#!/usr/bin/env python
# encoding: utf-8

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.path import Path
from matplotlib.spines import Spine
from matplotlib.projections.polar import PolarAxes
from matplotlib.projections import register_projection
plt.style.use('ggplot')

def _radar_factory(num_vars):
    theta = 2*np.pi * np.linspace(0, 1-1./num_vars, num_vars)
    theta += np.pi/2

    def unit_poly_verts(theta):
        x0, y0, r = [0.5] * 3
        verts = [(r*np.cos(t) + x0, r*np.sin(t) + y0) for t in theta]
        return verts

    class RadarAxes(PolarAxes):
        name = 'radar'
        RESOLUTION = 1

        def fill(self, *args, **kwargs):
            closed = kwargs.pop('closed', True)
            return super(RadarAxes, self).fill(closed=closed, *args, **kwargs)

        def plot(self, *args, **kwargs):
            lines = super(RadarAxes, self).plot(*args, **kwargs)
            for line in lines:
                self._close_line(line)

        def _close_line(self, line):
            x, y = line.get_data()
            # FIXME: markers at x[0], y[0] get doubled-up
            if x[0] != x[-1]:
                x = np.concatenate((x, [x[0]]))
                y = np.concatenate((y, [y[0]]))
                line.set_data(x, y)

        def set_varlabels(self, labels):
            self.set_thetagrids(theta * 180/np.pi, labels)

        def _gen_axes_patch(self):
            verts = unit_poly_verts(theta)
            return plt.Polygon(verts, closed=True, edgecolor='k')

        def _gen_axes_spines(self):
            spine_type = 'circle'
            verts = unit_poly_verts(theta)
            verts.append(verts[0])
            path = Path(verts)
            spine = Spine(self, spine_type, path)
            spine.set_transform(self.transAxes)
            return {'polar': spine}

    register_projection(RadarAxes)
    return theta

def radar_graph(labels = [], values = [], optimum = []):
    N = len(labels) 
    theta = _radar_factory(N)
    max_val = max(max(optimum), max(values))

    fig = plt.figure(figsize=(3,3))
    ax = fig.add_subplot(1, 1, 1, projection='radar')

    ax.plot(theta, values, color='k')
    ax.plot(theta, optimum, color='r')
    ax.set_varlabels(labels)
    return fig, ax

def my_autopct(values):
    def my_autopct(pct):
        total = sum(values)
        val = int(round(pct*total/100.0))
        return f'{val}'
    return my_autopct

def pivot_table_to_pie(pv, pies_per_lines = 3):
    nbr_pies = len(pv.columns)
    nbr_cols = min(pies_per_lines, nbr_pies)
    nbr_rows = max(nbr_pies % nbr_cols,1)
    f, axs = plt.subplots(nbr_rows, nbr_cols, figsize = (4*nbr_cols,4*nbr_rows))
    for (c, ax) in zip(pv, axs.flatten()):
        datas = pv[c]
        explode = [0.1]*len(datas)
        pv[c].plot(kind="pie",
                             ax=ax,
                             use_index = False,
                             title = f"{c} (total={datas.sum()})",
                             legend = False,
                             autopct=my_autopct(datas),
                             explode = explode,
                            )
        ax.set_ylabel("")
    for i in range(nbr_pies//nbr_cols, nbr_cols*nbr_rows):
        axs.flat[i].axis("off")
    return (f, axs)

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