出力されたデータをcsvファイルに書き込みたい

前提・実現したいこと

mindwave mobile2 で取得したデータをリアルタイムでグラフ化しました。その値をcsvファイルに保存したいのですが画像のようになってうまくいきません。
attentionの列もしくは行
meditationの列もしくは行
といったように各列か行に１種類のデータを書き込みたいです。
data = の部分に配列を多く書き込みすぎているとは思うのですが良い解決方法が浮かばず、調べても分からなかったので質問させていただきました。

該当のソースコード

python
1
2import thinkgear
3import re
4import matplotlib.pyplot as plt
5import numpy as np
6import csv
7
8PORT = '/dev/tty.MindWaveMobile-SerialPo'
9
10attention_array = np.zeros(100)
11meditation_array = np.zeros(100)
12
13delta_array = np.zeros(100)
14theta_array = np.zeros(100)
15lowalpha_array = np.zeros(100)
16highalpha_array = np.zeros(100)
17lowbeta_array = np.zeros(100)
18highbeta_array = np.zeros(100)
19lowgamma_array = np.zeros(100)
20midgamma_array = np.zeros(100)
21
22#fig = plt.figure()
23
24def Plot(attention_array, meditation_array, delta_array, theta_array, lowalpha_array, highalpha_array, lowbeta_array, highbeta_array, lowgamma_array, midgamma_array):
25    plt.subplot(5,2,1)
26    line, = plt.plot(attention_array, color = 'red')
27    plt.ylabel("Attention")
28
29    plt.subplot(5,2,2)
30    line2, = plt.plot(meditation_array, color = 'blue')
31    plt.ylabel("Meditation")
32
33    plt.subplot(5,2,3)
34    line3, = plt.plot(delta_array, color = 'black')
35    plt.ylabel("Delta")
36
37    plt.subplot(5,2,4)
38    line4, = plt.plot(theta_array, color = 'deeppink')
39    plt.ylabel("Theta")
40
41    plt.subplot(5,2,5)
42    line5, = plt.plot(lowalpha_array, color = 'orange')
43    plt.ylabel("Lowalpha")
44
45    plt.subplot(5,2,6)
46    line6, = plt.plot(highalpha_array, color = 'red')
47    plt.ylabel("Highalpha")
48
49    plt.subplot(5,2,7)
50    line7, = plt.plot(lowbeta_array, color = 'royalblue')
51    plt.ylabel("Lowbeta")
52
53    plt.subplot(5,2,8)
54    line8, = plt.plot(highbeta_array, color = 'blue')
55    plt.ylabel("Highbeta")
56
57    plt.subplot(5,2,9)
58    line9, = plt.plot(lowgamma_array, color = 'lime')
59    plt.ylabel("Lowgamma")
60
61    plt.subplot(5,2,10)
62    line10, = plt.plot(midgamma_array, color = 'green')
63    plt.ylabel("Midgamma")
64
65    plt.pause(0.01)
66    line.remove()
67    line2.remove()
68    line3.remove()
69    line4.remove()
70    line5.remove()
71    line6.remove()
72    line7.remove()
73    line8.remove()
74    line9.remove()
75    line10.remove()
76
77for packets in thinkgear.ThinkGearProtocol(PORT).get_packets():
78    for p in packets:
79
80        if isinstance(p, thinkgear.ThinkGearRawWaveData):
81                continue
82
83        t = str(p)
84        if t != '':
85            differencer = t[0:1] 
86            if int(differencer) == 2:
87                attention = t[1:]  
88                attention_array = np.append(attention_array, attention)
89                attention_array = attention_array[1:101]
90            elif int(differencer) == 3:
91                meditation = t[1:]
92                meditation_array = np.append(meditation_array, meditation)
93                meditation_array = meditation_array[1:101]
94
95        
96        
97        if isinstance(p, thinkgear.ThinkGearEEGPowerData):
98            buf = str(p)
99
100            idx_d0 = buf.find("delta=")
101            buf2 = buf[idx_d0+6:]
102            idx_d1 = buf2.find(",")
103
104            idx_d2 = buf.find("theta=")
105            buf3 = buf[idx_d2+6:]
106            idx_d2 = buf3.find(",")
107
108            idx_d3 = buf.find("lowalpha=")
109            buf4 = buf[idx_d3+9:]
110            idx_d3 = buf4.find(",")
111
112            idx_d4 = buf.find("highalpha=")
113            buf5 = buf[idx_d4+10:]
114            idx_d4 = buf5.find(",")
115
116            idx_d5 = buf.find("lowbeta=")
117            buf6 = buf[idx_d5+8:]
118            idx_d5 = buf6.find(",")
119
120            idx_d6 = buf.find("highbeta=")
121            buf7 = buf[idx_d6+9:]
122            idx_d6 = buf7.find(",")
123
124            idx_d7 = buf.find("lowgamma=")
125            buf8 = buf[idx_d7+9:]
126            idx_d7 = buf8.find(",")
127
128            idx_d8 = buf.find("midgamma=")
129            buf9 = buf[idx_d8+9:]
130            idx_d8 = buf9.find(")")
131            
132
133            delta = int(buf2[:idx_d1])
134            theta = int(buf3[:idx_d2])
135            lowalpha = int(buf4[:idx_d3])
136            highalpha = int(buf5[:idx_d4])
137            lowbeta = int(buf6[:idx_d5])
138            highbeta = int(buf7[:idx_d6])
139            lowgamma = int(buf8[:idx_d7])
140            midgamma = int(buf9[:idx_d8])
141
142            delta_array = np.append(delta_array, delta)
143            delta_array = delta_array[1:101]
144            
145            theta_array = np.append(theta_array, theta)
146            theta_array = theta_array[1:101]
147            
148            lowalpha_array = np.append(lowalpha_array, lowalpha)
149            lowalpha_array = lowalpha_array[1:101]
150            
151            highalpha_array = np.append(highalpha_array, highalpha)
152            highalpha_array = highalpha_array[1:101]
153            
154            lowbeta_array = np.append(lowbeta_array, lowbeta)
155            lowbeta_array = lowbeta_array[1:101]
156            
157            highbeta_array = np.append(highbeta_array, highbeta)
158            highbeta_array = highbeta_array[1:101]
159            
160            lowgamma_array = np.append(lowgamma_array, lowgamma)
161            lowgamma_array = lowgamma_array[1:101]
162            
163            midgamma_array = np.append(midgamma_array, midgamma)
164            midgamma_array = midgamma_array[1:101]
165
166        data = [[attention_array], [meditation_array], [delta_array], [theta_array], [lowalpha_array], [highalpha_array], [lowbeta_array], [highbeta_array], [lowgamma_array], [midgamma_array]]
167        with open('test.csv', 'w') as file:
168            writer = csv.writer(file, lineterminator = '\n')
169            writer.writerows(data)
170
171        
172        Plot(attention_array, meditation_array, delta_array, theta_array, lowalpha_array, highalpha_array, lowbeta_array, highbeta_array, lowgamma_array, midgamma_array)
173
174
175
176

行動規範の内容に同意します

回答1件

ベストアンサー

python
1        data = [[attention_array], [meditation_array], [delta_array], [theta_array], [lowalpha_array], [highalpha_array], [lowbeta_array], [highbeta_array], [lowgamma_array], [midgamma_array]]

を

python
1        data = [list(attention_array), list(meditation_array), list(delta_array), list(theta_array), list(lowalpha_array), list(highalpha_array), list(lowbeta_array), list(highbeta_array), list(lowgamma_array), list(midgamma_array)]