renamed the LArray class as Array -> larray/inout

Author: alixdamman

larray/inout/common.py

@@ -3,7 +3,7 @@
 import os
 from collections import OrderedDict
 
-from larray.core.array import LArray
+from larray.core.array import Array
 
 
 def _get_index_col(nb_axes=None, index_col=None, wide=True):
@@ -112,7 +112,7 @@ def read(self, keys, *args, **kwargs):
         -------
         Metadata
             List of metadata to load.
-        OrderedDict(str, LArray/Axis/Group)
+        OrderedDict(str, Array/Axis/Group)
             Dictionary containing the loaded objects.
         """
         display = kwargs.pop('display', False)
@@ -144,7 +144,7 @@ def dump(self, metadata, key_values, *args, **kwargs):
         ----------
         metadata: Metadata
             List of metadata to dump.
-        key_values : list of (str, LArray/Axis/Group) pairs
+        key_values : list of (str, Array/Axis/Group) pairs
             Name and data of objects to dump.
         kwargs :
             * display: whether or not to display when the dump of each object is started/done.
@@ -155,7 +155,7 @@ def dump(self, metadata, key_values, *args, **kwargs):
         if metadata is not None:
             self._dump_metadata(metadata)
         for key, value in key_values:
-            if isinstance(value, LArray) and value.ndim == 0:
+            if isinstance(value, Array) and value.ndim == 0:
                 if display:
                     print('Cannot dump {}. Dumping 0D arrays is currently not supported.'.format(key))
                 continue

larray/inout/csv.py

@@ -9,7 +9,7 @@
 import pandas as pd
 import numpy as np
 
-from larray.core.array import LArray, aslarray, ndtest
+from larray.core.array import Array, aslarray, ndtest
 from larray.core.axis import Axis
 from larray.core.constants import nan
 from larray.core.group import Group
@@ -42,7 +42,7 @@ def read_csv(filepath_or_buffer, nb_axes=None, index_col=None, sep=',', headerse
         Separator.
     headersep : str or None, optional
         Separator for headers.
-    fill_value : scalar or LArray, optional
+    fill_value : scalar or Array, optional
         Value used to fill cells corresponding to label combinations which are not present in the input.
         Defaults to NaN.
     sort_rows : bool, optional
@@ -61,7 +61,7 @@ def read_csv(filepath_or_buffer, nb_axes=None, index_col=None, sep=',', headerse
 
     Returns
     -------
-    LArray
+    Array
 
     Notes
     -----
@@ -251,7 +251,7 @@ def read_eurostat(filepath_or_buffer, **kwargs):
 
     Returns
     -------
-    LArray
+    Array
     """
     return read_csv(filepath_or_buffer, sep='\t', headersep=',', **kwargs)
 
@@ -351,7 +351,7 @@ def _read_item(self, key, type, *args, **kwargs):
             raise TypeError()
 
     def _dump_item(self, key, value, *args, **kwargs):
-        if isinstance(value, LArray):
+        if isinstance(value, Array):
             value.to_csv(self._to_filepath(key), *args, **kwargs)
         elif isinstance(value, Axis):
             self.axes[key] = value

larray/inout/excel.py

@@ -11,7 +11,7 @@
 except ImportError:
     xw = None
 
-from larray.core.array import LArray, aslarray
+from larray.core.array import Array, aslarray
 from larray.core.axis import Axis
 from larray.core.constants import nan
 from larray.core.group import Group, _translate_sheet_name
@@ -33,7 +33,7 @@
 def read_excel(filepath, sheet=0, nb_axes=None, index_col=None, fill_value=nan, na=nan,
                sort_rows=False, sort_columns=False, wide=True, engine=None, range=slice(None), **kwargs):
     r"""
-    Reads excel file from sheet name and returns an LArray with the contents
+    Reads excel file from sheet name and returns an Array with the contents
 
     Parameters
     ----------
@@ -49,7 +49,7 @@ def read_excel(filepath, sheet=0, nb_axes=None, index_col=None, fill_value=nan,
         array is assumed to have one axis. Defaults to None.
     index_col : list, optional
         Positions of columns for the n-1 first axes (ex. [0, 1, 2, 3]). Defaults to None (see nb_axes above).
-    fill_value : scalar or LArray, optional
+    fill_value : scalar or Array, optional
         Value used to fill cells corresponding to label combinations which are not present in the input.
         Defaults to NaN.
     sort_rows : bool, optional
@@ -71,7 +71,7 @@ def read_excel(filepath, sheet=0, nb_axes=None, index_col=None, fill_value=nan,
 
     Returns
     -------
-    LArray
+    Array
 
     Examples
     --------
@@ -292,7 +292,7 @@ def _read_item(self, key, type, *args, **kwargs):
 
     def _dump_item(self, key, value, *args, **kwargs):
         kwargs['engine'] = 'xlsxwriter'
-        if isinstance(value, LArray):
+        if isinstance(value, Array):
             value.to_excel(self.handle, key, *args, **kwargs)
         elif isinstance(value, Axis):
             self.axes[key] = value
@@ -395,7 +395,7 @@ def _read_item(self, key, type, *args, **kwargs):
             raise TypeError()
 
     def _dump_item(self, key, value, *args, **kwargs):
-        if isinstance(value, LArray):
+        if isinstance(value, Array):
             self.handle[key] = value.dump(*args, **kwargs)
         elif isinstance(value, Axis):
             self.axes[key] = value

larray/inout/hdf.py

@@ -5,7 +5,7 @@
 import numpy as np
 from pandas import HDFStore
 
-from larray.core.array import LArray
+from larray.core.array import Array
 from larray.core.axis import Axis
 from larray.core.constants import nan
 from larray.core.group import Group, LGroup, _translate_group_key_hdf
@@ -27,7 +27,7 @@ def read_hdf(filepath_or_buffer, key, fill_value=nan, na=nan, sort_rows=False, s
         Path and name where the HDF5 file is stored or a HDFStore object.
     key : str or Group
         Name of the array.
-    fill_value : scalar or LArray, optional
+    fill_value : scalar or Array, optional
         Value used to fill cells corresponding to label combinations which are not present in the input.
         Defaults to NaN.
     sort_rows : bool, optional
@@ -44,7 +44,7 @@ def read_hdf(filepath_or_buffer, key, fill_value=nan, na=nan, sort_rows=False, s
 
     Returns
     -------
-    LArray
+    Array
 
     Examples
     --------
@@ -76,7 +76,7 @@ def read_hdf(filepath_or_buffer, key, fill_value=nan, na=nan, sort_rows=False, s
         # for backward compatibility but any object read from an hdf file should have an attribute 'type'
         _type = attrs.type if 'type' in attrs else 'Array'
         _meta = attrs.metadata if 'metadata' in attrs else None
-        if _type == 'Array':
+        if _type in ['Array', 'LArray']:
             # cartesian product is not necessary if the array was written by LArray
             cartesian_prod = writer != 'LArray'
             res = df_aslarray(pd_obj, sort_rows=sort_rows, sort_columns=sort_columns, fill_value=fill_value,
@@ -141,7 +141,7 @@ def _read_item(self, key, type, *args, **kwargs):
         return read_hdf(self.handle, hdf_key, *args, **kwargs)
 
     def _dump_item(self, key, value, *args, **kwargs):
-        if isinstance(value, LArray):
+        if isinstance(value, Array):
             hdf_key = '/' + key
             value.to_hdf(self.handle, hdf_key, *args, **kwargs)
         elif isinstance(value, Axis):

larray/inout/misc.py

@@ -26,7 +26,7 @@ def from_lists(data, nb_axes=None, index_col=None, fill_value=nan, sort_rows=Fal
         is assumed to have one axis. Defaults to None.
     index_col : list, optional
         Positions of columns for the n-1 first axes (ex. [0, 1, 2, 3]). Defaults to None (see nb_axes above).
-    fill_value : scalar or LArray, optional
+    fill_value : scalar or Array, optional
         Value used to fill cells corresponding to label combinations which are not present in the input.
         Defaults to NaN.
     sort_rows : bool, optional
@@ -41,7 +41,7 @@ def from_lists(data, nb_axes=None, index_col=None, fill_value=nan, sort_rows=Fal
 
     Returns
     -------
-    LArray
+    Array
 
     Examples
     --------
@@ -144,7 +144,7 @@ def from_string(s, nb_axes=None, index_col=None, sep=' ', wide=True, **kwargs):
 
     Returns
     -------
-    LArray
+    Array
 
     Examples
     --------

larray/inout/pandas.py

@@ -6,7 +6,7 @@
 import numpy as np
 import pandas as pd
 
-from larray.core.array import LArray
+from larray.core.array import Array
 from larray.core.axis import Axis, AxisCollection
 from larray.core.group import LGroup
 from larray.core.constants import nan
@@ -74,7 +74,7 @@ def cartesian_product_df(df, sort_rows=False, sort_columns=False, fill_value=nan
 
 def from_series(s, sort_rows=False, fill_value=nan, meta=None, **kwargs):
     r"""
-    Converts Pandas Series into LArray.
+    Converts Pandas Series into Array.
 
     Parameters
     ----------
@@ -91,11 +91,11 @@ def from_series(s, sort_rows=False, fill_value=nan, meta=None, **kwargs):
 
     Returns
     -------
-    LArray
+    Array
 
     See Also
     --------
-    LArray.to_series
+    Array.to_series
 
     Examples
     --------
@@ -137,13 +137,13 @@ def from_series(s, sort_rows=False, fill_value=nan, meta=None, **kwargs):
         name = decode(s.name, 'utf8') if s.name is not None else decode(s.index.name, 'utf8')
         if sort_rows:
             s = s.sort_index()
-        return LArray(s.values, Axis(s.index.values, name), meta=meta)
+        return Array(s.values, Axis(s.index.values, name), meta=meta)
 
 
 def from_frame(df, sort_rows=False, sort_columns=False, parse_header=False, unfold_last_axis_name=False,
                fill_value=nan, meta=None, cartesian_prod=True, **kwargs):
     r"""
-    Converts Pandas DataFrame into LArray.
+    Converts Pandas DataFrame into Array.
 
     Parameters
     ----------
@@ -171,18 +171,18 @@ def from_frame(df, sort_rows=False, sort_columns=False, parse_header=False, unfo
         Metadata (title, description, author, creation_date, ...) associated with the array.
         Keys must be strings. Values must be of type string, int, float, date, time or datetime.
     cartesian_prod : bool, optional
-        Whether or not to expand the dataframe to a cartesian product dataframe as needed by LArray.
+        Whether or not to expand the dataframe to a cartesian product dataframe as needed by Array.
         This is an expensive operation but is absolutely required if you cannot guarantee your dataframe is already
         well formed. If True, arguments `sort_rows` and `sort_columns` must be set to False.
         Defaults to True.
 
     Returns
     -------
-    LArray
+    Array
 
     See Also
     --------
-    LArray.to_frame
+    Array.to_frame
 
     Examples
     --------
@@ -249,13 +249,13 @@ def from_frame(df, sort_rows=False, sort_columns=False, parse_header=False, unfo
 
     axes = AxisCollection([Axis(labels, name) for labels, name in zip(axes_labels, axes_names)])
     data = df.values.reshape(axes.shape)
-    return LArray(data, axes, meta=meta)
+    return Array(data, axes, meta=meta)
 
 
 def df_aslarray(df, sort_rows=False, sort_columns=False, raw=False, parse_header=True, wide=True, cartesian_prod=True,
                 **kwargs):
     r"""
-    Prepare Pandas DataFrame and then convert it into LArray.
+    Prepare Pandas DataFrame and then convert it into Array.
 
     Parameters
     ----------
@@ -280,14 +280,14 @@ def df_aslarray(df, sort_rows=False, sort_columns=False, raw=False, parse_header
         If False, the array is assumed to be stored in "narrow" format: one column per axis plus one value column.
         Defaults to True.
     cartesian_prod : bool, optional
-        Whether or not to expand the dataframe to a cartesian product dataframe as needed by LArray.
+        Whether or not to expand the dataframe to a cartesian product dataframe as needed by Array.
         This is an expensive operation but is absolutely required if you cannot guarantee your dataframe is already
         well formed. If True, arguments `sort_rows` and `sort_columns` must be set to False.
         Defaults to True.
 
     Returns
     -------
-    LArray
+    Array
     """
     # we could inline df_aslarray into the functions that use it, so that the original (non-cartesian) df is freed from
     # memory at this point, but it would be much uglier and would not lower the peak memory usage which happens during

larray/inout/pickle.py

@@ -5,7 +5,7 @@
 
 from larray.core.axis import Axis
 from larray.core.group import Group
-from larray.core.array import LArray
+from larray.core.array import Array
 from larray.core.metadata import Metadata
 from larray.util.misc import pickle
 from larray.inout.session import register_file_handler
@@ -30,7 +30,7 @@ def list_items(self):
         # groups
         items += [(key, 'Group') for key, value in self.data.items() if isinstance(value, Group)]
         # arrays
-        items += [(key, 'Array') for key, value in self.data.items() if isinstance(value, LArray)]
+        items += [(key, 'Array') for key, value in self.data.items() if isinstance(value, Array)]
         return items
 
     def _read_item(self, key, type, *args, **kwargs):
@@ -40,7 +40,7 @@ def _read_item(self, key, type, *args, **kwargs):
             raise TypeError()
 
     def _dump_item(self, key, value, *args, **kwargs):
-        if isinstance(value, (LArray, Axis, Group)):
+        if isinstance(value, (Array, Axis, Group)):
             self.data[key] = value
         else:
             raise TypeError()

larray/inout/sas.py

@@ -14,7 +14,7 @@
 def read_sas(filepath, nb_axes=None, index_col=None, fill_value=nan, na=nan, sort_rows=False, sort_columns=False,
              **kwargs):
     r"""
-    Reads sas file and returns an LArray with the contents
+    Reads sas file and returns an Array with the contents
         nb_axes: number of axes of the output array
     or
         index_col: Positions of columns for the n-1 first axes (ex. [0, 1, 2, 3])

larray/inout/stata.py

@@ -9,7 +9,7 @@
 
 def read_stata(filepath_or_buffer, index_col=None, sort_rows=False, sort_columns=False, **kwargs):
     r"""
-    Reads Stata .dta file and returns an LArray with the contents
+    Reads Stata .dta file and returns an Array with the contents
 
     Parameters
     ----------
@@ -26,15 +26,15 @@ def read_stata(filepath_or_buffer, index_col=None, sort_rows=False, sort_columns
 
     Returns
     -------
-    LArray
+    Array
 
     See Also
     --------
-    LArray.to_stata
+    Array.to_stata
 
     Notes
     -----
-    The round trip to Stata (LArray.to_stata followed by read_stata) loose the name of the "column" axis.
+    The round trip to Stata (Array.to_stata followed by read_stata) loose the name of the "column" axis.
 
     Examples
     --------