simplify docs

doc/openmatrix.rst

@@ -8,7 +8,7 @@ Larch embeds a python interface for interacting with
 `open matrix (OMX) <https://github.com/osPlanning/omx/wiki>`_ files.
 This data format rests on HDF5, the exact same underlying technology used in
 :class:`DT` files.  This makes merging and linking to open matrix data easy and
-fun. 
+fun.
 
 .. py:class:: OMX(filename)
 
@@ -39,24 +39,6 @@ Importing Data
 	(this may be relaxed in the future). The matrix must already be set up
 	with the correct size before importing the datatable.
 
-	Parameters
-	----------
-	filepath : str or buffer
-		This argument will be fed directly to the :func:`pandas.read_csv` function.
-	one_based : bool
-		If True (the default) it is assumed that zones are indexed sequentially starting with 1 
-		(as is typical for travel demand forecasting applications).
-		Otherwise, it is assumed that zones are indexed sequentially starting with 0 (typical for other c and python applications).
-	chunksize : int
-		The number of rows of the source file to read as a chunk.  Reading a giant file in moderate sized
-		chunks can be much faster and less memory intensive than reading the entire file.
-	column_map : dict or None
-		If given, this dict maps columns of the input file to OMX tables, with the keys as
-		the columns in the input and the values as the tables in the output.
-	default_atom : str or dtype
-		The default atomic type for imported data when the table does not already exist in this
-		openmatrix.
-
 
 
 
@@ -71,22 +53,6 @@ Importing Data
 	This method is functionally the same as :meth:`import_datatable` but uses a different implementation.
 	It is much more memory intensive but also much faster than the non-3d version.
 
-	Parameters
-	----------
-	filepath : str or buffer
-		This argument will be fed directly to the :func:`pandas.read_csv` function.
-	one_based : bool
-		If True (the default) it is assumed that zones are indexed sequentially starting with 1 
-		(as is typical for travel demand forecasting applications).
-		Otherwise, it is assumed that zones are indexed sequentially starting with 0 (typical for other c and python applications).
-	chunksize : int
-		The number of rows of the source file to read as a chunk.  Reading a giant file in moderate sized
-		chunks can be much faster and less memory intensive than reading the entire file.
-	default_atom : str or dtype
-		The default atomic type for imported data when the table does not already exist in this
-		openmatrix.
-
-
 
 
 
@@ -98,25 +64,6 @@ Importing Data
 	(this may be relaxed in the future). The matrix must already be set up
 	with the correct shape before importing the datatable.
 
-	Parameters
-	----------
-	filepath : str or buffer
-		This argument will be fed directly to the :func:`pandas.read_csv` function.
-	chunksize : int
-		The number of rows of the source file to read as a chunk.  Reading a giant file in moderate sized
-		chunks can be much faster and less memory intensive than reading the entire file.
-	column_map : dict or None
-		If given, this dict maps columns of the input file to OMX tables, with the keys as
-		the columns in the input and the values as the tables in the output.
-	n_rows : int or None
-		If given, this is the number of rows in the source file.  It can be omitted and will 
-		be discovered automatically, but only for source files with consecutive zone numbering.
-	zone_ix : str or None
-		If given, this is the column name in the source file that gives the zone numbers.
-	zone_ix1 : 1 or 0
-		The smallest zone number.  Defaults to 1
-	drop_zone : int or None
-		If given, zones with this number (typically 0 or -1) will be ignored.