diff options
Diffstat (limited to 'dev-python/pytables/files')
| -rw-r--r-- | dev-python/pytables/files/pytables-3.6.1-numpy-float.patch | 176 |
1 files changed, 176 insertions, 0 deletions
diff --git a/dev-python/pytables/files/pytables-3.6.1-numpy-float.patch b/dev-python/pytables/files/pytables-3.6.1-numpy-float.patch new file mode 100644 index 000000000000..71fa3b85dacf --- /dev/null +++ b/dev-python/pytables/files/pytables-3.6.1-numpy-float.patch @@ -0,0 +1,176 @@ +From d2a480d14f29fb1d2baee292bc6a2cca4817dcbd 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] 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(-) + +diff --git a/bench/bsddb-table-bench.py b/bench/bsddb-table-bench.py +index dd9f875b..a2e02361 100644 +--- a/bench/bsddb-table-bench.py ++++ b/bench/bsddb-table-bench.py +@@ -83,11 +83,11 @@ def createFile(filename, totalrows, recsize, verbose): + # 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, recsize, verbose): + #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 +diff --git a/bench/postgres-search-bench.py b/bench/postgres-search-bench.py +index d2c9f4f4..7fe83f6a 100644 +--- a/bench/postgres-search-bench.py ++++ b/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 +diff --git a/bench/pytables-search-bench.py b/bench/pytables-search-bench.py +index 726d30b1..6417186b 100644 +--- a/bench/pytables-search-bench.py ++++ b/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 +diff --git a/bench/recarray2-test.py b/bench/recarray2-test.py +index a8602d80..bf55389d 100644 +--- a/bench/recarray2-test.py ++++ b/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') + +diff --git a/bench/shelve-bench.py b/bench/shelve-bench.py +index d30739d8..a591ed1e 100644 +--- a/bench/shelve-bench.py ++++ b/bench/shelve-bench.py +@@ -65,8 +65,8 @@ def createFile(filename, totalrows, recsize): + # 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 = NA.array(NA.arange(32), type=NA.float64) ++ arr2 = NA.array(NA.arange(32), type=NA.float64) + elif recsize == "medium": + d = Medium() + else: +@@ -87,15 +87,15 @@ def createFile(filename, totalrows, recsize): + #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 = NA.array([i]*32, NA.float64) ++ #d.float2 = NA.array([i**2]*32, NA.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 = NA.array([i ** 2] * 2, NA.float64) + #d.float1 = float(i) + #d.float2 = float(i) + d.grid_i = i +diff --git a/bench/sqlite-search-bench.py b/bench/sqlite-search-bench.py +index 76dc7c57..dc611695 100644 +--- a/bench/sqlite-search-bench.py ++++ b/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): +diff --git a/tables/atom.py b/tables/atom.py +index f92e16ad..f93d915b 100644 +--- a/tables/atom.py ++++ b/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) + + """ +-- +2.32.0 + |