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

# Use this notebook to obtain "expected" values for 
# ```
# test_geom_imshow_alpha.py
# ```
# test suite.

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import numpy as np
from lets_plot import *

LetsPlot.setup_html()


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LetsPlot.set_theme(flavor_solarized_light())


# ### Greyscale image

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arr = np.array([
    [50, 150, 200],
    [200, 100, 50]
    ])


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ggplot() + geom_imshow(arr, alpha=.5)


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# 'norm' = False
ggplot() + geom_imshow(arr, norm=False, alpha=.5)


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# With NaN-s
arr_nan = np.array([
    [50., np.nan, 200.],
    [np.nan, 100., 50.]
    ])

ggplot() + geom_imshow(arr_nan, alpha=0.5)


# ### Alpha + cmap

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ggplot() + geom_imshow(arr, cmap="magma", alpha=0.5)


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# With NaN-s
arr_nan = np.array([
    [50., np.nan, 200.],
    [np.nan, 100., 50.]
    ])

ggplot() + geom_imshow(arr_nan, cmap="magma", alpha=0.5)


# ### Color image

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# RGB image

A2x3x3 = np.array([
    [[255, 0, 0], [0, 255, 0], [0, 0, 255]],
    [[0, 255, 0], [0, 0, 255], [255, 0, 0]]
    ])

ggplot() + geom_imshow(A2x3x3)


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ggplot() + geom_imshow(A2x3x3, alpha=0.5)


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# RGBA image (with alpha channel)

A2x3x4 = np.array([
    [[1, 0, 0, 1], [0, 1, 0, 1], [0, 0, 1, 1]],
    [[0, 1, 0, 0.3], [0, 0, 1, 0.3], [1, 0, 0, 0.3]]
    ])


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ggplot() + geom_imshow(A2x3x4)


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ggplot() + geom_imshow(A2x3x4, alpha=0.5)


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_.as_dict()


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