measurement data transfer

This commit is contained in:
schoener 2022-09-06 11:57:32 +02:00
parent 18855417b9
commit 688e9b7666
16 changed files with 241 additions and 4 deletions

0
Data.txt Normal file
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@ -0,0 +1,55 @@
-3.23 9.68 9.68
0.0 12.9 6.45
0.0 9.68 6.45
3.23 12.9 6.45
6.45 9.68 9.68
0.0 3.23 3.23
0.0 6.45 6.45
0.0 3.23 6.45
0.0 3.23 6.45
0.0 6.45 6.45
0.0 -6.45 6.45
0.0 -3.23 6.45
0.0 -6.45 6.45
0.0 -6.45 6.45
3.23 -3.23 6.45
0.0 -12.9 9.68
0.0 -16.13 6.45
0.0 -12.9 9.68
0.0 -9.68 6.45
-3.23 -12.9 9.68
0.0 -19.35 9.68
0.0 -19.35 9.68
0.0 -22.58 6.45
0.0 -19.35 6.45
0.0 -19.35 6.45
0.0 -29.03 6.45
0.0 -29.03 6.45
-3.23 -29.03 6.45
0.0 -32.26 9.68
-3.23 -29.03 9.68
0.0 -35.48 6.45
0.0 -38.71 9.68
0.0 -38.71 6.45
-3.23 -38.71 6.45
0.0 -35.48 6.45
0.0 -45.16 6.45
0.0 -45.16 9.68
-3.23 -45.16 6.45
0.0 -45.16 6.45
-3.23 -45.16 6.45
0.0 -51.61 6.45
-3.23 -51.61 9.68
-3.23 -51.61 6.45
-3.23 -54.84 6.45
-3.23 -51.61 6.45
-3.23 -61.29 9.68
-3.23 -61.29 6.45
0.0 -58.06 9.68
-3.23 -64.52 9.68
-3.23 -61.29 9.68
0.0 -67.74 9.68
-3.23 -70.97 9.68
-3.23 -67.74 16.13
-3.23 -70.97 6.45
-3.23 -70.97 9.68

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@ -14,4 +14,14 @@ HH_Coil.set_d_min(47.4)
HH_Coil.print_info()
HH_Coil.max_field_one_coil(5)
HH_Coil.max_field_one_coil(5)
# %%
#By_cal = np.array([9.68, 12.9, 9.68, 12.9, 9.68, 3.23, 6.45, 3.23, 3.23, 6.45, -6.45, -3.23, -6.45, -6.45, -3.23, -12.9, -16.13, -12.9, -9.68, -12.9, -19.35, -19.35, -22.58, -19.35, -19.35, -29.03, -29.03, -29.03, -32.26, -29.03, -35.48, -38.71, -38.71, -38.71, -35.48, -45.16, -45.16, -45.16, -45.16, -45.16, -51.61, -51.61, -51.61, -54.84, -51.61, -61.29, -61.29, -58.06, -64.52, -61.29, -67.74, -70.97, -67.74, -70.97, -70.97])
#np.save('Data/By_cal.npy',By_cal)
# %%
B = np.load('Data/Bz_AHH.npy')
print(B)
print(len(B))

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@ -0,0 +1,55 @@
0.0 9.68 6.45
0.0 12.9 6.45
-3.23 9.68 6.45
0.0 12.9 6.45
0.0 9.68 6.45
3.23 19.35 6.45
0.0 19.35 6.45
3.23 19.35 3.23
0.0 19.35 3.23
0.0 19.35 6.45
0.0 29.03 3.23
0.0 25.81 3.23
0.0 25.81 6.45
0.0 25.81 6.45
0.0 25.81 6.45
3.23 35.48 9.68
0.0 32.26 3.23
0.0 35.48 6.45
3.23 35.48 6.45
0.0 35.48 6.45
0.0 45.16 3.23
0.0 45.16 3.23
0.0 41.94 3.23
0.0 45.16 3.23
0.0 41.94 3.23
0.0 51.61 3.23
0.0 51.61 6.45
0.0 51.61 3.23
0.0 48.39 3.23
3.23 48.39 3.23
3.23 58.06 3.23
0.0 58.06 3.23
0.0 61.29 3.23
0.0 61.29 3.23
0.0 58.06 3.23
0.0 67.74 3.23
3.23 67.74 6.45
3.23 67.74 3.23
0.0 67.74 3.23
0.0 67.74 3.23
0.0 74.19 3.23
0.0 77.42 6.45
3.23 74.19 3.23
0.0 74.19 3.23
3.23 74.19 6.45
0.0 83.87 3.23
0.0 87.1 0.0
0.0 80.65 3.23
3.23 87.1 3.23
3.23 83.87 3.23
0.0 93.55 0.0
6.45 93.55 3.23
0.0 90.32 0.0
0.0 93.55 3.23
3.23 90.32 3.23

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@ -0,0 +1,55 @@
0.0 9.68 6.45
0.0 9.68 6.45
0.0 12.9 3.23
0.0 9.68 6.45
3.23 9.68 6.45
3.23 3.23 6.45
0.0 0.0 6.45
0.0 0.0 6.45
0.0 0.0 6.45
0.0 3.23 6.45
0.0 -9.68 9.68
0.0 -9.68 6.45
0.0 -12.9 6.45
0.0 -9.68 6.45
0.0 -9.68 9.68
0.0 -22.58 9.68
-3.23 -22.58 6.45
0.0 -22.58 6.45
0.0 -19.35 6.45
0.0 -22.58 6.45
-3.23 -32.26 6.45
0.0 -32.26 6.45
-3.23 -32.26 6.45
0.0 -32.26 6.45
0.0 -32.26 6.45
-3.23 -41.94 9.68
-3.23 -41.94 6.45
-3.23 -45.16 6.45
0.0 -45.16 6.45
-3.23 -45.16 6.45
0.0 -54.84 9.68
-3.23 -54.84 6.45
-3.23 -51.61 9.68
-3.23 -58.06 9.68
-3.23 -51.61 6.45
0.0 -64.52 9.68
-3.23 -64.52 6.45
-3.23 -64.52 9.68
0.0 -61.29 9.68
-3.23 -64.52 9.68
0.0 -74.19 9.68
-3.23 -74.19 12.9
-3.23 -74.19 9.68
0.0 -77.42 6.45
3.23 -74.19 9.68
0.0 -87.1 12.9
-3.23 -87.1 9.68
-3.23 -87.1 9.68
0.0 -83.87 9.68
0.0 -83.87 12.9
-3.23 -96.77 9.68
-3.23 -96.77 9.68
-3.23 -96.77 9.68
-3.23 -96.77 9.68
-3.23 -96.77 9.68

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@ -0,0 +1,55 @@
0.0 12.9 6.45
0.0 12.9 6.45
0.0 9.68 6.45
3.23 12.9 6.45
0.0 12.9 6.45
3.23 22.58 6.45
0.0 22.58 6.45
0.0 19.35 3.23
0.0 22.58 6.45
0.0 22.58 6.45
0.0 35.48 6.45
0.0 32.26 3.23
0.0 32.26 6.45
0.0 32.26 3.23
0.0 32.26 3.23
0.0 41.94 3.23
0.0 41.94 3.23
0.0 41.94 3.23
3.23 45.16 6.45
0.0 41.94 9.68
0.0 54.84 3.23
0.0 54.84 3.23
0.0 54.84 3.23
0.0 54.84 3.23
0.0 51.61 3.23
3.23 67.74 6.45
3.23 64.52 3.23
0.0 64.52 6.45
0.0 64.52 3.23
3.23 64.52 3.23
3.23 77.42 3.23
3.23 77.42 3.23
3.23 74.19 3.23
0.0 77.42 9.68
3.23 80.65 6.45
0.0 87.1 3.23
3.23 87.1 3.23
3.23 87.1 0.0
0.0 87.1 0.0
0.0 87.1 3.23
3.23 96.77 0.0
3.23 96.77 3.23
3.23 100.0 6.45
0.0 96.77 3.23
3.23 96.77 3.23
3.23 112.9 3.23
3.23 109.68 3.23
3.23 109.68 3.23
0.0 109.68 0.0
6.45 109.68 3.23
3.23 119.35 3.23
0.0 119.35 0.0
3.23 122.58 0.0
3.23 119.35 3.23
3.23 116.13 0.0

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@ -1,19 +1,24 @@
import serial
import re
import matplotlib.pyplot as plt
import numpy as np
#connect to device, check if correct port
ser =serial.Serial('COM4',19200)
ser =serial.Serial('COM3',19200)
if not ser.isOpen():
ser.open()
print('com3 is open', ser.isOpen())
Bx=[]
By=[]
Bz=[]
x=[]
i=0
f=open('Data.txt','w')
f=open('Data/Cal_neg.txt','w')
fig, axs=plt.subplots(1,3)
#plug in number of measurement points (here 35)
#save all data in a txt sheet
for k in range(0,10):
for k in range(0, 55 ):
a=ser.readline()
data=str(a,'utf-8')
@ -44,3 +49,5 @@ axs[2].set_title('Bz')
axs[2].set(ylabel='G')
print(By)
plt.show()
np.save('Data/By_cal_neg.npy', By)