File tables-pr862-lowercasefdtype.patch of Package python-tables
From 88668dcf041a52f0da51bee04da3c2f95eb69e41 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Zbigniew=20J=C4=99drzejewski-Szmek?= <zbyszek@in.waw.pl>
Date: Sun, 24 Jan 2021 16:36:21 +0100
Subject: [PATCH 1/7] Use lowercase float/int as numpy dtype
Float64 is gone with numpy 1.20, which causes doctests to fail
(https://bugzilla.redhat.com/show_bug.cgi?id=1914335).
Similarly all uses of Float32, Int32 should be replaced by float32 and int32.
>>> numpy.__version__
'1.19.4'
>>> [k for k in numpy.sctypeDict.keys() if str(k).lower().startswith('float')]
['float16', 'Float16', 'float32', 'Float32', 'float64', 'Float64', 'float128', 'Float128', 'float_', 'float']
>>> numpy.__version__
'1.20.0rc2'
>>> [k for k in numpy.sctypeDict.keys() if str(k).lower().startswith('float')]
['float16', 'float32', 'float64', 'float128', 'float_', 'float']
---
bench/bsddb-table-bench.py | 10 +++++-----
bench/postgres-search-bench.py | 4 ++--
bench/pytables-search-bench.py | 6 +++---
bench/recarray2-test.py | 2 +-
bench/shelve-bench.py | 10 +++++-----
bench/sqlite-search-bench.py | 4 ++--
tables/atom.py | 2 +-
7 files changed, 19 insertions(+), 19 deletions(-)
Index: tables-3.6.1/bench/bsddb-table-bench.py
===================================================================
--- tables-3.6.1.orig/bench/bsddb-table-bench.py
+++ tables-3.6.1/bench/bsddb-table-bench.py
@@ -83,11 +83,11 @@ def createFile(filename, totalrows, recs
# Get the record object associated with the new table
if recsize == "big":
isrec = Big()
- arr = np.array(np.arange(32), type=np.Float64)
- arr2 = np.array(np.arange(32), type=np.Float64)
+ arr = np.array(np.arange(32), type=np.float64)
+ arr2 = np.array(np.arange(32), type=np.float64)
elif recsize == "medium":
isrec = Medium()
- arr = np.array(np.arange(2), type=np.Float64)
+ arr = np.array(np.arange(2), type=np.float64)
else:
isrec = Small()
# print d
@@ -107,8 +107,8 @@ def createFile(filename, totalrows, recs
#d['TDCcount'] = i % 256
d['ADCcount'] = (i * 256) % (1 << 16)
if recsize == "big":
- #d.float1 = np.array([i]*32, np.Float64)
- #d.float2 = np.array([i**2]*32, np.Float64)
+ #d.float1 = np.array([i]*32, np.float64)
+ #d.float2 = np.array([i**2]*32, np.float64)
arr[0] = 1.1
d['float1'] = arr
arr2[0] = 2.2
Index: tables-3.6.1/bench/postgres-search-bench.py
===================================================================
--- tables-3.6.1.orig/bench/postgres-search-bench.py
+++ tables-3.6.1/bench/postgres-search-bench.py
@@ -15,11 +15,11 @@ def flatten(l):
def fill_arrays(start, stop):
- col_i = numpy.arange(start, stop, type=numpy.Int32)
+ col_i = numpy.arange(start, stop, type=numpy.int32)
if userandom:
col_j = numpy.random.uniform(0, nrows, size=[stop - start])
else:
- col_j = numpy.array(col_i, type=numpy.Float64)
+ col_j = numpy.array(col_i, type=numpy.float64)
return col_i, col_j
# Generator for ensure pytables benchmark compatibility
Index: tables-3.6.1/bench/pytables-search-bench.py
===================================================================
--- tables-3.6.1.orig/bench/pytables-search-bench.py
+++ tables-3.6.1/bench/pytables-search-bench.py
@@ -37,11 +37,11 @@ def create_db(filename, nrows):
stop = (j + 1) * step
if stop > nrows:
stop = nrows
- arr_f8 = np.arange(i, stop, type=np.Float64)
- arr_i4 = np.arange(i, stop, type=np.Int32)
+ arr_f8 = np.arange(i, stop, type=np.float64)
+ arr_i4 = np.arange(i, stop, type=np.int32)
if userandom:
arr_f8 += np.random.normal(0, stop * scale, shape=[stop - i])
- arr_i4 = np.array(arr_f8, type=np.Int32)
+ arr_i4 = np.array(arr_f8, type=np.int32)
recarr = np.rec.fromarrays([arr_i4, arr_i4, arr_f8, arr_f8])
table.append(recarr)
j += 1
Index: tables-3.6.1/bench/recarray2-test.py
===================================================================
--- tables-3.6.1.orig/bench/recarray2-test.py
+++ tables-3.6.1/bench/recarray2-test.py
@@ -22,7 +22,7 @@ delta = 0.000001
# Creation of recarrays objects for test
x1 = np.array(np.arange(reclen))
x2 = chararray.array(None, itemsize=7, shape=reclen)
-x3 = np.array(np.arange(reclen, reclen * 3, 2), np.Float64)
+x3 = np.array(np.arange(reclen, reclen * 3, 2), np.float64)
r1 = recarray.fromarrays([x1, x2, x3], names='a,b,c')
r2 = recarray2.fromarrays([x1, x2, x3], names='a,b,c')
Index: tables-3.6.1/bench/shelve-bench.py
===================================================================
--- tables-3.6.1.orig/bench/shelve-bench.py
+++ tables-3.6.1/bench/shelve-bench.py
@@ -2,7 +2,7 @@
from __future__ import print_function
from tables import *
-import numpy as NA
+import numpy as np
import struct
import sys
import shelve
@@ -45,8 +45,8 @@ class Medium(IsDescription):
class Big(IsDescription):
name = StringCol(itemsize=16) # 16-character String
- #float1 = Float64Col(shape=32, dflt=NA.arange(32))
- #float2 = Float64Col(shape=32, dflt=NA.arange(32))
+ #float1 = Float64Col(shape=32, dflt=np.arange(32))
+ #float2 = Float64Col(shape=32, dflt=np.arange(32))
float1 = Float64Col(shape=32, dflt=range(32))
float2 = Float64Col(shape=32, dflt=[2.2] * 32)
ADCcount = Int16Col() # signed short integer
@@ -65,8 +65,8 @@ def createFile(filename, totalrows, recs
# Get the record object associated with the new table
if recsize == "big":
d = Big()
- arr = NA.array(NA.arange(32), type=NA.Float64)
- arr2 = NA.array(NA.arange(32), type=NA.Float64)
+ arr = np.arange(32, dtype=np.float64)
+ arr2 = np.arange(32, dtype=np.float64)
elif recsize == "medium":
d = Medium()
else:
@@ -87,15 +87,15 @@ def createFile(filename, totalrows, recs
#d.TDCcount = i % 256
d.ADCcount = (i * 256) % (1 << 16)
if recsize == "big":
- #d.float1 = NA.array([i]*32, NA.Float64)
- #d.float2 = NA.array([i**2]*32, NA.Float64)
+ #d.float1 = np.array([i]*32, np.float64)
+ #d.float2 = np.array([i**2]*32, np.float64)
arr[0] = 1.1
d.float1 = arr
arr2[0] = 2.2
d.float2 = arr2
pass
else:
- d.float1 = NA.array([i ** 2] * 2, NA.Float64)
+ d.float1 = np.array([i ** 2] * 2, np.float64)
#d.float1 = float(i)
#d.float2 = float(i)
d.grid_i = i
Index: tables-3.6.1/bench/sqlite-search-bench.py
===================================================================
--- tables-3.6.1.orig/bench/sqlite-search-bench.py
+++ tables-3.6.1/bench/sqlite-search-bench.py
@@ -136,10 +136,10 @@ CREATE INDEX ivar3 ON small(var3);
if randomvalues:
var3 = np.random.uniform(minimum, maximum, shape=[j - i])
else:
- var3 = np.arange(i, j, type=np.Float64)
+ var3 = np.arange(i, j, type=np.float64)
if noise:
var3 += np.random.uniform(-3, 3, shape=[j - i])
- var2 = np.array(var3, type=np.Int32)
+ var2 = np.array(var3, type=np.int32)
var1 = np.array(None, shape=[j - i], dtype='s4')
if not heavy:
for n in range(j - i):
Index: tables-3.6.1/tables/atom.py
===================================================================
--- tables-3.6.1.orig/tables/atom.py
+++ tables-3.6.1/tables/atom.py
@@ -338,7 +338,7 @@ class Atom(metaclass=MetaAtom):
Traceback (most recent call last):
...
ValueError: unknown NumPy scalar type: 'S5'
- >>> Atom.from_sctype('Float64')
+ >>> Atom.from_sctype('float64')
Float64Atom(shape=(), dflt=0.0)
"""
Index: tables-3.6.1/doc/source/cookbook/custom_data_types.rst
===================================================================
--- tables-3.6.1.orig/doc/source/cookbook/custom_data_types.rst
+++ tables-3.6.1/doc/source/cookbook/custom_data_types.rst
@@ -65,9 +65,8 @@ Submitted by Kevin R. Thornton.
if __name__ == '__main__':
- x = np.array(np.random.rand(100))
- x=np.reshape(x,(50,2))
- x.dtype=[('x',np.float),('y',np.float)]
+ x = np.random.rand(100).reshape(50,2)
+ x.dtype = [('x',float), ('y',float)]
h5file = tables.open_file('tester.hdf5', 'w')
mtab = h5file.createDerivedFromTable(h5file.root, 'random', x)
Index: tables-3.6.1/examples/array4.py
===================================================================
--- tables-3.6.1.orig/examples/array4.py
+++ tables-3.6.1/examples/array4.py
@@ -9,7 +9,7 @@ fileh = tables.open_file(file, mode="w")
# Get the root group
group = fileh.root
# Set the type codes to test
-dtypes = [np.int8, np.uint8, np.int16, np.int, np.float32, np.float]
+dtypes = [np.int8, np.uint8, np.int16, int, np.float32, float]
i = 1
for dtype in dtypes:
# Create an array of dtype, with incrementally bigger ranges
Index: tables-3.6.1/tables/hdf5extension.pyx
===================================================================
--- tables-3.6.1.orig/tables/hdf5extension.pyx
+++ tables-3.6.1/tables/hdf5extension.pyx
@@ -1447,7 +1447,7 @@ cdef class Array(Leaf):
chunkshapes = getshape(self.rank, self.dims_chunk)
# object arrays should not be read directly into memory
- if atom.dtype != numpy.object:
+ if atom.dtype != object:
# Get the fill value
dflts = numpy.zeros((), dtype=atom.dtype)
fill_data = dflts.data
Index: tables-3.6.1/tables/tests/test_vlarray.py
===================================================================
--- tables-3.6.1.orig/tables/tests/test_vlarray.py
+++ tables-3.6.1/tables/tests/test_vlarray.py
@@ -181,7 +181,7 @@ class BasicTestCase(common.TempFileMixin
vlarray = self.h5file.get_node("/vlarray1")
# Get a numpy array of objects
- rows = numpy.array(vlarray[:], dtype=numpy.object)
+ rows = numpy.array(vlarray[:], dtype=object)
for slc in [0, numpy.array(1), 2, numpy.array([3]), [4]]:
# Read the rows in slc
Index: tables-3.6.1/tables/tests/test_numpy.py
===================================================================
--- tables-3.6.1.orig/tables/tests/test_numpy.py
+++ tables-3.6.1/tables/tests/test_numpy.py
@@ -462,7 +462,6 @@ class TableReadTestCase(common.TempFileM
for colname in table.colnames:
numcol = table.read(field=colname)
typecol = table.coltypes[colname]
- #nctypecode = np.typeNA[numcol.dtype.char[0]]
nctypecode = np.sctypeDict[numcol.dtype.char[0]]
if typecol != "string":
if common.verbose:
Index: tables-3.6.1/tables/utilsextension.pyx
===================================================================
--- tables-3.6.1.orig/tables/utilsextension.pyx
+++ tables-3.6.1/tables/utilsextension.pyx
@@ -220,7 +220,7 @@ cdef str cstr_to_pystr(const char* cstri
import_array()
# NaN-aware sorting with NaN as the greatest element
-# numpy.isNaN only takes floats, this should work for strings too
+# numpy.isnan only takes floats, this should work for strings too
cpdef nan_aware_lt(a, b): return a < b or (b != b and a == a)
cpdef nan_aware_le(a, b): return a <= b or b != b
cpdef nan_aware_gt(a, b): return a > b or (a != a and b == b)
Index: tables-3.6.1/examples/tutorial2.py
===================================================================
--- tables-3.6.1.orig/examples/tutorial2.py
+++ tables-3.6.1/examples/tutorial2.py
@@ -62,9 +62,8 @@ for tablename in ("TParticle1", "TPartic
particle['lati'] = i
particle['longi'] = 10 - i
# Detectable errors start here. Play with them!
- particle['pressure'] = np.array(
- i * np.arange(2 * 3)).reshape((2, 4)) # Incorrect
- # particle['pressure'] = array(i*arange(2*3)).reshape((2,3)) # Correct
+ particle['pressure'] = i * np.arange(2 * 4).reshape(2, 4) # Incorrect
+ # particle['pressure'] = i * arange(2 * 3).reshape(2, 3) # Correct
# End of errors
particle['temperature'] = (i ** 2) # Broadcasting
# This injects the Record values
