minor adjustments after trial and error

Model.py

@@ -197,13 +197,9 @@ class Model:
         # Bi = (1 + (self.CMDN_tot * self.Km_CMDN)/(self.Km_CMDN+(Cai))**2)**(-1)
         # Bss = 1 / ((self.CMDN_tot * self.Km_CMDN) / (self.Km_CMDN + Cass) ** 2)
 
-        Bi = 1 / (
-            1 + (self.CMDN_tot * self.Km_CMDN) / (self.Km_CMDN + Cai) ** 2
-        )
+        Bi = 1 / (1 + (self.CMDN_tot * self.Km_CMDN) / (self.Km_CMDN + Cai) ** 2)
 
-        Bss = 1 / (
-            1 + (self.CMDN_tot * self.Km_CMDN) / (self.Km_CMDN + Cass) ** 2
-        )
+        Bss = 1 / (1 + (self.CMDN_tot * self.Km_CMDN) / (self.Km_CMDN + Cass) ** 2)
 
         J_xfer = (Cass - Cai) / self.tau_xfer
 
@@ -216,9 +212,7 @@ class Model:
         J_trpn = (
             self.k_htrpn_positive * Cai * (self.HTRPN_tot - HTRPNCa)
             - self.k_htrpn_negative * HTRPNCa
-            + self.k_ltrpn_positive
-            * Cai
-            * (self.LTRPN_tot - LTRPNCa)
+            + self.k_ltrpn_positive * Cai * (self.LTRPN_tot - LTRPNCa)
             - self.k_ltrpn_negative * LTRPNCa
         )
 
@@ -258,9 +252,7 @@ class Model:
 
         P_C1 = 1 - (P_C2 + P_O1 + P_O2)
 
-        dP_O1dt = (
-            self.k_a_positive * (Cass) ** self.n_ryr * P_C1
-        )
+        dP_O1dt = self.k_a_positive * (Cass) ** self.n_ryr * P_C1
         -self.k_a_negative * P_O1 - self.k_a_positive * (Cass) ** self.m_ryr * P_O1
         +self.k_b_negative * P_O2 - self.k_c_positive * P_O1 + self.k_c_negative * P_C2
 

fitter.py

@@ -25,8 +25,8 @@ class Fitter:
         self.tspan = [0, 1000]
         self.dt = 1  # 1.0
         self.time_points = np.arange(*self.tspan, self.dt)
-        
-        model=Model()
+
+        model = Model()
         self.initial_values = model.get_initial_values()
 
         self.iteration = 0  # least squares iteration counter
@@ -61,7 +61,12 @@ class Fitter:
         model.K_pc_half = K_pc_half
         model.tau_xfer = tau_xfer
 
-        model.solve(times=self.time_points, tspan=self.tspan, dt=self.dt, initial_values=self.initial_values)
+        model.solve(
+            times=self.time_points,
+            tspan=self.tspan,
+            dt=self.dt,
+            initial_values=self.initial_values,
+        )
 
         _calc_curr = model.calculated_current()
         calculated_current = (
@@ -207,7 +212,7 @@ if __name__ == "__main__":
 
     eid_cleaned = re.sub(
         r"[^\w.-]", "", eid
-    )  # Eemalda kõik eritähed ja jääb alles alphanumbrilised tähed, sidekriipsud ja punktid
+    )  # Eemaldab eritahed
     fig.savefig(f"plot_{eid_cleaned}.png")
     fig.savefig(f"plot_{eid_cleaned}.pdf")