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Klaus Wölfel
wendelin
Commits
53341de0
Commit
53341de0
authored
Nov 28, 2023
by
Klaus Wölfel
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erp5_wendelin: Data Array View Line implementation using unstructured_to_structured method
parent
07dbbed6
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bt5/erp5_wendelin/DocumentTemplateItem/portal_components/document.erp5.DataArrayViewLine.py
...Item/portal_components/document.erp5.DataArrayViewLine.py
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bt5/erp5_wendelin/DocumentTemplateItem/portal_components/document.erp5.DataArrayViewLine.py
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53341de0
...
...
@@ -4,26 +4,21 @@
# Copyright (c) 2018 Nexedi SA and Contributors. All Rights Reserved.
# Klaus Wölfel <klaus@nexedi.com>
#
# WARNING: This program as such is intended to be used by professional
# programmers who take the whole responsability of assessing all potential
# consequences resulting from its eventual inadequacies and bugs
# End users who are looking for a ready-to-use solution with commercial
# garantees and support are strongly adviced to contract a Free Software
# Service Company
# This program is free software: you can Use, Study, Modify and Redistribute
# it under the terms of the GNU General Public License version 3, or (at your
# option) any later version, as published by the Free Software Foundation.
#
# This program is Free Software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
# You can also Link and Combine this program with other software covered by
# the terms of any of the Free Software licenses or any of the Open Source
# Initiative approved licenses and Convey the resulting work. Corresponding
# source of such a combination shall include the source code for all other
# software used.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# This program is distributed WITHOUT ANY WARRANTY; without even the implied
# warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
# See COPYING file for full licensing terms.
# See https://www.nexedi.com/licensing for rationale and options.
#
##############################################################################
import
numpy
as
np
...
...
@@ -32,6 +27,142 @@ from Products.ERP5Type.Base import TempBase
from
Products.ERP5Type.Utils
import
createExpressionContext
,
\
evaluateExpressionFromString
def
_get_fields_and_offsets
(
dt
,
offset
=
0
):
"""
Returns a flat list of (dtype, count, offset) tuples of all the
scalar fields in the dtype "dt", including nested fields, in left
to right order.
"""
# counts up elements in subarrays, including nested subarrays, and returns
# base dtype and count
def
count_elem
(
dt
):
count
=
1
while
dt
.
shape
!=
():
for
size
in
dt
.
shape
:
count
*=
size
dt
=
dt
.
base
return
dt
,
count
fields
=
[]
for
name
in
dt
.
names
:
field
=
dt
.
fields
[
name
]
f_dt
,
f_offset
=
field
[
0
],
field
[
1
]
f_dt
,
n
=
count_elem
(
f_dt
)
if
f_dt
.
names
is
None
:
fields
.
append
((
np
.
dtype
((
f_dt
,
(
n
,))),
n
,
f_offset
+
offset
))
else
:
subfields
=
_get_fields_and_offsets
(
f_dt
,
f_offset
+
offset
)
size
=
f_dt
.
itemsize
for
i
in
range
(
n
):
if
i
==
0
:
# optimization: avoid list comprehension if no subarray
fields
.
extend
(
subfields
)
else
:
fields
.
extend
([(
d
,
c
,
o
+
i
*
size
)
for
d
,
c
,
o
in
subfields
])
return
fields
def
unstructured_to_structured
(
arr
,
dtype
=
None
,
names
=
None
,
align
=
False
,
copy
=
False
,
casting
=
'unsafe'
):
"""
Converts an n-D unstructured array into an (n-1)-D structured array.
The last dimension of the input array is converted into a structure, with
number of field-elements equal to the size of the last dimension of the
input array. By default all output fields have the input array's dtype, but
an output structured dtype with an equal number of fields-elements can be
supplied instead.
Nested fields, as well as each element of any subarray fields, all count
towards the number of field-elements.
Parameters
----------
arr : ndarray
Unstructured array or dtype to convert.
dtype : dtype, optional
The structured dtype of the output array
names : list of strings, optional
If dtype is not supplied, this specifies the field names for the output
dtype, in order. The field dtypes will be the same as the input array.
align : boolean, optional
Whether to create an aligned memory layout.
copy : bool, optional
See copy argument to `numpy.ndarray.astype`. If true, always return a
copy. If false, and `dtype` requirements are satisfied, a view is
returned.
casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
See casting argument of `numpy.ndarray.astype`. Controls what kind of
data casting may occur.
Returns
-------
structured : ndarray
Structured array with fewer dimensions.
Examples
--------
>>> from numpy.lib import recfunctions as rfn
>>> dt = np.dtype([('a', 'i4'), ('b', 'f4,u2'), ('c', 'f4', 2)])
>>> a = np.arange(20).reshape((4,5))
>>> a
array([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19]])
>>> rfn.unstructured_to_structured(a, dt)
array([( 0, ( 1., 2), [ 3., 4.]), ( 5, ( 6., 7), [ 8., 9.]),
(10, (11., 12), [13., 14.]), (15, (16., 17), [18., 19.])],
dtype=[('a', '<i4'), ('b', [('f0', '<f4'), ('f1', '<u2')]), ('c', '<f4', (2,))])
"""
if
arr
.
shape
==
():
raise
ValueError
(
'arr must have at least one dimension'
)
n_elem
=
arr
.
shape
[
-
1
]
if
n_elem
==
0
:
# too many bugs elsewhere for this to work now
raise
NotImplementedError
(
"last axis with size 0 is not supported"
)
if
dtype
is
None
:
if
names
is
None
:
names
=
[
'f{}'
.
format
(
n
)
for
n
in
range
(
n_elem
)]
out_dtype
=
np
.
dtype
([(
n
,
arr
.
dtype
)
for
n
in
names
],
align
=
align
)
fields
=
_get_fields_and_offsets
(
out_dtype
)
dts
,
counts
,
offsets
=
zip
(
*
fields
)
else
:
if
names
is
not
None
:
raise
ValueError
(
"don't supply both dtype and names"
)
# if dtype is the args of np.dtype, construct it
dtype
=
np
.
dtype
(
dtype
)
# sanity check of the input dtype
fields
=
_get_fields_and_offsets
(
dtype
)
if
len
(
fields
)
==
0
:
dts
,
counts
,
offsets
=
[],
[],
[]
else
:
dts
,
counts
,
offsets
=
zip
(
*
fields
)
if
n_elem
!=
sum
(
counts
):
raise
ValueError
(
'The length of the last dimension of arr must '
'be equal to the number of fields in dtype'
)
out_dtype
=
dtype
if
align
and
not
out_dtype
.
isalignedstruct
:
raise
ValueError
(
"align was True but dtype is not aligned"
)
names
=
[
'f{}'
.
format
(
n
)
for
n
in
range
(
len
(
fields
))]
# Use a series of views and casts to convert to a structured array:
# first view as a packed structured array of one dtype
packed_fields
=
np
.
dtype
({
'names'
:
names
,
'formats'
:
[(
arr
.
dtype
,
dt
.
shape
)
for
dt
in
dts
]})
arr
=
np
.
ascontiguousarray
(
arr
).
view
(
packed_fields
)
# next cast to an unpacked but flattened format with varied dtypes
flattened_fields
=
np
.
dtype
({
'names'
:
names
,
'formats'
:
dts
,
'offsets'
:
offsets
,
'itemsize'
:
out_dtype
.
itemsize
})
arr
=
arr
.
astype
(
flattened_fields
,
copy
=
copy
,
casting
=
casting
)
# finally view as the final nested dtype and remove the last axis
return
arr
.
view
(
out_dtype
)[...,
0
]
class
GetIndex
(
TempBase
):
def
__getitem__
(
self
,
idx
):
return
idx
...
...
@@ -51,27 +182,33 @@ class DataArrayViewLine(DataArray):
"""
Get numpy view of Parent Data Array according to index.
"""
zbigarray
=
self
.
getPredecessorValue
().
getArray
()
getindex
=
GetIndex
(
"getindex"
)
index_expression
=
self
.
getIndexExpression
()
dtype_expression
=
self
.
getDtypeExpression
()
zbigarray
=
self
.
getPredecessorValue
().
getArray
()
array_view
=
zbigarray
[:]
name_list
=
self
.
getNameList
()
dtype_expression
=
self
.
getDtypeExpression
()
if
dtype_expression
is
not
None
or
name_list
:
if
dtype_expression
is
None
:
dtype
=
zbigarray
.
dtype
else
:
dtype
=
evaluateExpressionFromString
(
createExpressionContext
(
None
,
portal
=
getindex
),
dtype_expression
)
dtype
=
np
.
dtype
(
dtype
).
newbyteorder
(
'|'
)
# copy=True did not return a copy
if
name_list
:
dtype
.
names
=
name_list
if
zbigarray
.
dtype
.
names
is
None
and
dtype
.
names
is
not
None
:
array_view
=
unstructured_to_structured
(
array_view
,
dtype
)
else
:
array_view
=
array_view
.
view
(
dtype
)
index
=
evaluateExpressionFromString
(
createExpressionContext
(
None
,
portal
=
getindex
),
"python: portal[%s]"
%
index_expression
"python: portal[%s]"
%
self
.
getIndexExpression
()
)
try
:
array_view
=
zbigarray
[
index
]
except
TypeError
:
array
=
zbigarray
[:]
if
isinstance
(
index
,
list
)
and
array_view
.
dtype
.
names
:
array
=
array_view
new_dtype
=
np
.
dtype
({
name
:
array
.
dtype
.
fields
[
name
]
for
name
in
index
})
array_view
=
np
.
ndarray
(
array
.
shape
,
new_dtype
,
array
,
0
,
array
.
strides
)
if
dtype_expression
is
not
None
:
dtype
=
np
.
dtype
(
evaluateExpressionFromString
(
createExpressionContext
(
None
,
portal
=
getindex
),
dtype_expression
))
if
name_list
:
dtype
.
names
=
name_list
return
np
.
ndarray
((
array_view
.
shape
[
0
],),
dtype
,
zbigarray
[:],
0
,
array_view
.
strides
[
0
])
else
:
array_view
=
array_view
[
index
]
return
array_view
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