1.0.4

docs/conf.py

@@ -47,9 +47,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = "1.0.3"
+version = "1.0.4"
 # The full version, including alpha/beta/rc tags.
-release = "1.0.3"
+release = "1.0.4"
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

histogrammar/defs.py

@@ -97,6 +97,7 @@ def specialize(self):
         except (ImportError, AttributeError):
             pass
         self.fill = FillMethod(self, self.fill)
+        self.plot = PlotMethod(self, self.plot)
         return self
 
     @staticmethod
@@ -179,14 +180,20 @@ def fill(self, datum, weight=1.0):
         """
         raise NotImplementedError
 
+    def plot(self, httpServer=None, **parameters):
+        """Generate a VEGA visualization and serve it via HTTP."""
+        raise NotImplementedError
+
     def __getstate__(self):
         state = dict(self.__dict__)
         del state["fill"]
+        del state["plot"]
         return state
 
     def __setstate__(self, dict):
         self.__dict__ = dict
         self.fill = FillMethod(self, self.fill)
+        self.plot = PlotMethod(self, self.plot)
 
     def copy(self):
         """Copy this container, making a clone with no reference to the original. """

histogrammar/plot/bokeh.py

@@ -20,7 +20,7 @@
 import math
 
 class HistogramMethods(object):
-    def bokeh(self,glyphType="line",glyphSize=1,fillColor="red",lineColor="black",lineAlpha=1,fillAlpha=0.1,lineDash='solid'):
+    def plotbokeh(self,glyphType="line",glyphSize=1,fillColor="red",lineColor="black",lineAlpha=1,fillAlpha=0.1,lineDash='solid'):
 
         #glyphs
         from bokeh.models.glyphs import Rect, Segment, Line, Patches, Arc
@@ -66,7 +66,7 @@ def bokeh(self,glyphType="line",glyphSize=1,fillColor="red",lineColor="black",li
         return GlyphRenderer(glyph=glyph,data_source=source)
 
 class SparselyHistogramMethods(object):
-    def bokeh(self,glyphType="line",glyphSize=1,fillColor="red",lineColor="black",lineAlpha=1,fillAlpha=0.1,lineDash='solid'):
+    def plotbokeh(self,glyphType="line",glyphSize=1,fillColor="red",lineColor="black",lineAlpha=1,fillAlpha=0.1,lineDash='solid'):
 
         #glyphs
         from bokeh.models.glyphs import Rect, Segment, Line, Patches, Arc
@@ -114,7 +114,7 @@ def bokeh(self,glyphType="line",glyphSize=1,fillColor="red",lineColor="black",li
 
 
 class ProfileMethods(object):
-    def bokeh(self,glyphType="line",glyphSize=1,fillColor="red",lineColor="black",lineAlpha=1,fillAlpha=0.1,lineDash='solid'):
+    def plotbokeh(self,glyphType="line",glyphSize=1,fillColor="red",lineColor="black",lineAlpha=1,fillAlpha=0.1,lineDash='solid'):
 
         #glyphs
         from bokeh.models.glyphs import Rect, Segment, Line, Patches, Arc
@@ -166,7 +166,7 @@ class SparselyProfileMethods(object):
     pass
 
 class ProfileErrMethods(object):
-    def bokeh(self,glyphType="line",glyphSize=1,fillColor="red",lineColor="black",lineAlpha=1,fillAlpha=0.1,lineDash='solid'):
+    def plotbokeh(self,glyphType="line",glyphSize=1,fillColor="red",lineColor="black",lineAlpha=1,fillAlpha=0.1,lineDash='solid'):
 
         #glyphs
         from bokeh.models.glyphs import Rect, Segment, Line, Patches, Arc
@@ -231,7 +231,7 @@ class StackedHistogramMethods(object):
     fillAlphaDefaults = [0.1]*nMaxStacked
     lineDashDefaults = ["solid"]*nMaxStacked
 
-    def bokeh(self,glyphTypes=glyphTypeDefaults,glyphSizes=glyphSizeDefaults,fillColors=fillColorDefaults,lineColors=lineColorDefaults,lineAlphas=lineAlphaDefaults,fillAlphas=fillAlphaDefaults,lineDashes = lineDashDefaults):
+    def plotbokeh(self,glyphTypes=glyphTypeDefaults,glyphSizes=glyphSizeDefaults,fillColors=fillColorDefaults,lineColors=lineColorDefaults,lineAlphas=lineAlphaDefaults,fillAlphas=fillAlphaDefaults,lineDashes = lineDashDefaults):
         nChildren = len(self.children)-1
 
         assert len(glyphSizes) >= nChildren
@@ -245,7 +245,7 @@ def bokeh(self,glyphTypes=glyphTypeDefaults,glyphSizes=glyphSizeDefaults,fillCol
         stackedGlyphs = list()
         #for ichild, p in enumerate(self.children,start=1):
         for ichild in range(nChildren):
-            stackedGlyphs.append(self.children[ichild+1].bokeh(glyphTypes[ichild],glyphSizes[ichild],fillColors[ichild],lineColors[ichild],lineAlphas[ichild],fillAlphas[ichild],lineDashes[ichild]))
+            stackedGlyphs.append(self.children[ichild+1].plotbokeh(glyphTypes[ichild],glyphSizes[ichild],fillColors[ichild],lineColors[ichild],lineAlphas[ichild],fillAlphas[ichild],lineDashes[ichild]))
 
         return stackedGlyphs
 

histogrammar/plot/mpl.py → histogrammar/plot/matplotlib.py

@@ -41,7 +41,7 @@ def set2Dsparse(sparse, yminBin, ymaxBin, grid):
     return grid
 
 class HistogramMethods(object):
-    def matplotlib(self, name=None, **kwargs):
+    def plotmatplotlib(self, name=None, **kwargs):
         """
             name : title of the plot.
             kwargs :  `matplotlib.patches.Rectangle` properties.
@@ -68,7 +68,7 @@ def matplotlib(self, name=None, **kwargs):
         return ax
 
 class SparselyHistogramMethods(object):
-    def matplotlib(self, name=None, **kwargs):
+    def plotmatplotlib(self, name=None, **kwargs):
         """
             name : title of the plot.
             kwargs :  `matplotlib.patches.Rectangle` properties.
@@ -95,7 +95,7 @@ def matplotlib(self, name=None, **kwargs):
         return ax
 
 class ProfileMethods(object):
-    def matplotlib(self, name=None, **kwargs):
+    def plotmatplotlib(self, name=None, **kwargs):
         """ Plotting method for Bin of Average
               name : title of the plot.
               kwargs : matplotlib.collections.LineCollection properties.
@@ -120,7 +120,7 @@ def matplotlib(self, name=None, **kwargs):
         return ax
 
 class SparselyProfileMethods(object):
-    def matplotlib(self, name=None, **kwargs):
+    def plotmatplotlib(self, name=None, **kwargs):
         """ Plotting method for SparselyBin of Average
               name : title of the plot.
               kwargs : matplotlib.collections.LineCollection properties.
@@ -150,7 +150,7 @@ def matplotlib(self, name=None, **kwargs):
         return ax
 
 class ProfileErrMethods(object):
-    def matplotlib(self, name=None, aspect=True, **kwargs):
+    def plotmatplotlib(self, name=None, aspect=True, **kwargs):
         """ Plotting method for Bin of Deviate
               name : title of the plot.
               aspect :
@@ -189,7 +189,7 @@ def matplotlib(self, name=None, aspect=True, **kwargs):
         return ax
 
 class SparselyProfileErrMethods(object):
-    def matplotlib(self, name=None, aspect=True, **kwargs):
+    def plotmatplotlib(self, name=None, aspect=True, **kwargs):
         """ Plotting method for
         """
         import matplotlib.pyplot as plt
@@ -235,7 +235,7 @@ def matplotlib(self, name=None, aspect=True, **kwargs):
         return ax
 
 class StackedHistogramMethods(object):
-    def matplotlib(self, name=None, **kwargs):
+    def plotmatplotlib(self, name=None, **kwargs):
         """ Plotting method for
         """
         import matplotlib.pyplot as plt
@@ -247,7 +247,7 @@ def matplotlib(self, name=None, **kwargs):
 
         for i, hist in enumerate(self.values):
             color = color_cycle[i]
-            hist.matplotlib(color=color, label=hist.name, **kwargs)
+            hist.plotmatplotlib(color=color, label=hist.name, **kwargs)
             color_cycle.append(color)
 
         if name is not None:
@@ -257,7 +257,7 @@ def matplotlib(self, name=None, **kwargs):
         return ax
 
 class PartitionedHistogramMethods(object):
-    def matplotlib(self, name=None, **kwargs):
+    def plotmatplotlib(self, name=None, **kwargs):
         """ Plotting method for
         """
         import matplotlib.pyplot as plt
@@ -269,7 +269,7 @@ def matplotlib(self, name=None, **kwargs):
 
         for i, hist in enumerate(self.values):
             color = color_cycle[i]
-            hist.matplotlib(color=color, label=hist.name, **kwargs)
+            hist.plotmatplotlib(color=color, label=hist.name, **kwargs)
             color_cycle.append(color)
 
         if name is not None:
@@ -279,7 +279,7 @@ def matplotlib(self, name=None, **kwargs):
         return ax
 
 class FractionedHistogramMethods(object):
-    def matplotlib(self, name=None, **kwargs):
+    def plotmatplotlib(self, name=None, **kwargs):
         """ Plotting method for
         """
         import matplotlib.pyplot as plt
@@ -319,7 +319,7 @@ def matplotlib(self, name=None, **kwargs):
         return ax
 
 class TwoDimensionallyHistogramMethods(object):
-    def matplotlib(self, name=None, **kwargs):
+    def plotmatplotlib(self, name=None, **kwargs):
         """ Plotting method for Bin of Bin of Count
               name : title of the plot.
               kwargs: matplotlib.collections.QuadMesh properties.
@@ -350,7 +350,7 @@ def matplotlib(self, name=None, **kwargs):
 
 
 class SparselyTwoDimensionallyHistogramMethods(object):
-    def matplotlib(self, name=None, **kwargs):
+    def plotmatplotlib(self, name=None, **kwargs):
         """ Plotting method for SparselyBin of SparselyBin of Count
               name : title of the plot.
               kwargs: matplotlib.collections.QuadMesh properties.

histogrammar/plot/root.py

@@ -67,15 +67,15 @@ def setTH2sparse(sparse, yminBin, ymaxBin, th2):
 # "Public" methods; what we want to attach to the Histogram as a mix-in.
 
 class HistogramMethods(object):
-    def root(self, name, title="", binType="D"):
+    def plotroot(self, name, title="", binType="D"):
         import ROOT
         constructor = getattr(ROOT, "TH1" + binType)
         th1 = constructor(name, title, len(self.values), self.low, self.high)
         setTH1(self.entries, [x.entries for x in self.values], self.underflow.entries, self.overflow.entries, th1)
         return th1
 
 class SparselyHistogramMethods(object):
-    def root(self, name, title="", binType="D"):
+    def plotroot(self, name, title="", binType="D"):
         import ROOT
         constructor = getattr(ROOT, "TH1" + binType)
         if self.minBin is None or self.maxBin is None:
@@ -87,7 +87,7 @@ def root(self, name, title="", binType="D"):
         return th1
 
 class ProfileMethods(object):
-    def root(self, name, title=""):
+    def plotroot(self, name, title=""):
         import ROOT
         tprofile = ROOT.TProfile(name, title, len(self.values), self.low, self.high)
         tprofile.SetBinContent(0, self.underflow.entries*self.underflow.entries)
@@ -103,7 +103,7 @@ def root(self, name, title=""):
         return tprofile
 
 class SparselyProfileMethods(object):
-    def root(self, name, title=""):
+    def plotroot(self, name, title=""):
         import ROOT
         if self.minBin is None or self.maxBin is None:
             tprofile = ROOT.TProfile(name, title, 1, self.origin, self.origin + 1.0)
@@ -124,7 +124,7 @@ def root(self, name, title=""):
         return tprofile
 
 class ProfileErrMethods(object):
-    def root(self, name, title=""):
+    def plotroot(self, name, title=""):
         import ROOT
         tprofile = ROOT.TProfile(name, title, len(self.values), self.low, self.high)
         tprofile.SetBinContent(0, self.underflow.entries*self.underflow.entries)
@@ -140,7 +140,7 @@ def root(self, name, title=""):
         return tprofile
 
 class SparselyProfileErrMethods(object):
-    def root(self, name, title=""):
+    def plotroot(self, name, title=""):
         import ROOT
         if self.minBin is None or self.maxBin is None:
             tprofile = ROOT.TProfile(name, title, 1, self.origin, self.origin + 1.0)
@@ -161,15 +161,15 @@ def root(self, name, title=""):
         return tprofile
 
 class StackedHistogramMethods(object):
-    def root(self, *names):
+    def plotroot(self, *names):
         import ROOT
         out = OrderedDict()
         for n, (c, v) in zip(names, self.cuts):
             if isinstance(n, (list, tuple)) and len(n) == 2:
                 name, title = n
             else:
                 name, title = n, ""
-            out[c] = v.root(name, title)
+            out[c] = v.plotroot(name, title)
 
         def Draw(self, options=""):
             first = True
@@ -183,15 +183,15 @@ def Draw(self, options=""):
         return out
 
 class PartitionedHistogramMethods(object):
-    def root(self, *names):
+    def plotroot(self, *names):
         import ROOT
         out = OrderedDict()
         for n, (c, v) in zip(names, self.cuts):
             if isinstance(n, (list, tuple)) and len(n) == 2:
                 name, title = n
             else:
                 name, title = n, ""
-            out[c] = v.root(name, title)
+            out[c] = v.plotroot(name, title)
 
         def Draw(self, options=""):
             first = True
@@ -205,9 +205,9 @@ def Draw(self, options=""):
         return out
 
 class FractionedHistogramMethods(object):
-    def root(self, numeratorName, denominatorName):
+    def plotroot(self, numeratorName, denominatorName):
         import ROOT
-        denominator = self.denominator.root(denominatorName)
+        denominator = self.denominator.plotroot(denominatorName)
         num = denominator.GetNbinsX()
         low = denominator.GetBinLowEdge(1)
         high = denominator.GetBinLowEdge(num) + denominator.GetBinWidth(num)
@@ -225,7 +225,7 @@ def root(self, numeratorName, denominatorName):
         return ROOT.TEfficiency(numerator, denominator)
 
 class TwoDimensionallyHistogramMethods(object):
-    def root(self, name, title="", binType="D"):
+    def plotroot(self, name, title="", binType="D"):
         import ROOT
         constructor = getattr(ROOT, "TH2" + binType)
         sample = self.values[0]
@@ -236,7 +236,7 @@ def root(self, name, title="", binType="D"):
         return th2
 
 class SparselyTwoDimensionallyHistogramMethods(object):
-    def root(self, name, title="", binType="D"):
+    def plotroot(self, name, title="", binType="D"):
         import ROOT
         constructor = getattr(ROOT, "TH2" + binType)
         yminBin, ymaxBin, ynum, ylow, yhigh = prepareTH2sparse(self)