Merge pull request #106 from neurolib-dev/imp/explorationUtils_plotting

Improvement/explorationUtils for plotting

README.md

@@ -1,32 +1,22 @@
 <p align="center">
-  <a href="https://travis-ci.org/neurolib-dev/neurolib">
-  	<img alt="Header image of neurolib - A Python simulation framework foreasy whole-brain neural mass modeling." src="https://github.com/neurolib-dev/neurolib/raw/master/resources/readme_header.png" ></a>
+  	<img alt="Header image of neurolib - A Python simulation framework foreasy whole-brain neural mass modeling." src="https://github.com/neurolib-dev/neurolib/raw/master/resources/readme_header.png" >
 </p> 
 <p align="center">
   <a href="https://github.com/neurolib-dev/neurolib/actions">
   	<img alt="Build" src="https://img.shields.io/github/workflow/status/neurolib-dev/neurolib/ci"></a>
-
   <a href="https://zenodo.org/badge/latestdoi/236208651">
   	<img alt="DOI" src="https://zenodo.org/badge/236208651.svg"></a>
-
-
   <a href="https://github.com/neurolib-dev/neurolib/releases">
   	<img alt="Release" src="https://img.shields.io/github/v/release/neurolib-dev/neurolib"></a>
-
   <br>
-
   <a href="https://codecov.io/gh/neurolib-dev/neurolib">
   	<img alt="codecov" src="https://codecov.io/gh/neurolib-dev/neurolib/branch/master/graph/badge.svg"></a>
-
   <a href="https://pepy.tech/project/neurolib">
   	<img alt="Downloads" src="https://pepy.tech/badge/neurolib"></a>
-
   <a href="https://github.com/psf/black">
   	<img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
-
   <a href="https://mybinder.org/v2/gh/neurolib-dev/neurolib.git/master?filepath=examples">
   	<img alt="Launch in binder" src="https://mybinder.org/badge_logo.svg"></a>
-
 </p>
 
 

neurolib/optimize/evolution/evolutionaryUtils.py

@@ -92,7 +92,7 @@ def plotScoresDistribution(scores, gIdx, save_plots=None, color="C0"):
     plt.show()
 
 
-def plotSeabornScatter1(evolution, dfPop=None, save_plots=None, color="C0"):
+def plotSeabornScatter1(evolution, dfPop=None, save_plots=None, color="C0", line_kws={}, scatter_kws={}):
     import matplotlib.pyplot as plt
     import seaborn as sns
 
@@ -105,12 +105,18 @@ def plotSeabornScatter1(evolution, dfPop=None, save_plots=None, color="C0"):
         dfPop = evolution.dfPop()
 
     fig = plt.figure()
+
+    _line_kws = {"color": color}
+    _line_kws.update(line_kws)
+    _scatter_kws = {"alpha": 0.5, "color": color}
+    _scatter_kws.update(scatter_kws)
+
     sm = sns.pairplot(
         dfPop,
         vars=vars,
         diag_kind="kde",
         kind="reg",
-        plot_kws={"line_kws": {"color": color}, "scatter_kws": {"alpha": 0.5, "color": color},},
+        plot_kws={"line_kws": _line_kws, "scatter_kws": _scatter_kws,},
         diag_kws={"color": color},
     )
 
@@ -191,10 +197,10 @@ def plotProgress(evolution, reverse=True):
 
     gens, all_scores = evolution.getScoresDuringEvolution(reverse=reverse)
 
-    fig, axs = plt.subplots(2, 1, figsize=(3.5, 3), dpi=150, sharex=True, gridspec_kw={"height_ratios": [2, 1]},)
+    fig, axs = plt.subplots(2, 1, figsize=(3.5, 3), sharex=True, gridspec_kw={"height_ratios": [2, 1]},)
     im = axs[0].imshow(all_scores.T, aspect="auto", origin="lower")
     axs[0].set_ylabel("Individuals")
-    cbar_ax = fig.add_axes([0.93, 0.42, 0.02, 0.3])
+    cbar_ax = fig.add_axes([1.0, 0.55, 0.02, 0.3])
     fig.colorbar(im, cax=cbar_ax, label="Score")
 
     axs[1].plot(gens, np.nanmean(all_scores, axis=1), label="Average")
@@ -203,6 +209,7 @@ def plotProgress(evolution, reverse=True):
     )
     axs[1].set_xlabel("Generation")
     axs[1].set_ylabel("Score")
+    plt.tight_layout()
     plt.show()
 
 

neurolib/utils/devutils.py

@@ -2,6 +2,8 @@
 import numpy as np
 import scipy
 
+import sys
+
 import neurolib.utils.functions as func
 
 
@@ -333,3 +335,24 @@ def rolling_window(array, window=(0,), asteps=None, wsteps=None, axes=None, toen
     new_shape = new_shape[new_shape != 0]
 
     return np.lib.stride_tricks.as_strided(array, shape=new_shape, strides=new_strides)
+
+
+def get_size(obj, seen=None):
+    """Recursively finds size of objects"""
+    size = sys.getsizeof(obj)
+    if seen is None:
+        seen = set()
+    obj_id = id(obj)
+    if obj_id in seen:
+        return 0
+    # Important mark as seen *before* entering recursion to gracefully handle
+    # self-referential objects
+    seen.add(obj_id)
+    if isinstance(obj, dict):
+        size += sum([get_size(v, seen) for v in obj.values()])
+        size += sum([get_size(k, seen) for k in obj.keys()])
+    elif hasattr(obj, "__dict__"):
+        size += get_size(obj.__dict__, seen)
+    elif hasattr(obj, "__iter__") and not isinstance(obj, (str, bytes, bytearray)):
+        size += sum([get_size(i, seen) for i in obj])
+    return size