#11334: Update numpy to 1.7.0
--------------------------------------------------------------+-------------
Reporter: jason | Owner:
tbd
Type: task | Status:
new
Priority: major | Milestone:
sage-5.7
Component: packages | Resolution:
Keywords: sd40.5 | Work issues:
Report Upstream: Fixed upstream, in a later stable release. | Reviewers:
Authors: | Merged in:
Dependencies: #12415, #13992 | Stopgaps:
--------------------------------------------------------------+-------------
Comment (by strogdon):
This references the failure in the test
{{{
sage -t -long -force_lib "devel/sage-main/sage/plot/matrix_plot.py"
}}}
I have some concerns with the following block of code in matrix_plot.py
{{{
try:
if sparse:
xy_data_array = mat
else:
xy_data_array = np.asarray(mat, dtype = float)
except TypeError:
raise TypeError, "mat must be a Matrix or a two dimensional array"
except ValueError:
raise ValueError, "can not convert entries to floating point
numbers"
if len(xy_data_array.shape) < 2:
raise TypeError, "mat must be a Matrix or a two dimensional array"
}}}
The subject failure occurs when the object "mat" is not sparse. In which
case, the errors are thrown by
{{{
np.asarray(mat, dtype = float)
}}}
I have not been able to pass any object "mat" to np.asarray() that returns
a {{{TypeError}}} or {{{ValueError}}}
that remotely hints of the cause as being due to
{{{
"mat must be a Matrix or a two dimensional array"
}}}
I question whether this information can be returned by np.asarray() when
used from Sage. I could be wrong though. The referenced failure does
return a {{{TypeError}}}
[http://trac.sagemath.org/sage_trac/ticket/11334#comment:68 See above].
But this error reflects the inability to coerce the symbolic [sin(x),
cos(x)] expressions to floats. It is possible to generate a
{{{ValueError}}} when the object "mat" contains complex entries:
{{{
sage: import numpy
sage: numpy.asarray([[1+1j,2+3j],[1,1]], dtype=float)
---------------------------------------------------------------------------
ValueError Traceback (most recent call
last)
<ipython-input-5-2bd7229efabd> in <module>()
----> 1 numpy.asarray([[Integer(1)+ComplexNumber(0,
'1'),Integer(2)+ComplexNumber(0, '3')],[Integer(1),Integer(1)]],
dtype=float)
/storage/sage/sage-5.7.beta3/local/lib/python2.7/site-
packages/numpy/core/numeric.pyc in asarray(a, dtype, order)
318
319 """
--> 320 return array(a, dtype, copy=False, order=order)
321
322 def asanyarray(a, dtype=None, order=None):
ValueError: setting an array element with a sequence.
}}}
This is they type of error that's returned for the referenced test when
using numpy-1.5.1. Sage interprets this error as
{{{
"can not convert entries to floating point numbers"
}}}
This seems to be a correct interpretation, at least from the python side
with the numpy of this ticket:
{{{
>>> import numpy
>>> numpy.asarray([[1+1j,2+3j],[1,1]], dtype=float)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/storage/sage/sage-5.7.beta3/local/lib/python2.7/site-
packages/numpy/core/numeric.py", line 320, in asarray
return array(a, dtype, copy=False, order=order)
TypeError: can't convert complex to float
}}}
although here there is a {{{TypeError}}}?
So it seems to me that regardless of whether there is a {{{TypeError}}} or
{{{ValueError}}} the root cause is inability to coerce to a float. The
question of whether "mat" is a Matrix or appropriate array is determined
by the lines in the code that parse the shape attribute of an object that
has been successfully converted to a ndarray. But this is probably minor
compared to #12415. Perhaps Mike (mhansen) has some input?
--
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/11334#comment:86>
Sage <http://www.sagemath.org>
Sage: Creating a Viable Open Source Alternative to Magma, Maple, Mathematica,
and MATLAB
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