def __setitem__(self, key, value):
"""
Set a row, or set of rows, in the array.
It takes different actions depending on the type of the `key`
parameter: if it is an integer, the corresponding table row is
set to `value` (a record, list or tuple capable of being
converted to the table field format). If `key` is a slice, the
row slice determined by it is set to `value` (a NumPy record
array, ``NestedRecArray`` or list of rows).
In addition, NumPy-style point selections are supported. In
particular, if `key` is a list of row coordinates, the set of
rows determined by it is set to `value`. Furthermore, if `key`
is an array of boolean values, only the coordinates where `key`
is ``True`` are set to values from `value`. Note that for the
latter to work it is necessary that `key` list would contain
exactly as many rows as the table has.
.. Note:: When updating the rows of a `VLArray` object which
uses a pseudo-atom, there is a problem: you can only update
values with *exactly* the same size in bytes than the
original row. This is very difficult to meet with
``object`` pseudo-atoms, because ``cPickle`` applied on a
Python object does not guarantee to return the same number
of bytes than over another object, even if they are of the
same class. This effectively limits the kinds of objects
than can be updated in variable-length arrays.
Example of use::
vlarray[0] = vlarray[0] * 2 + 3
vlarray[99] = arange(96) * 2 + 3
# Negative values for the index are supported.
vlarray[-99] = vlarray[5] * 2 + 3
vlarray[1:30:2] = list_of_rows
vlarray[[1,3]] = new_1_and_3_rows
"""
self._v_file._checkWritable()
if is_idx(key):
# If key is not a sequence, convert to it
coords = [key]
value = [value]
elif isinstance(key, slice):
(start, stop, step) = self._processRange(key.start, key.stop,
key.step)
coords = range(start, stop, step)
# Try with a boolean or point selection
elif type(key) in (list, tuple) or isinstance(key, numpy.ndarray):
coords = self._pointSelection(key)
else:
raise IndexError("Invalid index or slice: %r" % (key, ))
# Do the assignment row by row
self._assign_values(coords, value)
def __setitem__(self, key, value):
"""
Set a row, or set of rows, in the array.
It takes different actions depending on the type of the `key`
parameter: if it is an integer, the corresponding table row is
set to `value` (a record, list or tuple capable of being
converted to the table field format). If `key` is a slice, the
row slice determined by it is set to `value` (a NumPy record
array, ``NestedRecArray`` or list of rows).
In addition, NumPy-style point selections are supported. In
particular, if `key` is a list of row coordinates, the set of
rows determined by it is set to `value`. Furthermore, if `key`
is an array of boolean values, only the coordinates where `key`
is ``True`` are set to values from `value`. Note that for the
latter to work it is necessary that `key` list would contain
exactly as many rows as the table has.
.. Note:: When updating the rows of a `VLArray` object which
uses a pseudo-atom, there is a problem: you can only update
values with *exactly* the same size in bytes than the
original row. This is very difficult to meet with
``object`` pseudo-atoms, because ``cPickle`` applied on a
Python object does not guarantee to return the same number
of bytes than over another object, even if they are of the
same class. This effectively limits the kinds of objects
than can be updated in variable-length arrays.
Example of use::
vlarray[0] = vlarray[0] * 2 + 3
vlarray[99] = arange(96) * 2 + 3
# Negative values for the index are supported.
vlarray[-99] = vlarray[5] * 2 + 3
vlarray[1:30:2] = list_of_rows
vlarray[[1,3]] = new_1_and_3_rows
"""
self._v_file._checkWritable()
if is_idx(key):
# If key is not a sequence, convert to it
coords = [key]
value = [value]
elif isinstance(key, slice):
(start, stop, step) = self._processRange(
key.start, key.stop, key.step )
coords = range(start, stop, step)
# Try with a boolean or point selection
elif type(key) in (list, tuple) or isinstance(key, numpy.ndarray):
coords = self._pointSelection(key)
else:
raise IndexError("Invalid index or slice: %r" % (key,))
# Do the assignment row by row
self._assign_values(coords, value)
def __getitem__(self, key):
"""Get a row or a range of rows from the array.
If key argument is an integer, the corresponding array row is returned
as an object of the current flavor. If key is a slice, the range of
rows determined by it is returned as a list of objects of the current
flavor.
In addition, NumPy-style point selections are supported. In
particular, if key is a list of row coordinates, the set of rows
determined by it is returned. Furthermore, if key is an array of
boolean values, only the coordinates where key is True are returned.
Note that for the latter to work it is necessary that key list would
contain exactly as many rows as the array has.
Examples
--------
::
a_row = vlarray[4]
a_list = vlarray[4:1000:2]
a_list2 = vlarray[[0,2]] # get list of coords
a_list3 = vlarray[[0,-2]] # negative values accepted
a_list4 = vlarray[numpy.array([True,...,False])] # array of bools
"""
self._g_check_open()
if is_idx(key):
key = operator.index(key)
# Index out of range protection
if key >= self.nrows:
raise IndexError("Index out of range")
if key < 0:
# To support negative values
key += self.nrows
(start, stop, step) = self._process_range(key, key + 1, 1)
return self.read(start, stop, step)[0]
elif isinstance(key, slice):
start, stop, step = self._process_range(key.start, key.stop,
key.step)
return self.read(start, stop, step)
# Try with a boolean or point selection
elif type(key) in (list, tuple) or isinstance(key, numpy.ndarray):
coords = self._point_selection(key)
return self._read_coordinates(coords)
else:
raise IndexError("Invalid index or slice: %r" % (key, ))
def __getitem__(self, key):
"""Get a row or a range of rows from the array.
If key argument is an integer, the corresponding array row is returned
as an object of the current flavor. If key is a slice, the range of
rows determined by it is returned as a list of objects of the current
flavor.
In addition, NumPy-style point selections are supported. In
particular, if key is a list of row coordinates, the set of rows
determined by it is returned. Furthermore, if key is an array of
boolean values, only the coordinates where key is True are returned.
Note that for the latter to work it is necessary that key list would
contain exactly as many rows as the array has.
Examples
--------
::
a_row = vlarray[4]
a_list = vlarray[4:1000:2]
a_list2 = vlarray[[0,2]] # get list of coords
a_list3 = vlarray[[0,-2]] # negative values accepted
a_list4 = vlarray[numpy.array([True,...,False])] # array of bools
"""
self._g_check_open()
if is_idx(key):
# Index out of range protection
if key >= self.nrows:
raise IndexError("Index out of range")
if key < 0:
# To support negative values
key += self.nrows
(start, stop, step) = self._process_range(key, key + 1, 1)
return self.read(start, stop, step)[0]
elif isinstance(key, slice):
start, stop, step = self._process_range(
key.start, key.stop, key.step)
return self.read(start, stop, step)
# Try with a boolean or point selection
elif type(key) in (list, tuple) or isinstance(key, numpy.ndarray):
coords = self._point_selection(key)
return self._read_coordinates(coords)
else:
raise IndexError("Invalid index or slice: %r" % (key,))
def _interpret_indexing(self, keys):
"""Internal routine used by __getitem__ and __setitem__"""
maxlen = len(self.shape)
shape = (maxlen,)
startl = numpy.empty(shape=shape, dtype=SizeType)
stopl = numpy.empty(shape=shape, dtype=SizeType)
stepl = numpy.empty(shape=shape, dtype=SizeType)
stop_None = numpy.zeros(shape=shape, dtype=SizeType)
if not isinstance(keys, tuple):
keys = (keys,)
nkeys = len(keys)
dim = 0
# Here is some problem when dealing with [...,...] params
# but this is a bit weird way to pass parameters anyway
for key in keys:
ellipsis = 0 # Sentinel
if isinstance(key, type(Ellipsis)):
ellipsis = 1
for diml in range(dim, len(self.shape) - (nkeys - dim) + 1):
startl[dim] = 0
stopl[dim] = self.shape[diml]
stepl[dim] = 1
dim += 1
elif dim >= maxlen:
raise IndexError("Too many indices for object '%s'" %
self._v_pathname)
elif is_idx(key):
# Protection for index out of range
if key >= self.shape[dim]:
raise IndexError("Index out of range")
if key < 0:
# To support negative values (Fixes bug #968149)
key += self.shape[dim]
start, stop, step = self._process_range(
key, key + 1, 1, dim=dim)
stop_None[dim] = 1
elif isinstance(key, slice):
start, stop, step = self._process_range(
key.start, key.stop, key.step, dim=dim)
else:
raise TypeError("Non-valid index or slice: %s" % key)
if not ellipsis:
startl[dim] = start
stopl[dim] = stop
stepl[dim] = step
dim += 1
# Complete the other dimensions, if needed
if dim < len(self.shape):
for diml in range(dim, len(self.shape)):
startl[dim] = 0
stopl[dim] = self.shape[diml]
stepl[dim] = 1
dim += 1
# Compute the shape for the container properly. Fixes #1288792
shape = []
for dim in range(len(self.shape)):
# The negative division operates differently with python scalars
# and numpy scalars (which are similar to C conventions). See:
# http://www.python.org/doc/faq/programming.html#why-does-22-10-return-3
# and
# http://www.peterbe.com/Integer-division-in-programming-languages
# for more info on this issue.
# I've finally decided to rely on the len(xrange) function.
# F. Alted 2006-09-25
# Switch to `lrange` to allow long ranges (see #99).
# use xrange, since it supports large integers as of Python 2.6
# see github #181
new_dim = len(range(startl[dim], stopl[dim], stepl[dim]))
if not (new_dim == 1 and stop_None[dim]):
shape.append(new_dim)
return startl, stopl, stepl, shape
def _interpret_indexing(self, keys):
"""Internal routine used by __getitem__ and __setitem__"""
maxlen = len(self.shape)
shape = (maxlen, )
startl = numpy.empty(shape=shape, dtype=SizeType)
stopl = numpy.empty(shape=shape, dtype=SizeType)
stepl = numpy.empty(shape=shape, dtype=SizeType)
stop_None = numpy.zeros(shape=shape, dtype=SizeType)
if not isinstance(keys, tuple):
keys = (keys, )
nkeys = len(keys)
dim = 0
# Here is some problem when dealing with [...,...] params
# but this is a bit weird way to pass parameters anyway
for key in keys:
ellipsis = 0 # Sentinel
if isinstance(key, type(Ellipsis)):
ellipsis = 1
for diml in xrange(dim, len(self.shape) - (nkeys - dim) + 1):
startl[dim] = 0
stopl[dim] = self.shape[diml]
stepl[dim] = 1
dim += 1
elif dim >= maxlen:
raise IndexError("Too many indices for object '%s'" %
self._v_pathname)
elif is_idx(key):
# Protection for index out of range
if key >= self.shape[dim]:
raise IndexError("Index out of range")
if key < 0:
# To support negative values (Fixes bug #968149)
key += self.shape[dim]
start, stop, step = self._process_range(key,
key + 1,
1,
dim=dim)
stop_None[dim] = 1
elif isinstance(key, slice):
start, stop, step = self._process_range(key.start,
key.stop,
key.step,
dim=dim)
else:
raise TypeError("Non-valid index or slice: %s" % key)
if not ellipsis:
startl[dim] = start
stopl[dim] = stop
stepl[dim] = step
dim += 1
# Complete the other dimensions, if needed
if dim < len(self.shape):
for diml in xrange(dim, len(self.shape)):
startl[dim] = 0
stopl[dim] = self.shape[diml]
stepl[dim] = 1
dim += 1
# Compute the shape for the container properly. Fixes #1288792
shape = []
for dim in xrange(len(self.shape)):
# The negative division operates differently with python scalars
# and numpy scalars (which are similar to C conventions). See:
# http://www.python.org/doc/faq/programming.html#why-does-22-10-return-3
# and
# http://www.peterbe.com/Integer-division-in-programming-languages
# for more info on this issue.
# I've finally decided to rely on the len(xrange) function.
# F. Alted 2006-09-25
# Switch to `lrange` to allow long ranges (see #99).
# use xrange, since it supports large integers as of Python 2.6
# see github #181
new_dim = len(xrange(startl[dim], stopl[dim], stepl[dim]))
if not (new_dim == 1 and stop_None[dim]):
shape.append(new_dim)
return startl, stopl, stepl, shape