samadhi/visual_test.py at main · jkanev/samadhi · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125

import numpy as np
import matplotlib.pyplot as plt
import numpy as np

# Create sum of sine waves of different frequencies
dt = 0.005
t0 = np.arange(0, 5*np.pi, dt)
f = [(abs(np.sin(1*t0))),
     (abs(np.sin(2*t0))),
     (abs(np.sin(3*t0))),
     (abs(np.sin(4*t0))),
     (abs(np.sin(5*t0))),
     ((np.sin(2*t0)+1)*10.0)]

# Create 10 circles of different lengths
M = 40 # number of circles
N = 200 # points per circle
lines = [None] * M
ylim = 32
thickness = 0.5
ax = None
fig = None
freq_start = 1.0
freq_step = 0.005
r = [[]] * M  # the interpolated circle data, zeros for now, consisting of M*N circles s[M][1..5], all the same length
s = [[]] * M  # the raw circle data, zeros for now, consisting of M*N circles s[M][1..5]
t = [[]] * M  # the base to plot against, will go from 0 to 2pi, t[M]
for m in range(0, M):
    s[m] = [[]]*5
    freq = freq_start + m*freq_step  # our circle frequency
    print(freq)
    for n in range(0, 5):
        s[m][n] = np.zeros(int((2 / freq) * np.pi / dt))
    #t[m] = [m for m in np.arange(0, 2 * np.pi * (1 + 2 / len(s[m][0])), 2 * np.pi / (len(s[m][0])))[0:len(s[m][0])]]
    t[m] = [m for m in np.arange(0, 2 * np.pi*(1.0 + 1.0/N), 2 * np.pi / (N-1.0))]

# Average over all circles - pre-calculate parts of the sum of sines
for m in range(0, M):
    for n in range(0, 5):
        # only plot if you can fill the entire circle
        for i in range(0, (len(f[n]) // len(s[m][n])) * len(s[m][n])):
            value = f[n][i] - 0.5
            index = i % len(s[m][n])
            s[m][n][index] += value  # add to front
            s[m][n][-(index + 1)] += value  # add to back, so beginning and end match and the circle stays closed

# downsample so all circles have the same length (N samples)
for m in range(0, M):
    r[m] = [[]]*5
    for n in range(0, 5):
        r[m][n] = np.zeros(N)
        for i in range(0, N-1):
            index = int(float(i)*(len(s[m][n])-1)/(N-1.0))
            r[m][n][i] = s[m][n][index]
        r[m][n][N-1] = s[m][n][0]    # close the circle

first = True
s = 0    # index into speed vector
p = 0.0
q = 1.0
k = 0
for f0 in np.arange(0, 1000, 0.01):
    c1 = np.square(np.sin(2*f0))
    c2 = np.square(np.sin(3*f0))
    c3 = np.square(np.sin(4*f0))
    c4 = np.square(np.sin(5*f0))
    c5 = np.square(np.sin(6*f0))
    norm = c1 + c2 + c3 + c4 + c5
    print("Frequency bands: {:.2f}, {:.2f}, {:.2f}, {:.2f}, {:.2f}".format(c1, c2, c3, c4, c5), end='\r')

    # initialise plot if we're here for first time
    if first:
        #plt.plot(t[0], s[0][0])
        fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
        ax.grid(False)
        ax.set_xticks([])
        ax.set_yticks([])
        ax.set_theta_zero_location("N")
        ax.set_ylim(0.0, ylim)
        ax.set_facecolor('k')
        fig.set_facecolor('k')
        fig.canvas.toolbar.pack_forget()
        plt.subplots_adjust(top=1, bottom=0)
        manager = plt.get_current_fig_manager()
        manager.full_screen_toggle()
        plt.show(block=False)

    # plot curves
    last_data = []
    for m in range(0, M):
        #offset = np.sqrt((M-m))
        offset = M-m
        offset = np.sqrt(np.sqrt(offset*offset*offset))  # x^(3/4)
        data = c1 * np.roll(r[m][0], k) + c2 * np.roll(r[m][1], 0) + c3 * np.roll(r[m][2], -k) + c4 * np.roll(r[m][3], 0) + c5 * np.roll(r[m][4], k) + 1
        data /= data.max()
        data *= offset
        data += offset
        if first:
            try:
                if len(last_data):
                    [lines[m]] = ax.plot(t[m], p*last_data + q*data, '.', linewidth=thickness, color=(m/M, 0.5*m/M, 1-m/M))
            except BaseException as e:
                print("Plot exception {} for curve n={}".format(e, m))
        else:
            try:
                if len(last_data):
                    lines[m].set_ydata(p*last_data + q*data)
                    if m == 1:
                        lines[m].set_color((c1*q*m/M, c2*q*0.5*m/M, (1.0 - 0.5*c3)*q*(1 - m/M)))
                    elif m == M-1:
                        lines[m].set_color((c1*p*m/M, c2*p*0.5*m/M, (1.0 - 0.5*c3)*p*(1 - m/M)))
                    else:
                        lines[m].set_color((c1*m/M, c2*0.5*m/M, (1.0 - 0.5*c3)*(1-m/M)))
            except BaseException as e:
                print("Plot exception {} for curve n={}".format(e, m))
        last_data = data
    plt.pause(0.001)
    first = False
    s += 1
    if s > len(f[5]):
        s = 0
    p = f[5][s] % 1
    q = 1.0 - p
    k += 1