = plot_image(x, ax=ax_, vmin=v[0], vmax=v[1], **kwargs)
        im.flat[i] = im_
        if cbar == 'many':
            fig.colorbar(im_, ax=ax_)
    if cbar == 'one':
        fig.colorbar(im[0], ax=ax)
    return im, ax

<filename>dival/util/plot.py<gh_stars>10-100
# -*- coding: utf-8 -*-
"""Provides utility functions for visualization."""
from warnings import warn
from math import ceil
import matplotlib.pyplot as plt
# import mpl_toolkits.axes_grid.axes_size as Size
# from mpl_toolkits.axes_grid import Divider
import numpy as np


def plot_image(x, fig=None, ax=None, **kwargs):
    """Plot image using matplotlib's :meth:`imshow` method.

    Parameters
    ----------
    x : array-like or PIL image
        The image data. For further information see `imshow documentation
        <https://matplotlib.org/api/_as_gen/matplotlib.pyplot.imshow.html>`_.
    fig : :class:`matplotlib.figure.Figure`, optional
        The figure to plot the image in. If ``fig is None``, but `ax` is given,
        it is retrieved from `ax`. If both ``fig is None`` and ``ax is None``,
        a new figure is created.
    ax : :class:`matplotlib.axes.Axes`, optional
        The axes to plot the image in. If `None`, an axes object is created
        in `fig`.
    kwargs : dict, optional
        Keyword arguments passed to ``ax.imshow``.

    Returns
    -------
    im : :class:`matplotlib.image.AxesImage`
        The image that was plotted.
    ax : :class:`matplotlib.axes.Axes`
        The axes the image was plotted in.
    """
    if fig is None:
        if ax is None:
            fig = plt.figure()
        else:
            fig = ax.get_figure()
    if ax is None:
        ax = fig.add_subplot(111)
    kwargs.setdefault('cmap', 'gray')
    xticks = kwargs.pop('xticks', None)
    yticks = kwargs.pop('yticks', None)
    if xticks is not None:
        ax.set_xticks(xticks)
    if yticks is not None:
        ax.set_yticks(yticks)
    im = ax.imshow(np.asarray(x).T, **kwargs)
    return im, ax


def plot_images(x_list, nrows=1, ncols=-1, fig=None, vrange='equal',
                cbar='auto', rect=None, fig_size=None, **kwargs):
    """Plot multiple images using matplotlib's :meth:`imshow` method in
    subplots.

    Parameters
    ----------
    x_list : sequence of (array-like or PIL image)
        List of the image data. For further information see `imshow
        documentation
        <https://matplotlib.org/api/_as_gen/matplotlib.pyplot.imshow.html>`_.
    nrows : int, optional
        The number of subplot rows (the default is 1). If -1, it is computed by
        ``ceil(len(x_list)/ncols)``, or set to 1 if `ncols` is not given.
    ncols : int, optional
        The number of subplot columns. If -1, it is computed by
        ``ceil(len(x_list)/nrows)`` (default). If both `nrows` and `ncols` are
        given, the value of `ncols` is ignored.
    vrange : {``'equal'``, ``'individual'``} or [list of ](float, float),\
             optional
        Value ranges for the colors of the images.
        If a string is passed, the range is auto-computed:

            ``'equal'``
                The same colors are used for all images.
            ``'individual'``
                The colors differ between the images.

        If a tuple of floats is passed, it is used for all images.
        If a list of tuples of floats is passed, each tuple is used for one
        image.
    cbar : {``'one'``, ``'many'``, ``'auto'``, ``'none'``}, optional
        Colorbar option.
        If ``cbar=='one'``, one colorbar is shown. Only possible if the value
        ranges used for the colors (cf. `vrange`) are the same for all images.
        If ``cbar=='many'``, a colorbar is shown for every image.
        If ``cbar=='auto'``, either ``'one'`` or ``'many'`` is chosen,
        depending on whether `vrange` is equal for all images.
        If ``cbar=='none'``, no colorbars are shown.
    fig : :class:`matplotlib.figure.Figure`, optional
        The figure to plot the images in. If `None`, a new figure is created.
    kwargs : dict, optional
        Keyword arguments passed to `plot_image`, which in turn passes them to
        ``imshow``.

    Returns
    -------
    im : ndarray of :class:`matplotlib.image.AxesImage`
        The images that were plotted.
    ax : ndarray of :class:`matplotlib.axes.Axes`
        The axes the images were plotted in.
    """
    try:
        x_list = list(x_list)
    except TypeError:
        raise TypeError('x_list must be iterable. Pass a sequence or use '
                        '`plot_image` to plot single images.')
    for i in range(len(x_list)):
        x_list[i] = np.asarray(x_list[i])
    if fig is None:
        fig = plt.figure()
    if nrows is None or nrows == -1:
        if ncols is None or ncols == -1:
            nrows = 1
        else:
            nrows = ceil(len(x_list)/ncols)
    ncols = ceil(len(x_list)/nrows)
    if rect is None:
        rect = [0.1, 0.1, 0.8, 0.8]
    if fig_size is not None:
        fig.set_size_inches(fig_size)
    if isinstance(vrange, str):
        if vrange == 'equal':
            vrange_ = [(min((np.min(x) for x in x_list)),
                        max((np.max(x) for x in x_list)))] * len(x_list)
            VRANGE_EQUAL = True
        elif vrange == 'individual':
            vrange_ = [(np.min(x), np.max(x)) for x in x_list]
            VRANGE_EQUAL = False
        else:
            raise ValueError("`vrange` must be 'equal' or 'individual'")
    elif isinstance(vrange, tuple) and len(vrange) == 2:
        vrange_ = [vrange] * len(x_list)
        VRANGE_EQUAL = True
    else:
        vrange_ = vrange
        VRANGE_EQUAL = False
    if not VRANGE_EQUAL:
        if cbar == 'one':
            warn("cannot use cbar='one' when vrange is not equal for all"
                 "images, falling back to cbar='many'")
        if cbar != 'none':
            cbar = 'many'
    elif cbar == 'auto':
        cbar = 'one'
    ax = fig.subplots(nrows, ncols)
    if isinstance(ax, plt.Axes):
        ax = np.atleast_1d(ax)
    im = np.empty(ax.shape, dtype=object)
    for i, (x, ax_, v) in enumerate(zip(x_list, ax.flat, vrange_)):
        im_, _ = plot_image(x, ax=ax_, vmin=v[0], vmax=v[1], **kwargs)
        im.flat[i] = im_
        if cbar == 'many':
            fig.colorbar(im_, ax=ax_)
    if cbar == 'one':
        fig.colorbar(im[0], ax=ax)
    return im, ax

# -*- coding: utf-8 -*- Provides utility functions for visualization. # import mpl_toolkits.axes_grid.axes_size as Size # from mpl_toolkits.axes_grid import Divider Plot image using matplotlib's :meth:`imshow` method.      Parameters     ----------     x : array-like or PIL image         The image data. For further information see `imshow documentation         <https://matplotlib.org/api/_as_gen/matplotlib.pyplot.imshow.html>`_.     fig : :class:`matplotlib.figure.Figure`, optional         The figure to plot the image in. If ``fig is None``, but `ax` is given,         it is retrieved from `ax`. If both ``fig is None`` and ``ax is None``,         a new figure is created.     ax : :class:`matplotlib.axes.Axes`, optional         The axes to plot the image in. If `None`, an axes object is created         in `fig`.     kwargs : dict, optional         Keyword arguments passed to ``ax.imshow``.      Returns     -------     im : :class:`matplotlib.image.AxesImage`         The image that was plotted.     ax : :class:`matplotlib.axes.Axes`         The axes the image was plotted in. Plot multiple images using matplotlib's :meth:`imshow` method in     subplots.      Parameters     ----------     x_list : sequence of (array-like or PIL image)         List of the image data. For further information see `imshow         documentation         <https://matplotlib.org/api/_as_gen/matplotlib.pyplot.imshow.html>`_.     nrows : int, optional         The number of subplot rows (the default is 1). If -1, it is computed by         ``ceil(len(x_list)/ncols)``, or set to 1 if `ncols` is not given.     ncols : int, optional         The number of subplot columns. If -1, it is computed by         ``ceil(len(x_list)/nrows)`` (default). If both `nrows` and `ncols` are         given, the value of `ncols` is ignored.     vrange : {``'equal'``, ``'individual'``} or [list of ](float, float),\              optional         Value ranges for the colors of the images.         If a string is passed, the range is auto-computed:              ``'equal'``                 The same colors are used for all images.             ``'individual'``                 The colors differ between the images.          If a tuple of floats is passed, it is used for all images.         If a list of tuples of floats is passed, each tuple is used for one         image.     cbar : {``'one'``, ``'many'``, ``'auto'``, ``'none'``}, optional         Colorbar option.         If ``cbar=='one'``, one colorbar is shown. Only possible if the value         ranges used for the colors (cf. `vrange`) are the same for all images.         If ``cbar=='many'``, a colorbar is shown for every image.         If ``cbar=='auto'``, either ``'one'`` or ``'many'`` is chosen,         depending on whether `vrange` is equal for all images.         If ``cbar=='none'``, no colorbars are shown.     fig : :class:`matplotlib.figure.Figure`, optional         The figure to plot the images in. If `None`, a new figure is created.     kwargs : dict, optional         Keyword arguments passed to `plot_image`, which in turn passes them to         ``imshow``.      Returns     -------     im : ndarray of :class:`matplotlib.image.AxesImage`         The images that were plotted.     ax : ndarray of :class:`matplotlib.axes.Axes`         The axes the images were plotted in.