from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

from matplotlib.externals import six

import matplotlib.pyplot as plt
from matplotlib.testing.decorators import image_comparison, cleanup

from mpl_toolkits.axes_grid1 import make_axes_locatable
from mpl_toolkits.axes_grid1 import AxesGrid

from matplotlib.colors import LogNorm

import numpy as np


@image_comparison(baseline_images=['divider_append_axes'])
def test_divider_append_axes():

    # the random data
    np.random.seed(0)
    x = np.random.randn(1000)
    y = np.random.randn(1000)

    fig, axScatter = plt.subplots()

    # the scatter plot:
    axScatter.scatter(x, y)

    # create new axes on the right and on the top of the current axes
    # The first argument of the new_vertical(new_horizontal) method is
    # the height (width) of the axes to be created in inches.
    divider = make_axes_locatable(axScatter)
    axHistbot = divider.append_axes("bottom", 1.2, pad=0.1, sharex=axScatter)
    axHistright = divider.append_axes("right", 1.2, pad=0.1, sharey=axScatter)
    axHistleft = divider.append_axes("left", 1.2, pad=0.1, sharey=axScatter)
    axHisttop = divider.append_axes("top", 1.2, pad=0.1, sharex=axScatter)

    # now determine nice limits by hand:
    binwidth = 0.25
    xymax = np.max([np.max(np.fabs(x)), np.max(np.fabs(y))])
    lim = (int(xymax/binwidth) + 1) * binwidth

    bins = np.arange(-lim, lim + binwidth, binwidth)
    axHisttop.hist(x, bins=bins)
    axHistbot.hist(x, bins=bins)
    axHistleft.hist(y, bins=bins, orientation='horizontal')
    axHistright.hist(y, bins=bins, orientation='horizontal')

    axHistbot.invert_yaxis()
    axHistleft.invert_xaxis()

    axHisttop.xaxis.set_ticklabels(())
    axHistbot.xaxis.set_ticklabels(())
    axHistleft.yaxis.set_ticklabels(())
    axHistright.yaxis.set_ticklabels(())


@cleanup
def test_axesgrid_colorbar_log_smoketest():
    fig = plt.figure()
    grid = AxesGrid(fig, 111,  # modified to be only subplot
                    nrows_ncols=(1, 1),
                    label_mode="L",
                    cbar_location="top",
                    cbar_mode="single",
                    )

    Z = 10000 * np.random.rand(10, 10)
    im = grid[0].imshow(Z, interpolation="nearest", norm=LogNorm())

    grid.cbar_axes[0].colorbar(im)


if __name__ == '__main__':
    import nose
    nose.runmodule(argv=['-s', '--with-doctest'], exit=False)