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from __future__ import absolute_import
import os import sys
import numpy as np
# Copy-pasted from Python 3.4's shutil. def which(cmd, mode=os.F_OK | os.X_OK, path=None): """Given a command, mode, and a PATH string, return the path which conforms to the given mode on the PATH, or None if there is no such file.
`mode` defaults to os.F_OK | os.X_OK. `path` defaults to the result of os.environ.get("PATH"), or can be overridden with a custom search path.
""" # Check that a given file can be accessed with the correct mode. # Additionally check that `file` is not a directory, as on Windows # directories pass the os.access check. def _access_check(fn, mode): return (os.path.exists(fn) and os.access(fn, mode) and not os.path.isdir(fn))
# If we're given a path with a directory part, look it up directly rather # than referring to PATH directories. This includes checking relative to the # current directory, e.g. ./script if os.path.dirname(cmd): if _access_check(cmd, mode): return cmd return None
if path is None: path = os.environ.get("PATH", os.defpath) if not path: return None path = path.split(os.pathsep)
if sys.platform == "win32": # The current directory takes precedence on Windows. if not os.curdir in path: path.insert(0, os.curdir)
# PATHEXT is necessary to check on Windows. pathext = os.environ.get("PATHEXT", "").split(os.pathsep) # See if the given file matches any of the expected path extensions. # This will allow us to short circuit when given "python.exe". # If it does match, only test that one, otherwise we have to try # others. if any(cmd.lower().endswith(ext.lower()) for ext in pathext): files = [cmd] else: files = [cmd + ext for ext in pathext] else: # On other platforms you don't have things like PATHEXT to tell you # what file suffixes are executable, so just pass on cmd as-is. files = [cmd]
seen = set() for dir in path: normdir = os.path.normcase(dir) if not normdir in seen: seen.add(normdir) for thefile in files: name = os.path.join(dir, thefile) if _access_check(name, mode): return name return None
# Copy-pasted from numpy.lib.stride_tricks 1.11.2. def _maybe_view_as_subclass(original_array, new_array): if type(original_array) is not type(new_array): # if input was an ndarray subclass and subclasses were OK, # then view the result as that subclass. new_array = new_array.view(type=type(original_array)) # Since we have done something akin to a view from original_array, we # should let the subclass finalize (if it has it implemented, i.e., is # not None). if new_array.__array_finalize__: new_array.__array_finalize__(original_array) return new_array
# Copy-pasted from numpy.lib.stride_tricks 1.11.2. def _broadcast_to(array, shape, subok, readonly): shape = tuple(shape) if np.iterable(shape) else (shape,) array = np.array(array, copy=False, subok=subok) if not shape and array.shape: raise ValueError('cannot broadcast a non-scalar to a scalar array') if any(size < 0 for size in shape): raise ValueError('all elements of broadcast shape must be non-' 'negative') needs_writeable = not readonly and array.flags.writeable extras = ['reduce_ok'] if needs_writeable else [] op_flag = 'readwrite' if needs_writeable else 'readonly' broadcast = np.nditer( (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras, op_flags=[op_flag], itershape=shape, order='C').itviews[0] result = _maybe_view_as_subclass(array, broadcast) if needs_writeable and not result.flags.writeable: result.flags.writeable = True return result
# Copy-pasted from numpy.lib.stride_tricks 1.11.2. def broadcast_to(array, shape, subok=False): """Broadcast an array to a new shape.
Parameters ---------- array : array_like The array to broadcast. shape : tuple The shape of the desired array. subok : bool, optional If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array (default).
Returns ------- broadcast : array A readonly view on the original array with the given shape. It is typically not contiguous. Furthermore, more than one element of a broadcasted array may refer to a single memory location.
Raises ------ ValueError If the array is not compatible with the new shape according to NumPy's broadcasting rules.
Notes ----- .. versionadded:: 1.10.0
Examples -------- >>> x = np.array([1, 2, 3]) >>> np.broadcast_to(x, (3, 3)) array([[1, 2, 3], [1, 2, 3], [1, 2, 3]]) """ return _broadcast_to(array, shape, subok=subok, readonly=True) |