"""Example to show bug in Polar plots with Log radial scale."""

import sys
import matplotlib.pyplot as plt
import matplotlib as mpl
import pandas as pd
import numpy as np

import matplotlib

print(f"Matplotlib version: {matplotlib._version.version}")
print(f"Python version: {sys.version}")


_freq = np.arange(100, 10000, 200)
_angle = np.arange(-180, 180, 5) / 57.29

freqs, angles = np.meshgrid(_freq, _angle)
vals = np.random.random(freqs.shape)


fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(111, projection="polar")

ax.set_rscale("log")
ax.set_rlim(200, 20000)

colormesh = ax.pcolormesh(angles, freqs, vals)


# Define a trivial format_coord
# without this function, we get an overflow when cursor hovers
# over axis.
def format_coord(x, y):
    return f"{x}, {y}"


ax.format_coord = format_coord


# Demonstrate the bug. Transform from data coordinates to graphics
# coordinates and then back. The radial value ends up with an
# extra factor of 10^(minimum value of r axis).
# This bug is located in:
# matplotlib.projections.polar.InvertedPolarTransform.transform_non_affine
# see workaround at bottom of this file for more info.

#                     ang, rval
x, r = test_coords = (0.1, 1000)
round_trip_x, round_trip_r = ax.transData.inverted().transform(
    ax.transData.transform(test_coords)
)

if np.isclose(round_trip_x, x):
    print("X value made it through scaling round trip")
else:
    print(f"X value did not make it through scaling was/is: {x}/{round_trip_x}")

if np.isclose(round_trip_r, r):
    print("Y value made it through scaling round trip")
else:
    print(f"Y value did not make it through scaling was/is: {r}/{round_trip_r}")


plt.show()