import os
 import sys
 

 import holoviews
 import matplotlib.pyplot as plt
 import matplotlib.tri as mtri
 from PIL import Image, ImageDraw

 
 sys.path.insert(0, os.path.abspath(".."))  # to get adaptive on the path
 

 import adaptive  # noqa: E402, isort:skip

 
 holoviews.notebook_extension("matplotlib")

 
 
 def create_and_run_learner():
     def ring(xy):
         import numpy as np

         x, y = xy
         a = 0.2

         return x + np.exp(-((x ** 2 + y ** 2 - 0.75 ** 2) ** 2) / a ** 4)

 
     learner = adaptive.Learner2D(ring, bounds=[(-1, 1), (-1, 1)])
     adaptive.runner.simple(learner, goal=lambda l: l.loss() < 0.01)
     return learner
 
 
 def plot_learner_and_save(learner, fname):
     fig, ax = plt.subplots()

     tri = learner.interpolator(scaled=True).tri

     triang = mtri.Triangulation(*tri.points.T, triangles=tri.vertices)

     ax.triplot(triang, c="k", lw=0.8)

     ax.imshow(learner.plot().Image.I.data, extent=(-0.5, 0.5, -0.5, 0.5))
     ax.set_xticks([])
     ax.set_yticks([])
     plt.savefig(fname, bbox_inches="tight", transparent=True, dpi=300, pad_inches=-0.1)
 
 
 def add_rounded_corners(fname, rad):
     im = Image.open(fname)

     circle = Image.new("L", (rad * 2, rad * 2), 0)

     draw = ImageDraw.Draw(circle)
     draw.ellipse((0, 0, rad * 2, rad * 2), fill=255)

     alpha = Image.new("L", im.size, 255)

     w, h = im.size
     alpha.paste(circle.crop((0, 0, rad, rad)), (0, 0))
     alpha.paste(circle.crop((0, rad, rad, rad * 2)), (0, h - rad))
     alpha.paste(circle.crop((rad, 0, rad * 2, rad)), (w - rad, 0))
     alpha.paste(circle.crop((rad, rad, rad * 2, rad * 2)), (w - rad, h - rad))
     im.putalpha(alpha)
     return im
 
 

 if __name__ == "__main__":

     learner = create_and_run_learner()

     fname = "source/_static/logo_docs.png"

     plot_learner_and_save(learner, fname)
     im = add_rounded_corners(fname, rad=200)
     im.thumbnail((200, 200), Image.ANTIALIAS)  # resize
     im.save(fname)