Newer
Older
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
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
import h5py
import matplotlib.pyplot as plt
import numpy as np
import sys
import re
import ast
from scipy.optimize import curve_fit
import os
from scipy import interpolate
# Solo levanto algunos experimentos
Calib_Files = """000004035-UV_Scan_withcalib_Haeffner
000004036-UV_Scan_withcalib_Haeffner
000004062-UV_Scan_withcalib_Haeffner
000004063-UV_Scan_withcalib_Haeffner
000004064-UV_Scan_withcalib_Haeffner
000004065-UV_Scan_withcalib_Haeffner
000004066-UV_Scan_withcalib_Haeffner
000004067-UV_Scan_withcalib_Haeffner
000004068-UV_Scan_withcalib_Haeffner
000004069-UV_Scan_withcalib_Haeffner
000004071-UV_Scan_withcalib_Haeffner
000004072-UV_Scan_withcalib_Haeffner
000004073-UV_Scan_withcalib_Haeffner
000004074-UV_Scan_withcalib_Haeffner
000004075-UV_Scan_withcalib_Haeffner
000004077-UV_Scan_withcalib_Haeffner
000004078-UV_Scan_withcalib_Haeffner
000004114-UV_Scan_withcalib_Haeffner
000004115-UV_Scan_withcalib_Haeffner
000004116-UV_Scan_withcalib_Haeffner
000004119-UV_Scan_withcalib_Haeffner
000004120-UV_Scan_withcalib_Haeffner
000004129-UV_Scan_withcalib_Haeffner
000004130-UV_Scan_withcalib_Haeffner
000004131-UV_Scan_withcalib_Haeffner
000004132-UV_Scan_withcalib_Haeffner
000004133-UV_Scan_withcalib_Haeffner
000004134-UV_Scan_withcalib_Haeffner"""
Calib_Files_1005 = """000004114-UV_Scan_withcalib_Haeffner
"""
#carpeta pc nico labo escritorio:
#C:\Users\Usuario\Documents\artiq\artiq_experiments\analisis\plots\20211004_EspectrosUV\Data
def SeeKeys(files):
for i, fname in enumerate(files.split()):
data = h5py.File(fname+'.h5', 'r') # Leo el h5: Recordar que nuestros datos estan en 'datasets'
print(fname)
print(list(data['datasets'].keys()))
#%%
Amps = []
Freqs = []
Counts = []
for i, fname in enumerate(Calib_Files.split()):
print(SeeKeys(Calib_Files))
print(i)
print(fname)
data = h5py.File(fname+'.h5', 'r') # Leo el h5: Recordar que nuestros datos estan en 'datasets'
print(list(data['datasets'].keys()))
Amps.append(np.array(data['datasets']['UV_Amplitudes']))
Freqs.append(np.array(data['datasets']['UV_Frequencies']))
Counts.append(np.array(data['datasets']['counts_spectrum']))
#%%
def Lorentzian(f, A, gamma, x0):
return (A/np.pi)*0.5*gamma/(((f-x0)**2)+((0.5*gamma)**2)) + 5
j = 17 #el 15 es lindo tambien
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
plt.figure()
#plt.plot([f - 225 for f in FreqsChosen], CountsChosen, 'o', label='2.4 uW')
plt.plot([f - 225 for f in FreqsChosen], CountsChosen, 'o')
plt.plot([f - 225 for f in freqslong], Lorentzian(freqslong, *popt), label='Lorentzian fit')
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
#plt.axvline(2*95-225, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz')
j = 18 #el 15 es lindo tambien
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
plt.plot(FreqsChosen, CountsChosen, 'o', label='1.1 uW')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*95, linestyle='--', linewidth=1, label='UV Cooling Freq')
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz')
#%%
def Lorentzian(f, A, gamma, x0):
return (A/np.pi)*0.5*gamma/(((f-x0)**2)+((0.5*gamma)**2)) + 0
j = 22
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*100, linestyle='--', linewidth=1, label='UV cooling freq')
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.title('Pot UV: 2.8 uW')
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz')
j = 23
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*105, linestyle='--', linewidth=1, label='UV cooling freq')
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.title('Pot UV: 2.8 uW')
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz')
j = 24
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*110, linestyle='--', linewidth=1, label='UV cooling freq')
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.title('Pot UV: 2.8 uW')
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz')
#%%
j = 25
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*110, linestyle='--', linewidth=1, label='UV cooling freq')
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.title('Pot UV: 2.8 uW, otra polarizacion')
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz')
j = 26
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*110, linestyle='--', linewidth=1, label='UV cooling freq')
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.title('Pot UV: 2.8 uW, otra polarizacion')
#plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz')
j = 27
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*110, linestyle='--', linewidth=1, label='UV cooling freq')
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.title('Pot UV: 2.8 uW, otra polarizacion')
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz')
#%% SIMULACION DE DOS CAMPANAS
dif = 20
amprand = 0.001
Suma = Lorentzian(np.array(FreqsChosen), 1, 23, 215) + amprand*(np.random.rand()-0.5) + Lorentzian(np.array(FreqsChosen), 1, 23, 215+dif) + amprand*(np.random.rand()-0.5)
popt, pcov = curve_fit(Lorentzian, FreqsChosen, Suma)
plt.figure()
plt.plot(FreqsChosen, Suma, 'o')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*105, linestyle='--', linewidth=1, label='UV cooling freq')
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.title('Pot UV: 2.8 uW')
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz')