Mailman 3 January 2023 - SciPy-User

How to display a RGB image (MFISH)?
by jp April 3, 2023

April 3, 2023

Hi, I have written a script to try to combine five images into a three channels RGB images<http://dip4fish.blogspot.com/2011/05/trying-to-combine-mfish-images-into-rg…> . The resulting RGB image looks like a grey scale image instead of a color one. I have three np.array Rnorm, Gnorm, Bnorm which are copied into a rgb array: *rgb = np.zeros((shape[0],shape[1],3),dtype=float) mxr=np.max(R) mxg=np.max(G) mxb=np.max(B) Rnorm=np.uint8((255*(R/mxr)))Gnorm=np.uint8((255*(R/mxg)))Bnorm=np.uint8((255*(R/mxb)))#copy each RGB component in an RGB array rgb[:,:,0]=Rnorm rgb[:,:,1]=Gnorm rgb[:,:,2]=Bnorm* *pylab.subplot(224, aspect='equal',frameon=False, xticks=[], yticks=[]) pylab.imshow(rgb) pylab.show()* Any advice? Thank you Jean-Patrick

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NumPy 1.23.2 release
by Charles R Harris March 22, 2023

March 22, 2023

Hi All, On behalf of the NumPy team, I am pleased to announce the release of NumPy 1.23.2. NumPy 1.23.2 is a maintenance release that fixes bugs discovered after the 1.23.1 release. Notable features are: - Typing changes needed for Python 3.11 - Wheels for Python 3.11.0rc1 The Python versions supported for this release are 3.8-3.11. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.23.2>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.23.2>. *Contributors* A total of 9 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Alexander Grund + - Bas van Beek - Charles Harris - Jon Cusick + - Matti Picus - Michael Osthege + - Pal Barta + - Ross Barnowski - Sebastian Berg *Pull requests merged* A total of 15 pull requests were merged for this release. - #22030: ENH: Add ``__array_ufunc__`` typing support to the ``nin=1`` ufuncs - #22031: MAINT, TYP: Fix ``np.angle`` dtype-overloads - #22032: MAINT: Do not let ``_GenericAlias`` wrap the underlying classes'... - #22033: TYP,MAINT: Allow ``einsum`` subscripts to be passed via integer... - #22034: MAINT,TYP: Add object-overloads for the ``np.generic`` rich comparisons - #22035: MAINT,TYP: Allow the ``squeeze`` and ``transpose`` method to... - #22036: BUG: Fix subarray to object cast ownership details - #22037: BUG: Use ``Popen`` to silently invoke f77 -v - #22038: BUG: Avoid errors on NULL during deepcopy - #22039: DOC: Add versionchanged for converter callable behavior. - #22057: MAINT: Quiet the anaconda uploads. - #22078: ENH: reorder includes for testing on top of system installations... - #22106: TST: fix test_linear_interpolation_formula_symmetric - #22107: BUG: Fix skip condition for test_loss_of_precision[complex256] - #22115: BLD: Build python3.11.0rc1 wheels. Cheers, Charles Harris

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scipy.optimize.minimize for sparse matrices
by simon zhang Jan. 24, 2023

Jan. 24, 2023

I am trying to minimize a cost function that consists of sparse matrices using scipy.optimize.minimze and it seems like scipy.optimize.minimize isn't designed for sparse matrices operations. Does anyone know any other functions that allow me to minimize a function made up of sparse matrices and vectors? Or does anyone have any suggestion how to approach my problem? Thank you.

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Re: Getting scipy.interpolate.pchip_interpolate to return the first derivative of a pchip interpolation
by Samuel Dupree Jan. 23, 2023

Jan. 23, 2023

Thank you for all the responses, however my question still remains: how does pchip_interpolate know the identity of the function that generated the data and the first derivative to be interpolated? It can't because all pchip_interpolate gets is a list of numbers. The identity of the functions are not passed to it unless there is a way pchip_interpolate knows. Sam Dupree. On 1/23/23 14:35, scipy-user-request(a)python.org wrote: > Send SciPy-User mailing list submissions to > scipy-user(a)python.org > > To subscribe or unsubscribe via the World Wide Web, visit > https://mail.python.org/mailman3/lists/scipy-user.python.org/ > or, via email, send a message with subject or body 'help' to > scipy-user-request(a)python.org > > You can reach the person managing the list at > scipy-user-owner(a)python.org > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of SciPy-User digest..." > > Today's Topics: > > 1. Re: SciPy-User Digest, Vol 231, Issue 1 (Samuel Dupree) > 2. Re: SciPy-User Digest, Vol 231, Issue 1 (Evgeni Burovski) > 3. Re: SciPy-User Digest, Vol 231, Issue 1 (Rusty Gentile) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Mon, 23 Jan 2023 13:25:50 -0500 > From: Samuel Dupree <sdupree(a)speakeasy.net> > Subject: [SciPy-User] Re: SciPy-User Digest, Vol 231, Issue 1 > To: scipy-user(a)python.org, scipy-user-request(a)python.org > Message-ID: <efbf3750-f7d3-5469-1978-8188befae150(a)speakeasy.net> > Content-Type: text/plain; charset=UTF-8; format=flowed > > The problem I have is if the interpolator only sees numbers. Unless > there is some undercover means by which the interpolator sees the > function used to generate the numbers passed to it, how does it know the > conversion factor is used argument to the sine function? Furthermore, If > I were to rewrite the program as follows, I still get the same results. > > > > import numpy as np > import matplotlib.pyplot as plt > from scipy.interpolate import pchip_interpolate > > x_observed = np.linspace(0.0, 360.0, 100) > xx_observed = np.pi*x_observed/180 > > y_observed = np.sin(xx_observed) > dydx_observed = np.cos(xx_observed) > > x = np.linspace(min(x_observed), max(x_observed), num=100) > y = pchip_interpolate(x_observed, y_observed, x, der=0, axis=0) > dydx = pchip_interpolate(x_observed, y_observed, x, der=1, axis=0) > > > ndim = len( dydx ) > print() > for i in range(0,ndim): > print( dydx_observed[i], " ", dydx[i] ) > > > plt.plot(x_observed, y_observed, "bo" , label="observation funct") > plt.plot(x_observed, dydx_observed, "rx" , label="observation deriv") > > plt.plot(x , y , "c-", label="pchip interpolation funct") > plt.plot(x , dydx , "k-", label="pchip interpolation deriv") > plt.legend() > plt.grid() > plt.savefig("pchip_example_01.png") > plt.show() > > > Any thoughts? > > Sam Dupree. > > {snip] > > _______________________________________________ > SciPy-User mailing list -- scipy-user(a)python.org > To unsubscribe send an email to scipy-user-leave(a)python.org > https://mail.python.org/mailman3/lists/scipy-user.python.org/ > > > ------------------------------ > > End of SciPy-User Digest, Vol 231, Issue 2 > ****************************************** >

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Re: SciPy-User Digest, Vol 231, Issue 1
by Samuel Dupree Jan. 23, 2023

Jan. 23, 2023

The problem I have is if the interpolator only sees numbers. Unless there is some undercover means by which the interpolator sees the function used to generate the numbers passed to it, how does it know the conversion factor is used argument to the sine function? Furthermore, If I were to rewrite the program as follows, I still get the same results. import numpy as np import matplotlib.pyplot as plt from scipy.interpolate import pchip_interpolate x_observed = np.linspace(0.0, 360.0, 100) xx_observed = np.pi*x_observed/180 y_observed = np.sin(xx_observed) dydx_observed = np.cos(xx_observed) x = np.linspace(min(x_observed), max(x_observed), num=100) y = pchip_interpolate(x_observed, y_observed, x, der=0, axis=0) dydx = pchip_interpolate(x_observed, y_observed, x, der=1, axis=0) ndim = len( dydx ) print() for i in range(0,ndim): print( dydx_observed[i], " ", dydx[i] ) plt.plot(x_observed, y_observed, "bo" , label="observation funct") plt.plot(x_observed, dydx_observed, "rx" , label="observation deriv") plt.plot(x , y , "c-", label="pchip interpolation funct") plt.plot(x , dydx , "k-", label="pchip interpolation deriv") plt.legend() plt.grid() plt.savefig("pchip_example_01.png") plt.show() Any thoughts? Sam Dupree. On 1/23/23 12:00, scipy-user-request(a)python.org wrote: > Send SciPy-User mailing list submissions to > scipy-user(a)python.org > > To subscribe or unsubscribe via the World Wide Web, visit > https://mail.python.org/mailman3/lists/scipy-user.python.org/ > or, via email, send a message with subject or body 'help' to > scipy-user-request(a)python.org > > You can reach the person managing the list at > scipy-user-owner(a)python.org > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of SciPy-User digest..." > > Today's Topics: > > 1. Re: Getting scipy.interpolate.pchip_interpolate to return the first derivative of a pchip interpolation > (Evgeni Burovski) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Mon, 23 Jan 2023 11:20:45 +0300 > From: Evgeni Burovski <evgeny.burovskiy(a)gmail.com> > Subject: [SciPy-User] Re: Getting scipy.interpolate.pchip_interpolate > to return the first derivative of a pchip interpolation > To: SciPy Users List <scipy-user(a)python.org> > Message-ID: > <CAMRo0ita9yhVLcETaBNPOaL5mYMvm8N1KQV-=km0r+p5cJPekg(a)mail.gmail.com> > Content-Type: text/plain; charset="UTF-8" > > Well, the derivative of sin(x*pi/180) is pi/180 * cos(x*pi/180), and > the interpolator picks this up. > > On Mon, Jan 23, 2023 at 8:50 AM Samuel Dupree <sdupree(a)speakeasy.net> wrote: >> I'm running SciPy ver. 1.9.3 under Python ver. 3.9.15 on a Mac Pro (2019) desktop running Mac OSX ver. 13.1 Ventura. The problem I'm having is getting scipy.interpolate.pchip_interpolate to return the first derivative of a pchip interpolation. >> >> The test program I'm using is given below (and attached to this note). >> >> >> import numpy as np >> import matplotlib.pyplot as plt >> from scipy.interpolate import pchip_interpolate >> >> x_observed = np.linspace(0.0, 360.0, 51) >> y_observed = np.sin(np.pi*x_observed/180) >> dydx_observed = np.cos(np.pi*x_observed/180) >> >> x = np.linspace(min(x_observed), max(x_observed), num=100) >> y = pchip_interpolate(x_observed, y_observed, x, der=0, axis=0) >> dydx = pchip_interpolate(x_observed, y_observed, x, der=1, axis=0) >> >> plt.plot(x_observed, y_observed, "bo" , label="observation funct") >> plt.plot(x_observed, dydx_observed, "rx" , label="observation deriv") >> plt.plot(x , y , "c-", label="pchip interpolation funct") >> plt.plot(x , dydx , "k-", label="pchip interpolation deriv") >> plt.legend() >> plt.savefig("pchip_example_01.png") >> plt.show() >> >> >> The program generates values of the sine function (y_observed) over the range of 0 to 360 degrees. (x_observed). In a similar fashion, the cosine function (first derivative of the sine function) is generated over the same range (dydx_observed). pchip_interpolate is used to perform the interpolation over a specified range for the function and its first derivative. A composite plot is generated showing the points for the function (the sine) and its first derivative (cosine). The interpolated points overlay the function (sine) as expected. However, the first derivative returned fails to overlay the cosine function. The plot is attached to this note. >> >> Upon closer inspection, I believe I know what is going on, but I don't understand why. >> >> The line for the first derivative that failed to coincide with the points in the plot for the cosine is actually the interpolated first derivative scaled by the factor pi/180. When I multiply the interpolated values for the first derivative by 180/pi, the interpolated first derivative coincides with the points for the cosine as expected. >> >> What I don't understand is how the interpolator came up with the scale factor it did and applied it using pure numbers. >> >> Any thoughts? >> >> Sam Dupree >> >> _______________________________________________ >> SciPy-User mailing list -- scipy-user(a)python.org >> To unsubscribe send an email to scipy-user-leave(a)python.org >> https://mail.python.org/mailman3/lists/scipy-user.python.org/ >> Member address: evgeny.burovskiy(a)gmail.com > ------------------------------ > > Subject: Digest Footer > > _______________________________________________ > SciPy-User mailing list -- scipy-user(a)python.org > To unsubscribe send an email to scipy-user-leave(a)python.org > https://mail.python.org/mailman3/lists/scipy-user.python.org/ > > > ------------------------------ > > End of SciPy-User Digest, Vol 231, Issue 1 > ****************************************** >

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Getting scipy.interpolate.pchip_interpolate to return the first derivative of a pchip interpolation
by Samuel Dupree Jan. 23, 2023

Jan. 23, 2023

I'm running SciPy ver. 1.9.3 under Python ver. 3.9.15 on a Mac Pro (2019) desktop running Mac OSX ver. 13.1 Ventura. The problem I'm having is getting scipy.interpolate.pchip_interpolate to return the first derivative of a pchip interpolation. The test program I'm using is given below (and attached to this note). import numpy as np import matplotlib.pyplot as plt from scipy.interpolate import pchip_interpolate x_observed = np.linspace(0.0, 360.0, 51) y_observed = np.sin(np.pi*x_observed/180) dydx_observed = np.cos(np.pi*x_observed/180) x = np.linspace(min(x_observed), max(x_observed), num=100) y = pchip_interpolate(x_observed, y_observed, x, der=0, axis=0) dydx = pchip_interpolate(x_observed, y_observed, x, der=1, axis=0) plt.plot(x_observed, y_observed, "bo" , label="observation funct") plt.plot(x_observed, dydx_observed, "rx" , label="observation deriv") plt.plot(x , y , "c-", label="pchip interpolation funct") plt.plot(x , dydx , "k-", label="pchip interpolation deriv") plt.legend() plt.savefig("pchip_example_01.png") plt.show() The program generates values of the sine function (y_observed) over the range of 0 to 360 degrees. (x_observed). In a similar fashion, the cosine function (first derivative of the sine function) is generated over the same range (dydx_observed). pchip_interpolate is used to perform the interpolation over a specified range for the function and its first derivative. A composite plot is generated showing the points for the function (the sine) and its first derivative (cosine). The interpolated points overlay the function (sine) as expected. However, the first derivative returned fails to overlay the cosine function. The plot is attached to this note. Upon closer inspection, I believe I know what is going on, but I don't understand why. The line for the first derivative that failed to coincide with the points in the plot for the cosine is actually the interpolated first derivative scaled by the factor pi/180. When I multiply the interpolated values for the first derivative by 180/pi, the interpolated first derivative coincides with the points for the cosine as expected. What I don't understand is how the interpolator came up with the scale factor it did and applied it using pure numbers. Any thoughts? Sam Dupree

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Getting scipy.interpolate.pchip_interpolate to return the first derivative of a pchip interpolation
by sdupree＠speakeasy.net Jan. 23, 2023

Jan. 23, 2023

I'm running SciPy ver. 1.9.3 under Python ver. 3.9.15 on a Mac Pro (2019) desktop running Mac OSX ver. 13.1 Ventura. The problem I'm having is getting scipy.interpolate.pchip_interpolate to return the first derivative of a pchip interpolation. The test program I'm using is given below (and attached to this note). import numpy as np import matplotlib.pyplot as plt from scipy.interpolate import pchip_interpolate x_observed = np.linspace(0.0, 360.0, 51) y_observed = np.sin(np.pi*x_observed/180) dydx_observed = np.cos(np.pi*x_observed/180) x = np.linspace(min(x_observed), max(x_observed), num=100) y = pchip_interpolate(x_observed, y_observed, x, der=0, axis=0) dydx = pchip_interpolate(x_observed, y_observed, x, der=1, axis=0) plt.plot(x_observed, y_observed, "bo" , label="observation funct") plt.plot(x_observed, dydx_observed, "rx" , label="observation deriv") plt.plot(x , y , "c-", label="pchip interpolation funct") plt.plot(x , dydx , "k-", label="pchip interpolation deriv") plt.legend() plt.savefig("pchip_example_01.png") plt.show() The program generates values of the sine function (y_observed) over the range of 0 to 360 degrees. (x_observed). Similarly, the cosine function (first derivative of the sine function) is generated over the same range (dydx_observed). pchip_interpolate is used to perform the interpolation over a specified range for the function and its first derivative. A composite plot is generated showing the points for the function (the sine) and its first derivative (cosine). The interpolated points overlay the function (sine) as expected. However, the first derivative returned fails to overlay the cosine function. Upon closer inspection, I believe I know what is going on, but I don't understand why. The line for the first derivative that failed to coincide with the points in the plot for the cosine is actually the interpolated first derivative scaled by the factor pi/180. When I multiply the interpolated values for the first derivative by 180/pi, the interpolated first derivative coincides with the points for the cosine as expected. What I don't understand is how the interpolator came up with the scale factor it did and applied it using pure numbers. Any thoughts? Sam Dupree.

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