import matplotlib.pyplot as plt
from database import DataBaseLoad
import processing
import os
import numpy as np

# 1) Connect to the database
mydb_filename = os.path.abspath('../database.db')
mydb = DataBaseLoad(mydb_filename)
# 2) Define the position-orinetation at which
# we want the image
rowid = 5000
my_scene = processing.scene(mydb, rowid=rowid)
my_apcv = processing.apcv(my_scene, mydb.viewing_directions)

my_apcv_sph = processing.tools.cartesian_to_spherical(x=my_apcv[..., 0],
                                                      y=my_apcv[..., 1],
                                                      z=my_apcv[..., 2])
elevation = mydb.viewing_directions[...,
                                    processing.constants.__spherical_indeces__[
                                        'elevation']]
azimuth = mydb.viewing_directions[...,
                                  processing.constants.__spherical_indeces__[
                                      'azimuth']]


f, axarr = plt.subplots(1, 2, figsize=(15, 4))

to_plot_im = my_scene[:, :, :3, 0]
to_plot_im -= to_plot_im.min()
to_plot_im /= to_plot_im.max()
to_plot_im = to_plot_im * 255
to_plot_im = to_plot_im.astype(np.uint8)
to_plot_dist = my_scene[:, :, 3, 0]
ax = axarr[0]

for chan_i, chan_n in enumerate(['R', 'G', 'B']):
    color = chan_n
    ax.plot(np.rad2deg(my_apcv_sph[..., chan_i, 1]),
            np.rad2deg(my_apcv_sph[..., chan_i, 0]), 'o', color=color)
ax.imshow(to_plot_im, extent=[np.min(azimuth), np.max(azimuth),
                              np.max(elevation), np.min(elevation)])
ax.invert_yaxis()
ax = axarr[1]
color = 'k'
ax.plot(np.rad2deg(my_apcv_sph[..., 3, 1]),
        np.rad2deg(my_apcv_sph[..., 3, 0]), 'o', color=color)

ax.imshow(to_plot_dist, extent=[np.min(azimuth), np.max(azimuth),
                                np.max(elevation), np.min(elevation)])
ax.invert_yaxis()

f.show()