diff --git a/docs/conf.py b/docs/conf.py
index 6889c1d..6eec34e 100644
--- a/docs/conf.py
+++ b/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.
diff --git a/histogrammar/defs.py b/histogrammar/defs.py
index 5b1f166..b9bb368 100644
--- a/histogrammar/defs.py
+++ b/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. """
diff --git a/histogrammar/plot/bokeh.py b/histogrammar/plot/bokeh.py
index f451033..2d5495e 100644
--- a/histogrammar/plot/bokeh.py
+++ b/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
 
diff --git a/histogrammar/plot/mpl.py b/histogrammar/plot/matplotlib.py
similarity index 94%
rename from histogrammar/plot/mpl.py
rename to histogrammar/plot/matplotlib.py
index 1f583cb..8165238 100644
--- a/histogrammar/plot/mpl.py
+++ b/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.
diff --git a/histogrammar/plot/root.py b/histogrammar/plot/root.py
index 1ff5f4f..f99d7cd 100644
--- a/histogrammar/plot/root.py
+++ b/histogrammar/plot/root.py
@@ -67,7 +67,7 @@ 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)
@@ -75,7 +75,7 @@ def root(self, name, title="", binType="D"):
         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)
@@ -161,7 +161,7 @@ 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):
@@ -169,7 +169,7 @@ def root(self, *names):
                 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
@@ -183,7 +183,7 @@ 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):
@@ -191,7 +191,7 @@ def root(self, *names):
                 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)
diff --git a/histogrammar/specialized.py b/histogrammar/specialized.py
index b2fb8fe..5f9a0d7 100644
--- a/histogrammar/specialized.py
+++ b/histogrammar/specialized.py
@@ -28,7 +28,7 @@
 
 import histogrammar.plot.root
 import histogrammar.plot.bokeh
-import histogrammar.plot.mpl
+import histogrammar.plot.matplotlib
 
 def Histogram(num, low, high, quantity, selection=unweighted):
     """Convenience function for creating a conventional histogram."""
@@ -85,7 +85,7 @@ def TwoDimensionallySparselyHistogram(xbinWidth, xquantity,
 class HistogramMethods(Bin,
         histogrammar.plot.root.HistogramMethods,
         histogrammar.plot.bokeh.HistogramMethods,
-        histogrammar.plot.mpl.HistogramMethods):
+        histogrammar.plot.matplotlib.HistogramMethods):
     """Methods that are implicitly added to container combinations that look like histograms."""
 
     @property
@@ -123,7 +123,7 @@ def confidenceIntervalValues(self,absz=1.0):
 class SparselyHistogramMethods(SparselyBin,
         histogrammar.plot.root.SparselyHistogramMethods,
         histogrammar.plot.bokeh.SparselyHistogramMethods,
-        histogrammar.plot.mpl.SparselyHistogramMethods):
+        histogrammar.plot.matplotlib.SparselyHistogramMethods):
 
     """Methods that are implicitly added to container combinations that look like sparsely binned histograms."""
 
@@ -142,7 +142,7 @@ def confidenceIntervalValues(self,absz=1.0):
 class ProfileMethods(Bin,
         histogrammar.plot.root.ProfileMethods,
         histogrammar.plot.bokeh.ProfileMethods,
-        histogrammar.plot.mpl.ProfileMethods):
+        histogrammar.plot.matplotlib.ProfileMethods):
     '''Methods that are implicitly added to container combinations that look like a physicist's "profile plot."'''
 
     @property
@@ -176,7 +176,7 @@ def numericalNanflow(self):
 class SparselyProfileMethods(SparselyBin,
         histogrammar.plot.root.SparselyProfileMethods,
         histogrammar.plot.bokeh.SparselyProfileMethods,
-        histogrammar.plot.mpl.SparselyProfileMethods):
+        histogrammar.plot.matplotlib.SparselyProfileMethods):
     '''Methods that are implicitly added to container combinations that look like a sparsely binned physicist's "profile plot."'''
 
     @property
@@ -190,7 +190,7 @@ def factory(self):
 class ProfileErrMethods(Bin,
         histogrammar.plot.root.ProfileErrMethods,
         histogrammar.plot.bokeh.ProfileErrMethods,
-        histogrammar.plot.mpl.ProfileErrMethods):
+        histogrammar.plot.matplotlib.ProfileErrMethods):
 
     '''Methods that are implicitly added to container combinations that look like a physicist's "profile plot."'''
 
@@ -230,7 +230,7 @@ def numericalNanflow(self):
 class SparselyProfileErrMethods(SparselyBin,
         histogrammar.plot.root.SparselyProfileErrMethods,
         histogrammar.plot.bokeh.SparselyProfileErrMethods,
-        histogrammar.plot.mpl.SparselyProfileErrMethods):
+        histogrammar.plot.matplotlib.SparselyProfileErrMethods):
 
     '''Methods that are implicitly added to container combinations that look like a sparsely binned physicist's "profile plot."'''
 
@@ -245,7 +245,7 @@ def factory(self):
 class StackedHistogramMethods(Stack,
         histogrammar.plot.root.StackedHistogramMethods,
         histogrammar.plot.bokeh.StackedHistogramMethods,
-        histogrammar.plot.mpl.StackedHistogramMethods):
+        histogrammar.plot.matplotlib.StackedHistogramMethods):
     """Methods that are implicitly added to container combinations that look like stacked histograms."""
 
     @property
@@ -259,7 +259,7 @@ def factory(self):
 class PartitionedHistogramMethods(IrregularlyBin,
         histogrammar.plot.root.PartitionedHistogramMethods,
         histogrammar.plot.bokeh.PartitionedHistogramMethods,
-        histogrammar.plot.mpl.PartitionedHistogramMethods):
+        histogrammar.plot.matplotlib.PartitionedHistogramMethods):
     """Methods that are implicitly added to container combinations that look like partitioned histograms."""
 
     @property
@@ -273,7 +273,7 @@ def factory(self):
 class FractionedHistogramMethods(Fraction,
         histogrammar.plot.root.FractionedHistogramMethods,
         histogrammar.plot.bokeh.FractionedHistogramMethods,
-        histogrammar.plot.mpl.FractionedHistogramMethods):
+        histogrammar.plot.matplotlib.FractionedHistogramMethods):
     """Methods that are implicitly added to container combinations that look like fractioned histograms."""
 
     @property
@@ -287,7 +287,7 @@ def factory(self):
 class TwoDimensionallyHistogramMethods(Bin,
         histogrammar.plot.root.TwoDimensionallyHistogramMethods,
         histogrammar.plot.bokeh.TwoDimensionallyHistogramMethods,
-        histogrammar.plot.mpl.TwoDimensionallyHistogramMethods):
+        histogrammar.plot.matplotlib.TwoDimensionallyHistogramMethods):
     """Convenience function for creating a conventional, two-dimensional histogram."""
 
     @property
@@ -301,7 +301,7 @@ def factory(self):
 class SparselyTwoDimensionallyHistogramMethods(SparselyBin,
         histogrammar.plot.root.SparselyTwoDimensionallyHistogramMethods,
         histogrammar.plot.bokeh.SparselyTwoDimensionallyHistogramMethods,
-        histogrammar.plot.mpl.SparselyTwoDimensionallyHistogramMethods):
+        histogrammar.plot.matplotlib.SparselyTwoDimensionallyHistogramMethods):
     """Convenience function for creating a sparsely binned, two-dimensional histogram."""
 
     @property
diff --git a/histogrammar/tutorial/__init__.py b/histogrammar/tutorial/__init__.py
new file mode 100644
index 0000000..c18b0fc
--- /dev/null
+++ b/histogrammar/tutorial/__init__.py
@@ -0,0 +1,15 @@
+#!/usr/bin/env python
+
+# Copyright 2016 DIANA-HEP
+# 
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+# 
+#     http://www.apache.org/licenses/LICENSE-2.0
+# 
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/histogrammar/tutorial/cmsdata.py b/histogrammar/tutorial/cmsdata.py
new file mode 100644
index 0000000..4436e48
--- /dev/null
+++ b/histogrammar/tutorial/cmsdata.py
@@ -0,0 +1,186 @@
+#!/usr/bin/env python
+
+# Copyright 2016 DIANA-HEP
+# 
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+# 
+#     http://www.apache.org/licenses/LICENSE-2.0
+# 
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+Most of the examples must use some dataset, so I prepared a sample of CMS public data to be read with no dependencies. The data came from the CERN Open Data portal; it is 50 fb-1 of highly processed particle physics data from the CMS experiment, with 469,384 events selected by the 24 GeV/c isolated muon trigger.
+
+For convenience, it has been converted to compressed JSON. The code that reads it into classes is provided below for you to copy-paste.
+"""
+
+import json
+import math
+import zlib
+
+# handle with Python 3
+try:
+    import urllib2
+except ImportError:
+    import urllib.request as urllib2
+
+# class definitions
+
+class LorentzVector(object):
+    @property
+    def pt(self):
+        return math.sqrt(self.px**2 + self.py**2)
+    @property
+    def p(self):
+        return math.sqrt(self.px**2 + self.py**2 + self.pz**2)
+    @property
+    def mass(self):
+        return math.sqrt(self.E**2 - self.px**2 - self.py**2 - self.pz**2)
+    @property
+    def eta(self):
+        return 0.5*math.log((self.p + self.pz)/(self.p - self.pz))
+    @property
+    def phi(self):
+        return math.atan2(self.py, self.px)
+    def __add__(self, other):
+        out = LorentzVector()
+        out.px = self.px + other.px
+        out.py = self.py + other.py
+        out.pz = self.pz + other.pz
+        out.E = self.E + other.E
+        return out
+    def __repr__(self):
+        return "LorentzVector({}, {}, {}, {})".format(self.px, self.py, self.pz, self.E)
+
+class Jet(LorentzVector):
+    def __init__(self, px, py, pz, E, btag):
+        self.px = px
+        self.py = py
+        self.pz = pz
+        self.E = E
+        self.btag = btag
+    def __repr__(self):
+        return "Jet({}, {}, {}, {}, {})".format(self.px, self.py, self.pz, self.E, self.btag)
+    @staticmethod
+    def fromJson(params):
+        return Jet(params["px"],
+                   params["py"],
+                   params["pz"],
+                   params["E"],
+                   params["btag"])
+                   
+class Muon(LorentzVector):
+    def __init__(self, px, py, pz, E, q, iso):
+        self.px = px
+        self.py = py
+        self.pz = pz
+        self.E = E
+        self.q = q
+        self.iso = iso
+    def __repr__(self):
+        return "Muon({}, {}, {}, {}, {}, {})".format(self.px, self.py, self.pz, self.E, self.q, self.iso)
+    @staticmethod
+    def fromJson(params):
+        return Muon(params["px"],
+                    params["py"],
+                    params["pz"],
+                    params["E"],
+                    params["q"],
+                    params["iso"])
+
+class Electron(LorentzVector):
+    def __init__(self, px, py, pz, E, q, iso):
+        self.px = px
+        self.py = py
+        self.pz = pz
+        self.E = E
+        self.q = q
+        self.iso = iso
+    def __repr__(self):
+        return "Electron({}, {}, {}, {}, {}, {})".format(self.px, self.py, self.pz, self.E, self.q, self.iso)
+    @staticmethod
+    def fromJson(params):
+        return Electron(params["px"],
+                        params["py"],
+                        params["pz"],
+                        params["E"],
+                        params["q"],
+                        params["iso"])
+
+class Photon(LorentzVector):
+    def __init__(self, px, py, pz, E, iso):
+        self.px = px
+        self.py = py
+        self.pz = pz
+        self.E = E
+        self.iso = iso
+    def __repr__(self):
+        return "Photon({}, {}, {}, {}, {})".format(self.px, self.py, self.pz, self.E, self.iso)
+    @staticmethod
+    def fromJson(params):
+        return Photon(params["px"],
+                      params["py"],
+                      params["pz"],
+                      params["E"],
+                      params["iso"])
+
+class MET(object):
+    def __init__(self, px, py):
+        self.px = px
+        self.py = py
+    def __repr__(self):
+        return "MET({}, {})".format(self.px, self.py)
+    @property
+    def pt(self):
+        return math.sqrt(self.px**2 + self.py**2)
+    @staticmethod
+    def fromJson(params):
+        return MET(params["px"], params["py"])
+
+class Event(object):
+    def __init__(self, jets, muons, electrons, photons, met, numPrimaryVertices):
+        self.jets = jets
+        self.muons = muons
+        self.electrons = electrons
+        self.photons = photons
+        self.met = met
+        self.numPrimaryVertices = numPrimaryVertices
+    def __repr__(self):
+        return "Event({}, {}, {}, {}, {}, {})".format(self.jets, self.muons, self.electrons, self.photons, self.met, self.numPrimaryVertices)
+    @staticmethod
+    def fromJson(params):
+        return Event(list(map(Jet.fromJson, params["jets"])),
+                     list(map(Muon.fromJson, params["muons"])),
+                     list(map(Electron.fromJson, params["electrons"])),
+                     list(map(Photon.fromJson, params["photons"])),
+                     MET.fromJson(params["MET"]),
+                     params["numPrimaryVertices"])
+
+# event data iterator
+def EventIterator(location="http://histogrammar.org/docs/data/triggerIsoMu24_50fb-1.json.gz"):
+    READ_BLOCK_SIZE = 1024*8
+    webreader = urllib2.urlopen(location)
+    gzipUnzipper = zlib.decompressobj(16 + zlib.MAX_WBITS)
+    remainder = b""
+    eventsBatch = []
+    while True:
+        if len(eventsBatch) == 0:
+            compressedData = webreader.read(READ_BLOCK_SIZE)
+            data = remainder + gzipUnzipper.decompress(compressedData)
+            if len(data) == 0:
+                raise StopIteration
+            index = data.rfind(b"\n")
+            if index >= 0:
+                data, remainder = data[:index + 1], data[index + 1:]
+            else:
+                remainder = b""
+            eventsBatch = [Event.fromJson(json.loads(line.decode()))
+                               for line in reversed(data.split(b"\n"))
+                               if line != b""]
+        yield eventsBatch.pop()
diff --git a/histogrammar/util.py b/histogrammar/util.py
index 33d1926..1645eef 100644
--- a/histogrammar/util.py
+++ b/histogrammar/util.py
@@ -37,7 +37,7 @@ def _fn(fn):
     return _fn
 
 
-################################################################ attach sub-methods to the fill method
+################################################################ attach sub-methods to the fill and plot methods
 
 class FillMethod(object):
     def __init__(self, container, fill):
@@ -49,6 +49,25 @@ def __init__(self, container, fill):
     def __call__(self, *args, **kwds):
         return self.fill(*args, **kwds)
 
+class PlotMethod(object):
+    def __init__(self, container, plot):
+        self.container = container
+        self.plot = plot
+        try:
+            self.root = container.plotroot
+        except (AttributeError, KeyError):
+            pass
+        try:
+            self.bokeh = container.plotbokeh
+        except (AttributeError, KeyError):
+            pass
+        try:
+            self.matplotlib = container.plotmatplotlib
+        except (AttributeError, KeyError):
+            pass
+    def __call__(self, *args, **kwds):
+        return self.plot(*args, **kwds)
+
 ################################################################ handling key set comparisons with optional keys
 
 def hasKeys(test, required, optional=set()):
diff --git a/histogrammar/version.py b/histogrammar/version.py
index bca80b3..b149386 100644
--- a/histogrammar/version.py
+++ b/histogrammar/version.py
@@ -16,7 +16,7 @@
 
 import re
 
-__version__ = "1.0.3"
+__version__ = "1.0.4"
 
 version = __version__
 
diff --git a/scripts/hgwatch b/scripts/hgwatch
index eaaab6b..5450f35 100755
--- a/scripts/hgwatch
+++ b/scripts/hgwatch
@@ -37,14 +37,15 @@ commandSets = {
     # for --root
     "root": """
 import ROOT
+roothist = None
 
-# Must give hg.root the right number of "name" strings.
+# Must give hg.plot.root the right number of "name" strings.
 if isinstance(hg, Fraction):
-    roothist = hg.root(newName(), newName())
+    roothist = hg.plot.root(newName(), newName())
 elif isinstance(hg, (Stack, IrregularlyBin)):
-    roothist = hg.root(*[newName() for i in xrange(hg.cuts)])
+    roothist = hg.plot.root(*[newName() for i in xrange(hg.cuts)])
 else:
-    roothist = hg.root(newName())
+    roothist = hg.plot.root(newName())
 
 if isinstance(roothist, ROOT.TH2):
     roothist.Draw("colz")    # Preferred visualization.
diff --git a/tests/testbasic.py b/tests/testbasic.py
index 8174d6d..d29b08d 100644
--- a/tests/testbasic.py
+++ b/tests/testbasic.py
@@ -738,8 +738,8 @@ def testPlotHistogram(self):
             if sys.version_info[0] == 2 and sys.version_info[1] == 6:
                 raise ImportError   # Bokeh is not compatible with Python 2.6
             from histogrammar.plot.bokeh import plot,save,view
-            glyph1 = one.bokeh("histogram")
-            glyph2 = two.bokeh()
+            glyph1 = one.plot.bokeh("histogram")
+            glyph2 = two.plot.bokeh()
             c = plot(glyph1,glyph2)
             save(c,"plot_histogram.html")
             #self.checkHtml("example.html")
@@ -754,7 +754,7 @@ def testPlotProfileErr(self):
             if sys.version_info[0] == 2 and sys.version_info[1] == 6:
                 raise ImportError   # Bokeh is not compatible with Python 2.6
             from histogrammar.plot.bokeh import plot,save,view
-            glyph = one.bokeh("errors")
+            glyph = one.plot.bokeh("errors")
             c = plot(glyph)
             save(c,"plot_errors.html")
             #self.checkHtml("example.html")
@@ -773,7 +773,7 @@ def testPlotStack(self):
                 raise ImportError   # Bokeh is not compatible with Python 2.6
             from histogrammar.plot.bokeh import plot,save,view
             s = Stack.build(one,two)
-            glyph = s.bokeh()
+            glyph = s.plot.bokeh()
             c = plot(glyph)
             save(c,"plot_stack.html")
             #self.checkHtml("example.html")