[MRG] docs fixes

docs/index.rst

@@ -10,7 +10,6 @@ Documentation
 -------------
 
 .. toctree::
-   :numbered:
    :maxdepth: 2
 
    install

docs/reference/index.rst

@@ -41,26 +41,27 @@ what they are and what they do.
 Type Conversion Table
 ---------------------
 
-The primitive types are converted according to this table:
+Types are converted according to this table:
 
-===========  =========================
-ROOT         NumPy
-===========  =========================
-Char_t       np.int8
-UChar_t      np.uint8
-Short_t      np.int16
-UShort_t     np.uint16
-Int_t        np.int32
-UInt_t       np.uint32
-Float_t      np.float32
-Double_t     np.float64
-Long64_t     np.int64
-ULong64_t    np.uint64
-Bool_t       np.bool
-x[10]        (np.primitivetype, (10,))
-x[nx]        np.object
-vector<t>    np.object
-===========  =========================
+==================  =========================
+ROOT                NumPy
+==================  =========================
+Bool_t              np.bool
+Char_t              np.int8
+UChar_t             np.uint8
+Short_t             np.int16
+UShort_t            np.uint16
+Int_t               np.int32
+UInt_t              np.uint32
+Float_t             np.float32
+Double_t            np.float64
+Long64_t            np.int64
+ULong64_t           np.uint64
+x[10]               (np.primitivetype, (10,))
+x[nx]               np.object
+vector<t>           np.object
+vector<vector<t> >  np.object
+==================  =========================
 
 Variable length arrays (such as ``particletype[nparticle]``) and vectors
 (such as ``vector<int>``) are converted to NumPy arrays of the corresponding

root_numpy/_array.py

@@ -8,15 +8,12 @@
 
 
 def array(arr, copy=True):
-    """
-    Convert a ROOT TArray into a NumPy array.
+    """Convert a ROOT TArray into a NumPy array.
 
     Parameters
     ----------
-
     arr : ROOT TArray
         A ROOT TArrayD, TArrayF, TArrayL, TArrayI or TArrayS
-
     copy : bool, optional (default=True)
         If True (the default) then copy the underlying array, otherwise
         the NumPy array will view the same memory as the ROOT array.
@@ -28,7 +25,6 @@ def array(arr, copy=True):
 
     Examples
     --------
-
     >>> from root_numpy import array
     >>> from ROOT import TArrayD
     >>> a = TArrayD(5)

root_numpy/_evaluate.py

@@ -8,9 +8,7 @@
 
 
 def evaluate(root_object, array):
-    """
-    Evaluate a ROOT histogram, function, graph, or spline at all values
-    in a NumPy array and return the resulting array.
+    """Evaluate a ROOT histogram, function, graph, or spline over an array.
 
     Parameters
     ----------
@@ -44,6 +42,7 @@ def evaluate(root_object, array):
     >>> func = TF2("f2", "x*y")
     >>> evaluate(func, [[1, 1], [1, 2], [3, 1]])
     array([ 1.,  2.,  3.])
+
     """
     import ROOT
     array = np.asarray(array, dtype=np.double)

root_numpy/_graph.py

@@ -8,15 +8,12 @@
 
 
 def fill_graph(graph, array):
-    """
-    Fill a ROOT graph with a NumPy array.
+    """Fill a ROOT graph with a NumPy array.
 
     Parameters
     ----------
-
     hist : a ROOT TGraph or TGraph2D
         The ROOT graph to fill.
-
     array : numpy array of shape [n_samples, n_dimensions]
         The values to fill the graph with. The number of columns
         must match the dimensionality of the graph.

root_numpy/_hist.py

@@ -8,30 +8,24 @@
 
 
 def fill_hist(hist, array, weights=None, return_indices=False):
-    """
-    Fill a ROOT histogram with a NumPy array.
+    """Fill a ROOT histogram with a NumPy array.
 
     Parameters
     ----------
-
     hist : a ROOT TH1, TH2, or TH3
         The ROOT histogram to fill.
-
     array : numpy array of shape [n_samples, n_dimensions]
         The values to fill the histogram with. The number of columns
         must match the dimensionality of the histogram. Supply a flat
         numpy array when filling a 1D histogram.
-
     weights : numpy array
         A flat numpy array of weights for each sample in ``array``.
-
     return_indices : bool, optional (default=False)
         If True then return an array of the bin indices filled for each element
         in ``array``.
 
     Returns
     -------
-
     indices : numpy array or None
         If ``return_indices`` is True, then return an array of the bin indices
         filled for each element in ``array`` otherwise return None.

root_numpy/_matrix.py

@@ -7,24 +7,20 @@
 
 
 def matrix(mat):
-    """
-    Convert a ROOT TMatrix into a NumPy matrix.
+    """Convert a ROOT TMatrix into a NumPy matrix.
 
     Parameters
     ----------
-
     mat : ROOT TMatrixT
         A ROOT TMatrixD or TMatrixF
 
     Returns
     -------
-
     mat : numpy.matrix
         A NumPy matrix
 
     Examples
     --------
-
     >>> from root_numpy import matrix
     >>> from ROOT import TMatrixD
     >>> a = TMatrixD(4, 4)

root_numpy/_sample.py

@@ -7,19 +7,14 @@
 
 
 def random_sample(root_object, n_samples, seed=None):
-    """
-    Construct a NumPy array from a random sampling of a ROOT function or
-    histogram.
+    """Create a random array by sampling a ROOT function or histogram.
 
     Parameters
     ----------
-
     root_object : a ROOT function (TF1, TF2, TF3) or histogram (TH1, TH2, TH3)
         The ROOT function or histogram to sample.
-
     n_samples : positive int
         The number of random samples to generate.
-
     seed : None, positive int or 0, optional (default=None)
         The random seed, set via ROOT.gRandom.SetSeed(seed):
         http://root.cern.ch/root/html/TRandom3.html#TRandom3:SetSeed
@@ -28,7 +23,6 @@ def random_sample(root_object, n_samples, seed=None):
 
     Returns
     -------
-
     array : a numpy array
         A numpy array with a shape corresponding to the dimensionality
         of the function or histogram. A flat array is returned when sampling
@@ -37,7 +31,6 @@ def random_sample(root_object, n_samples, seed=None):
 
     Examples
     --------
-
     >>> from root_numpy import random_sample
     >>> from ROOT import TF1, TF2, TF3
     >>> random_sample(TF1("f1", "TMath::DiLog(x)"), 1E4, seed=1)