Little simplifications.

cellfile.py

@@ -100,11 +100,6 @@ class CellFile(object):
         # how the cell zones are defined
         self.identity_definition = "anatomy"
 
-        # attributes set during a growth process
-        self.has_grown = False
-        self.start_time, self.stop_time = None, None
-        self.activation_delay = None
-
     def concentration_scale(self):
         """Return a 'characterstic concentration' uswful for plotting.
 
@@ -149,12 +144,12 @@ class CellFile(object):
 
         Returns
         -------
-        zone_1 : 1-D ndarray of ints
+        zone_1 : list of ints
             Lists of the indices of the cells above the division threshold.
-        zone_2 : 1-D ndarray of ints
+        zone_2 : list of ints
             Lists of the indices of the cells between the division threshold
             and the enlargement threshold.
-        zone_3 : 1-D ndarray of ints
+        zone_3 : list of ints
             Lists of the indices of the cells below the division threshold.
         """
         div_id_conc = cell_conc[self.div_id_index]
@@ -220,7 +215,7 @@ class CellFile(object):
             raise UserWarning("Identities are incomplete!")
         return identities
 
-    def get_cell_zones_anatomy(self, time=-1):
+    def get_cell_zones_anatomy(self, time):
         """Return cell zones as defined by the anatomical criterion.
 
         Returns
@@ -243,7 +238,7 @@ class CellFile(object):
                     zone_2.append(cell.indices[i])
                 elif identity == "non growing":
                     zone_3.append(cell.indices[i])
-        return np.sort(zone_1), np.sort(zone_2), np.sort(zone_3)
+        return zone_1, zone_2, zone_3
 
     def get_cell_concentrations(self, u, concentration_operator):
         """Return signal concentrations of the cells."""
@@ -629,7 +624,7 @@ class CellFile(object):
         return self.M_primer, RdX_flux_diff
 
     def evolution_matrices(self, nodes_per_cell):
-        """Compute the diffusion matrix of a signal."""
+        """Compute and return the evolution matrix of a signal profile."""
         if "uniform diffusion" in self.transport_mechanisms:
             self.set_counters_and_masks(nodes_per_cell)
             M_init, RdX_flux_diff = self.init_diffusion_matrix(nodes_per_cell)
@@ -738,8 +733,9 @@ class CellFile(object):
             Start time of the simulation.
         stop_time : datetime instance
             Stop time of the simulation.
-        activation_time : datetime instance, optional, default: None
-            Activation time of the simulation.
+        activation_time : datetime instance, optional, default: 0
+            Time at which the cambium is activated (i.e. starts to respond to
+            signals).
         input_time_step : float, optional, default: 3600
             Time step between input value updates, in seconds.
         growth_time_step : float, optional, default: 3600
@@ -762,18 +758,15 @@ class CellFile(object):
             quantity of signals the file (the default is False).
 
         """
-        self.start_time, self.stop_time = start_time, stop_time
         if activation_time is None:
-            self.activation_delay = timedelta(0)
+            activation_delay = start_time
         else:
-            self.activation_delay = activation_time - self.start_time
-        activation_delay_seconds = self.activation_delay.total_seconds()
-        total_time = (self.stop_time - self.start_time).total_seconds()
+            activation_delay = (activation_time - start_time).total_seconds()
+        total_time = (stop_time - start_time).total_seconds()
+        self.start_time, self.stop_time = start_time, stop_time
         self.date_list = self.date_list[:1]
-        delta = timedelta(seconds=snapshot_time_step)
         self.growth_time_step = growth_time_step
-        self.snapshot_time_step = snapshot_time_step
-        self.conversion = self.data_time_unit / self.snapshot_time_step
+        self.conversion = self.data_time_unit / snapshot_time_step
         self.initial_nodes_per_cell = nodes_per_cell
         self.nodes_per_cell = nodes_per_cell*np.ones(self.nb_cells, dtype=int)
         self.nb_nodes = self.nodes_per_cell.sum()
@@ -915,7 +908,7 @@ class CellFile(object):
         # cell identity lists bases on anatomy
         self.inactive_cells, self.growing_cells, self.non_growing_cells, \
             self.small_cells = [], [], [], []
-        if activation_delay_seconds > 0:
+        if activation_delay > 0:
             inactive = True
             self.inactive_cells = range(self.nb_cells)
         else:
@@ -940,7 +933,7 @@ class CellFile(object):
         self.init_history()
         self.make_history(u, PIN, check_conservation)
         current_time = 0
-        sample_time = 0
+        self.sample_time = 0
 
         for tw in range(nb_time_windows):
 
@@ -1025,7 +1018,7 @@ class CellFile(object):
 
             current_time += time_window
             # update cell identities
-            if inactive and current_time >= activation_delay_seconds:
+            if inactive and current_time >= activation_delay:
                 inactive = False
                 self.inactive_cells = []
                 self.cell_conc = self.get_cell_concentrations(
@@ -1044,17 +1037,16 @@ class CellFile(object):
                 self.get_gradient_zones(self.cell_conc)
             # snapshot
             self.make_history(u, PIN, check_conservation)
-            self.date += delta
+            self.date += timedelta(seconds=snapshot_time_step)
             self.date_list.append(self.date)
             identities = self.get_cells_identities()
             for i, cell in enumerate(self.cells):
                 cell.indices.append(i)
-                cell.dates.append(sample_time)
+                cell.dates.append(self.sample_time)
                 cell.diameters.append(self.D_real[i])
                 cell.strain_rates.append(self.S[i])
                 cell.identities.append(identities[i])
-            sample_time += 1
-        self.has_grown = True
+            self.sample_time += 1
 
     def Gamma(self, X, R, D):
         """Map from Omega_0 to Omega_t."""

plotutils.py

@@ -301,10 +301,10 @@ def fill_cell_file_drawing(
                 # an arrow on one well-selected membrane
                 elif show_transport_polarity == "one":
                     zone_1, zone_2, zone_3 = cf.get_cell_zones_anatomy(time)
-                    if zone_2.size:
+                    if zone_2:
                         cell_index = zone_2[len(zone_2)//2]
                     else:
-                        cell_index = nb_cells / 2
+                        cell_index = nb_cells // 2
                     x_pos = rectangle_positions[cell_index]
                     arrows.append(Arrow(x_pos - polarity * arrow_stem/2, y_pos,
                                         polarity * arrow_stem, 0,