# being a bit too dynamic
# pylint: disable=E1101
from __future__ import division

from collections import namedtuple
from distutils.version import LooseVersion
import re
import warnings

import numpy as np

import pandas.compat as compat
from pandas.compat import lrange, map, range, string_types, zip
from pandas.errors import AbstractMethodError
from pandas.util._decorators import Appender, cache_readonly

from pandas.core.dtypes.common import (
    is_hashable, is_integer, is_iterator, is_list_like, is_number)
from pandas.core.dtypes.generic import (
    ABCDataFrame, ABCIndexClass, ABCMultiIndex, ABCPeriodIndex, ABCSeries)
from pandas.core.dtypes.missing import isna, notna, remove_na_arraylike

from pandas.core.base import PandasObject
import pandas.core.common as com
from pandas.core.config import get_option
from pandas.core.generic import _shared_doc_kwargs, _shared_docs

from pandas.io.formats.printing import pprint_thing
from pandas.plotting._compat import _mpl_ge_3_0_0
from pandas.plotting._style import _get_standard_colors, plot_params
from pandas.plotting._tools import (
    _flatten, _get_all_lines, _get_xlim, _handle_shared_axes, _set_ticks_props,
    _subplots, format_date_labels, table)

try:
    from pandas.plotting import _converter
except ImportError:
    _HAS_MPL = False
else:
    _HAS_MPL = True
    if get_option('plotting.matplotlib.register_converters'):
        _converter.register(explicit=False)


def _raise_if_no_mpl():
    # TODO(mpl_converter): remove once converter is explicit
    if not _HAS_MPL:
        raise ImportError("matplotlib is required for plotting.")


def _get_standard_kind(kind):
    return {'density': 'kde'}.get(kind, kind)


def _gca(rc=None):
    import matplotlib.pyplot as plt
    with plt.rc_context(rc):
        return plt.gca()


def _gcf():
    import matplotlib.pyplot as plt
    return plt.gcf()


class MPLPlot(object):
    """
    Base class for assembling a pandas plot using matplotlib

    Parameters
    ----------
    data :

    """

    @property
    def _kind(self):
        """Specify kind str. Must be overridden in child class"""
        raise NotImplementedError

    _layout_type = 'vertical'
    _default_rot = 0
    orientation = None
    _pop_attributes = ['label', 'style', 'logy', 'logx', 'loglog',
                       'mark_right', 'stacked']
    _attr_defaults = {'logy': False, 'logx': False, 'loglog': False,
                      'mark_right': True, 'stacked': False}

    def __init__(self, data, kind=None, by=None, subplots=False, sharex=None,
                 sharey=False, use_index=True,
                 figsize=None, grid=None, legend=True, rot=None,
                 ax=None, fig=None, title=None, xlim=None, ylim=None,
                 xticks=None, yticks=None,
                 sort_columns=False, fontsize=None,
                 secondary_y=False, colormap=None,
                 table=False, layout=None, **kwds):

        _raise_if_no_mpl()
        _converter._WARN = False
        self.data = data
        self.by = by

        self.kind = kind

        self.sort_columns = sort_columns

        self.subplots = subplots

        if sharex is None:
            if ax is None:
                self.sharex = True
            else:
                # if we get an axis, the users should do the visibility
                # setting...
                self.sharex = False
        else:
            self.sharex = sharex

        self.sharey = sharey
        self.figsize = figsize
        self.layout = layout

        self.xticks = xticks
        self.yticks = yticks
        self.xlim = xlim
        self.ylim = ylim
        self.title = title
        self.use_index = use_index

        self.fontsize = fontsize

        if rot is not None:
            self.rot = rot
            # need to know for format_date_labels since it's rotated to 30 by
            # default
            self._rot_set = True
        else:
            self._rot_set = False
            self.rot = self._default_rot

        if grid is None:
            grid = False if secondary_y else self.plt.rcParams['axes.grid']

        self.grid = grid
        self.legend = legend
        self.legend_handles = []
        self.legend_labels = []

        for attr in self._pop_attributes:
            value = kwds.pop(attr, self._attr_defaults.get(attr, None))
            setattr(self, attr, value)

        self.ax = ax
        self.fig = fig
        self.axes = None

        # parse errorbar input if given
        xerr = kwds.pop('xerr', None)
        yerr = kwds.pop('yerr', None)
        self.errors = {kw: self._parse_errorbars(kw, err)
                       for kw, err in zip(['xerr', 'yerr'], [xerr, yerr])}

        if not isinstance(secondary_y, (bool, tuple, list,
                                        np.ndarray, ABCIndexClass)):
            secondary_y = [secondary_y]
        self.secondary_y = secondary_y

        # ugly TypeError if user passes matplotlib's `cmap` name.
        # Probably better to accept either.
        if 'cmap' in kwds and colormap:
            raise TypeError("Only specify one of `cmap` and `colormap`.")
        elif 'cmap' in kwds:
            self.colormap = kwds.pop('cmap')
        else:
            self.colormap = colormap

        self.table = table

        self.kwds = kwds

        self._validate_color_args()

    def _validate_color_args(self):
        if 'color' not in self.kwds and 'colors' in self.kwds:
            warnings.warn(("'colors' is being deprecated. Please use 'color'"
                           "instead of 'colors'"))
            colors = self.kwds.pop('colors')
            self.kwds['color'] = colors

        if ('color' in self.kwds and self.nseries == 1 and
                not is_list_like(self.kwds['color'])):
            # support series.plot(color='green')
            self.kwds['color'] = [self.kwds['color']]

        if ('color' in self.kwds and isinstance(self.kwds['color'], tuple) and
                self.nseries == 1 and len(self.kwds['color']) in (3, 4)):
            # support RGB and RGBA tuples in series plot
            self.kwds['color'] = [self.kwds['color']]

        if ('color' in self.kwds or 'colors' in self.kwds) and \
                self.colormap is not None:
            warnings.warn("'color' and 'colormap' cannot be used "
                          "simultaneously. Using 'color'")

        if 'color' in self.kwds and self.style is not None:
            if is_list_like(self.style):
                styles = self.style
            else:
                styles = [self.style]
            # need only a single match
            for s in styles:
                if re.match('^[a-z]+?', s) is not None:
                    raise ValueError(
                        "Cannot pass 'style' string with a color "
                        "symbol and 'color' keyword argument. Please"
                        " use one or the other or pass 'style' "
                        "without a color symbol")

    def _iter_data(self, data=None, keep_index=False, fillna=None):
        if data is None:
            data = self.data
        if fillna is not None:
            data = data.fillna(fillna)

        # TODO: unused?
        # if self.sort_columns:
        #     columns = com.try_sort(data.columns)
        # else:
        #     columns = data.columns

        for col, values in data.iteritems():
            if keep_index is True:
                yield col, values
            else:
                yield col, values.values

    @property
    def nseries(self):
        if self.data.ndim == 1:
            return 1
        else:
            return self.data.shape[1]

    def draw(self):
        self.plt.draw_if_interactive()

    def generate(self):
        self._args_adjust()
        self._compute_plot_data()
        self._setup_subplots()
        self._make_plot()
        self._add_table()
        self._make_legend()
        self._adorn_subplots()

        for ax in self.axes:
            self._post_plot_logic_common(ax, self.data)
            self._post_plot_logic(ax, self.data)

    def _args_adjust(self):
        pass

    def _has_plotted_object(self, ax):
        """check whether ax has data"""
        return (len(ax.lines) != 0 or
                len(ax.artists) != 0 or
                len(ax.containers) != 0)

    def _maybe_right_yaxis(self, ax, axes_num):
        if not self.on_right(axes_num):
            # secondary axes may be passed via ax kw
            return self._get_ax_layer(ax)

        if hasattr(ax, 'right_ax'):
            # if it has right_ax proparty, ``ax`` must be left axes
            return ax.right_ax
        elif hasattr(ax, 'left_ax'):
            # if it has left_ax proparty, ``ax`` must be right axes
            return ax
        else:
            # otherwise, create twin axes
            orig_ax, new_ax = ax, ax.twinx()
            # TODO: use Matplotlib public API when available
            new_ax._get_lines = orig_ax._get_lines
            new_ax._get_patches_for_fill = orig_ax._get_patches_for_fill
            orig_ax.right_ax, new_ax.left_ax = new_ax, orig_ax

            if not self._has_plotted_object(orig_ax):  # no data on left y
                orig_ax.get_yaxis().set_visible(False)

            if self.logy or self.loglog:
                new_ax.set_yscale('log')
            return new_ax

    def _setup_subplots(self):
        if self.subplots:
            fig, axes = _subplots(naxes=self.nseries,
                                  sharex=self.sharex, sharey=self.sharey,
                                  figsize=self.figsize, ax=self.ax,
                                  layout=self.layout,
                                  layout_type=self._layout_type)
        else:
            if self.ax is None:
                fig = self.plt.figure(figsize=self.figsize)
                axes = fig.add_subplot(111)
            else:
                fig = self.ax.get_figure()
                if self.figsize is not None:
                    fig.set_size_inches(self.figsize)
                axes = self.ax

        axes = _flatten(axes)

        if self.logx or self.loglog:
            [a.set_xscale('log') for a in axes]
        if self.logy or self.loglog:
            [a.set_yscale('log') for a in axes]

        self.fig = fig
        self.axes = axes

    @property
    def result(self):
        """
        Return result axes
        """
        if self.subplots:
            if self.layout is not None and not is_list_like(self.ax):
                return self.axes.reshape(*self.layout)
            else:
                return self.axes
        else:
            sec_true = isinstance(self.secondary_y, bool) and self.secondary_y
            all_sec = (is_list_like(self.secondary_y) and
                       len(self.secondary_y) == self.nseries)
            if (sec_true or all_sec):
                # if all data is plotted on secondary, return right axes
                return self._get_ax_layer(self.axes[0], primary=False)
            else:
                return self.axes[0]

    def _compute_plot_data(self):
        data = self.data

        if isinstance(data, ABCSeries):