Code for a complex radar plot

complex_radar_plot.py

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns # improves plot aesthetics

def _invert(x, limits):
    """inverts a value x on a scale from
    limits[0] to limits[1]"""
    return limits[1] - (x - limits[0])

def _scale_data(data, ranges):
    """scales data[1:] to ranges[0],
    inverts if the scale is reversed"""
    for d, (y1, y2) in zip(data[1:], ranges[1:]):
        assert (y1 <= d <= y2) or (y2 <= d <= y1)
    x1, x2 = ranges[0]
    d = data[0]
    if x1 > x2:
        d = _invert(d, (x1, x2))
        x1, x2 = x2, x1
    sdata = [d]
    for d, (y1, y2) in zip(data[1:], ranges[1:]):
        if y1 > y2:
            d = _invert(d, (y1, y2))
            y1, y2 = y2, y1
        sdata.append((d-y1) / (y2-y1) 
                     * (x2 - x1) + x1)
    return sdata

class ComplexRadar():
    def __init__(self, fig, variables, ranges,
                 n_ordinate_levels=6):
        angles = np.arange(0, 360, 360./len(variables))
        
        axes = [fig.add_axes([0.1,0.1,0.9,0.9],polar=True,
                label = "axes{}".format(i)) 
                for i in range(len(variables))]
        l, text = axes[0].set_thetagrids(angles, 
                                         labels=variables)
        [txt.set_rotation(angle-90) for txt, angle 
             in zip(text, angles)]
        for ax in axes[1:]:
            ax.patch.set_visible(False)
            ax.grid("off")
            ax.xaxis.set_visible(False)
        for i, ax in enumerate(axes):
            grid = np.linspace(*ranges[i], 
                               num=n_ordinate_levels)
            gridlabel = ["{}".format(round(x,2)) 
                         for x in grid]
            if ranges[i][0] > ranges[i][1]:
                grid = grid[::-1] # hack to invert grid
                          # gridlabels aren't reversed
            gridlabel[0] = "" # clean up origin
            ax.set_rgrids(grid, labels=gridlabel,
                         angle=angles[i])
            #ax.spines["polar"].set_visible(False)
            ax.set_ylim(*ranges[i])
        # variables for plotting
        self.angle = np.deg2rad(np.r_[angles, angles[0]])
        self.ranges = ranges
        self.ax = axes[0]
    def plot(self, data, *args, **kw):
        sdata = _scale_data(data, self.ranges)
        self.ax.plot(self.angle, np.r_[sdata, sdata[0]], *args, **kw)
    def fill(self, data, *args, **kw):
        sdata = _scale_data(data, self.ranges)
        self.ax.fill(self.angle, np.r_[sdata, sdata[0]], *args, **kw)


if __name__ == "__main__":
    # example data
    variables = ("Normal Scale", "Inverted Scale", "Inverted 2", 
                "Normal Scale 2", "Normal 3", "Normal 4 %", "Inverted 3 %")
    data = (1.76, 1.1, 1.2, 
            4.4, 3.4, 86.8, 20)
    ranges = [(0.1, 2.3), (1.5, 0.3), (1.3, 0.5),
            (1.7, 4.5), (1.5, 3.7), (70, 87), (100, 10)]
            
    # plotting
    fig1 = plt.figure(figsize=(6, 6))
    radar = ComplexRadar(fig1, variables, ranges)
    radar.plot(data)
    radar.fill(data, alpha=0.2)
    plt.show()

@amarruedo797 I had the same problem and for me, removing the lines 50 and 51 did the trick. I'm not 100% sure why that is the case, but I'm guessing newer matplotlib versions recognize when the ticks are reversed and do it automatically for the grid as well, so we're rereversing them with that line.

@w-t-effi Thanks ! That solved my issue of not getting the axes inverted .