From 818dc0b2b05d19768ad0e4072d6a0bb7debccb4f Mon Sep 17 00:00:00 2001
From: flatberg <flatberg@pvv.ntnu.no>
Date: Wed, 14 Mar 2007 16:27:23 +0000
Subject: [PATCH] added a logger for constructor calls

---
 fluents/plots.py | 37 ++++++++++++++++++++++++++-----------
 1 file changed, 26 insertions(+), 11 deletions(-)

diff --git a/fluents/plots.py b/fluents/plots.py
index eed9999..08c331b 100644
--- a/fluents/plots.py
+++ b/fluents/plots.py
@@ -2,6 +2,7 @@ import pygtk
 import gobject
 import gtk
 
+import matplotlib
 from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg
 from matplotlib.nxutils import points_inside_poly
 from matplotlib.figure import Figure
@@ -17,8 +18,15 @@ import fluents
 import logger
 import view
 
+def plotlogger(func, name=None):
+    def wrapped(parent, *args, **kw):
+        parent.__args = args
+        parent.__kw = kw
+        return func(parent, *args, **kw)
+    return wrapped
 
-class Plot (view.View):
+
+class Plot(view.View):
     def __init__(self, title):
         view.View.__init__(self, title)
         logger.log('debug', 'plot %s init' %title)
@@ -132,6 +140,7 @@ class LineViewPlot(Plot):
 
     fixme: slow
     """
+    @plotlogger
     def __init__(self, dataset, major_axis=1, minor_axis=None, name="Line view"):
         Plot.__init__(self, name)
         self.dataset = dataset
@@ -233,7 +242,7 @@ class LineViewPlot(Plot):
 class ScatterMarkerPlot(Plot):
     """The ScatterMarkerPlot is faster than regular scatterplot, but
        has no color and size options."""
-    
+    @plotlogger
     def __init__(self, dataset_1, dataset_2, id_dim, sel_dim,
                  id_1, id_2, s=6, name="Scatter plot"):
         Plot.__init__(self, name)
@@ -306,12 +315,14 @@ class ScatterMarkerPlot(Plot):
 
 class ScatterPlot(Plot):
     """The ScatterPlot is slower than scattermarker, but has size option."""
-    def __init__(self, dataset_1, dataset_2, id_dim, sel_dim, id_1, id_2, c='b', s=30, sel_dim_2=None, name="Scatter plot"):
+    @plotlogger
+    def __init__(self, dataset_1, dataset_2, id_dim, sel_dim, id_1, id_2, c='b', s=30, sel_dim_2=None, name="Scatter plot", **kw):
 
         Plot.__init__(self, name)
         self.dataset_1 = dataset_1
         self.s = s
         self.c = c
+        self.kw = kw
         self.current_dim = id_dim
         
         x_index = dataset_1[sel_dim][id_1]
@@ -355,7 +366,8 @@ class ScatterPlot(Plot):
     def init_draw(self):
         lw = scipy.zeros(self.xaxis_data.shape)
         self.sc = self.axes.scatter(self.xaxis_data, self.yaxis_data,
-                                  s=self.s, c=self.c, linewidth=lw, zorder=3)
+                                    s=self.s, c=self.c, linewidth=lw,
+                                    zorder=3, **self.kw)
         self.axes.axhline(0, color='k', lw=1., zorder=1)
         self.axes.axvline(0, color='k', lw=1., zorder=1)
         self.selection_collection = self.axes.scatter(self.xaxis_data,
@@ -449,6 +461,7 @@ class ScatterPlot(Plot):
         
         
 class ImagePlot(Plot):
+    @plotlogger
     def __init__(self, dataset, **kw):
         Plot.__init__(self, kw.get('name', 'Image Plot'))
         self.dataset = dataset
@@ -469,7 +482,7 @@ class HistogramPlot(Plot):
     If dataset is 1-dim the current_dim is set and selections may
     be performed. For dataset> 1.dim the histogram is over all values
     and selections are not defined,"""
-    
+    @plotlogger
     def __init__(self, dataset, **kw):
         Plot.__init__(self, kw['name'])
         self.dataset = dataset
@@ -556,6 +569,7 @@ class BarPlot(Plot):
     Ordinary bar plot for (column) vectors.
     For matrices there is one color for each row.
     """
+    @plotlogger
     def __init__(self, dataset, **kw):
         Plot.__init__(self, kw.get('name', 'Bar Plot'))
         self.dataset = dataset
@@ -564,8 +578,7 @@ class BarPlot(Plot):
         self.axes.grid(False)
         n, m = dataset.shape
         if m>1:
-            sm = matplotlib.cm.ScalarMappable()
-            clrs = sm.to_rgba(range(n))
+            clrs = matplotlib.cm.ScalarMappable().to_rgba(range(n))
             for i, row in enumerate(dataset.asarray()):
                 left = scipy.arange(i+1, m*n+1, n)
                 height = row
@@ -584,6 +597,7 @@ class BarPlot(Plot):
         
 
 class NetworkPlot(Plot):
+    @plotlogger
     def __init__(self, dataset, pos=None, nodecolor='b', nodesize=40,
                  prog='neato', with_labels=False, name='Network Plot'):
 
@@ -606,9 +620,9 @@ class NetworkPlot(Plot):
 
         # Initial draw
         self.default_props = {'nodesize' : 50,
-                              'nodecolor' : 'gray',
-                              'edge_color' : (.5, .5, .5, 1),
-                              'edge_color_selected' : (1,0,0,1)}
+                              'nodecolor' : 'blue',
+                              'edge_color' : 'gray',
+                              'edge_color_selected' : 'red'}
         self.node_collection = None
         self.edge_collection = None
         self.node_labels = None
@@ -634,7 +648,7 @@ class NetworkPlot(Plot):
                                                             self._pos,
                                                             ax=self.axes,
                                                             edge_color=edge_color)
-        # edge color rgba-array
+        # edge color rgba-arrays
         self._edge_color_rgba = scipy.repmat(ColorConverter().to_rgba(edge_color),
                                        self.graph.number_of_edges(),1)
         self._edge_color_selected = ColorConverter().to_rgba(self.default_props['edge_color_selected'])
@@ -693,6 +707,7 @@ class NetworkPlot(Plot):
 
 
 class VennPlot(Plot):
+    @plotlogger
     def __init__(self, name="Venn diagram"):
         Plot.__init__(self, name)