ralf/Calcium_Model
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debugging of fitter, many issues still persist

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ralf 2024-07-11 13:05:32 +03:00
parent 6e7a727b1a
commit 7cf6590f94
1 changed files with 76 additions and 72 deletions
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fitter.py
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@ -6,7 +6,8 @@ import re
from scipy.optimize import least_squares from scipy.optimize import least_squares
from model import Model from scipy.linalg import svd
from Model import Model
from Data import Data from Data import Data
@ -81,7 +82,7 @@ class Fitter:
plt.show() plt.show()
# exit() # exit()
return res # , measured_fluo - calculated_fluo) return res, err # , measured_fluo - calculated_fluo)
def optimize(self, init_parameters=None): def optimize(self, init_parameters=None):
t0 = time.time() t0 = time.time()
@ -102,7 +103,7 @@ class Fitter:
(10, 100, 100, 1, 100, 10, 10), (10, 100, 100, 1, 100, 10, 10),
) )
res = least_squares(self.cost_func, init_parameters, bounds=bounds, xtol=1e-10) res, err = least_squares(self.cost_func, init_parameters, bounds=bounds, xtol=1e-10)
print() print()
print(" Parameters: [gGaL, ECal, K_pc_half, tau_xfer, tau_RC, offset]") print(" Parameters: [gGaL, ECal, K_pc_half, tau_xfer, tau_RC, offset]")
print(" Initial:", init_parameters.tolist()) print(" Initial:", init_parameters.tolist())
@ -149,6 +150,7 @@ class Fitter:
ax2.set_xlabel("time, ms") ax2.set_xlabel("time, ms")
ax2.set_ylabel("current, pA/pF") ax2.set_ylabel("current, pA/pF")
ax2.legend(frameon=False) ax2.legend(frameon=False)
return res, fig return res, fig
def covcor_from_lsq(res): def covcor_from_lsq(res):
@ -173,8 +175,8 @@ class Fitter:
plt.ylabel('Variables') plt.ylabel('Variables')
plt.show() plt.show()
if __name__ == "__main__":
if __name__ == "__main__":
filename = "ltcc_current.h5" filename = "ltcc_current.h5"
eid = "0033635a51b096dc449eb9964e70443a67fc16b9587ae3ff6564eea1fa0e3437_2018.06.18 14:48:40" eid = "0033635a51b096dc449eb9964e70443a67fc16b9587ae3ff6564eea1fa0e3437_2018.06.18 14:48:40"
@ -183,6 +185,8 @@ if __name__ == "__main__":
fit = Fitter(Model, data) fit = Fitter(Model, data)
res, fig = fit.optimize()
fit_hist = pd.DataFrame.from_dict(fit.fit_results, orient='index').T fit_hist = pd.DataFrame.from_dict(fit.fit_results, orient='index').T
fit_hist.index.name = 'Iterations' fit_hist.index.name = 'Iterations'