Re: [Numpy-discussion] nose changes checked in
On Mon, Jun 16, 2008 at 21:18, Alan McIntyre <[EMAIL PROTECTED]> wrote: > On Mon, Jun 16, 2008 at 9:04 PM, Charles R Harris > <[EMAIL PROTECTED]> wrote: >> In [1]: numpy.test() >> Not implemented: Defined_Binary_Op >> Not implemented: Defined_Binary_Op >> Defined_Operator not defined used by Generic_Spec >> Needs match implementation: Allocate_Stmt >> Needs match implementation: Associate_Construct > > > That stream of "Not implemented" and "Needs match implementation" > stuff comes from numpy/f2py/lib/parser/test_Fortran2003.py and > Fortran2003.py. I can silence most of that output by disabling those > module-level "if 1:" blocks in those two files, but there's still > complaints about Defined_Binary_Op not being implemented. If someone > more knowledgeable about that module could comment on that I'd > appreciate it. These files were for the in-development g3 version of f2py. That development has moved outside of numpy, so I think they can be removed wholesale. Some of them seem to require a Fortran 90 compiler, so I have had them fail for me. Removing these is a high priority. Pearu, can you confirm? Can we give you the task of removing the unused g3 portions of f2py for the 1.2 release? -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] nose changes checked in
On Mon, Jun 16, 2008 at 8:18 PM, Alan McIntyre <[EMAIL PROTECTED]> wrote: > On Mon, Jun 16, 2008 at 9:04 PM, Charles R Harris > <[EMAIL PROTECTED]> wrote: > > Did you add any documentation to the readme? Any particular version > > dependency for Nose? > > I did update README.txt, but I forgot to put the minimum Nose version > in there; thanks for mentioning that. I just checked in an update > that includes it. > > > Hmm, plenty of output, 1 failure, and it looks like a future warning in > > histogram needs to be disabled. > > > > In [1]: numpy.test() > > Not implemented: Defined_Binary_Op > > Not implemented: Defined_Binary_Op > > Defined_Operator not defined used by Generic_Spec > > Needs match implementation: Allocate_Stmt > > Needs match implementation: Associate_Construct > > > That stream of "Not implemented" and "Needs match implementation" > stuff comes from numpy/f2py/lib/parser/test_Fortran2003.py and > Fortran2003.py. I can silence most of that output by disabling those > module-level "if 1:" blocks in those two files, but there's still > complaints about Defined_Binary_Op not being implemented. If someone > more knowledgeable about that module could comment on that I'd > appreciate it. > > I'll also look into that test_linalg failure first thing in the > morning; I don' get that here. > > > Looks slower than the old testing framework, but not enough to matter. > > There were at least a couple of tests that didn't get run under the > old framework, but the ones I can recall didn't look complicated > enough to make a difference. > > Looks like the buildbots need nose installed or upgraded as well. > Thanks for doing this. It looks like the transition to nose is going to be pretty smooth. Chuck ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] nose changes checked in
On Mon, Jun 16, 2008 at 9:04 PM, Charles R Harris <[EMAIL PROTECTED]> wrote: > Did you add any documentation to the readme? Any particular version > dependency for Nose? I did update README.txt, but I forgot to put the minimum Nose version in there; thanks for mentioning that. I just checked in an update that includes it. > Hmm, plenty of output, 1 failure, and it looks like a future warning in > histogram needs to be disabled. > > In [1]: numpy.test() > Not implemented: Defined_Binary_Op > Not implemented: Defined_Binary_Op > Defined_Operator not defined used by Generic_Spec > Needs match implementation: Allocate_Stmt > Needs match implementation: Associate_Construct That stream of "Not implemented" and "Needs match implementation" stuff comes from numpy/f2py/lib/parser/test_Fortran2003.py and Fortran2003.py. I can silence most of that output by disabling those module-level "if 1:" blocks in those two files, but there's still complaints about Defined_Binary_Op not being implemented. If someone more knowledgeable about that module could comment on that I'd appreciate it. I'll also look into that test_linalg failure first thing in the morning; I don' get that here. > Looks slower than the old testing framework, but not enough to matter. There were at least a couple of tests that didn't get run under the old framework, but the ones I can recall didn't look complicated enough to make a difference. Looks like the buildbots need nose installed or upgraded as well. Thanks, Alan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] nose changes checked in
On Mon, Jun 16, 2008 at 8:39 PM, Robert Kern <[EMAIL PROTECTED]> wrote: > On Mon, Jun 16, 2008 at 19:28, Alan McIntyre <[EMAIL PROTECTED]> wrote: > Please port over the changes I made to scipy.testing in scipy's r4424 > in order to avoid importing nose until the actual execution of tests. Done in r5289. ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Polyfit
2008/6/16 Chandler Latour <[EMAIL PROTECTED]>: > I believe I'm bound to python. > In terms of forcing the regression through the origin, the purpose is partly > for visualization but it also should fit the data. It would not make sense > to model the data with an initial value other than 0. Polyfit is just a thin wrapper around numpy.linalg.lstsq. You can do something like: A = np.power.outer(xs,np.arange(1,n)) outputs = np.linalg.lstsq(A,ys) Anne ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] nose changes checked in
On Mon, Jun 16, 2008 at 6:28 PM, Alan McIntyre <[EMAIL PROTECTED]> wrote: > Hi all, > > I just checked in the switch to use nose to run unit tests. Please > let me know if you experience any difficulties as a result. > Did you add any documentation to the readme? Any particular version dependency for Nose? Hmm, plenty of output, 1 failure, and it looks like a future warning in histogram needs to be disabled. In [1]: numpy.test() Not implemented: Defined_Binary_Op Not implemented: Defined_Binary_Op Defined_Operator not defined used by Generic_Spec Needs match implementation: Allocate_Stmt Needs match implementation: Associate_Construct Needs match implementation: Backspace_Stmt Needs match implementation: Block_Data Needs match implementation: Case_Construct Needs match implementation: Case_Selector Needs match implementation: Case_Stmt Needs match implementation: Control_Edit_Desc Needs match implementation: Data_Component_Def_Stmt Needs match implementation: Data_Implied_Do Needs match implementation: Data_Stmt Needs match implementation: Data_Stmt_Set Needs match implementation: Deallocate_Stmt Needs match implementation: Derived_Type_Def Needs match implementation: Endfile_Stmt Needs match implementation: Entry_Stmt Needs match implementation: Enum_Def Needs match implementation: Flush_Stmt Needs match implementation: Forall_Construct Needs match implementation: Forall_Header Needs match implementation: Forall_Triplet_Spec Needs match implementation: Format_Item Needs match implementation: Function_Stmt Needs match implementation: Generic_Binding Needs match implementation: Generic_Spec Needs match implementation: Implicit_Part Needs match implementation: Inquire_Stmt Needs match implementation: Interface_Block Needs match implementation: Interface_Body Needs match implementation: Interface_Stmt Needs match implementation: Internal_Subprogram_Part Needs match implementation: Io_Implied_Do Needs match implementation: Io_Implied_Do_Control Needs match implementation: Main_Program Needs match implementation: Module Needs match implementation: Module_Subprogram_Part Needs match implementation: Namelist_Stmt Needs match implementation: Pointer_Assignment_Stmt Needs match implementation: Position_Edit_Desc Needs match implementation: Proc_Attr_Spec Needs match implementation: Proc_Component_Def_Stmt Needs match implementation: Procedure_Declaration_Stmt Needs match implementation: Procedure_Stmt Needs match implementation: Read_Stmt Needs match implementation: Rewind_Stmt Needs match implementation: Select_Type_Construct Needs match implementation: Select_Type_Stmt Needs match implementation: Specific_Binding Needs match implementation: Target_Stmt Needs match implementation: Type_Bound_Procedure_Part Needs match implementation: Where_Construct - Nof match implementation needs: 51 out of 224 Nof tests needs: 224 out of 224 Total number of classes: 529 - ./usr/lib/python2.5/site-packages/numpy/lib/function_base.py:166: FutureWarning: The semantics of histogram will be modified in release 1.2 to improve outlier handling. The new behavior can be obtained using new=True. Note that the new version accepts/returns the bin edges instead of the left bin edges. Please read the docstring for more information. Please read the docstring for more information.""", FutureWarning) /usr/lib/python2.5/site-packages/numpy/lib/function_base.py:193: FutureWarning: The semantic for bins will change in version 1.2. The bins will become the bin edges, instead of the left bin edges. """, FutureWarning) ...E.
Re: [Numpy-discussion] nose changes checked in
On Mon, Jun 16, 2008 at 19:28, Alan McIntyre <[EMAIL PROTECTED]> wrote: > Hi all, > > I just checked in the switch to use nose to run unit tests. Please > let me know if you experience any difficulties as a result. Please port over the changes I made to scipy.testing in scipy's r4424 in order to avoid importing nose until the actual execution of tests. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] nose changes checked in
Hi all, I just checked in the switch to use nose to run unit tests. Please let me know if you experience any difficulties as a result. Thanks, Alan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Polyfit
I believe I'm bound to python. In terms of forcing the regression through the origin, the purpose is partly for visualization but it also should fit the data. It would not make sense to model the data with an initial value other than 0. On Jun 16, 2008, at 4:33 PM, Simon Palmer wrote: At the risk of uttering a heresy, are you bound to Python for this? I bet you could find a C library that will work well, plus it is not a hard algorithm to code yourself. I am pretty sure I have used a numerical recipes algorithm for regression in my distant past. Also I can't help thinking the idea of forcing your regression fit through the origin is a of a bit strange thing to do. Do you want it to pass through the origin for visualisation purposes? What if the origin is not a statistically valid place for the regression fit to pass through? On Mon, Jun 16, 2008 at 9:25 PM, Charles R Harris <[EMAIL PROTECTED] > wrote: On Mon, Jun 16, 2008 at 1:47 PM, Chandler Latour <[EMAIL PROTECTED]> wrote: Yes, exactly what I meant. Polyfit just fits polynomials, there is no way of fixing the constant to zero. Your best bet is to use linalg.lstsq directly to fit the function you want. Chuck ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Polyfit
At the risk of uttering a heresy, are you bound to Python for this? I bet you could find a C library that will work well, plus it is not a hard algorithm to code yourself. I am pretty sure I have used a numerical recipes algorithm for regression in my distant past. Also I can't help thinking the idea of forcing your regression fit through the origin is a of a bit strange thing to do. Do you want it to pass through the origin for visualisation purposes? What if the origin is not a statistically valid place for the regression fit to pass through? On Mon, Jun 16, 2008 at 9:25 PM, Charles R Harris <[EMAIL PROTECTED]> wrote: > > > On Mon, Jun 16, 2008 at 1:47 PM, Chandler Latour <[EMAIL PROTECTED]> > wrote: > >> Yes, exactly what I meant. >> > > Polyfit just fits polynomials, there is no way of fixing the constant to > zero. Your best bet is to use linalg.lstsq directly to fit the function you > want. > > Chuck > > > > ___ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > > ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Polyfit
On Mon, Jun 16, 2008 at 1:47 PM, Chandler Latour <[EMAIL PROTECTED]> wrote: > Yes, exactly what I meant. > Polyfit just fits polynomials, there is no way of fixing the constant to zero. Your best bet is to use linalg.lstsq directly to fit the function you want. Chuck ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Polyfit
Yes, exactly what I meant. On Jun 16, 2008, at 2:39 PM, Charles R Harris wrote: On Mon, Jun 16, 2008 at 1:30 PM, Chandler Latour <[EMAIL PROTECTED]> wrote: Hello, I'm new to the whole numpy scene, but I've been wanting to run a regression on some data. I belive that polyfit is the way to go, but I was wondering if there exists a way to force the intercept to be 0. Any help would be much appreciated. You mean fit a line passing through the origin? Chuck ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Polyfit
On Mon, Jun 16, 2008 at 1:30 PM, Chandler Latour <[EMAIL PROTECTED]> wrote: > Hello, > > I'm new to the whole numpy scene, but I've been wanting to run a > regression on some data. I belive that polyfit is the way to go, but > I was wondering if there exists a way to force the intercept to be 0. > Any help would be much appreciated. > You mean fit a line passing through the origin? Chuck ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Polyfit
Hello, I'm new to the whole numpy scene, but I've been wanting to run a regression on some data. I belive that polyfit is the way to go, but I was wondering if there exists a way to force the intercept to be 0. Any help would be much appreciated. Thanks ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Detecting phase windings
I have a speed problem with the approach I'm using to detect phase wrappings in a 3D data set. In my application, phaseField is a 3D array containing the phase values of a field. In order to detect the vortices/phase windings at each point, I check for windings on each of 3 faces of a 2x2 cube with the following code: def HasVortex(cube): ''' cube is a 2x2x2 array containing the phase values returns True if any of 3 orthogonal faces contains a phase wrapping ''' # extract 3 cube faces - flatten to make indexing easier c1 = cube[0,:,:].flatten() c3 = cube[:,0,:].flatten() c5 = cube[:,:,0].flatten() # now order the phases in a circuit around each face, finishing in the same corner as we began # Use numpy's phase unwrapping code, which has a default threshold of pi u1 = unwrap(c1[cwi]) u3 = unwrap(c3[cwi]) u5 = unwrap(c5[cwi]) # check whether the final unwrapped value coincides with the value in the cell we started at return not allclose(r_[u1[0],u3[0],u5[0]], r_[u1[4],u3[4],u5[4]]) vortexArray = array([int(HasVortex(phaseField[x:x+2,y:y+2,z:z+2])) for x in range(phaseField.shape[0]-1) for y in range(phaseField.shape[1]-1) for z in range(phaseField.shape[2]-1)]\ ).reshape((xs-1,ys-1,zs-1)) Whilst this does what I want, it's incredibly slow. I'm wondering whether anyone has done this before, or can think of a better approach. My thoughts about a better approach are to stack the values along 3 new dimensions making a 6D array and use unwrap along the 3 new dimensions. Something like the following may give you an idea of what I mean, but it's a toy example trying to extend 2D into 3D, rather than 3D into 6D, because I haven't come to grips with enough of numpy's axis reshaping and stacking tricks to avoid getting a severe headache when trying to generalize it: a = array([[1.,3.], [6.,5.]]) b = np.dstack((a, roll(a,-1,axis=1), roll(roll(a,-1,axis=0),-1,axis=1), roll(a,-1,axis=0), a)) print np.unwrap(b, axis=2) A problem with this approach is that the memory requirements for the stacked version will be much greater, so some version using views would be preferable. Any ideas? Gary Ruben ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
