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63 lines
1.6 KiB
Python
63 lines
1.6 KiB
Python
import numpy as np
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import matplotlib
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import matplotlib.pyplot as plt
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lookup_tables_u16 = []
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lookup_tables_u8 = []
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ADC_RESOLUTION = 4096
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OUTPUT_RESOLUTION = 2 ** 16 - 1
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# linear to exponential conversion
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space = np.linspace(0, 1, num=ADC_RESOLUTION)
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values = np.power(space, 2) * OUTPUT_RESOLUTION
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lookup_tables_u16.append(('linear_to_exp', values))
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print(values.size)
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fig, ax = plt.subplots()
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ax.plot(space, values)
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other_values = OUTPUT_RESOLUTION - np.flip(values)
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ax.plot(space, OUTPUT_RESOLUTION - (np.flip(values)))
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ax.set(xlabel='space', ylabel='values')
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ax.grid()
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#plt.show()
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# Left pan Lookup table
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space = np.linspace(0, (np.pi / 2.0), num=ADC_RESOLUTION)
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l_pan = np.sqrt(space * (2.0 / np.pi) * np.sin(space))
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r_pan = np.sqrt(((np.pi / 2.0) - space) * (2.0 / np.pi) * np.cos(space))
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l_pan = np.floor(l_pan * OUTPUT_RESOLUTION)
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r_pan = np.floor(r_pan * OUTPUT_RESOLUTION)
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fig, ax = plt.subplots()
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ax.plot(space, l_pan)
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ax.plot(space, r_pan)
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ax.set(xlabel='space', ylabel='values')
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ax.grid()
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#plt.show()
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lookup_tables_u16.append(('left_sin_pan', l_pan))
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print(l_pan.size)
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lookup_tables_u16.append(('right_cos_pan', r_pan))
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print(r_pan.size)
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# led gamma correction
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gamma_green = 2.4
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gamma_red = 2.8
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max_in = 4095
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max_out = 65535
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input_vals = np.linspace(0, max_in, num=max_in + 1)
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gamma_correction_red = ((input_vals / max_in) ** gamma_red) * max_out + 0.5
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gamma_correction_green = ((input_vals / max_in) ** gamma_green) * max_out + 0.5
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lookup_tables_u16.append(('led_red_gamma', np.floor(gamma_correction_red)))
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lookup_tables_u16.append(('led_green_gamma', np.floor(gamma_correction_green)))
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