Here are a couple of scripts that might help (I used them to compare casting
tables between various versions of NumPy):
Casting Table Creation Script
========================
import numpy as np
operators = np.set_numeric_ops().values()
types = '?bhilqpBHILQPfdgFDGO'
to_check = ['add', 'divide', 'minimum', 'maximum', 'remainder', 'true_divide',
'logical_or', 'bitwise_or', 'right_shift', 'less', 'equal']
operators = [op for op in operators if op.__name__ in to_check]
def type_wrap(op):
def func(obj1, obj2):
try:
result = op(obj1, obj2)
char = result.dtype.char
except:
char = 'X'
return char
return func
def coerce():
result = {}
for op in operators:
d = {}
name = op.__name__
print name
op = type_wrap(op)
for type1 in types:
s1 = np.dtype(type1).type(2)
a1 = np.dtype(type1).type([1,2,3])
for type2 in types:
s2 = np.dtype(type2).type(1)
a2 = np.dtype(type2).type([2,3,4])
codes = []
# scalar <op> scalar
codes.append(op(s1, s2))
# scalar <op> array
codes.append(op(s1, a2))
# array <op> scalar
codes.append(op(a1, s2))
# array <op> array
codes.append(op(a1, a2))
d[type1,type2] = codes
result[name] = d
#for check_key in to_check:
# for key in result.keys():
# if key == check_key:
# continue
# if result[key] == result[check_key]:
# del result[key]
#assert set(result.keys()) == set(to_check)
return result
import sys
if sys.maxint > 2**33:
bits = 64
else:
bits = 32
def write():
import cPickle
file = open('coercion-%s-%sbit.pkl'%(np.__version__, bits),'w')
cPickle.dump(coerce(),file,protocol=2)
file.close()
if __name__ == '__main__':
write()
Comparison Script
================
import numpy as np
def compare(result1, result2):
for op in result1.keys():
print "**** ", op, " ****"
if op not in result2:
print op, " not in the first"
table1 = result1[op]
table2 = result2[op]
if table1 == table2:
print "Tables are the same"
else:
if set(table1.keys()) != set(table2.keys()):
print "Keys are not the same"
continue
for key in table1.keys():
if table1[key] != table2[key]:
print "Different at ", key, ": ", table1[key], table2[key]
import cPickle
import sys
if __name__ == '__main__':
name1 = 'coercion-1.5.1-64bit.pkl'
name2 = 'coercion-1.6.1-64bit.pkl'
if len(sys.argv) > 1:
name1 = 'coercion-%s-64bit.pkl' % sys.argv[1]
if len(sys.argv) > 2:
name2 = 'coercion-%s-64bit.pkl' % sys.argv[2]
result1 = cPickle.load(open(name1))
result2 = cPickle.load(open(name2))
compare(result1, result2)
On Sep 20, 2012, at 3:09 PM, Nathaniel Smith wrote:
> On Mon, Sep 17, 2012 at 10:22 AM, Matthew Brett <matthew.br...@gmail.com>
> wrote:
>> Hi,
>>
>> On Sun, Sep 9, 2012 at 6:12 PM, Frédéric Bastien <no...@nouiz.org> wrote:
>>> The third is releated to change to the casting rules in numpy. Before
>>> a scalar complex128 * vector float32 gived a vector of dtype
>>> complex128. Now it give a vector of complex64. The reason is that now
>>> the scalar of different category only change the category, not the
>>> precision. I would consider a must that we warn clearly about this
>>> interface change. Most people won't see it, but people that optimize
>>> there code heavily could depend on such thing.
>>
>> It seems to me that it would be a very good idea to put the casting
>> table results into the tests to make sure we are keeping track of this
>> kind of thing.
>>
>> I'm happy to try to do it if no-one else more qualified has time.
>
> I haven't seen any PRs show up from anyone else in the last few days,
> and this would indeed be an excellent test to have, so that would be
> awesome.
>
> -n
> _______________________________________________
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> NumPy-Discussion@scipy.org
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