Mailman 3 March 2006 - SciPy-User

Periodic spline interpolation bug / memory error?
by Zachary Pincus March 15, 2006

March 15, 2006

Hi folks, I'm trying to estimate smooth contours with scipy's parametric splines, given a set of (x, y) points known to lie along the contour. Now, because contours are closed, special care must be taken to ensure that the interpolated value at the last point be the same as the interpolated value at the first point. I assume that the 'per' option to scipy.interpolate.splprep is designed to allow for this, as per the documentation: > per -- If non-zero, data points are considered periodic with period > x[m-1] - x[0] and a smooth periodic spline > approximation is returned. > Values of y[m-1] and w[m-1] are not used. However, I cannot get this to work on my computer. Setting 'per = true' always results in memory errors or other problems. Here is a simple example to reproduce the problem: # first make x and y points along the unit circle, from zero to just below two pi In [1]: import numpy, scipy, scipy.interpolate In [2]: twopi = numpy.arange(0, 2 * numpy.pi, 0.1) In [3]: xs = numpy.cos(twopi) In [4]: ys = numpy.sin(twopi) In [5]: tck, uout = scipy.interpolate.splprep([xs, ys], u = twopi, per = True) Warning: Setting x[0][63]=x[0][0] Warning: Setting x[1][63]=x[1][0] ...[here my machine grinds for 2-3 minutes]... Warning: The required storage space exceeds the available strorage space. Probably causes: nest to small or s is too small. (fp>s) At this point, the returned tck arrays are just all zeros. Sometimes I get other malloc errors printed to stdout and memory error exceptions, e.g.: Python(6820,0xa000ed68) malloc: *** vm_allocate(size=3716243456) failed (error code=3) Python(6820,0xa000ed68) malloc: *** error: can't allocate region Python(6820,0xa000ed68) malloc: *** set a breakpoint in szone_error to debug During the time that my machine is grinding, python is using very little CPU -- the grind is all because python is allocating huge amounts of memory, causing the pager to go nuts. If I explicitly make the last value of the x and y input arrays equal to the first value (as the warnings say that the function is doing), I get the same problem: In [6]: xs[-1] = xs[0] In [7]: ys[-1] = ys[0] In [8]: tck, uout = scipy.interpolate.splprep([xs, ys], u = twopi, per = True) #same thing Any thoughts? Zach Pincus Program in Biomedical Informatics and Department of Biochemistry Stanford University School of Medicine

2 5

Bug in scipy.integrate.ode?
by LATORNELL, Doug March 15, 2006

March 15, 2006

In [2]: numpy.__version__ Out[2]: '0.9.7.2247' In [4]: scipy.__version__ Out[4]: '0.4.7.1711' Trivial integration of a decaying exponential: from scipy import * def f(t, y): return -log(2) / 2 * y r = integrate.ode(f).set_integrator('vode') r.set_initial_value(1.0) while r.successful() and r.t <= 2: r.integrate(r.t + 0.1) print r.t, r.y Produces: Python 2.4.1 (#1, Sep 3 2005, 13:08:59) Type "copyright", "credits" or "license" for more information. IPython 0.6.15 -- An enhanced Interactive Python. ? -> Introduction to IPython's features. %magic -> Information about IPython's 'magic' % functions. help -> Python's own help system. object? -> Details about 'object'. ?object also works, ?? prints more. In [1]: ## working on region in file /tmp/python-23462ATK.py... Found integrator vode ------------------------------------------------------------------------ --- exceptions.NameError Traceback (most recent call last) /home/doug/python/<console> /tmp/python-23462ATK.py 6 7 r = integrate.ode(f).set_integrator('vode') ----> 8 r.set_initial_value(1.0) 9 while r.successful() and r.t <= 2: 10 r.integrate(r.t + 0.1) /usr/local/lib/python2.4/site-packages/scipy/integrate/ode.py in set_initial_value(self, y, t) 141 def set_initial_value(self,y,t=0.0): 142 """Set initial conditions y(t) = y.""" --> 143 if isscalar(y): 144 y = [y] 145 n_prev = len(self.y) NameError: global name 'isscalar' is not defined The fix appears to be to add 'isscalar' to the 'from numpy import ...' at line 94 in scipy/integrate/ode.py Doug This email and any files transmitted with it may contain privileged or confidential information and may be read or used only by the intended recipient. If you are not the intended recipient of the email or any of its attachments, please be advised that you have received this email in error and any use, dissemination, distribution, forwarding, printing or copying of this email or any attached files is strictly prohibited. If you have received this email in error, please immediately purge it and all attachments and notify the sender by reply email or contact the sender at the number listed.

2 1

non contiguous numpy arrays
by Gary S. Thompson March 15, 2006

March 15, 2006

Hi I have read the stuff on the numpy interface and understand most of if(?) ;-) However I want to interface numpy to an array which is stored as a series of data blocks which are not contiguous in memory... Help! so for example I hava 3d matrix of 1024*512*128 where data is stored in blocks within memory which are 16x16x16 floats an read in from disk on demand... regards gary -- ------------------------------------------------------------------- Dr Gary Thompson Astbury Centre for Structural Molecular Biology, University of Leeds, Astbury Building, Leeds, LS2 9JT, West-Yorkshire, UK Tel. +44-113-3433024 email: garyt(a)bmb.leeds.ac.uk Fax +44-113-2331407 -------------------------------------------------------------------

2 1

installation problems
by FONTAINE Philipe March 15, 2006

March 15, 2006

I have installed scipy with all the needed packages When I load it from Python, it gives me the following messages: >>> from scipy import * Traceback (most recent call last): File "<stdin>", line 1, in ? File "/usr/local/lib/python2.3/site- packages/scipy/signal/__init__.py", line 9, in ? from bsplines import * File "/usr/local/lib/python2.3/site- packages/scipy/signal/bsplines.py", line 3, in ? import scipy.special File "/usr/local/lib/python2.3/site- packages/scipy/special/__init__.py", line 10, in ? import orthogonal File "/usr/local/lib/python2.3/site- packages/scipy/special/orthogonal.py", line 66, in ? from scipy.linalg import eig File "/usr/local/lib/python2.3/site- packages/scipy/linalg/__init__.py", line 8, in ? from basic import * File "/usr/local/lib/python2.3/site-packages/scipy/linalg/basic.py", line 228, in ? import decomp File "/usr/local/lib/python2.3/site-packages/scipy/linalg/decomp.py", line 18, in ? from blas import get_blas_funcs File "/usr/local/lib/python2.3/site-packages/scipy/linalg/blas.py", line 15, in ? import fblas ImportError: /usr/local/lib/python2.3/site- packages/scipy/linalg/fblas.so: undefined symbol: srotmg_ did someone have the same problem? Anyone knows the how to solve it Many Thanks Philippe

5 4

scipy 0.4.6 / numpy 0.9.5 | overwriting functions
by Jelle Feringa / EZCT Architecture & Design Research March 15, 2006

March 15, 2006

Dear Group, I'm having some issues running scipy 0.4.6 / numpy 0.9.5, which are hard to comprehend for me. Perhaps someone is able to inform me what is going wrong here. I've tried installing numpy 0.9.6, and scipy failed to load when 0.9.6 was installed. I referred back to 0.9.5 and am getting the following errors (see end of mail). Am I making a serious mistake here setting up scipy/numpy or is this the current state of affairs? Also I've been experimenting with the Delaunay module. I've been able to compile it using Mike Fletchers setup: http://www.vrplumber.com/programming/mstoolkit/ Its really a wonderful addition to scipy and compiles perfectly out of the box. Thanks so much for the effort. Cheers, jelle No scipy-style subpackage 'scipy.test' found in c:\Python24\lib\site-packages\scipy. Ignoring. No scipy-style subpackage 'scipy.base' found in c:\Python24\lib\site-packages\scipy. Ignoring. Overwriting utils=<module 'scipy.utils' from 'c:\Python24\lib\site-packages\scipy\utils\__init__.pyc'> from c:\Python24\lib\site-packages\scipy\utils\__init__.pyc (was <module 'scipy.base.utils' from 'c:\Python24\lib\site-packages\scipy\base\utils.pyc'> from c:\Python24\lib\site-packages\scipy\base\utils.pyc) Overwriting info=<function info at 0x00F6D330> from scipy.utils.helpmod (was <function info at 0x00FB6F70> from scipy.misc.helpmod) Overwriting factorial=<function factorial at 0x00ED7B30> from scipy.utils.common (was <function factorial at 0x00FB6AF0> from scipy.misc.common) Overwriting factorial2=<function factorial2 at 0x00ED7AF0> from scipy.utils.common (was <function factorial2 at 0x00FB6B30> from scipy.misc.common) Overwriting factorialk=<function factorialk at 0x00EE9C70> from scipy.utils.common (was <function factorialk at 0x00FB6B70> from scipy.misc.common) Overwriting comb=<function comb at 0x00EE5AF0> from scipy.utils.common (was <function comb at 0x00FB6BB0> from scipy.misc.common) Overwriting who=<function who at 0x00F4D8F0> from scipy.utils.common (was <function who at 0x00FB6CF0> from scipy.misc.common) Overwriting lena=<function lena at 0x00F4D8B0> from scipy.utils.common (was <function lena at 0x00FB6CB0> from scipy.misc.common) Overwriting central_diff_weights=<function central_diff_weights at 0x00EE5A30> from scipy.utils.common (was <function central_diff_weights at 0x00FB6BF0> from scipy.misc.common) Overwriting derivative=<function derivative at 0x00F4D830> from scipy.utils.common (was <function derivative at 0x00FB6C30> from scipy.misc.common) Overwriting pade=<function pade at 0x00F4D870> from scipy.utils.common (was <function pade at 0x00FB6C70> from scipy.misc.common) Overwriting info=<function info at 0x00FB6F70> from scipy.misc.helpmod (was <function info at 0x00F6D330> from scipy.utils.helpmod) Overwriting factorial=<function factorial at 0x00FB6AF0> from scipy.misc.common (was <function factorial at 0x00ED7B30> from scipy.utils.common) Overwriting factorial2=<function factorial2 at 0x00FB6B30> from scipy.misc.common (was <function factorial2 at 0x00ED7AF0> from scipy.utils.common) Overwriting factorialk=<function factorialk at 0x00FB6B70> from scipy.misc.common (was <function factorialk at 0x00EE9C70> from scipy.utils.common) Overwriting comb=<function comb at 0x00FB6BB0> from scipy.misc.common (was <function comb at 0x00EE5AF0> from scipy.utils.common) Overwriting who=<function who at 0x00FB6CF0> from scipy.misc.common (was <function who at 0x00F4D8F0> from scipy.utils.common) Overwriting lena=<function lena at 0x00FB6CB0> from scipy.misc.common (was <function lena at 0x00F4D8B0> from scipy.utils.common) Overwriting central_diff_weights=<function central_diff_weights at 0x00FB6BF0> from scipy.misc.common (was <function central_diff_weights at 0x00EE5A30> from scipy.utils.common) Overwriting derivative=<function derivative at 0x00FB6C30> from scipy.misc.common (was <function derivative at 0x00F4D830> from scipy.utils.common) Overwriting pade=<function pade at 0x00FB6C70> from scipy.misc.common (was <function pade at 0x00F4D870> from scipy.utils.common) Overwriting test=<module 'scipy.test' from 'c:\Python24\lib\site-packages\scipy\test\__init__.pyc'> from c:\Python24\lib\site-packages\scipy\test\__init__.pyc (was <function test at 0x00FB6770> from scipy) Overwriting ScipyTest=<class scipy.test.testing.ScipyTest at 0x00EA0900> from scipy.test.testing (was <class numpy.testing.numpytest.NumpyTest at 0x00B9BDE0> from numpy.testing.numpytest) Overwriting fft=<function fft at 0x00FB9BF0> from scipy.basic.fft_lite (was <function fft at 0x00DECCF0> from numpy.dft.fftpack) Overwriting ifft=<function inverse_fft at 0x00FB9C30> from scipy.basic.fft_lite (was <function inverse_fft at 0x00DECD30> from numpy.dft.fftpack) Overwriting rand=<built-in method rand of mtrand.RandomState object at 0x00AAD1F0> (was <built-in method rand of mtrand.RandomState object at 0x00AAD0F0>) Overwriting randn=<built-in method randn of mtrand.RandomState object at 0x00AAD1F0> (was <built-in method randn of mtrand.RandomState object at 0x00AAD0F0>) Overwriting random=<module 'scipy.basic.random' from 'c:\Python24\lib\site-packages\scipy\basic\random.pyc'> from c:\Python24\lib\site-packages\scipy\basic\random.pyc (was <module 'numpy.random' from 'c:\Python24\lib\site-packages\numpy\random\__init__.pyc'> from c:\Python24\lib\site-packages\numpy\random\__init__.pyc) Overwriting linalg=<module 'scipy.basic.linalg' from 'c:\Python24\lib\site-packages\scipy\basic\linalg.pyc'> from c:\Python24\lib\site-packages\scipy\basic\linalg.pyc (was <module 'numpy.linalg' from 'c:\Python24\lib\site-packages\numpy\linalg\__init__.pyc'> from c:\Python24\lib\site-packages\numpy\linalg\__init__.pyc) Overwriting disp=<function disp at 0x00E63CB0> from scipy.base.function_base (was <function disp at 0x00CA74F0> from numpy.lib.function_base) Overwriting all=<function all at 0x00E0BDF0> from scipy.base.oldnumeric (was <function all at 0x00BDD0F0> from numpy.core.oldnumeric) Overwriting atleast_2d=<function atleast_2d at 0x00E631B0> from scipy.base.shape_base (was <function atleast_2d at 0x00CA26F0> from numpy.lib.shape_base) Overwriting ptp=<function ptp at 0x00E63870> from scipy.base.function_base (was <function ptp at 0x00BDD1B0> from numpy.core.oldnumeric) Overwriting unicode_=<type 'unicode_arrtype'> from __builtin__ (was <type 'unicodescalar'> from __builtin__) Overwriting string=<type 'string_arrtype'> from __builtin__ (was <type 'stringscalar'> from __builtin__) Overwriting float96=<type 'float96_arrtype'> from __builtin__ (was <type 'float96scalar'> from __builtin__) Overwriting void=<type 'void_arrtype'> from __builtin__ (was <type 'voidscalar'> from __builtin__) Overwriting unicode0=<type 'unicode_arrtype'> from __builtin__ (was <type 'unicodescalar'> from __builtin__) Overwriting void0=<type 'void_arrtype'> from __builtin__ (was <type 'voidscalar'> from __builtin__) Overwriting tri=<function tri at 0x00E682B0> from scipy.base.twodim_base (was <function tri at 0x00CA2DF0> from numpy.lib.twodim_base) Overwriting arrayrange=<built-in function arange> from scipy.base.multiarray (was <built-in function arange> from numpy.core.multiarray) Overwriting indices=<function indices at 0x00E0A970> from scipy.base.numeric (was <function indices at 0x00BD34F0> from numpy.core.numeric) Overwriting set_numeric_ops=<built-in function set_numeric_ops> from scipy.base.multiarray (was <built-in function set_numeric_ops> from numpy.core.multiarray) Overwriting cosh=<ufunc 'cosh'> (was <ufunc 'cosh'>) Overwriting object0=<type 'object_arrtype'> from __builtin__ (was <type 'objectscalar'> from __builtin__) Overwriting restoredot=<built-in function restoredot> from scipy.lib._dotblas (was <built-in function restoredot> from numpy.core._dotblas) Overwriting index_exp=<scipy.base.index_tricks._index_expression_class object at 0x00E14BB0> from scipy.base.index_tricks (was <numpy.lib.index_tricks._index_expression_class object at 0x00C98290> from numpy.lib.index_tricks) Overwriting nanargmax=<function nanargmax at 0x00E63C70> from scipy.base.function_base (was <function nanargmax at 0x00CA74B0> from numpy.lib.function_base) Overwriting power=<ufunc 'power'> (was <ufunc 'power'>) Overwriting typename=<function typename at 0x00E15A30> from scipy.base.type_check (was <function typename at 0x00C965B0> from numpy.lib.type_check) Overwriting diag=<function diag at 0x00E68270> from scipy.base.twodim_base (was <function diag at 0x00CA2DB0> from numpy.lib.twodim_base) Overwriting sum=<function sum at 0x00E0BCB0> from scipy.base.oldnumeric (was <function sum at 0x00BD8F70> from numpy.core.oldnumeric) Overwriting polyfit=<function polyfit at 0x00E6AC30> from scipy.base.polynomial (was <function polyfit at 0x00CAC230> from numpy.lib.polynomial) Overwriting nanmin=<function nanmin at 0x00E63BB0> from scipy.base.function_base (was <function nanmin at 0x00CA73F0> from numpy.lib.function_base) Overwriting memmap=<class 'scipy.base.memmap.memmap'> from scipy.base.memmap (was <class 'numpy.core.memmap.memmap'> from numpy.core.memmap) Overwriting nan_to_num=<function nan_to_num at 0x00E15970> from scipy.base.type_check (was <function nan_to_num at 0x00C964F0> from numpy.lib.type_check) Overwriting complex64=<type 'complex64_arrtype'> from __builtin__ (was <type 'complex64scalar'> from __builtin__) Overwriting logspace=<function logspace at 0x00E63530> from scipy.base.function_base (was <function logspace at 0x00CA2EF0> from numpy.lib.function_base) Overwriting sinh=<ufunc 'sinh'> (was <ufunc 'sinh'>) Overwriting vstack=<function vstack at 0x00E63230> from scipy.base.shape_base (was <function vstack at 0x00CA2770> from numpy.lib.shape_base) Overwriting MachAr=<class 'scipy.base.machar.MachAr'> from scipy.base.machar (was <class 'numpy.lib.machar.MachAr'> from numpy.lib.machar) Overwriting asscalar=<function asscalar at 0x00E159F0> from scipy.base.type_check (was <function asscalar at 0x00C96570> from numpy.lib.type_check) Overwriting less_equal=<ufunc 'less_equal'> (was <ufunc 'less_equal'>) Overwriting object_=<type 'object_arrtype'> from __builtin__ (was <type 'objectscalar'> from __builtin__) Overwriting divide=<ufunc 'divide'> (was <ufunc 'divide'>) Overwriting csingle=<type 'complex64_arrtype'> from __builtin__ (was <type 'complex64scalar'> from __builtin__) Overwriting unsignedinteger=<type 'unsignedinteger_arrtype'> from __builtin__ (was <type 'unsignedintegerscalar'> from __builtin__) Overwriting sign=<function sign at 0x00E156B0> from scipy.base.ufunclike (was <ufunc 'sign'>) Overwriting fastCopyAndTranspose=<built-in function _fastCopyAndTranspose> from scipy.base.multiarray (was <built-in function _fastCopyAndTranspose> from numpy.core.multiarray) Overwriting bitwise_and=<ufunc 'bitwise_and'> (was <ufunc 'bitwise_and'>) Overwriting uintc=<type 'uint32_arrtype'> from __builtin__ (was <type 'uint32scalar'> from __builtin__) Overwriting register_dtype=<built-in function register_dtype> from scipy.base.multiarray (was <built-in function register_dtype> from numpy.core.multiarray) Overwriting select=<function select at 0x00E636F0> from scipy.base.function_base (was <function select at 0x00CA70B0> from numpy.lib.function_base) Overwriting eye=<function eye at 0x00E68230> from scipy.base.twodim_base (was <function eye at 0x00CA2D70> from numpy.lib.twodim_base) Overwriting newbuffer=<built-in function newbuffer> from scipy.base.multiarray (was <built-in function newbuffer> from numpy.core.multiarray) Overwriting negative=<ufunc 'negative'> (was <ufunc 'negative'>) Overwriting mintypecode=<function mintypecode at 0x00E155B0> from scipy.base.type_check (was <function mintypecode at 0x00C961B0> from numpy.lib.type_check) Overwriting sort=<function sort at 0x00E0B970> from scipy.base.oldnumeric (was <function sort at 0x00BD8BF0> from numpy.core.oldnumeric) Overwriting uint0=<type 'uint32_arrtype'> from __builtin__ (was <type 'uint32scalar'> from __builtin__) Overwriting uint8=<type 'uint8_arrtype'> from __builtin__ (was <type 'uint8scalar'> from __builtin__) Overwriting chararray=<module 'scipy.base.chararray' from 'c:\Python24\lib\site-packages\scipy\base\chararray.pyc'> from c:\Python24\lib\site-packages\scipy\base\chararray.pyc (was <class 'numpy.core.defchararray.chararray'> from numpy.core.defchararray) Overwriting linspace=<function linspace at 0x00E634F0> from scipy.base.function_base (was <function linspace at 0x00CA2C70> from numpy.lib.function_base) Overwriting resize=<function resize at 0x00E0BAB0> from scipy.base.oldnumeric (was <function resize at 0x00BD8D30> from numpy.core.oldnumeric) Overwriting uint64=<type 'uint64_arrtype'> from __builtin__ (was <type 'uint64scalar'> from __builtin__) Overwriting ma=<module 'scipy.base.ma' from 'c:\Python24\lib\site-packages\scipy\base\ma.pyc'> from c:\Python24\lib\site-packages\scipy\base\ma.pyc (was <module 'numpy.core.ma' from 'c:\Python24\lib\site-packages\numpy\core\ma.pyc'> from c:\Python24\lib\site-packages\numpy\core\ma.pyc) Overwriting true_divide=<ufunc 'true_divide'> (was <ufunc 'true_divide'>) Overwriting Inf=1.#INF (was 1.#INF) Overwriting finfo=<class 'scipy.base.getlimits.finfo'> from scipy.base.getlimits (was <class 'numpy.lib.getlimits.finfo'> from numpy.lib.getlimits) Overwriting seterrcall=<function seterrcall at 0x00E0AC70> from scipy.base.numeric (was <function seterrcall at 0x00BD3B70> from numpy.core.numeric) Overwriting logical_or=<ufunc 'logical_or'> (was <ufunc 'logical_or'>) Overwriting minimum=<ufunc 'minimum'> (was <ufunc 'minimum'>) Overwriting tan=<ufunc 'tan'> (was <ufunc 'tan'>) Overwriting absolute=<ufunc 'absolute'> (was <ufunc 'absolute'>) Overwriting array_repr=<function array_repr at 0x00E0A4B0> from scipy.base.numeric (was <function array_repr at 0x00BD3030> from numpy.core.numeric) Overwriting polymul=<function polymul at 0x00E6AD30> from scipy.base.polynomial (was <function polymul at 0x00CAC330> from numpy.lib.polynomial) Overwriting array_str=<function array_str at 0x00E0A930> from scipy.base.numeric (was <function array_str at 0x00BD34B0> from numpy.core.numeric) Overwriting sin=<ufunc 'sin'> (was <ufunc 'sin'>) Overwriting longlong=<type 'int64_arrtype'> from __builtin__ (was <type 'int64scalar'> from __builtin__) Overwriting product=<function product at 0x00E0BCF0> from scipy.base.oldnumeric (was <function product at 0x00BD8FB0> from numpy.core.oldnumeric) Overwriting int16=<type 'int16_arrtype'> from __builtin__ (was <type 'int16scalar'> from __builtin__) Overwriting str_=<type 'string_arrtype'> from __builtin__ (was <type 'stringscalar'> from __builtin__) Overwriting mat=<class 'scipy.base.matrix.matrix'> from scipy.base.matrix (was <class 'numpy.core.defmatrix.matrix'> from numpy.core.defmatrix) Overwriting asanyarray=<function asanyarray at 0x00E05AF0> from scipy.base.numeric (was <function asanyarray at 0x00BCC670> from numpy.core.numeric) Overwriting uint=<type 'uint32_arrtype'> from __builtin__ (was <type 'uint32scalar'> from __builtin__) Overwriting update_use_defaults=<built-in function update_use_defaults> from scipy.base.umath (was <built-in function update_use_defaults> from numpy.core.umath) Overwriting amin=<function amin at 0x00E637F0> from scipy.base.function_base (was <function amin at 0x00BDD230> from numpy.core.oldnumeric) Overwriting correlate=<function correlate at 0x00E05C30> from scipy.base.numeric (was <function correlate at 0x00BCC7B0> from numpy.core.numeric) Overwriting fromstring=<built-in function fromstring> from scipy.base.multiarray (was <built-in function fromstring> from numpy.core.multiarray) Overwriting left_shift=<ufunc 'left_shift'> (was <ufunc 'left_shift'>) Overwriting searchsorted=<function searchsorted at 0x00E0BA70> from scipy.base.oldnumeric (was <function searchsorted at 0x00BD8CF0> from numpy.core.oldnumeric) Overwriting int64=<type 'int64_arrtype'> from __builtin__ (was <type 'int64scalar'> from __builtin__) Overwriting dsplit=<function dsplit at 0x00E63470> from scipy.base.shape_base (was <function dsplit at 0x00CA29B0> from numpy.lib.shape_base) Overwriting arraytype=<type 'scipy.ndarray'> from scipy (was <type 'numpy.ndarray'> from numpy) Overwriting can_cast=<built-in function can_cast> from scipy.base.multiarray (was <built-in function can_cast> from numpy.core.multiarray) Overwriting cumsum=<function cumsum at 0x00E0BE30> from scipy.base.oldnumeric (was <function cumsum at 0x00BDD130> from numpy.core.oldnumeric) Overwriting roots=<function roots at 0x00E6AB70> from scipy.base.polynomial (was <function roots at 0x00CAC170> from numpy.lib.polynomial) Overwriting outer=<function outer at 0x00E05CB0> from scipy.base.numeric (was <function outer at 0x00BCC830> from numpy.core.numeric) Overwriting fix=<function fix at 0x00E155F0> from scipy.base.ufunclike (was <function fix at 0x00C961F0> from numpy.lib.ufunclike) Overwriting choose=<function choose at 0x00E0B7F0> from scipy.base.oldnumeric (was <function choose at 0x00BD8A70> from numpy.core.oldnumeric) Overwriting empty_like=<function empty_like at 0x00E05BB0> from scipy.base.numeric (was <function empty_like at 0x00BCC730> from numpy.core.numeric) Overwriting greater=<ufunc 'greater'> (was <ufunc 'greater'>) Overwriting polyint=<function polyint at 0x00E6ABB0> from scipy.base.polynomial (was <function polyint at 0x00CAC1B0> from numpy.lib.polynomial) Overwriting arctan2=<ufunc 'arctan2'> (was <ufunc 'arctan2'>) Overwriting complexfloating=<type 'complexfloating_arrtype'> from __builtin__ (was <type 'complexfloatingscalar'> from __builtin__) Overwriting PZERO=0.0 (was 0.0) Overwriting isfortran=<function isfortran at 0x00E05B30> from scipy.base.numeric (was <function isfortran at 0x00BCC6B0> from numpy.core.numeric) Overwriting asfarray=<function asfarray at 0x00E15730> from scipy.base.type_check (was <function asfarray at 0x00C962F0> from numpy.lib.type_check) Overwriting fliplr=<function fliplr at 0x00E68170> from scipy.base.twodim_base (was <function fliplr at 0x00CA2CB0> from numpy.lib.twodim_base) Overwriting alen=<function alen at 0x00E63830> from scipy.base.function_base (was <function alen at 0x00BDD270> from numpy.core.oldnumeric) Overwriting recarray=<class 'scipy.base.records.recarray'> from scipy.base.records (was <class 'numpy.core.records.recarray'> from numpy.core.records) Overwriting fmod=<ufunc 'fmod'> (was <ufunc 'fmod'>) Overwriting intp=<type 'int32_arrtype'> from __builtin__ (was <type 'int32scalar'> from __builtin__) Overwriting ndenumerate=<class 'scipy.base.index_tricks.ndenumerate'> from scipy.base.index_tricks (was <class 'numpy.lib.index_tricks.ndenumerate'> from numpy.lib.index_tricks) Overwriting ogrid=<scipy.base.index_tricks.nd_grid object at 0x00E14B10> from scipy.base.index_tricks (was <numpy.lib.index_tricks.nd_grid object at 0x00C981D0> from numpy.lib.index_tricks) Overwriting nanargmin=<function nanargmin at 0x00E63BF0> from scipy.base.function_base (was <function nanargmin at 0x00CA7430> from numpy.lib.function_base) Overwriting r_=<scipy.base.index_tricks.concatenator object at 0x00E14B50> from scipy.base.index_tricks (was <numpy.lib.index_tricks.concatenator object at 0x00C98210> from numpy.lib.index_tricks) Overwriting allclose=<function allclose at 0x00E0AAB0> from scipy.base.numeric (was <function allclose at 0x00BD39B0> from numpy.core.numeric) Overwriting extract=<function extract at 0x00E63AF0> from scipy.base.function_base (was <function extract at 0x00CA7330> from numpy.lib.function_base) Overwriting vsplit=<function vsplit at 0x00E63430> from scipy.base.shape_base (was <function vsplit at 0x00CA2970> from numpy.lib.shape_base) Overwriting ulonglong=<type 'uint64_arrtype'> from __builtin__ (was <type 'uint64scalar'> from __builtin__) Overwriting matrix=<class 'scipy.base.matrix.matrix'> from scipy.base.matrix (was <class 'numpy.core.defmatrix.matrix'> from numpy.core.defmatrix) Overwriting asarray=<function asarray at 0x00E05AB0> from scipy.base.numeric (was <function asarray at 0x00BCC630> from numpy.core.numeric) Overwriting poly1d=<class 'scipy.base.polynomial.poly1d'> from scipy.base.polynomial (was <class 'numpy.lib.polynomial.poly1d'> from numpy.lib.polynomial) Overwriting rec=<module 'scipy.base.records' from 'c:\Python24\lib\site-packages\scipy\base\records.pyc'> from c:\Python24\lib\site-packages\scipy\base\records.pyc (was <module 'numpy.core.records' from 'c:\Python24\lib\site-packages\numpy\core\records.pyc'> from c:\Python24\lib\site-packages\numpy\core\records.pyc) Overwriting uint32=<type 'uint32_arrtype'> from __builtin__ (was <type 'uint32scalar'> from __builtin__) Overwriting log2=<function log2 at 0x00E156F0> from scipy.base.ufunclike (was <function log2 at 0x00C962B0> from numpy.lib.ufunclike) Overwriting cumproduct=<function cumproduct at 0x00E0BE70> from scipy.base.oldnumeric (was <function cumproduct at 0x00BDD170> from numpy.core.oldnumeric) Overwriting diagonal=<function diagonal at 0x00E0BAF0> from scipy.base.oldnumeric (was <function diagonal at 0x00BD8DB0> from numpy.core.oldnumeric) Overwriting atleast_1d=<function atleast_1d at 0x00E63170> from scipy.base.shape_base (was <function atleast_1d at 0x00CA26B0> from numpy.lib.shape_base) Overwriting column_stack=<function column_stack at 0x00E632B0> from scipy.base.shape_base (was <function column_stack at 0x00CA27F0> from numpy.lib.shape_base) Overwriting put=<function put at 0x00E0B870> from scipy.base.oldnumeric (was <function put at 0x00BD8AF0> from numpy.core.oldnumeric) Overwriting byte=<type 'int8_arrtype'> from __builtin__ (was <type 'int8scalar'> from __builtin__) Overwriting remainder=<ufunc 'remainder'> (was <ufunc 'remainder'>) Overwriting arccos=<ufunc 'arccos'> (was <ufunc 'arccos'>) Overwriting signedinteger=<type 'signedinteger_arrtype'> from __builtin__ (was <type 'signedintegerscalar'> from __builtin__) Overwriting ndim=<function ndim at 0x00E0BEB0> from scipy.base.oldnumeric (was <function ndim at 0x00BDD330> from numpy.core.oldnumeric) Overwriting rank=<function rank at 0x00E0BEF0> from scipy.base.oldnumeric (was <function rank at 0x00BDD370> from numpy.core.oldnumeric) Overwriting ldexp=<ufunc 'ldexp'> (was <ufunc 'ldexp'>) Overwriting array=<built-in function array> from scipy.base.multiarray (was <built-in function array> from numpy.core.multiarray) Overwriting common_type=<function common_type at 0x00E15A70> from scipy.base.type_check (was <function common_type at 0x00C965F0> from numpy.lib.type_check) Overwriting size=<function size at 0x00E0BF30> from scipy.base.oldnumeric (was <function size at 0x00BDD3B0> from numpy.core.oldnumeric) Overwriting logical_xor=<ufunc 'logical_xor'> (was <ufunc 'logical_xor'>) Overwriting geterrcall=<function geterrcall at 0x00E0ACB0> from scipy.base.numeric (was <function geterrcall at 0x00BD3BB0> from numpy.core.numeric) Overwriting cross_correlate=<function correlate at 0x00E05C30> from scipy.base.numeric (was <function correlate at 0x00BCC7B0> from numpy.core.numeric) Overwriting sometrue=<function sometrue at 0x00E0BD30> from scipy.base.oldnumeric (was <function sometrue at 0x00BDD030> from numpy.core.oldnumeric) Overwriting bool8=<type 'bool_arrtype'> from __builtin__ (was <type 'boolscalar'> from __builtin__) Overwriting alltrue=<function alltrue at 0x00E0BD70> from scipy.base.oldnumeric (was <function alltrue at 0x00BDD070> from numpy.core.oldnumeric) Overwriting zeros=<built-in function zeros> from scipy.base.multiarray (was <built-in function zeros> from numpy.core.multiarray) Overwriting complex192=<type 'complex192_arrtype'> from __builtin__ (was <type 'complex192scalar'> from __builtin__) Overwriting nansum=<function nansum at 0x00E63B70> from scipy.base.function_base (was <function nansum at 0x00CA73B0> from numpy.lib.function_base) Overwriting bool_=<type 'bool_arrtype'> from __builtin__ (was <type 'boolscalar'> from __builtin__) Overwriting inexact=<type 'inexact_arrtype'> from __builtin__ (was <type 'inexactscalar'> from __builtin__) Overwriting broadcast=<type 'scipy.broadcast'> from scipy (was <type 'numpy.broadcast'> from numpy) Overwriting short=<type 'int16_arrtype'> from __builtin__ (was <type 'int16scalar'> from __builtin__) Overwriting typecodes={'All': '?bhilqpBHILQPfdgFDGSUVO', 'AllInteger': 'bBhHiIlLqQpP', 'AllFloat': 'fdgFDG', 'UnsignedInteger': 'BHILQP', 'Float': 'fdg', 'Character': 'S1', 'Complex': 'FDG', 'Integer': 'bhilqp'} (was {'All': '?bhilqpBHILQPfdgFDGSUVO', 'AllInteger': 'bBhHiIlLqQpP', 'AllFloat': 'fdgFDG', 'UnsignedInteger': 'BHILQP', 'Float': 'fdg', 'Character': 'S1', 'Complex': 'FDG', 'Integer': 'bhilqp'}) Overwriting rot90=<function rot90 at 0x00E681F0> from scipy.base.twodim_base (was <function rot90 at 0x00CA2D30> from numpy.lib.twodim_base) Overwriting copy=<function copy at 0x00E63770> from scipy.base.function_base (was <function copy at 0x00CA7130> from numpy.lib.function_base) Overwriting ubyte=<type 'uint8_arrtype'> from __builtin__ (was <type 'uint8scalar'> from __builtin__) Overwriting not_equal=<ufunc 'not_equal'> (was <ufunc 'not_equal'>) Overwriting fromfunction=<function fromfunction at 0x00E0A9B0> from scipy.base.numeric (was <function fromfunction at 0x00BD3530> from numpy.core.numeric) Overwriting double=<type 'float64_arrtype'> from __builtin__ (was <type 'float64scalar'> from __builtin__) Overwriting getbuffer=<built-in function getbuffer> from scipy.base.multiarray (was <built-in function getbuffer> from numpy.core.multiarray) Overwriting clip=<function clip at 0x00E0BC70> from scipy.base.oldnumeric (was <function clip at 0x00BD8F30> from numpy.core.oldnumeric) Overwriting frompyfunc=<built-in function frompyfunc> from scipy.base.umath (was <built-in function frompyfunc> from numpy.core.umath) Overwriting conjugate=<ufunc 'conjugate'> (was <ufunc 'conjugate'>) Overwriting alterdot=<built-in function alterdot> from scipy.lib._dotblas (was <built-in function alterdot> from numpy.core._dotblas) Overwriting polyval=<function polyval at 0x00E6AC70> from scipy.base.polynomial (was <function polyval at 0x00CAC270> from numpy.lib.polynomial) Overwriting angle=<function angle at 0x00E639B0> from scipy.base.function_base (was <function angle at 0x00CA71F0> from numpy.lib.function_base) Overwriting apply_over_axes=<function apply_over_axes at 0x00E630B0> from scipy.base.shape_base (was <function apply_over_axes at 0x00CA2630> from numpy.lib.shape_base) Overwriting right_shift=<ufunc 'right_shift'> (was <ufunc 'right_shift'>) Overwriting take=<function take at 0x00E0B770> from scipy.base.oldnumeric (was <function take at 0x00BD89F0> from numpy.core.oldnumeric) Overwriting sarray=<function sarray at 0x00E0B730> from scipy.base.oldnumeric (was <function sarray at 0x00BD89B0> from numpy.core.oldnumeric) Overwriting outerproduct=<function outer at 0x00E05CB0> from scipy.base.numeric (was <function outer at 0x00BCC830> from numpy.core.numeric) Overwriting trace=<function trace at 0x00E0BB30> from scipy.base.oldnumeric (was <function trace at 0x00BD8DF0> from numpy.core.oldnumeric) Overwriting compress=<function compress at 0x00E0BC30> from scipy.base.oldnumeric (was <function compress at 0x00BD8EF0> from numpy.core.oldnumeric) Overwriting multiply=<ufunc 'multiply'> (was <ufunc 'multiply'>) Overwriting amax=<function amax at 0x00E637B0> from scipy.base.function_base (was <function amax at 0x00BDD1F0> from numpy.core.oldnumeric) Overwriting logical_not=<ufunc 'logical_not'> (was <ufunc 'logical_not'>) Overwriting average=<function average at 0x00E635F0> from scipy.base.function_base (was <function average at 0x00CA2FB0> from numpy.lib.function_base) Overwriting nbytes={<type 'int64_arrtype'>: 8, <type 'int16_arrtype'>: 2, <type 'int32_arrtype'>: 4, <type 'unicode_arrtype'>: 0, <type 'uint32_arrtype'>: 4, <type 'int32_arrtype'>: 4, <type 'void_arrtype'>: 0, <type 'complex192_arrtype'>: 24, <type 'uint64_arrtype'>: 8, <type 'string_arrtype'>: 0, <type 'complex64_arrtype'>: 8, <type 'object_arrtype'>: 4, <type 'float32_arrtype'>: 4, <type 'uint8_arrtype'>: 1, <type 'complex128_arrtype'>: 16, <type 'int8_arrtype'>: 1, <type 'float64_arrtype'>: 8, <type 'uint32_arrtype'>: 4, <type 'uint16_arrtype'>: 2, <type 'float96_arrtype'>: 12, <type 'bool_arrtype'>: 1} from scipy.base.numerictypes (was {<type 'int64scalar'>: 8, <type 'int16scalar'>: 2, <type 'int8scalar'>: 1, <type 'unicodescalar'>: 0, <type 'objectscalar'>: 4, <type 'complex128scalar'>: 16, <type 'boolscalar'>: 1, <type 'complex64scalar'>: 8, <type 'float96scalar'>: 12, <type 'float64scalar'>: 8, <type 'uint32scalar'>: 4, <type 'int32scalar'>: 4, <type 'stringscalar'>: 0, <type 'uint32scalar'>: 4, <type 'complex192scalar'>: 24, <type 'int32scalar'>: 4, <type 'uint16scalar'>: 2, <type 'uint8scalar'>: 1, <type 'uint64scalar'>: 8, <type 'voidscalar'>: 0, <type 'float32scalar'>: 4} from numpy.core.numerictypes) Overwriting exp=<ufunc 'exp'> (was <ufunc 'exp'>) Overwriting arctanh=<ufunc 'arctanh'> (was <ufunc 'arctanh'>) Overwriting dot=<built-in function dot> from scipy.lib._dotblas (was <built-in function dot> from numpy.core._dotblas) Overwriting longfloat=<type 'float96_arrtype'> from __builtin__ (was <type 'float96scalar'> from __builtin__) Overwriting frexp=<ufunc 'frexp'> (was <ufunc 'frexp'>) Overwriting putmask=<function putmask at 0x00E0B8B0> from scipy.base.oldnumeric (was <function putmask at 0x00BD8B30> from numpy.core.oldnumeric) Overwriting swapaxes=<function swapaxes at 0x00E0B8F0> from scipy.base.oldnumeric (was <function swapaxes at 0x00BD8B70> from numpy.core.oldnumeric) Overwriting infty=1.#INF (was 1.#INF) Overwriting digitize=<built-in function digitize> from scipy.base._compiled_base (was <built-in function digitize> from numpy.lib._compiled_base) Overwriting NZERO=0.0 (was 0.0) Overwriting UFuncType=<type 'scipy.ufunc'> from scipy (was <type 'numpy.ufunc'> from numpy) Overwriting ceil=<ufunc 'ceil'> (was <ufunc 'ceil'>) Overwriting ones=<function ones at 0x00E0AA30> from scipy.base.numeric (was <function ones at 0x00BD3930> from numpy.core.numeric) Overwriting UfuncType=<type 'scipy.ufunc'> from scipy (was <type 'numpy.ufunc'> from numpy) Overwriting geterr=<function geterr at 0x00E0ABB0> from scipy.base.numeric (was <function geterr at 0x00BD3AB0> from numpy.core.numeric) Overwriting convolve=<function convolve at 0x00E05C70> from scipy.base.numeric (was <function convolve at 0x00BCC7F0> from numpy.core.numeric) Overwriting isreal=<function isreal at 0x00E15870> from scipy.base.type_check (was <function isreal at 0x00C963F0> from numpy.lib.type_check) Overwriting where=<built-in function where> from scipy.base.multiarray (was <built-in function where> from numpy.core.multiarray) Overwriting isfinite=<ufunc 'isfinite'> (was <ufunc 'isfinite'>) Overwriting argmax=<function argmax at 0x00E0B9F0> from scipy.base.oldnumeric (was <function argmax at 0x00BD8C70> from numpy.core.oldnumeric) Overwriting polyder=<function polyder at 0x00E6ABF0> from scipy.base.polynomial (was <function polyder at 0x00CAC1F0> from numpy.lib.polynomial) Overwriting isnan=<ufunc 'isnan'> (was <ufunc 'isnan'>) Overwriting NINF=-1.#INF (was -1.#INF) Overwriting sort_complex=<function sort_complex at 0x00E63A30> from scipy.base.function_base (was <function sort_complex at 0x00CA7270> from numpy.lib.function_base) Overwriting concatenate=<built-in function concatenate> from scipy.base.multiarray (was <built-in function concatenate> from numpy.core.multiarray) Overwriting vdot=<built-in function vdot> from scipy.lib._dotblas (was <built-in function vdot> from numpy.core._dotblas) Overwriting bincount=<built-in function bincount> from scipy.base._compiled_base (was <built-in function bincount> from numpy.lib._compiled_base) Overwriting transpose=<function transpose at 0x00E0B930> from scipy.base.oldnumeric (was <function transpose at 0x00BD8BB0> from numpy.core.oldnumeric) Overwriting array2string=<function array2string at 0x00E0A6F0> from scipy.base.arrayprint (was <function array2string at 0x00BD3270> from numpy.core.arrayprint) Overwriting vectorize=<class 'scipy.base.function_base.vectorize'> from scipy.base.function_base (was <class 'numpy.lib.function_base.vectorize'> from numpy.lib.function_base) Overwriting set_printoptions=<function set_printoptions at 0x00E0A5F0> from scipy.base.arrayprint (was <function set_printoptions at 0x00BD3170> from numpy.core.arrayprint) Overwriting trim_zeros=<function trim_zeros at 0x00E63A70> from scipy.base.function_base (was <function trim_zeros at 0x00CA72B0> from numpy.lib.function_base) Overwriting cos=<ufunc 'cos'> (was <ufunc 'cos'>) Overwriting float64=<type 'float64_arrtype'> from __builtin__ (was <type 'float64scalar'> from __builtin__) Overwriting ushort=<type 'uint16_arrtype'> from __builtin__ (was <type 'uint16scalar'> from __builtin__) Overwriting equal=<ufunc 'equal'> (was <ufunc 'equal'>) Overwriting cumprod=<function cumprod at 0x00E638F0> from scipy.base.function_base (was <function cumprod at 0x00BDD2F0> from numpy.core.oldnumeric) Overwriting float_=<type 'float64_arrtype'> from __builtin__ (was <type 'float64scalar'> from __builtin__) Overwriting vander=<function vander at 0x00E68370> from scipy.base.twodim_base (was <function vander at 0x00CA2EB0> from numpy.lib.twodim_base) Overwriting load=<function load at 0x00E0A9F0> from scipy.base.numeric (was <function load at 0x00BD3830> from numpy.core.numeric) Overwriting poly=<function poly at 0x00E6AB30> from scipy.base.polynomial (was <function poly at 0x00CAC130> from numpy.lib.polynomial) Overwriting bitwise_or=<ufunc 'bitwise_or'> (was <ufunc 'bitwise_or'>) Overwriting diff=<function diff at 0x00E63970> from scipy.base.function_base (was <function diff at 0x00CA71B0> from numpy.lib.function_base) Overwriting iterable=<function iterable at 0x00E63570> from scipy.base.function_base (was <function iterable at 0x00CA2F30> from numpy.lib.function_base) Overwriting array_split=<function array_split at 0x00E63370> from scipy.base.shape_base (was <function array_split at 0x00CA28B0> from numpy.lib.shape_base) Overwriting piecewise=<function piecewise at 0x00E636B0> from scipy.base.function_base (was <function piecewise at 0x00CA7070> from numpy.lib.function_base) Overwriting invert=<ufunc 'invert'> (was <ufunc 'invert'>) Overwriting UFUNC_PYVALS_NAME='UFUNC_PYVALS' (was 'UFUNC_PYVALS') Overwriting c_=<scipy.base.index_tricks.concatenator object at 0x00E14B70> from scipy.base.index_tricks (was <numpy.lib.index_tricks.concatenator object at 0x00C98230> from numpy.lib.index_tricks) Overwriting flexible=<type 'flexible_arrtype'> from __builtin__ (was <type 'flexiblescalar'> from __builtin__) Overwriting pi=3.1415926535897931 (was 3.1415926535897931) Overwriting empty=<built-in function empty> from scipy.base.multiarray (was <built-in function empty> from numpy.core.multiarray) Overwriting isposinf=<function isposinf at 0x00E15630> from scipy.base.ufunclike (was <function isposinf at 0x00C96230> from numpy.lib.ufunclike) Overwriting imag=<function imag at 0x00E157F0> from scipy.base.type_check (was <function imag at 0x00C96370> from numpy.lib.type_check) Overwriting apply_along_axis=<function apply_along_axis at 0x00E63070> from scipy.base.shape_base (was <function apply_along_axis at 0x00CA25F0> from numpy.lib.shape_base) Overwriting tanh=<ufunc 'tanh'> (was <ufunc 'tanh'>) Overwriting dstack=<function dstack at 0x00E632F0> from scipy.base.shape_base (was <function dstack at 0x00CA2830> from numpy.lib.shape_base) Overwriting cast={<type 'int64_arrtype'>: <function <lambda> at 0x00DEEBB0>, <type 'int16_arrtype'>: <function <lambda> at 0x00DEEBF0>, <type 'int32_arrtype'>: <function <lambda> at 0x00DEEC30>, <type 'unicode_arrtype'>: <function <lambda> at 0x00DEEC70>, <type 'uint32_arrtype'>: <function <lambda> at 0x00DEECB0>, <type 'int32_arrtype'>: <function <lambda> at 0x00DEECF0>, <type 'object_arrtype'>: <function <lambda> at 0x00DEEE70>, <type 'void_arrtype'>: <function <lambda> at 0x00DEED30>, <type 'uint64_arrtype'>: <function <lambda> at 0x00DEEDB0>, <type 'complex128_arrtype'>: <function <lambda> at 0x00DEEF30>, <type 'complex64_arrtype'>: <function <lambda> at 0x00DEEE30>, <type 'complex192_arrtype'>: <function <lambda> at 0x00DEED70>, <type 'float96_arrtype'>: <function <lambda> at 0x00E050B0>, <type 'float32_arrtype'>: <function <lambda> at 0x00DEEEB0>, <type 'uint8_arrtype'>: <function <lambda> at 0x00DEEEF0>, <type 'int8_arrtype'>: <function <lambda> at 0x00DEEF70>, <type 'float64_arrtype'>: <function <lambda> at 0x00DEEFB0>, <type 'uint32_arrtype'>: <function <lambda> at 0x00E05030>, <type 'uint16_arrtype'>: <function <lambda> at 0x00E05070>, <type 'string_arrtype'>: <function <lambda> at 0x00DEEDF0>, <type 'bool_arrtype'>: <function <lambda> at 0x00E050F0>} from scipy.base.numerictypes (was {<type 'int64scalar'>: <function <lambda> at 0x00BC6570>, <type 'int16scalar'>: <function <lambda> at 0x00BC65B0>, <type 'int8scalar'>: <function <lambda> at 0x00BC65F0>, <type 'objectscalar'>: <function <lambda> at 0x00BC6670>, <type 'stringscalar'>: <function <lambda> at 0x00BC6870>, <type 'complex128scalar'>: <function <lambda> at 0x00BC66B0>, <type 'boolscalar'>: <function <lambda> at 0x00BC66F0>, <type 'float64scalar'>: <function <lambda> at 0x00BC67B0>, <type 'uint32scalar'>: <function <lambda> at 0x00BC67F0>, <type 'int32scalar'>: <function <lambda> at 0x00BC6830>, <type 'complex64scalar'>: <function <lambda> at 0x00BC6730>, <type 'uint32scalar'>: <function <lambda> at 0x00BC68B0>, <type 'float96scalar'>: <function <lambda> at 0x00BC6770>, <type 'int32scalar'>: <function <lambda> at 0x00BC6930>, <type 'uint16scalar'>: <function <lambda> at 0x00BC6970>, <type 'unicodescalar'>: <function <lambda> at 0x00BC6630>, <type 'uint8scalar'>: <function <lambda> at 0x00BC69B0>, <type 'uint64scalar'>: <function <lambda> at 0x00BC69F0>, <type 'voidscalar'>: <function <lambda> at 0x00BC6A30>, <type 'complex192scalar'>: <function <lambda> at 0x00BC68F0>, <type 'float32scalar'>: <function <lambda> at 0x00BC6A70>} from numpy.core.numerictypes) Overwriting mgrid=<scipy.base.index_tricks.nd_grid object at 0x00E14AD0> from scipy.base.index_tricks (was <numpy.lib.index_tricks.nd_grid object at 0x00C981B0> from numpy.lib.index_tricks) Overwriting utils=<module 'scipy.base.utils' from 'c:\Python24\lib\site-packages\scipy\base\utils.pyc'> from c:\Python24\lib\site-packages\scipy\base\utils.pyc (was <module 'scipy.utils' from 'c:\Python24\lib\site-packages\scipy\utils\__init__.pyc'> from c:\Python24\lib\site-packages\scipy\utils\__init__.pyc) Overwriting longdouble=<type 'float96_arrtype'> from __builtin__ (was <type 'float96scalar'> from __builtin__) Overwriting ArrayType=<type 'scipy.ndarray'> from scipy (was <type 'numpy.ndarray'> from numpy) Overwriting signbit=<ufunc 'signbit'> (was <ufunc 'signbit'>) Overwriting conj=<ufunc 'conjugate'> (was <ufunc 'conjugate'>) Overwriting asmatrix=<function asmatrix at 0x00E65370> from scipy.base.matrix (was <function asmatrix at 0x00BDDBF0> from numpy.core.defmatrix) Overwriting floating=<type 'floating_arrtype'> from __builtin__ (was <type 'floatingscalar'> from __builtin__) Overwriting flatiter=<type 'scipy.flatiter'> from scipy (was <type 'numpy.flatiter'> from numpy) Overwriting bitwise_xor=<ufunc 'bitwise_xor'> (was <ufunc 'bitwise_xor'>) Overwriting fabs=<ufunc 'fabs'> (was <ufunc 'fabs'>) Overwriting generic=<type 'generic_arrtype'> from __builtin__ (was <type 'genericscalar'> from __builtin__) Overwriting reshape=<function reshape at 0x00E0B7B0> from scipy.base.oldnumeric (was <function reshape at 0x00BD8A30> from numpy.core.oldnumeric) Overwriting NaN=-1.#IND (was -1.#IND) Overwriting cross=<function cross at 0x00E05D70> from scipy.base.numeric (was <function cross at 0x00BCC8B0> from numpy.core.numeric) Overwriting sqrt=<ufunc 'sqrt'> (was <ufunc 'sqrt'>) Overwriting any=<function any at 0x00E0BDB0> from scipy.base.oldnumeric (was <function any at 0x00BDD0B0> from numpy.core.oldnumeric) Overwriting split=<function split at 0x00E633B0> from scipy.base.shape_base (was <function split at 0x00CA28F0> from numpy.lib.shape_base) Overwriting floor_divide=<ufunc 'floor_divide'> (was <ufunc 'floor_divide'>) Overwriting format_parser=<class scipy.base.records.format_parser at 0x00E94540> from scipy.base.records (was <class numpy.core.records.format_parser at 0x00BF3D20> from numpy.core.records) Overwriting binary_repr=<function binary_repr at 0x00E63030> from scipy.base.function_base (was <function binary_repr at 0x00BD35B0> from numpy.core.numeric) Overwriting flipud=<function flipud at 0x00E681B0> from scipy.base.twodim_base (was <function flipud at 0x00CA2CF0> from numpy.lib.twodim_base) Overwriting iscomplexobj=<function iscomplexobj at 0x00E158B0> from scipy.base.type_check (was <function iscomplexobj at 0x00C96430> from numpy.lib.type_check) Overwriting polydiv=<function polydiv at 0x00E6ADB0> from scipy.base.polynomial (was <function polydiv at 0x00CAC370> from numpy.lib.polynomial) Overwriting identity=<function identity at 0x00E0AA70> from scipy.base.numeric (was <function identity at 0x00BD3970> from numpy.core.numeric) Overwriting greater_equal=<ufunc 'greater_equal'> (was <ufunc 'greater_equal'>) Overwriting PINF=1.#INF (was 1.#INF) Overwriting less=<ufunc 'less'> (was <ufunc 'less'>) Overwriting UFUNC_BUFSIZE_DEFAULT=10000 (was 10000) Overwriting NAN=-1.#IND (was -1.#IND) Overwriting typeDict={0: <type 'bool_arrtype'>, 1: <type 'int8_arrtype'>, 2: <type 'uint8_arrtype'>, 3: <type 'int16_arrtype'>, 4: <type 'uint16_arrtype'>, 5: <type 'int32_arrtype'>, 6: <type 'uint32_arrtype'>, 7: <type 'int32_arrtype'>, 8: <type 'uint32_arrtype'>, 9: <type 'int64_arrtype'>, 10: <type 'uint64_arrtype'>, 11: <type 'float32_arrtype'>, 12: <type 'float64_arrtype'>, 13: <type 'float96_arrtype'>, 14: <type 'complex64_arrtype'>, 15: <type 'complex128_arrtype'>, 16: <type 'complex192_arrtype'>, 17: <type 'object_arrtype'>, 18: <type 'string_arrtype'>, 19: <type 'unicode_arrtype'>, 20: <type 'void_arrtype'>, 'unicode': <type 'unicode_arrtype'>, 'cfloat': <type 'complex64_arrtype'>, 'Int32': <type 'int32_arrtype'>, 'Complex192': <type 'complex192_arrtype'>, 'Complex64': <type 'complex64_arrtype'>, 'uint16': <type 'uint16_arrtype'>, 'c16': <type 'complex128_arrtype'>, 'float32': <type 'float32_arrtype'>, 'int32': <type 'int32_arrtype'>, 'D': <type 'complex128_arrtype'>, 'float96': <type 'float96_arrtype'>, 'H': <type 'uint16_arrtype'>, 'void': <type 'void_arrtype'>, 'unicode0': <type 'unicode_arrtype'>, 'L': <type 'uint32_arrtype'>, 'P': <type 'uint32_arrtype'>, 'void0': <type 'void_arrtype'>, 'd': <type 'float64_arrtype'>, 'h': <type 'int16_arrtype'>, 'l': <type 'int32_arrtype'>, 'p': <type 'int32_arrtype'>, 'Uint16': <type 'uint16_arrtype'>, 'object0': <type 'object_arrtype'>, 'complex64': <type 'complex64_arrtype'>, 'b1': <type 'bool_arrtype'>, 'Uint32': <type 'uint32_arrtype'>, 'String0': <type 'string_arrtype'>, 'ulonglong': <type 'uint64_arrtype'>, 'Uint8': <type 'uint8_arrtype'>, 'I': <type 'uint32_arrtype'>, 'uint32': <type 'uint32_arrtype'>, '?': <type 'bool_arrtype'>, 'Void0': <type 'void_arrtype'>, 'object': <type 'object_arrtype'>, 'G': <type 'complex192_arrtype'>, 'O': <type 'object_arrtype'>, 'S': <type 'string_arrtype'>, 'byte': <type 'int8_arrtype'>, 'g': <type 'float96_arrtype'>, 'float64': <type 'float64_arrtype'>, 'ushort': <type 'uint16_arrtype'>, 'U': <type 'unicode_arrtype'>, 'cdouble': <type 'complex128_arrtype'>, 'uintp': <type 'uint32_arrtype'>, 'float': <type 'float32_arrtype'>, 'Bool8': <type 'bool_arrtype'>, 'bool8': <type 'bool_arrtype'>, 'intp': <type 'int32_arrtype'>, 'u8': <type 'uint64_arrtype'>, 'Float96': <type 'float96_arrtype'>, 'u4': <type 'uint32_arrtype'>, 'Unicode0': <type 'unicode_arrtype'>, 'u1': <type 'uint8_arrtype'>, 'complex128': <type 'complex128_arrtype'>, 'long': <type 'int32_arrtype'>, 'u2': <type 'uint16_arrtype'>, 'f8': <type 'float64_arrtype'>, 'ubyte': <type 'uint8_arrtype'>, 'Int8': <type 'int8_arrtype'>, 'Uint64': <type 'uint64_arrtype'>, 'complex192': <type 'complex192_arrtype'>, 'B': <type 'uint8_arrtype'>, 'F': <type 'complex64_arrtype'>, 'uint8': <type 'uint8_arrtype'>, 'c8': <type 'complex64_arrtype'>, 'Int64': <type 'int64_arrtype'>, 'V': <type 'void_arrtype'>, 'int8': <type 'int8_arrtype'>, 'uint64': <type 'uint64_arrtype'>, 'b': <type 'int8_arrtype'>, 'c24': <type 'complex192_arrtype'>, 'f': <type 'float32_arrtype'>, 'double': <type 'float64_arrtype'>, 'clongdouble': <type 'complex192_arrtype'>, 'f12': <type 'float96_arrtype'>, 'f4': <type 'float32_arrtype'>, 'int': <type 'int32_arrtype'>, 'longdouble': <type 'float96_arrtype'>, 'Complex128': <type 'complex128_arrtype'>, 'string': <type 'string_arrtype'>, 'q': <type 'int64_arrtype'>, 'Int16': <type 'int16_arrtype'>, 'Float64': <type 'float64_arrtype'>, 'bool': <type 'bool_arrtype'>, 'Float32': <type 'float32_arrtype'>, 'string0': <type 'string_arrtype'>, 'longlong': <type 'int64_arrtype'>, 'i8': <type 'int64_arrtype'>, 'int16': <type 'int16_arrtype'>, 'ulong': <type 'uint32_arrtype'>, 'i1': <type 'int8_arrtype'>, 'i2': <type 'int16_arrtype'>, 'i4': <type 'int32_arrtype'>, 'Q': <type 'uint64_arrtype'>, 'uint': <type 'uint32_arrtype'>, 'short': <type 'int16_arrtype'>, 'i': <type 'int32_arrtype'>, 'Object0': <type 'object_arrtype'>, 'int64': <type 'int64_arrtype'>} (was {0: <type 'boolscalar'>, 1: <type 'int8scalar'>, 2: <type 'uint8scalar'>, 3: <type 'int16scalar'>, 4: <type 'uint16scalar'>, 5: <type 'int32scalar'>, 6: <type 'uint32scalar'>, 7: <type 'int32scalar'>, 8: <type 'uint32scalar'>, 9: <type 'int64scalar'>, 10: <type 'uint64scalar'>, 11: <type 'float32scalar'>, 12: <type 'float64scalar'>, 13: <type 'float96scalar'>, 14: <type 'complex64scalar'>, 15: <type 'complex128scalar'>, 16: <type 'complex192scalar'>, 17: <type 'objectscalar'>, 18: <type 'stringscalar'>, 19: <type 'unicodescalar'>, 20: <type 'voidscalar'>, 'cfloat': <type 'complex128scalar'>, 'longfloat': <type 'float96scalar'>, 'Int32': <type 'int32scalar'>, 'unicode_': <type 'unicodescalar'>, 'uint16': <type 'uint16scalar'>, 'c16': <type 'complex128scalar'>, 'float32': <type 'float32scalar'>, 'int32': <type 'int32scalar'>, 'D': <type 'complex128scalar'>, 'float96': <type 'float96scalar'>, 'H': <type 'uint16scalar'>, 'void': <type 'voidscalar'>, 'unicode0': <type 'unicodescalar'>, 'L': <type 'uint32scalar'>, 'P': <type 'uint32scalar'>, 'void0': <type 'voidscalar'>, 'd': <type 'float64scalar'>, 'h': <type 'int16scalar'>, 'l': <type 'int32scalar'>, 'p': <type 'int32scalar'>, 'object0': <type 'objectscalar'>, 'complex64': <type 'complex64scalar'>, 'b1': <type 'boolscalar'>, 'String0': <type 'stringscalar'>, 'ulonglong': <type 'uint64scalar'>, 'i1': <type 'int8scalar'>, 'uint32': <type 'uint32scalar'>, '?': <type 'boolscalar'>, 'Void0': <type 'voidscalar'>, 'G': <type 'complex192scalar'>, 'O': <type 'objectscalar'>, 'UInt8': <type 'uint8scalar'>, 'S': <type 'stringscalar'>, 'byte': <type 'int8scalar'>, 'UInt64': <type 'uint64scalar'>, 'g': <type 'float96scalar'>, 'float64': <type 'float64scalar'>, 'ushort': <type 'uint16scalar'>, 'float_': <type 'float64scalar'>, 'U': <type 'unicodescalar'>, 'object_': <type 'objectscalar'>, 'complex_': <type 'complex128scalar'>, 'cdouble': <type 'complex128scalar'>, 'uintp': <type 'uint32scalar'>, 'intc': <type 'int32scalar'>, 'csingle': <type 'complex64scalar'>, 'bool8': <type 'boolscalar'>, 'Bool': <type 'boolscalar'>, 'intp': <type 'int32scalar'>, 'uintc': <type 'uint32scalar'>, 'u8': <type 'uint64scalar'>, 'Float96': <type 'float96scalar'>, 'u4': <type 'uint32scalar'>, 'int_': <type 'int32scalar'>, 'Unicode0': <type 'unicodescalar'>, 'u1': <type 'uint8scalar'>, 'complex128': <type 'complex128scalar'>, 'u2': <type 'uint16scalar'>, 'f8': <type 'float64scalar'>, 'ubyte': <type 'uint8scalar'>, 'Int8': <type 'int8scalar'>, 'complex192': <type 'complex192scalar'>, 'B': <type 'uint8scalar'>, 'uint0': <type 'uint32scalar'>, 'F': <type 'complex64scalar'>, 'bool_': <type 'boolscalar'>, 'uint8': <type 'uint8scalar'>, 'c8': <type 'complex64scalar'>, 'Int64': <type 'int64scalar'>, 'int0': <type 'int32scalar'>, 'V': <type 'voidscalar'>, 'int8': <type 'int8scalar'>, 'uint64': <type 'uint64scalar'>, 'b': <type 'int8scalar'>, 'c24': <type 'complex192scalar'>, 'f': <type 'float32scalar'>, 'double': <type 'float64scalar'>, 'UInt32': <type 'uint32scalar'>, 'clongdouble': <type 'complex192scalar'>, 'f12': <type 'float96scalar'>, 'f4': <type 'float32scalar'>, 'longdouble': <type 'float96scalar'>, 'single': <type 'float32scalar'>, 'string': <type 'stringscalar'>, 'q': <type 'int64scalar'>, 'Int16': <type 'int16scalar'>, 'Float64': <type 'float64scalar'>, 'UInt16': <type 'uint16scalar'>, 'Float32': <type 'float32scalar'>, 'string0': <type 'stringscalar'>, 'longlong': <type 'int64scalar'>, 'i8': <type 'int64scalar'>, 'int16': <type 'int16scalar'>, 'str_': <type 'stringscalar'>, 'I': <type 'uint32scalar'>, 'i2': <type 'int16scalar'>, 'i4': <type 'int32scalar'>, 'Q': <type 'uint64scalar'>, 'uint': <type 'uint32scalar'>, 'short': <type 'int16scalar'>, 'i': <type 'int32scalar'>, 'clongfloat': <type 'complex192scalar'>, 'Object0': <type 'objectscalar'>, 'int64': <type 'int64scalar'>}) Overwriting shape=<function shape at 0x00E0BBF0> from scipy.base.oldnumeric (was <function shape at 0x00BD8EB0> from numpy.core.oldnumeric) Overwriting setbufsize=<function setbufsize at 0x00E0ABF0> from scipy.base.numeric (was <function setbufsize at 0x00BD3AF0> from numpy.core.numeric) Overwriting cfloat=<type 'complex128_arrtype'> from __builtin__ (was <type 'complex128scalar'> from __builtin__) Overwriting uintp=<type 'uint32_arrtype'> from __builtin__ (was <type 'uint32scalar'> from __builtin__) Overwriting isscalar=<function isscalar at 0x00E15770> from scipy.base.type_check (was <function isscalar at 0x00BD3570> from numpy.core.numeric) Overwriting character=<type 'character_arrtype'> from __builtin__ (was <type 'characterscalar'> from __builtin__) Overwriting bigndarray=<type 'scipy.bigndarray'> from scipy (was <type 'numpy.bigndarray'> from numpy) Overwriting add=<ufunc 'add'> (was <ufunc 'add'>) Overwriting uint16=<type 'uint16_arrtype'> from __builtin__ (was <type 'uint16scalar'> from __builtin__) Overwriting ufunc=<type 'scipy.ufunc'> from scipy (was <type 'numpy.ufunc'> from numpy) Overwriting ravel=<function ravel at 0x00E0BB70> from scipy.base.oldnumeric (was <function ravel at 0x00BD8E30> from numpy.core.oldnumeric) Overwriting float32=<type 'float32_arrtype'> from __builtin__ (was <type 'float32scalar'> from __builtin__) Overwriting real=<function real at 0x00E157B0> from scipy.base.type_check (was <function real at 0x00C96330> from numpy.lib.type_check) Overwriting int32=<type 'int32_arrtype'> from __builtin__ (was <type 'int32scalar'> from __builtin__) Overwriting around=<function round_ at 0x00E63CF0> from scipy.base.function_base (was <function round_ at 0x00BDD3F0> from numpy.core.oldnumeric) Overwriting complex_=<type 'complex128_arrtype'> from __builtin__ (was <type 'complex128scalar'> from __builtin__) Overwriting issubclass_=<function issubclass_ at 0x00E97DB0> from scipy.base.utils (was <function issubclass_ at 0x00CAF0F0> from numpy.lib.utils) Overwriting atleast_3d=<function atleast_3d at 0x00E631F0> from scipy.base.shape_base (was <function atleast_3d at 0x00CA2730> from numpy.lib.shape_base) Overwriting isneginf=<function isneginf at 0x00E15670> from scipy.base.ufunclike (was <function isneginf at 0x00C96270> from numpy.lib.ufunclike) Overwriting integer=<type 'integer_arrtype'> from __builtin__ (was <type 'integerscalar'> from __builtin__) Overwriting unique=<function unique at 0x00E63AB0> from scipy.base.function_base (was <function unique at 0x00CA72F0> from numpy.lib.function_base) Overwriting mod=<ufunc 'remainder'> (was <ufunc 'remainder'>) Overwriting insert=<function insert at 0x00E63B30> from scipy.base.function_base (was <function insert at 0x00CA7370> from numpy.lib.function_base) Overwriting getbufsize=<function getbufsize at 0x00E0AC30> from scipy.base.numeric (was <function getbufsize at 0x00BD3B30> from numpy.core.numeric) Overwriting arange=<built-in function arange> from scipy.base.multiarray (was <built-in function arange> from numpy.core.multiarray) Overwriting asarray_chkfinite=<function asarray_chkfinite at 0x00E63670> from scipy.base.function_base (was <function asarray_chkfinite at 0x00CA7030> from numpy.lib.function_base) Overwriting hypot=<ufunc 'hypot'> (was <ufunc 'hypot'>) Overwriting logical_and=<ufunc 'logical_and'> (was <ufunc 'logical_and'>) Overwriting get_printoptions=<function get_printoptions at 0x00E0A630> from scipy.base.arrayprint (was <function get_printoptions at 0x00BD31B0> from numpy.core.arrayprint) Overwriting nonzero=<function nonzero at 0x00E0BBB0> from scipy.base.oldnumeric (was <function nonzero at 0x00BD8E70> from numpy.core.oldnumeric) Overwriting polysub=<function polysub at 0x00E6ACF0> from scipy.base.polynomial (was <function polysub at 0x00CAC2F0> from numpy.lib.polynomial) Overwriting fromfile=<built-in function fromfile> from scipy.base.multiarray (was <built-in function fromfile> from numpy.core.multiarray) Overwriting prod=<function prod at 0x00E638B0> from scipy.base.function_base (was <function prod at 0x00BDD2B0> from numpy.core.oldnumeric) Overwriting nanmax=<function nanmax at 0x00E63C30> from scipy.base.function_base (was <function nanmax at 0x00CA7470> from numpy.lib.function_base) Overwriting modf=<ufunc 'modf'> (was <ufunc 'modf'>) Overwriting hstack=<function hstack at 0x00E63270> from scipy.base.shape_base (was <function hstack at 0x00CA27B0> from numpy.lib.shape_base) Overwriting subtract=<ufunc 'subtract'> (was <ufunc 'subtract'>) Overwriting frombuffer=<built-in function frombuffer> from scipy.base.multiarray (was <built-in function frombuffer> from numpy.core.multiarray) Overwriting iscomplex=<function iscomplex at 0x00E15830> from scipy.base.type_check (was <function iscomplex at 0x00C963B0> from numpy.lib.type_check) Overwriting argsort=<function argsort at 0x00E0B9B0> from scipy.base.oldnumeric (was <function argsort at 0x00BD8C30> from numpy.core.oldnumeric) Overwriting arcsinh=<ufunc 'arcsinh'> (was <ufunc 'arcsinh'>) Overwriting intc=<type 'int32_arrtype'> from __builtin__ (was <type 'int32scalar'> from __builtin__) Overwriting ix_=<function ix_ at 0x00E68130> from scipy.base.index_tricks (was <function ix_ at 0x00CA2030> from numpy.lib.index_tricks) Overwriting Infinity=1.#INF (was 1.#INF) Overwriting log=<ufunc 'log'> (was <ufunc 'log'>) Overwriting cdouble=<type 'complex128_arrtype'> from __builtin__ (was <type 'complex128scalar'> from __builtin__) Overwriting complex128=<type 'complex128_arrtype'> from __builtin__ (was <type 'complex128scalar'> from __builtin__) Overwriting round_=<function round_ at 0x00E63CF0> from scipy.base.function_base (was <function round_ at 0x00BDD3F0> from numpy.core.oldnumeric) Overwriting inner=<built-in function inner> from scipy.lib._dotblas (was <built-in function inner> from numpy.core._dotblas) Overwriting int_=<type 'int32_arrtype'> from __builtin__ (was <type 'int32scalar'> from __builtin__) Overwriting log10=<ufunc 'log10'> (was <ufunc 'log10'>) Overwriting matrixmultiply=<built-in function dot> from scipy.base.multiarray (was <built-in function dot> from numpy.core.multiarray) Overwriting unwrap=<function unwrap at 0x00E639F0> from scipy.base.function_base (was <function unwrap at 0x00CA7230> from numpy.lib.function_base) Overwriting histogram=<function histogram at 0x00E635B0> from scipy.base.function_base (was <function histogram at 0x00CA2F70> from numpy.lib.function_base) Overwriting int0=<type 'int32_arrtype'> from __builtin__ (was <type 'int32scalar'> from __builtin__) Overwriting squeeze=<function squeeze at 0x00E63130> from scipy.base.shape_base (was <function squeeze at 0x00BD8D70> from numpy.core.oldnumeric) Overwriting int8=<type 'int8_arrtype'> from __builtin__ (was <type 'int8scalar'> from __builtin__) Overwriting seterr=<function seterr at 0x00E0AB70> from scipy.base.numeric (was <function seterr at 0x00BD3A70> from numpy.core.numeric) Overwriting argmin=<function argmin at 0x00E0BA30> from scipy.base.oldnumeric (was <function argmin at 0x00BD8CB0> from numpy.core.oldnumeric) Overwriting maximum=<ufunc 'maximum'> (was <ufunc 'maximum'>) Overwriting record=<class 'scipy.base.records.record'> from scipy.base.records (was <class 'numpy.core.records.record'> from numpy.core.records) Overwriting clongdouble=<type 'complex192_arrtype'> from __builtin__ (was <type 'complex192scalar'> from __builtin__) Overwriting isrealobj=<function isrealobj at 0x00E158F0> from scipy.base.type_check (was <function isrealobj at 0x00C96470> from numpy.lib.type_check) Overwriting arccosh=<ufunc 'arccosh'> (was <ufunc 'arccosh'>) Overwriting tril=<function tril at 0x00E682F0> from scipy.base.twodim_base (was <function tril at 0x00CA2E30> from numpy.lib.twodim_base) Overwriting char=<module 'scipy.base.chararray' from 'c:\Python24\lib\site-packages\scipy\base\chararray.pyc'> from c:\Python24\lib\site-packages\scipy\base\chararray.pyc (was <module 'numpy.core.defchararray' from 'c:\Python24\lib\site-packages\numpy\core\defchararray.pyc'> from c:\Python24\lib\site-packages\numpy\core\defchararray.pyc) Overwriting single=<type 'float32_arrtype'> from __builtin__ (was <type 'float32scalar'> from __builtin__) Overwriting ScalarType=(<type 'int'>, <type 'float'>, <type 'complex'>, <type 'long'>, <type 'bool'>, <type 'str'>, <type 'unicode'>, <type 'buffer'>, <type 'int64_arrtype'>, <type 'int16_arrtype'>, <type 'int32_arrtype'>, <type 'unicode_arrtype'>, <type 'uint32_arrtype'>, <type 'int32_arrtype'>, <type 'void_arrtype'>, <type 'complex192_arrtype'>, <type 'uint64_arrtype'>, <type 'string_arrtype'>, <type 'complex64_arrtype'>, <type 'object_arrtype'>, <type 'float32_arrtype'>, <type 'uint8_arrtype'>, <type 'complex128_arrtype'>, <type 'int8_arrtype'>, <type 'float64_arrtype'>, <type 'uint32_arrtype'>, <type 'uint16_arrtype'>, <type 'float96_arrtype'>, <type 'bool_arrtype'>) (was (<type 'int'>, <type 'float'>, <type 'complex'>, <type 'long'>, <type '

2 1

[ANN] NumPy 0.9.6 released
by Travis Oliphant March 15, 2006

March 15, 2006

This post is to announce the release of NumPy 0.9.6 which fixes some important bugs and has several speed improvments. NumPy is a multi-dimensional array-package for Python that allows rapid high-level array computing with Python. It is successor to both Numeric and Numarray. More information at http://numeric.scipy.org The release notes are attached: Best regards, NumPy Developers NumPy 0.9.6 is a bug-fix and optimization release with a few new features: New features (and changes): - bigndarray removed and support for Python2.5 ssize_t added giving full support in Python2.5 to very-large arrays on 64-bit systems. - Strides can be set more arbitrarily from Python (and checking is done to make sure memory won't be violated). - __array_finalize__ is now called for every array sub-class creation. - kron and repmat functions added - .round() method added for arrays - rint, square, reciprocal, and ones_like ufuncs added. - keyword arguments now possible for methods taking a single 'axis' argument - Swig and Pyrex examples added in doc/swig and doc/pyrex - NumPy builds out of the box for cygwin - Different unit testing naming schemes are now supported. - memusage in numpy.distutils works for NT platforms - numpy.lib.math functions now take vectors - Most functions in oldnumeric now return intput class where possible Speed ups: - x**n for integer n signficantly improved - array(<python scalar>) much faster - .fill() method is much faster Other fixes: - Output arrays to ufuncs works better. - Several ma (Masked Array) fixes. - umath code generation improved - many fixes to optimized dot function (fixes bugs in matrix-sub-class multiply) - scalartype fixes - improvements to poly1d - f2py fixed to handle character arrays in common blocks - Scalar arithmetic improved to handle mixed-mode operation. - Make sure Python intYY types correspond exactly with C PyArray_INTYY

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[Scipy Users] Weave documentation not on new scipy.org ?
by Cournapeau David March 14, 2006

March 14, 2006

Hi, I wanted to know if there is any documentation for weave on the new scipy.org webpage ? I remembered having seen some tutorial some time ago on the old page, but the link for weave leads to a non existant page on scipy.org. A search on the scipy.org website does not give any result either, Thank you, David

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Re: [SciPy-user] [Numpy-discussion] [ANN] NumPy 0.9.6 released
by Nadav Horesh March 14, 2006

March 14, 2006

There is a compatibility problem, at least with the last formal release of scipy. Should we checkout and compile scipy from svn? Nadav. -----Original Message----- From: numpy-discussion-admin(a)lists.sourceforge.net on behalf of Bill Baxter Sent: Tue 14-Mar-06 13:52 To: numpy-discussion; SciPy Users List Cc: Subject: Re: [Numpy-discussion] [ANN] NumPy 0.9.6 released Just wondering, does this one also require an update to scipy? And in general do numpy updates always require an update to scipy, too? Or is it only when the numpy C API interface changes? --bb On 3/14/06, Travis Oliphant <oliphant.travis(a)ieee.org> wrote: > > This post is to announce the release of NumPy 0.9.6 which fixes some > important bugs and has several speed improvments. > > NumPy is a multi-dimensional array-package for Python that allows rapid > high-level array computing with Python. It is successor to both Numeric > and Numarray. More information at http://numeric.scipy.org > > The release notes are attached: > > Best regards, > > NumPy Developers > > > > > > > NumPy 0.9.6 is a bug-fix and optimization release with a > few new features: > > > New features (and changes): > > - bigndarray removed and support for Python2.5 ssize_t added giving > full support in Python2.5 to very-large arrays on 64-bit systems. > > - Strides can be set more arbitrarily from Python (and checking is done > to make sure memory won't be violated). > > - __array_finalize__ is now called for every array sub-class creation. > > - kron and repmat functions added > > - .round() method added for arrays > > - rint, square, reciprocal, and ones_like ufuncs added. > > - keyword arguments now possible for methods taking a single 'axis' > argument > > - Swig and Pyrex examples added in doc/swig and doc/pyrex > > - NumPy builds out of the box for cygwin > > - Different unit testing naming schemes are now supported. > > - memusage in numpy.distutils works for NT platforms > > - numpy.lib.math functions now take vectors > > - Most functions in oldnumeric now return intput class where possible > > > Speed ups: > > - x**n for integer n signficantly improved > > - array(<python scalar>) much faster > > - .fill() method is much faster > > > Other fixes: > > - Output arrays to ufuncs works better. > > - Several ma (Masked Array) fixes. > > - umath code generation improved > > - many fixes to optimized dot function (fixes bugs in > matrix-sub-class multiply) > > - scalartype fixes > > - improvements to poly1d > > - f2py fixed to handle character arrays in common blocks > > - Scalar arithmetic improved to handle mixed-mode operation. > > - Make sure Python intYY types correspond exactly with C PyArray_INTYY > > > > > -- William V. Baxter III OLM Digital Kono Dens Building Rm 302 1-8-8 Wakabayashi Setagaya-ku Tokyo, Japan 154-0023 +81 (3) 3422-3380

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cspline1d_eval
by George Geller March 13, 2006

March 13, 2006

I was trying to follow the recipe at: http://www.scipy.org/Cookbook/Interpolation from numpy import r_, sin from scipy.signal import cspline1d, cspline1d_eval x = r_[0:10] dx = x[1]-x[0] newx = r_[-3:13:0.1] # notice outside the original domain y = sin(x) cj = cspline1d(y) newy = cspline1d_eval(cj, newx, dx=dx,x0=x[0]) from pylab import plot plot(newx, newy, x, y, 'o') First, with my installation the first import line has to read: from scipy import r_, sin Second, the cspline1d_eval function seems to no longer be part of scipy.signal: ggeller@hayes:~$ python Python 2.4.2 (#2, Sep 30 2005, 21:19:01) [GCC 4.0.2 20050808 (prerelease) (Ubuntu 4.0.1-4ubuntu8)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> from scipy.signal import cspline1d_eval Traceback (most recent call last): File "<stdin>", line 1, in ? ImportError: cannot import name cspline1d_eval Am I doing something really dumb, or is the recipe seriously obsolete? George

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maxentropy
by Matthew Cooper March 13, 2006

March 13, 2006

Hi, I am wondering if there is any additional documentation for the scipy.maxentropy module. I am interested in building a conditional maxent classifier using the module, but am having trouble making sense of it from the source. Any additional information you can provide is greatly appreciated. Thanks, Matt Cooper

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