Commit d53371b6 by Kirill Smelkov

bigarray: Add ArrayRef utility

ArrayRef is a tool to find out for a NumPy array its top-level root
parent and remember instructions how to recreate original array from
the root. For example if

	root = arange(1E7)
	z = root[1000:2000]
	a = z[10:20]

`ArrayRef(a)` will find out that the root array for `a` is `root` and
that `a` occupies 1010:1020 bytes in it. The vice versa operation is
also possible, for example given

	aref = ArrayRef(a)

it is possible to restore original `a` from `aref`:

	a_ = aref.deref()
	assert array_equal(a_, a)

the restoration works without copying by creating appropriate view of
root.

ArrayRef should work reliably for arrays of arbitrary dimensions,
strides etc - even fancy arrays created via stride tricks such as arrays
whose elements overlap each other should be supported.

This patch adds ArrayRef with support for regular ndarrays only.

The next patch will add ArrayRef support for BigArray and description
for ArrayRef rationale.
1 parent f785ac07
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
# BigArray submodule for Wendelin # BigArray submodule for Wendelin
# Copyright (C) 2014-2015 Nexedi SA and Contributors. # Copyright (C) 2014-2018 Nexedi SA and Contributors.
# Kirill Smelkov <kirr@nexedi.com> # Kirill Smelkov <kirr@nexedi.com>
# #
# This program is free software: you can Use, Study, Modify and Redistribute # This program is free software: you can Use, Study, Modify and Redistribute
...@@ -38,7 +38,8 @@ of physical RAM. ...@@ -38,7 +38,8 @@ of physical RAM.
from __future__ import print_function from __future__ import print_function
from wendelin.lib.calc import mul from wendelin.lib.calc import mul
from numpy import ndarray, dtype, sign, newaxis, asarray, argmax from numpy import ndarray, dtype, sign, newaxis, asarray, argmax, uint8
from numpy.lib.stride_tricks import DummyArray
import logging import logging
...@@ -473,3 +474,247 @@ class BigArray(object): ...@@ -473,3 +474,247 @@ class BigArray(object):
logging.warn('... address space can not be mapped at once and have to be') logging.warn('... address space can not be mapped at once and have to be')
logging.warn('... processed in chunks.') logging.warn('... processed in chunks.')
raise raise
# ----------------------------------------
# InvalidArrayRef is the exception raised when ArrayRef was tried to be
# dereferenced but found invalid.
class InvalidArrayRef(Exception):
pass
# _flatbytev returns []byte view of array a with index ↑ along with memory
def _flatbytev(a):
b = a[:].view(uint8)
# XXX vvv strictly speaking this might raise internally if numpy sees
# it cannot reshape without copy.
b.shape = -1 # flatten without copy
assert len(b.strides) == 1
if b.strides[0] < 0:
b = b[::-1]
assert b.strides[0] == +1
return b
# ArrayRef is a reference to NumPy array.
#
# The reference is represented by root array object and instructions how to
# create original array as some view of the root.
#
# Use ArrayRef(array) to create reference to an ndarray.
#
# Use .deref() to convert ArrayRef to pointed array object.
class ArrayRef(object):
# .root top-level array object
#
# below broot is []byte view of .root array with index ↑ along with memory
#
# .lo, .hi raw array data is broot[lo:hi]
# .z0 array[0,0,...,0] is pointing ->z0 in broot[lo:hi]
#
# .shape shape and strides of the array with data taken from
# .stridev broot[lo:hi] with .z0 as zero offset.
#
# .dtype dtype of the array
# .atype type of the array (e.g. np.ndarray, np.recarray, etc...)
# deref returns ndarray represented by this reference.
#
# if the reference was found invalid - e.g. it had nonsensical data or
# shape/stride out of range - InvalidArrayRef is raised.
def deref(self):
# broot is []byte view of root array with index ↑ along with memory
broot = _flatbytev(self.root)
# check lo:hi is in within correct range.
if not (0 <= self.lo <= self.hi <= len(broot)):
raise InvalidArrayRef("lo:hi ([%d, %d]) out of correct [0, %d] range" %
(self.lo, self.hi, len(broot)))
# bchild is raw []byte underling data for recreated array
bchild = broot[self.lo:self.hi]
if not (0 <= self.z0 < len(bchild)):
raise InvalidArrayRef("z0 (%d) out of correct [0, %d) range" %
(self.z0, len(bchild)))
# check .shape and .stridev are within correct range, before
# applying unsafe stride tricks.
if len(self.shape) != len(self.stridev):
raise InvalidArrayRef("shape/stridev len mismatch (#shape: %d; #stridev: %d)" %
(len(self.shape), len(self.stridev)))
# [boffmin:boffmax) is recreated array's byte range rooted at its zero point
boffmin = 0
boffmax = 0
for n, s in zip(self.shape, self.stridev):
if n < 0 or int(n) != n:
raise InvalidArrayRef("shape (%s) has invalid element: %s" % (self.shape, n))
if int(s) != s:
raise InvalidArrayRef("stridev %s has invalid element: %s" % (self.stridev, s))
if n == 0:
continue # [0] dimension - does not affect anything
if s > 0:
boffmax += s*(n-1)
else:
boffmin += s*(n-1)
# when element is read - memory is accessed ↑ for itemsize bytes.
# we need to adjust only boffmax because for boffmin it grows ↑ too.
boffmax += self.dtype.itemsize
# [xlo,xhi) is the bchild's range accessed with .shape and .stridev
xlo = self.z0 + boffmin
xhi = self.z0 + boffmax
if not (0 <= xlo <= xhi <= len(bchild)):
raise InvalidArrayRef(
"shape/stride invalid: cover [%d, %d) while raw data range is [%d, %d)" %
(self.lo + xlo, self.lo + xhi, self.lo, self.hi))
# bchild_z0 points to the same underlying data buffer as bchild, but
# zero offset corresponds to zero offset of original array.
#
# len(bchild_z0) == 1, so that we can be sure bchild_z0 -> bchild
# memory pinning always works, not only for positive offsets(*).
#
# (*) we cannot make len(bchild_z0) == 0 since then, when creating
# empty slice, numpy won't adjust the array pointer at all.
#
# it could be also possible to adjust 'data' in __array_interface__
# for += z0, but going explicitly via slicing is more safe.
bchild_z0 = bchild[self.z0: self.z0 + 1]
# restore original array shape/strides/dtype via unsafe trick.
#
# it should be safe to cover memory corresponding to both negative and
# positive offsets to bchild_z0, because bchild_z0 holds reference to
# bchild and bchild covers whole raw data range.
#
# it is also safe because we checked .shape and .stridev not to escape
# from bchild data buffer.
#
# the code below is very close to
#
# a = stride_tricks.as_strided(bchild_z0, shape=self.shape, strides=self.stridev)
#
# but we don't use as_strided() because we also have to change dtype
# with shape and strides in one go - else changing dtype after either
# via a.dtype = ..., or via a.view(dtype=...) can raise errors like
#
# "When changing to a larger dtype, its size must be a
# divisor of the total size in bytes of the last axis
# of the array."
aiface = dict(bchild_z0.__array_interface__)
aiface['shape'] = tuple(self.shape)
aiface['strides'] = tuple(self.stridev)
# type: for now we only care that itemsize is the same
aiface['typestr'] = '|V%d' % self.dtype.itemsize
aiface['descr'] = [('', aiface['typestr'])]
a = asarray(DummyArray(aiface, base=bchild_z0))
# restore full dtype - it should not raise here, since itemsize is the same
a.dtype = self.dtype
# restore full array type
a = a.view(type=self.atype)
# we are done
return a
# ArrayRef(a) creates reference to ndarray a.
def __init__(aref, a):
# find root
root = a # top-level ndarray
while 1:
base = root.base
# top-level ndarray
if base is None:
break
# it was an ndarray (sub)view.
if isinstance(base, ndarray):
root = base
continue
# it might be also ndarray proxy - e.g. np.lib.stride_tricks.DummyArray
# with holding valid .base but not being ndarray.
basebase = getattr(base, 'base', None)
if isinstance(basebase, ndarray):
root = basebase
continue
# base is neither ndarray (sub)class nor ndarray proxy.
#
# it is top-level ndarray with base taken from an object
# with buffer interface, e.g. as here:
#
# In [1]: s = '123'
# In [2]: x = ndarray(shape=(1,), buffer=s, dtype='|S3')
# In [3]: x
# Out[3]: array(['123'], dtype='|S3')
# In [4]: x.base
# Out[4]: '123'
#
# and so it should be treated as top-level ndarray.
break
# broot is []byte view of root with idx ↑ along memory
broot = _flatbytev(root)
# [boffmin:boffmax) is a's byte range rooted at its zero point
boffmin = 0
boffmax = 0
assert len(a.shape) == len(a.strides)
for n, s in zip(a.shape, a.strides):
assert n >= 0
if n == 0:
continue # [0] dimension - does not affect anything
assert n >= 1
if s > 0:
boffmax += s*(n-1)
else:
boffmin += s*(n-1)
# when element is read - memory is accessed ↑ for itemsize bytes.
# we need to adjust only boffmax because for boffmin it grows ↑ too.
boffmax += a.itemsize
# compute bytes δz in between broot's and a's zero points.
# δz should be >= 0, since broot ↑ along memory.
adata = a.__array_interface__.get('data')
rdata = broot.__array_interface__.get('data')
assert adata is not None, "TODO __array_interface__.data = None"
assert rdata is not None, "TODO __array_interface__.data = None"
assert isinstance(adata, tuple), "TODO __array_interface__.data is %r" % (adata,)
assert isinstance(rdata, tuple), "TODO __array_interface__.data is %r" % (rdata,)
# {a,r}data is (data, readonly)
zdelta = adata[0] - rdata[0]
assert zdelta >= 0
# broot[lo:hi] is raw []byte underlying data for a, with z0 pointing
# to a's zero point.
lo = zdelta + boffmin
hi = zdelta + boffmax
assert 0 <= lo <= hi <= len(broot)
z0 = zdelta - lo
# reference is ready for ndarray root
aref.root = root
aref.lo = lo
aref.hi = hi
aref.z0 = z0
aref.shape = a.shape
aref.stridev = a.strides
aref.dtype = a.dtype
aref.atype = type(a)
# we are done
return
# -*- coding: utf-8 -*-
# Wendeling.core.bigarray | Basic tests # Wendeling.core.bigarray | Basic tests
# Copyright (C) 2014-2015 Nexedi SA and Contributors. # Copyright (C) 2014-2018 Nexedi SA and Contributors.
# Kirill Smelkov <kirr@nexedi.com> # Kirill Smelkov <kirr@nexedi.com>
# #
# This program is free software: you can Use, Study, Modify and Redistribute # This program is free software: you can Use, Study, Modify and Redistribute
...@@ -18,12 +19,13 @@ ...@@ -18,12 +19,13 @@
# See COPYING file for full licensing terms. # See COPYING file for full licensing terms.
# See https://www.nexedi.com/licensing for rationale and options. # See https://www.nexedi.com/licensing for rationale and options.
from wendelin.bigarray import BigArray from wendelin.bigarray import BigArray, ArrayRef, _flatbytev
from wendelin.bigfile import BigFile from wendelin.bigfile import BigFile
from wendelin.lib.mem import memcpy from wendelin.lib.mem import memcpy
from wendelin.lib.calc import mul from wendelin.lib.calc import mul
from numpy import ndarray, dtype, int64, int32, uint32, uint8, all, zeros, arange, \ from numpy import ndarray, dtype, int64, int32, uint32, int16, uint8, all, zeros, arange, \
array_equal, asarray array_equal, asarray, newaxis, swapaxes
from numpy.lib.stride_tricks import as_strided
import numpy import numpy
from pytest import raises from pytest import raises
...@@ -588,3 +590,227 @@ def test_bigarray_to_ndarray(): ...@@ -588,3 +590,227 @@ def test_bigarray_to_ndarray():
for i in range(48,65): for i in range(48,65):
C = BigArray(((1<<i)-1,), uint8, Zh) C = BigArray(((1<<i)-1,), uint8, Zh)
raises(MemoryError, 'asarray(C)') raises(MemoryError, 'asarray(C)')
def test_arrayref():
# test data - all items are unique - so we can check array by content
data = zeros(PS, dtype=uint8)
data32 = data.view(uint32)
data32[:] = arange(len(data32), dtype=uint32)
data[:256] = arange(256, dtype=uint8) # first starting bytes are all unique
# regular ndarray without parent at all
ref = ArrayRef(data)
assert ref.root is data
assert ref.lo == 0
assert ref.hi == len(data)
assert ref.z0 == 0
assert ref.shape == data.shape
assert ref.stridev == data.strides
assert ref.dtype == data.dtype
assert array_equal(ref.deref(), data)
# regular ndarrays with parent
ref = ArrayRef(data32)
assert ref.root is data
assert ref.lo == 0
assert ref.hi == len(data)
assert ref.z0 == 0
assert ref.shape == data32.shape
assert ref.stridev == data32.strides
assert ref.dtype == data32.dtype
assert array_equal(ref.deref(), data32)
a = data[100:140]
ref = ArrayRef(a)
assert ref.root is data
assert ref.lo == 100
assert ref.hi == 140
assert ref.z0 == 0
assert ref.shape == (40,)
assert ref.stridev == (1,)
assert ref.dtype == data.dtype
assert array_equal(ref.deref(), a)
a = data[140:100:-1]
ref = ArrayRef(a)
assert ref.root is data
assert ref.lo == 101
assert ref.hi == 141
assert ref.z0 == 39
assert ref.shape == (40,)
assert ref.stridev == (-1,)
assert ref.dtype == data.dtype
assert array_equal(ref.deref(), a)
a = data[100:140:-1] # empty
ref = ArrayRef(a)
assert ref.root is data
assert ref.lo == 0
assert ref.hi == 1
assert ref.z0 == 0
assert ref.shape == (0,)
assert ref.stridev == (1,)
assert ref.dtype == data.dtype
assert array_equal(ref.deref(), a)
# rdata is the same as data[::-1] but without base - i.e. it is toplevel
m = memoryview(data[::-1])
rdata = asarray(m)
assert array_equal(rdata[::-1], data)
assert rdata.strides == (-1,)
m_ = rdata.base
assert isinstance(m_, memoryview)
#assert m_ is m XXX strangely it is another object, not exactly m
# XXX however rdata.strides<0 and no rdata.base.base is enough for us here.
raises(AttributeError, 'm_.base')
a = rdata[100:140]
ref = ArrayRef(a)
assert ref.root is rdata
assert ref.lo == PS - 140
assert ref.hi == PS - 100
assert ref.z0 == 39
assert ref.shape == (40,)
assert ref.stridev == (-1,)
assert ref.dtype == data.dtype
assert array_equal(ref.deref(), a)
for root in (data, rdata):
# refok verifies whether ArrayRef(x) works ok
def refok(x):
ref = ArrayRef(x)
assert ref.root is root
x_ = ref.deref()
assert array_equal(x_, x)
assert x_.dtype == x.dtype
assert type(x_) == type(x)
# check that deref won't access range outside lo:hi - by copying
# root, setting bytes in adjusted root outside lo:hi to either 0x00
# or 0xff and tweaking ref.root = root_.
root_ = numpy.copy(_flatbytev(root[:]))
root_[:ref.lo] = 0
root_[ref.hi:] = 0
ref.root = root_
assert array_equal(ref.deref(), x)
root_[:ref.lo] = 0xff
root_[ref.hi:] = 0xff
assert array_equal(ref.deref(), x)
if root is rdata:
a = root[::-1] # rdata
else:
a = root[:] # data
assert array_equal(a, data)
# subslices that is possible to get by just indexing
refok( a[:] )
refok( a[1:2] )
refok( a[1:10] )
refok( a[1:10:2] )
refok( a[1:10:3] )
refok( a[1:10:-1] ) # empty (.size = 0)
refok( a[10:1:-1] )
refok( a[10:1:-2] )
refok( a[10:1:-3] )
# long chain root -> a -> a[...] -> a[...] -> leaf
l = a[2:118]
l = l.view(uint32)[3:20]
l = l[1:9]
refok(l)
# not aligned - it is not possible to get to resulting slice just by indexing A
refok( a.view(uint8)[2:-2].view(uint32) )
refok( a.view(uint8)[2:-2].view(uint32)[::-1] )
refok( a.view(int64) ) # change of type ↑ in size
refok( a.view(int64)[::-1] )
refok( a.view(int16) ) # change of type ↓ in size
refok( a.view(int16)[::-1] )
# change of type to size not multiple of original
refok( a[1:1+5*10].view('V5') ) # 4 -> 5
refok( a[1:1+5*10].view('V5')[::-1] )
refok( a[1:1+3*10].view('V3') ) # 4 -> 3
refok( a[1:1+3*10].view('V3')[::-1] )
# intermediate parent with <0 stride
r = a[1:1+3*10].view('V3')[::-1]
refok( r[-2:2:-1] )
# 2d array
x = a.view(uint32).reshape((8, -1))
y = swapaxes(x, 0,1)
assert x.shape == (8, PS//(4*8))
assert x.strides == (PS//8, 4)
assert y.shape == (PS//(4*8), 8)
assert y.strides == (4, PS//8)
refok( x )
refok( y )
# array with both >0 and <0 strides
x_ = x[:,::-1]
y_ = y[:,::-1]
assert x_.shape == x.shape
assert x_.strides == (PS//8, -4)
assert y_.shape == y.shape
assert y_.strides == (4, -PS//8)
refok( x_ )
refok( y_ )
# array with [1] dimension
z1 = x[:, newaxis, :]
assert z1.shape == (8, 1, PS//(4*8))
assert z1.strides == (PS//8, 0, 4)
refok(z1)
# array with [0] dimension
z0 = z1[:, 0:0, :]
assert z0.shape == (8, 0, PS//(4*8))
assert z0.strides == (PS//8, 0, 4)
refok(z0)
# tricky array overlapping itself
t = a.view(uint32)
assert t.shape == (PS//4,)
assert t.strides == (4,)
assert t.itemsize == 4
t = as_strided(t, strides=(1,))
assert t.shape == (PS//4,)
assert t.strides == (1,)
assert t.itemsize == 4
refok(t)
# structured dtype
s = a.view(dtype=[('width', '<i2'), ('length', '<i2')])
assert s.shape == (PS//4,)
assert s.strides == (4,)
assert s.itemsize == 4
refok(s)
s_ = s['length']
assert s_.shape == (PS//4,)
assert s_.strides == (4,)
assert s_.itemsize == 2
refok(s_)
# ndarray subclass, e.g. np.recarray
r = s.view(type=numpy.recarray)
assert isinstance(r, numpy.recarray)
assert r.shape == (PS//4,)
assert r.strides == (4,)
assert r.itemsize == 4
assert array_equal(r.length, s['length'])
refok(r)
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