scipy-cookbook | Scipy Cookbook | Code Editor library
kandi X-RAY | scipy-cookbook Summary
kandi X-RAY | scipy-cookbook Summary
This is a conversion and second life of SciPy Cookbook (previously at as a bunch of Ipython notebooks. It can be found live at
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QUESTION
I'm new to C extensions for NumPy and I'm wondering if the following workflow is possible.
- Pre-allocate an array in NumPy
- Pass this array to a C extension
- Modify array data in-place in C
- Use the updated array in Python with standard NumPy functions
In particular, I'd like to do this while ensuring I'm making zero new copies of the data at any step.
I'm familiar with boilerplate on the C side such as PyModuleDef
, PyMethodDef
, and the PyObject*
arguments but a lot of examples I've seen involve coercion to C arrays which to my understanding involves copying and/or casting. I'm also aware of Cython though I don't know if it does similar coercions or copies under the hood. I'm specifically interested in simple indexed get- and set- operations on ndarray
with numeric (eg. int32
) values.
Could someone provide a minimal working example of creating a NumPy array, modifying it in-place in a C extension, and using the results in Python subsequently?
...ANSWER
Answered 2021-Dec-21 at 16:06Cython doesn't create new copies of numpy arrays unless you specifically request it to do so using numpy functions, so it is as efficient as it can be when dealing with numpy arrays, see Working with NumPy
choosing between writing raw C module and using cython depends on the purpose of the module written. if you are writing a module that will only be used by python to do a very small specific task with numpy arrays as fast as possible, then by all means do use cython, as it will automate registering the module correctly as well as handle the memory and prevent common mistakes that people do when writing C code (like memory management problems), as well as automate the compiler includes and allow an overall easier access to complicated functionality (like using numpy iterators).
however if your module is going to be used in other languages and has to be run independently from python and has to be used with python without any overhead, and implements some complex C data structures and requires a lot of C functionality then by all means create your own C extension (or even a dll), and you can pass pointers to numpy arrays from python (using numpy.ctypeslib.as_ctypes_type), or pass the python object itself and return it (but you must make a .pyd/so instead of dll), or even create numpy array on C side and have it managed by python (but you will have to understand the numpy C API).
QUESTION
I am learning how to solve systems of differential equations in Python. I took a code from online (https://scipy-cookbook.readthedocs.io/items/CoupledSpringMassSystem.html) and tried to run it. I get the error message: "cannot import name 'hold' from 'pylab'". I am not sure what is wrong with the code. Can anyone tell me what is incorrect in the code below:
...ANSWER
Answered 2021-Mar-28 at 14:19from their website, hold function has been Deprecated since version 2.0
Deprecated since version 2.0: pyplot.hold is deprecated. Future behavior will be consistent with the long-time default: plot commands add elements without first clearing the Axes and/or Figure.
QUESTION
I played a bit with Mayavi
and particularly with tvtk
but I struggle finding examples in which glyphs are placed on the scene at different orientation than default.
Based on this example I prepared the following scene with two cyllinders, one red and one blue,
...ANSWER
Answered 2020-Nov-05 at 10:30Ok, it turned out Actor
accepts orientation
argument which is in degrees (not in radians!). Also, the position of the actor has to be specified when actor is created and not when glyph is created!
QUESTION
I have been using scipy.integrate.solve_ivp to solve a system of 2nd order ODEs.
Assuming the code available here (note this uses odeint, but similar approach with solve_ivp): https://scipy-cookbook.readthedocs.io/items/CoupledSpringMassSystem.html
Now, making some parameters (b1 and b2) time & solution-dependent, say: e.g.
...ANSWER
Answered 2020-Oct-10 at 10:52Adapting your code to use solve_ivp
(which is the modern scipy
API to solve ODE) we can solve the system in a non intrusive way:
QUESTION
I read this tutorial https://scipy-cookbook.readthedocs.io/items/CorrelatedRandomSamples.html on how to get a matrix C so that C*C^T = R, with R being a given covariance matrix. The code example implements two differents methods, Cholesky decomposition or using the eigenvalues. To my suprise printing the resulting C of the two different methods gives me two different matrices:
Eigenvalue method result:
...ANSWER
Answered 2020-Jul-18 at 10:46I think I meanwhile found the answer. The matrix decompostion of the covariance matrix R into R = CC^T is not unambiguous. Different methods as calculating the Cholesky Decomposition or using eigenvalues yield different matrices C that fit the formula R = CC^T.
QUESTION
Following this post I'm trying to implement a one-dimensional smoothing algorithm. When creating a flat window for a simple moving average the call is as follows:
...ANSWER
Answered 2020-Jul-16 at 12:49numpy.ones(shape, dtype=None, order='C')
QUESTION
I have a bunch of similar curves, for example 1000 sine waves with slightly varying amplitude, frequency and phases, they look like as in this plot:
In the above plot the color of each sine wave is from the standard pandas colormap; I would like to get a plot where the color is related to the "density" of the curves.
My first idea is to imitate an old oscilloscope screen (search for "persistence mode" or look at https://en.wikipedia.org/wiki/Eye_pattern for some background):
and so I set one color for all the curves:
but the plot is "flat" and the "density" information is not so good.
I would really like a plot like this one:
In the above plot the yellow colour means that a number of curves between 25 and 30 "pass" through the same point (or the same pixel). I hand-made the above plot and I am asking whether it can be done better and more directly with pandas or matplotlib.
Above figures are made with this program, it takes a while (a dozen or seconds) because the Bresenham's line algorithm is not optimized.
...ANSWER
Answered 2020-May-03 at 14:04Matplotlib's hist2d
calculated the binning quite efficiently. The parameter bins
can set the number of bins in both x
and y
directions.
Drawing the curves with a thin line and combining them using a small alpha value is another approach.
QUESTION
I am learning how to code on python and I am trying to figure out how I could find the sum of solutions from an ODE system at a specific time.
For example, this is from the SciPy Cookbook the example is called "Modelling a Zombie Apocalypse" https://scipy-cookbook.readthedocs.io/items/Zombie_Apocalypse_ODEINT.html
Here is part of the code from the website:
...ANSWER
Answered 2020-Mar-27 at 02:58You just need to do S[4]
for living population and Z[4]
for zombie population. S
and Z
are the approximation values for those variable after solving the ODE system at each time t
.
Remember that values may not be int
so solution may not make sense to the physical problem:
QUESTION
I'm trying to write a simple python c-extension which includes some opencv code. Here is my c++ code:
...ANSWER
Answered 2020-Mar-15 at 20:51I found the answer.
Looks like Pythons Extension class from distutils.core module hass two additional input arguments for libraries which are library_dirs and libraries.
So I just had to change my setup.py code as below:
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