various update

plotter.py

@@ -99,7 +99,7 @@ def quiver(ax, map_h, map_v, extent, key_v=None, lognorm=False, label="", **kwar
     hh, vv = gethv(map_h, map_v, extent)
 
     # get norm information
-    norm_v = np.sqrt(map_h ** 2 + map_v ** 2)
+    norm_v = np.sqrt(map_h**2 + map_v**2)
     max_v = np.max(norm_v)
     min_v = np.min(norm_v)
 
@@ -456,7 +456,7 @@ class Plotter(Aggregator, BaseProcessor):
                     run=run,
                     **kwargs,
                 )
-                
+
                 if movie:
                     filenames[run].append(plot_filename)
 
@@ -968,8 +968,10 @@ class Plotter(Aggregator, BaseProcessor):
 
         if sinks:
             try:
-                self.current_processor.sinks()
-                data = pd.DataFrame(self.current_processor.get_value("/datasets/sinks"))
+                self.current_processor.load_sinks_rule()
+                data = pd.DataFrame(
+                    self.current_processor.get_value("/datasets/load_sinks_rule")
+                )
                 part_pos = data[["x", "y", "z"]].values
                 unit_length /= self.current_processor.lbox
             except KeyError:
@@ -1435,7 +1437,7 @@ class Plotter(Aggregator, BaseProcessor):
                 self.logger.warning(
                     "Errorbar may be meaningless when ytransform is used"
                 )
-                
+
         # Offset to start x when y in over a given value
         if wait_until_over is not None:
             offset = np.argmax(y > wait_until_over)
@@ -1480,7 +1482,7 @@ class Plotter(Aggregator, BaseProcessor):
                 (a, b, rho, _map_rule, stderr) = linregress(np.log10(x), np.log10(y))
                 self.logger.info(
                     "Power law fit y =  x^({}) *  {} with R^2 = {} and error is {}".format(
-                        a, 10 ** b, rho, stderr
+                        a, 10**b, rho, stderr
                     )
                 )
             else:
@@ -1504,12 +1506,12 @@ class Plotter(Aggregator, BaseProcessor):
                 residual = errfunc(c, np.log10(x), np.log10(y), yerr / y)
                 self.logger.info(
                     "Power law fit y =   x^({}) * {}  with residual {}".format(
-                        a, 10 ** b, residual
+                        a, 10**b, residual
                     )
                 )
             if label is None:
                 label = r"Power-law fit with index {:.1f}".format(a)
-            plt.plot(x, (10 ** b) * x ** a, label=label, **kwargs)
+            plt.plot(x, (10**b) * x**a, label=label, **kwargs)
 
     def _gen_from_log(self, logrule, name_y, name_x="time", description="Generated"):
         if name_x == "time":
@@ -1723,7 +1725,7 @@ class Plotter(Aggregator, BaseProcessor):
                     "/series/sinks_from_log/time",
                     "/series/sinks_from_log/ssm",
                     xunit=U.Myr,
-                    yunit=U.Msun / U.pc ** 2,
+                    yunit=U.Msun / U.pc**2,
                 ),
                 "Mass of the sinks as a function of time divided by surface",
                 kind="run",