fit final dataset again (3) add skipping already fitted ones
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@ -346,7 +346,7 @@ class Fitter:
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self.base_model.set_variable("v_offset", v_offset)
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# time2 = time.time()
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# print("time taken for finding v_offset: {:.2f}s".format(time2-time1))
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print(self.base_model.parameters)
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error_list = self.calculate_errors(error_weights)
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# print("sum: {:.2f}, ".format(sum(error_list)))
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if sum(error_list) < self.smallest_error:
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@ -14,8 +14,8 @@ from helperFunctions import plot_errors
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import multiprocessing as mp
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SAVE_DIRECTORY = "./results/ref_and_tau/with_out_both/"
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SAVE_DIRECTORY_BEST = "./results/ref_and_tau/wob_best/"
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SAVE_DIRECTORY = "./results/final_3"
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SAVE_DIRECTORY_BEST = "./results/final_3_best/"
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# [vs, sc, cv, isi_hist, bursty, f_inf, f_inf_slope, f_zero, f_zero_slope, f0_curve]
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ERROR_WEIGHTS = (1, 1, 1, 1, 1, 1, 1, 1, 0, 1)
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@ -26,6 +26,11 @@ def main():
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args = parser.parse_args()
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if args.cell is not None:
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cell_data = CellData(args.cell)
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cell_name = os.path.split(cell_data.get_data_path())[-1]
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if os.path.exists(SAVE_DIRECTORY + "/" + cell_name + "/"):
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print(cell_name, "already done")
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return
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start_parameters = [p for p in iget_start_parameters()]
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fit_cell_parallel(cell_data, start_parameters)
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quit()
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@ -60,7 +65,7 @@ def fit_cell_base(parameters):
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time1 = time.time()
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fitter = Fitter()
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fitter.set_data_reference_values(parameters[0])
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fmin, res_par = fitter.fit_routine_no_dend_tau_and_no_ref_period(parameters[2], ERROR_WEIGHTS)
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fmin, res_par = fitter.fit_routine(parameters[2], ERROR_WEIGHTS)
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cell_data = parameters[0]
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cell_name = os.path.split(cell_data.get_data_path())[-1]
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@ -1,5 +1,5 @@
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for file in data/ref_and_dend_set/*; do
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for file in data/final/*; do
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if [ -d "$file" ]; then
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nice python3 run_Fitter.py --cell $file
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fi
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