diff --git a/Fitter.py b/Fitter.py
index 7d1e325..baa48e5 100644
--- a/Fitter.py
+++ b/Fitter.py
@@ -132,8 +132,6 @@ class Fitter:
                         args=(error_weights,), x0=x0, method="Nelder-Mead",
                         options={"initial_simplex": initial_simplex, "xatol": 0.001, "maxfev": 600, "maxiter": 400})
 
-        plot_errors(self.errors)
-
         return fmin, self.base_model.get_parameters()
 
     def cost_function_all(self, X, error_weights=None):
@@ -197,10 +195,10 @@ class Fitter:
 
         # calculate errors with reference values
         error_bf = abs((baseline_freq - self.baseline_freq) / self.baseline_freq)
-        error_vs = abs((vector_strength - self.vector_strength) / 0.1)
+        error_vs = abs((vector_strength - self.vector_strength) / 0.01)
         error_cv = abs((coefficient_of_variation - self.coefficient_of_variation) / 0.2)
         error_bursty = (abs(burstiness - self.burstiness) / 0.2)
-        error_hist = np.mean((isi_bins - self.isi_bins) ** 2) / 200
+        error_hist = np.mean((isi_bins - self.isi_bins) ** 2) / 600
         # print("error hist: {:.2f}".format(error_hist))
         # print("Burstiness: cell {:.2f}, model: {:.2f}, error: {:.2f}".format(self.burstiness, burstiness, error_bursty))
 
@@ -214,12 +212,12 @@ class Fitter:
 
         # error_f_zero_slopes = calculate_list_error(f_zero_slopes, self.f_zero_slopes)
         error_f_zero_slope_at_straight = abs(self.f_zero_slope_at_straight - f_zero_slope_at_straight) \
-                                            / abs(self.f_zero_slope_at_straight+1 / 10)
-        error_f_zero = calculate_list_error(f_zeros, self.f_zero_values) / 25
+                                            / abs(self.f_zero_slope_at_straight+1)
+        error_f_zero = calculate_list_error(f_zeros, self.f_zero_values) / 10
 
         error_f0_curve = self.calculate_f0_curve_error(model, fi_curve_model) / 10
 
-        error_list = [error_bf, error_vs, error_sc, error_cv, error_hist, error_bursty,
+        error_list = [error_vs, error_sc, error_cv, error_hist, error_bursty,
                       error_f_inf, error_f_inf_slope, error_f_zero, error_f_zero_slope_at_straight, error_f0_curve]
 
         self.errors.append(error_list)
diff --git a/helperFunctions.py b/helperFunctions.py
index ed8bbbd..8b35a42 100644
--- a/helperFunctions.py
+++ b/helperFunctions.py
@@ -8,8 +8,8 @@ import matplotlib.pyplot as plt
 import time
 
 
-def plot_errors(list_errors):
-    names = ["error_bf", "error_vs", "error_sc", "error_cv", "error_bursty",
+def plot_errors(list_errors, save_path=None):
+    names = ["error_vs", "error_sc", "error_cv", "rms_isi_hist", "error_bursty",
              "error_f_inf", "error_f_inf_s", "error_f_zero", "error_f_zero_s_straight", "error_f0_curve"]
     data = np.array(list_errors)
 
@@ -23,7 +23,10 @@ def plot_errors(list_errors):
         axes[row, col].set_title(names[i])
         axes[row, col].set_yscale('log')
 
-    plt.savefig("figures/error_distributions/error_distribution_{}.png".format(time.strftime("%H:%M:%S")))
+    if save_path is None:
+        plt.show()
+    else:
+        plt.savefig(save_path + "error_distribution.png")
     plt.close()
 
 
diff --git a/run_Fitter.py b/run_Fitter.py
index 50bdce6..e5b57e7 100644
--- a/run_Fitter.py
+++ b/run_Fitter.py
@@ -10,16 +10,17 @@ import time
 import os
 import argparse
 import numpy as np
+from helperFunctions import plot_errors
 
 import multiprocessing as mp
 
 
 # SAVE_DIRECTORY = "./results/invivo_results/"
-SAVE_DIRECTORY = "./results/test_data_isi_hist_err_added/"
+SAVE_DIRECTORY = "./results/test_data/"
 # SAVE_DIRECTORY_BEST = "./results/invivo_best/"
-SAVE_DIRECTORY_BEST = "./results/test_data_best_isi_hist/"
+SAVE_DIRECTORY_BEST = "./results/test_data_best/"
 # [bf, vs, sc, cv, isi_hist, bursty, f_inf, f_inf_slope, f_zero, f_zero_slope, f0_curve]
-ERROR_WEIGHTS = (0, 2, 2, 1, 1, 0, 1, 1, 1, 0, 1)
+ERROR_WEIGHTS = (2, 2, 1, 1, 0, 1, 1, 1, 0, 1)
 
 
 def main():
@@ -70,6 +71,7 @@ def fit_cell_base(parameters):
     error = fitter.calculate_errors(model=LifacNoiseModel(res_par))
     save_path = SAVE_DIRECTORY + "/" + cell_path + "/start_parameter_{:}_err_{:.2f}/".format(parameters[1], sum(error))
     save_fitting_run_info(parameters[0], res_par, parameters[2], plot=True, save_path=save_path)
+    plot_errors(fitter.errors, save_path)
     time2 = time.time()
 
     del fitter
@@ -117,12 +119,12 @@ def iget_start_parameters():
     # mem_tau, input_scaling, noise_strength, dend_tau,
     # expand by tau_a, delta_a ?
 
-    mem_tau_list = [0.01]
-    input_scaling_list = [100]
-    noise_strength_list = [0.03]  # [0.02, 0.06]
-    dend_tau_list = [0.0015]
-    delta_a_list = [0.035, 0.065, 0.1]
-    tau_a_list = [0.1, 0.4]
+    mem_tau_list = [0.001]
+    input_scaling_list = [80]
+    noise_strength_list = [0.01]
+    dend_tau_list = [0.002]
+    delta_a_list = [0.01, 0.03, 0.065]
+    tau_a_list = [0.02, 0.04]
     ref_time_list = [0.00065, 0.0012]
 
     for mem_tau in mem_tau_list: