renamed the aslarray() function to asarray()

Author: alixdamman

doc/source/api.rst

@@ -714,7 +714,7 @@ Miscellaneous
 .. autosummary::
    :toctree: _generated/
 
-   aslarray
+   asarray
    from_frame
    from_series
    get_example_filepath

doc/source/tutorial/pandas.rst

@@ -8,9 +8,9 @@ To convert an Array object into a pandas DataFrame, the method :py:meth:`~Array.
     df = pop.to_frame()
     df
 
-Inversely, to convert a DataFrame into an Array object, use the function :py:func:`aslarray`:
+Inversely, to convert a DataFrame into an Array object, use the function :py:func:`asarray`:
 
 .. ipython:: python
 
-    pop = aslarray(df)
+    pop = asarray(df)
     pop

larray/__init__.py

@@ -6,7 +6,7 @@
 from larray.core.axis import Axis, AxisCollection, X
 from larray.core.group import Group, LGroup, LSet, IGroup, union
 from larray.core.array import (Array, zeros, zeros_like, ones, ones_like, empty, empty_like, full,
-                               full_like, sequence, labels_array, ndtest, aslarray, identity, diag,
+                               full_like, sequence, labels_array, ndtest, asarray, identity, diag,
                                eye, all, any, sum, prod, cumsum, cumprod, min, max, mean, ptp, var,
                                std, median, percentile, stack, zip_array_values, zip_array_items)
 from larray.core.session import Session, local_arrays, global_arrays, arrays
@@ -54,7 +54,7 @@
     'Group', 'LGroup', 'LSet', 'IGroup', 'union',
     # array
     'Array', 'zeros', 'zeros_like', 'ones', 'ones_like', 'empty', 'empty_like', 'full',
-    'full_like', 'sequence', 'labels_array', 'ndtest', 'aslarray', 'identity', 'diag', 'eye',
+    'full_like', 'sequence', 'labels_array', 'ndtest', 'asarray', 'identity', 'diag', 'eye',
     'all', 'any', 'sum', 'prod', 'cumsum', 'cumprod', 'min', 'max', 'mean', 'ptp', 'var', 'std',
     'median', 'percentile', 'stack',
     # session
@@ -93,8 +93,8 @@
 
 from larray.core.axis import x
 from larray.core.group import PGroup
-from larray.core.array import (LArray, create_sequential, ndrange, larray_equal, larray_nan_equal,
-                               nan_equal, element_equal)
+from larray.core.array import (LArray, aslarray, create_sequential, ndrange, larray_equal,
+                               larray_nan_equal, nan_equal, element_equal)
 
 
 _deprecated = [
@@ -103,7 +103,7 @@
     # group
     'PGroup',
     # array
-    'LArray',
+    'LArray', 'aslarray',
     'create_sequential', 'ndrange',
     'larray_equal', 'larray_nan_equal', 'nan_equal', 'element_equal',
 ]

larray/core/array.py

@@ -671,7 +671,7 @@ def element_equal(a1, a2, rtol=0, atol=0, nan_equals=False):
     import warnings
     warnings.warn("element_equal() is deprecated. Use array1.eq(array2, rtol, atol, nan_equals) instead.",
                   FutureWarning, stacklevel=2)
-    a1 = aslarray(a1)
+    a1 = asarray(a1)
     return a1.eq(a2, rtol, atol, nan_equals)
 
 
@@ -704,7 +704,7 @@ class Array(ABCArray):
     r"""
     An Array object represents a multidimensional, homogeneous array of fixed-size items with labeled axes.
 
-    The function :func:`aslarray` can be used to convert a NumPy array or Pandas DataFrame into an Array.
+    The function :func:`asarray` can be used to convert a NumPy array or Pandas DataFrame into an Array.
 
     Parameters
     ----------
@@ -1810,7 +1810,7 @@ def align(self, other, join='outer', fill_value=nan, axes=None):
         ValueError: Both arrays are not aligned because align method with join='exact'
         expected Axis(['a0', 'a1'], 'a') to be equal to Axis(['a0', 'a1', 'a2'], 'a')
         """
-        other = aslarray(other)
+        other = asarray(other)
         # reindex does not currently support anonymous axes
         if any(name is None for name in self.axes.names) or any(name is None for name in other.axes.names):
             raise ValueError("arrays with anonymous axes are currently not supported by Array.align")
@@ -5482,12 +5482,12 @@ def opmethod(self, other):
             if isinstance(other, Group) and np.isscalar(other.key):
                 other = other.eval()
 
-            # we could pass scalars through aslarray too but it is too costly performance-wise for only suppressing one
+            # we could pass scalars through asarray too but it is too costly performance-wise for only suppressing one
             # isscalar test and an if statement.
             # TODO: ndarray should probably be converted to larrays because that would harmonize broadcasting rules, but
             # it makes some tests fail for some reason.
             if not isinstance(other, (Array, np.ndarray)) and not np.isscalar(other):
-                other = aslarray(other)
+                other = asarray(other)
 
             if isinstance(other, Array):
                 # TODO: first test if it is not already broadcastable
@@ -5662,7 +5662,7 @@ def equals(self, other, rtol=0, atol=0, nans_equal=False, check_axes=False):
         Parameters
         ----------
         other : Array-like
-            Input array. aslarray() is used on a non-Array input.
+            Input array. asarray() is used on a non-Array input.
         rtol : float or int, optional
             The relative tolerance parameter (see Notes). Defaults to 0.
         atol : float or int, optional
@@ -5777,7 +5777,7 @@ def equals(self, other, rtol=0, atol=0, nans_equal=False, check_axes=False):
         False
         """
         try:
-            other = aslarray(other)
+            other = asarray(other)
         except Exception:
             return False
         try:
@@ -5794,7 +5794,7 @@ def eq(self, other, rtol=0, atol=0, nans_equal=False):
         Parameters
         ----------
         other : Array-like
-            Input array. aslarray() is used on a non-Array input.
+            Input array. asarray() is used on a non-Array input.
         rtol : float or int, optional
             The relative tolerance parameter (see Notes). Defaults to 0.
         atol : float or int, optional
@@ -5855,7 +5855,7 @@ def eq(self, other, rtol=0, atol=0, nans_equal=False):
         a    a0    a1    a2
            True  True  True
         """
-        other = aslarray(other)
+        other = asarray(other)
 
         if rtol == 0 and atol == 0:
             if not nans_equal:
@@ -6406,7 +6406,7 @@ def expand(v, length):
             values = [value[[k]] for k in value.axes[axis]]
         else:
             values = expand(value, num_inserts)
-        values = [aslarray(v) if not isinstance(v, Array) else v
+        values = [asarray(v) if not isinstance(v, Array) else v
                   for v in values]
 
         if label is not None:
@@ -8038,7 +8038,7 @@ def larray_equal(a1, a2):
     msg = "larray_equal() is deprecated. Use Array.equals() instead."
     warnings.warn(msg, FutureWarning, stacklevel=2)
     try:
-        a1 = aslarray(a1)
+        a1 = asarray(a1)
     except Exception:
         return False
     return a1.equals(a2)
@@ -8049,13 +8049,13 @@ def larray_nan_equal(a1, a2):
     msg = "larray_nan_equal() is deprecated. Use Array.equals() instead."
     warnings.warn(msg, FutureWarning, stacklevel=2)
     try:
-        a1 = aslarray(a1)
+        a1 = asarray(a1)
     except Exception:
         return False
     return a1.equals(a2, nans_equal=True)
 
 
-def aslarray(a, meta=None):
+def asarray(a, meta=None):
     r"""
     Converts input as Array if possible.
 
@@ -8075,15 +8075,15 @@ def aslarray(a, meta=None):
     --------
     >>> # NumPy array
     >>> np_arr = np.arange(6).reshape((2,3))
-    >>> aslarray(np_arr)
+    >>> asarray(np_arr)
     {0}*\{1}*  0  1  2
             0  0  1  2
             1  3  4  5
     >>> # Pandas dataframe
     >>> data = {'normal'  : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),
     ...         'reverse' : pd.Series([3., 2., 1.], index=['a', 'b', 'c'])}
     >>> df = pd.DataFrame(data)
-    >>> aslarray(df)
+    >>> asarray(df)
     {0}\{1}  normal  reverse
           a     1.0      3.0
           b     2.0      2.0
@@ -8108,6 +8108,9 @@ def aslarray(a, meta=None):
         return Array(a, meta=meta)
 
 
+aslarray = renamed_to(asarray, 'aslarray')
+
+
 def _check_axes_argument(func):
     @functools.wraps(func)
     def wrapper(*args, **kwargs):
@@ -9319,7 +9322,7 @@ def stack_one(array_name):
         return Session([(array_name, stack_one(array_name)) for array_name in array_names], meta=meta)
     else:
         if res_axes is None or dtype is None:
-            values = [aslarray(v) if not np.isscalar(v) else v
+            values = [asarray(v) if not np.isscalar(v) else v
                       for k, v in items]
 
             if res_axes is None:

larray/core/axis.py

@@ -3451,9 +3451,9 @@ def _flat_lookup(self, flat_indices):
                d1  a1  b2
                d2  a0  b0
         """
-        from larray.core.array import aslarray, Array, stack
+        from larray.core.array import asarray, Array, stack
 
-        flat_indices = aslarray(flat_indices)
+        flat_indices = asarray(flat_indices)
         axes_indices = np.unravel_index(flat_indices, self.shape)
         # This could return an Array with object dtype because axes labels can have different types (but not length)
         # TODO: this should be:

larray/core/metadata.py

@@ -148,8 +148,8 @@ def __larray__(self):
 
     @classmethod
     def from_array(cls, array):
-        from larray.core.array import aslarray
-        array = aslarray(array)
+        from larray.core.array import asarray
+        array = asarray(array)
         if array.ndim != 1:
             raise ValueError("Expected Array object of dimension 1. Got array of dimension {}".format(array.ndim))
 

larray/core/session.py

@@ -14,7 +14,7 @@
 from larray.core.group import Group
 from larray.core.axis import Axis
 from larray.core.constants import nan
-from larray.core.array import Array, get_axes, ndtest, zeros, zeros_like, sequence, aslarray
+from larray.core.array import Array, get_axes, ndtest, zeros, zeros_like, sequence, asarray
 from larray.util.misc import float_error_handler_factory, is_interactive_interpreter, renamed_to, inverseop, basestring
 from larray.inout.session import ext_default_engine, get_file_handler
 

larray/extra/ipfp.py

@@ -1,7 +1,7 @@
 import math
 from collections import deque
 
-from larray.core.array import Array, aslarray, ones, any
+from larray.core.array import Array, asarray, ones, any
 import numpy as np
 
 
@@ -142,7 +142,7 @@ def ipfp(target_sums, a=None, axes=None, maxiter=1000, threshold=0.5, stepstoabo
     assert no_convergence in {'ignore', 'warn', 'raise'}
     assert isinstance(display_progress, bool) or display_progress == 'condensed'
 
-    target_sums = [aslarray(ts) for ts in target_sums]
+    target_sums = [asarray(ts) for ts in target_sums]
 
     n = len(target_sums)
 
@@ -189,7 +189,7 @@ def has_anonymous_axes(a):
         if nzvzs in {'warn', 'fix'} and isinstance(a, Array):
             a = a.copy()
         else:
-            a = aslarray(a)
+            a = asarray(a)
         # TODO: this should be a builtin op
         a = a.rename({i: name if name is not None else 'axis{}'.format(i)
                       for i, name in enumerate(a.axes.names)})

larray/inout/csv.py

@@ -9,7 +9,7 @@
 import pandas as pd
 import numpy as np
 
-from larray.core.array import Array, aslarray, ndtest
+from larray.core.array import Array, asarray, ndtest
 from larray.core.axis import Axis
 from larray.core.constants import nan
 from larray.core.group import Group
@@ -370,7 +370,7 @@ def _read_metadata(self):
 
     def _dump_metadata(self, metadata):
         if len(metadata) > 0:
-            meta = aslarray(metadata)
+            meta = asarray(metadata)
             meta.to_csv(self._to_filepath('__metadata__'), sep=self.sep, wide=False, value_name='')
 
     def save(self):

larray/inout/excel.py

@@ -11,7 +11,7 @@
 except ImportError:
     xw = None
 
-from larray.core.array import Array, aslarray
+from larray.core.array import Array, asarray
 from larray.core.axis import Axis
 from larray.core.constants import nan
 from larray.core.group import Group, _translate_sheet_name
@@ -311,7 +311,7 @@ def _read_metadata(self):
 
     def _dump_metadata(self, metadata):
         if len(metadata) > 0:
-            metadata = aslarray(metadata)
+            metadata = asarray(metadata)
             metadata.to_excel(self.handle, '__metadata__', engine='xlsxwriter', wide=False, value_name='')
 
     def save(self):
@@ -414,7 +414,7 @@ def _read_metadata(self):
 
     def _dump_metadata(self, metadata):
         if len(metadata) > 0:
-            metadata = aslarray(metadata)
+            metadata = asarray(metadata)
             self.handle['__metadata__'] = metadata.dump(wide=False, value_name='')
 
     def save(self):