bugfix + docs update

GiulioRossetti · Jul 27, 2017 · 5bc2c0b · 5bc2c0b
1 parent e1a76c0
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Showing 10 changed files with 26 additions and 23 deletions.
diff --git a/docs/index.rst b/docs/index.rst
@@ -10,7 +10,7 @@ NDlib is a Python software package that allows to describe, simulate, and study
 
 =========== ============= =================== ==================  ==========  ===============
 **Release**    **Date**   **Python Versions**   **Main Author**   **GitHub**     **pypl**
-   2.0.1    May 31, 2017       2.7.x/3.x      `Giulio Rossetti`_  `Source`_   `Distribution`_
+   2.1.0    July 27, 2017       2.7.x/3.x     `Giulio Rossetti`_  `Source`_   `Distribution`_
 =========== ============= =================== ==================  ==========  ===============
 
 

diff --git a/docs/reference/viz/mpl/DiffusionPrevalence.rst b/docs/reference/viz/mpl/DiffusionPrevalence.rst
@@ -32,7 +32,7 @@ Below is shown an example of Diffusion Prevalence description and visualization
     cfg = mc.Configuration()
     cfg.add_model_parameter('beta', 0.001)
     cfg.add_model_parameter('gamma', 0.01)
-    cfg.add_model_parameter("percentage_infected", 16 0.05)
+    cfg.add_model_parameter("percentage_infected", 0.01)
     model.set_initial_status(cfg)
 
     # Simulation execution

diff --git a/docs/reference/viz/mpl/DiffusionTrend.rst b/docs/reference/viz/mpl/DiffusionTrend.rst
@@ -31,7 +31,7 @@ Below is shown an example of Diffusion Trend description and visualization for t
     cfg = mc.Configuration()
     cfg.add_model_parameter('beta', 0.001)
     cfg.add_model_parameter('gamma', 0.01)
-    cfg.add_model_parameter("percentage_infected", 16 0.05)
+    cfg.add_model_parameter("percentage_infected", 0.01)
     model.set_initial_status(cfg)
 
     # Simulation execution

diff --git a/docs/reference/viz/mpl/PrevalenceComparison.rst b/docs/reference/viz/mpl/PrevalenceComparison.rst
@@ -18,7 +18,8 @@ Below is shown an example of Diffusion Prevalence description and visualization
 
     import networkx as nx
     import ndlib.models.ModelConfig as mc
-    import ndlib.models.epidemics.SIRModel as sir 
+    import ndlib.models.epidemics.SIRModel as sir
+    import ndlib.models.epidemics.SIModel as si
     from ndlib.viz.mpl.PrevalenceComparison import DiffusionPrevalenceComparison
 
 
@@ -31,22 +32,21 @@ Below is shown an example of Diffusion Prevalence description and visualization
     # Model Configuration
     cfg = mc.Configuration()
     cfg.add_model_parameter('beta', 0.001)
-    cfg.add_model_parameter('gamma', 0.01)
-    cfg.add_model_parameter("percentage_infected", 16 0.05)
+    cfg.add_model_parameter('gamma', 0.02)
+    cfg.add_model_parameter("percentage_infected", 0.01)
     model.set_initial_status(cfg)
 
     # Simulation execution
     iterations = model.iteration_bunch(200)
     trends = model.build_trends(iterations)
 
     # 2° Model selection
-    model1 = sir.SIRModel(g)
+    model1 = si.SIModel(g)
 
     # 2° Model Configuration
     cfg = mc.Configuration()
-    cfg.add_model_parameter('beta', 0.004)
-    cfg.add_model_parameter('gamma', 0.02)
-    cfg.add_model_parameter("percentage_infected", 0.05)
+    cfg.add_model_parameter('beta', 0.001)
+    cfg.add_model_parameter("percentage_infected", 0.01)
     model1.set_initial_status(cfg)
 
     # 2° Simulation execution
@@ -59,9 +59,9 @@ Below is shown an example of Diffusion Prevalence description and visualization
 
 
 
-.. figure:: diff_prevalence.png
+.. figure:: prevalence_comparison.png
    :scale: 80 %
    :align: center 
-   :alt: SIR Diffusion Prevalence Example
+   :alt: SIR-SI Diffusion Prevalence Comparison Example
 
-   SIR Diffusion Prevalence Example.
+   SIR-SI Diffusion Prevalence Comparison Example.
diff --git a/docs/reference/viz/mpl/TrendComparison.rst b/docs/reference/viz/mpl/TrendComparison.rst
@@ -31,7 +31,7 @@ Below is shown an example of Diffusion Trend description and visualization for t
     cfg = mc.Configuration()
     cfg.add_model_parameter('beta', 0.001)
     cfg.add_model_parameter('gamma', 0.01)
-    cfg.add_model_parameter("percentage_infected", 0.05)
+    cfg.add_model_parameter("percentage_infected", 0.01)
     model.set_initial_status(cfg)
 
     # Simulation execution
@@ -43,9 +43,9 @@ Below is shown an example of Diffusion Trend description and visualization for t
 
     # 2° Model Configuration
     cfg = mc.Configuration()
-    cfg.add_model_parameter('beta', 0.004)
+    cfg.add_model_parameter('beta', 0.001)
     cfg.add_model_parameter('gamma', 0.02)
-    cfg.add_model_parameter("percentage_infected", 0.05)
+    cfg.add_model_parameter("percentage_infected", 0.01)
     model1.set_initial_status(cfg)
 
     # 2° Simulation execution
@@ -59,9 +59,9 @@ Below is shown an example of Diffusion Trend description and visualization for t
 
 
 
-.. figure:: diff_trend.png
+.. figure:: trend_comparison.png
    :scale: 80 %
    :align: center 
-   :alt: SIR Diffusion Trend Example
+   :alt: SIR-SI Diffusion Trend Comparison Example
 
-   SIR Diffusion Trend Example.
+   SIR-SI Diffusion Trend Comparison Example.
diff --git a/docs/reference/viz/mpl/diff_prevalence.png b/docs/reference/viz/mpl/diff_prevalence.png
diff --git a/docs/reference/viz/mpl/diff_trend.png b/docs/reference/viz/mpl/diff_trend.png
diff --git a/docs/reference/viz/mpl/prevalence_comparison.png b/docs/reference/viz/mpl/prevalence_comparison.png
diff --git a/docs/reference/viz/mpl/trend_comparison.png b/docs/reference/viz/mpl/trend_comparison.png
diff --git a/ndlib/viz/mpl/ComparisonViz.py b/ndlib/viz/mpl/ComparisonViz.py
@@ -16,7 +16,7 @@ class InitializationException(Exception):
 class ComparisonPlot(object):
     __metaclass__ = abc.ABCMeta
 
-    def __init__(self, models, trends, statuses=("Infected")):
+    def __init__(self, models, trends, statuses=["Infected"]):
         self.models = models
         self.trends = trends
         if len(models) != len(trends):
@@ -37,7 +37,10 @@ def __init__(self, models, trends, statuses=("Infected")):
             self.srev["%s_%s" % (model.name, i)] = srev
             i += 1
 
-        cls = set(statuses) & set(available_classes.keys())
+        if type(statuses) == list:
+            cls = set(statuses) & set(available_classes.keys())
+        else:
+            cls = set([statuses]) & set(available_classes.keys())
         if len(cls) > 0:
             self.classes = cls
         else:
@@ -77,12 +80,12 @@ def plot(self, filename, percentile=90):
                 mx = len(l[st][0])
                 if self.normalized:
                     plt.plot(range(0, mx), l[st][1]/self.nnodes, lw=2,
-                             label="%s - %s" % (self.mnames[i].split("_")[0], st), alpha=0.9, color=cols[h+j])
+                             label="%s - %s" % (k.split("_")[0], st), alpha=0.9, color=cols[h+j])
                     plt.fill_between(range(0,  mx), l[st][0]/self.nnodes,
                                      l[st][2]/self.nnodes, alpha=0.2, color=cols[h+j])
                 else:
                     plt.plot(range(0, mx), l[st][1], lw=2,
-                             label="%s - %s" % (self.mnames[i].split("_")[0], st), alpha=0.9, color=cols[h + j])
+                             label="%s - %s" % (k.split("_")[0], st), alpha=0.9, color=cols[h + j])
                     plt.fill_between(range(0, mx), l[st][0],
                                      l[st][2], alpha=0.2, color=cols[h + j])
                 j += 1