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21.09

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xaver
2020-09-21 20:12:16 +02:00
parent 042bdd7aa3
commit f1b7291ecf
4 changed files with 204 additions and 23 deletions
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64
apteronotus_code/sin_all_normal.py Normal file
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import matplotlib.pyplot as plt
import numpy as np
import pylab
from IPython import embed
from scipy.optimize import curve_fit
from jar_functions import gain_curve_fit
from jar_functions import avgNestedLists
identifier = [#'2018lepto1',
#'2018lepto4',
#'2018lepto5',
#'2018lepto76',
'2018lepto98',
'2019lepto03',
#'2019lepto24',
#'2019lepto27',
#'2019lepto30',
#'2020lepto04',
#'2020lepto06',
'2020lepto16',
'2020lepto19',
'2020lepto20'
]
tau = []
f_c = []
for ID in identifier:
print(ID)
amf = np.load('5Hz_amf_%s.npy' %ID)
gain = np.load('5Hz_gain_%s.npy' %ID)
sinv, sinc = curve_fit(gain_curve_fit, amf, gain)
#print('tau:', sinv[0])
tau.append(sinv[0])
f_cutoff = abs(1 / (2*np.pi*sinv[0]))
print('f_cutoff:', f_cutoff)
f_c.append(f_cutoff)
amf = [0.001, 0.002, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1]
all = []
for ident in identifier:
data = np.load('5Hz_gain_%s.npy' %ident)
all.append(data)
av = avgNestedLists(all)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(amf, av, 'o')
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_title('gaincurve_average_allfish_5Hz')
ax.set_ylabel('gain [Hz/(mV/cm)]')
ax.set_xlabel('envelope_frequency [Hz]')
ax.set_ylim(0.0008, )
ax.plot(f_c, np.full((len(identifier)), 0.0015), 'o', label = 'cutoff frequencies')
ax.legend()
plt.show()
embed()

97
apteronotus_code/sin_all_uniform.py Normal file
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import matplotlib.pyplot as plt
import numpy as np
import pylab
from IPython import embed
from scipy.optimize import curve_fit
from jar_functions import gain_curve_fit
from jar_functions import avgNestedLists
identifier_uniform = ['2018lepto1',
# '2018lepto4',
# '2018lepto5',
#'2018lepto76',
'2018lepto98',
# '2019lepto03',
'2019lepto24',
#'2019lepto27',
# '2019lepto30',
'2020lepto04',
# '2020lepto06',
# '2020lepto16',
'2020lepto19',
# '2020lepto20'
]
identifier = ['2018lepto1',
'2018lepto4',
'2018lepto5',
'2018lepto76',
'2018lepto98',
'2019lepto03',
'2019lepto24',
'2019lepto27',
'2019lepto30',
'2020lepto04',
'2020lepto06',
'2020lepto16',
'2020lepto19',
'2020lepto20'
]
tau = []
f_c = []
for ID in identifier:
print(ID)
amf = np.load('amf_%s.npy' %ID)
gain = np.load('gain_%s.npy' %ID)
sinv, sinc = curve_fit(gain_curve_fit, amf, gain)
#print('tau:', sinv[0])
tau.append(sinv[0])
f_cutoff = abs(1 / (2*np.pi*sinv[0]))
print('f_cutoff:', f_cutoff)
f_c.append(f_cutoff)
tau_uniform = []
f_c_uniform = []
for ID in identifier_uniform:
#print(ID)
amf = np.load('amf_%s.npy' %ID)
gain = np.load('gain_%s.npy' %ID)
sinv, sinc = curve_fit(gain_curve_fit, amf, gain)
#print('tau:', sinv[0])
tau_uniform.append(sinv[0])
f_cutoff = abs(1 / (2*np.pi*sinv[0]))
#print('f_cutoff:', f_cutoff)
f_c_uniform.append(f_cutoff)
amf = [0.001, 0.002, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1]
all = []
new_all = []
for ident in identifier:
data = np.load('gain_%s.npy' %ident)
all.append(data)
for ident in identifier_uniform:
data = np.load('gain_%s.npy' % ident)
new_all.append(data)
av = avgNestedLists(all)
new_av = avgNestedLists(new_all)
lim = 0.001
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(amf, av, 'o', color = 'orange', label = 'normal')
ax.plot(amf, new_av, 'o', color = 'blue', label = 'uniformed')
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_title('gaincurve_average_allfish')
ax.set_ylabel('gain [Hz/(mV/cm)]')
ax.set_xlabel('envelope_frequency [Hz]')
ax.set_ylim(0.0008, )
ax.plot(f_c, np.full((len(identifier)), 0.0015), 'o', color = 'orange', label = 'all cutoff frequencies')
ax.plot(f_c_uniform, np.full((len(identifier_uniform)), 0.001), 'o', color = 'blue', label = 'uniformed cutoff frequencies')
ax.legend()
plt.show()
embed()