8
votes
Python implementation for Frechet Distance
I realize this question was asked a while ago, but I recently needed the Freschet distance as well.
I couldn't find any implementations for Python, so I wrote my own based on the paper: "Computing ...
5
votes
Why do problems arise in FFT for smaller value of df in Python?
The discrete Fourier transform for a signal of period $T$ with $N$ samples reads in its inverse or reconstruction form as
$$
y(t)=\frac1{N}\sum_{k=-N/2}^{N/2}c_k e^{i2\pi k\frac{t}{T}}
$$
with ...
4
votes
Accepted
What are the Exact Rules for Significant Figures, Precision, and Uncertainty?
The rules of significant figures are rule-of-thumb way to communicate errors and should only be seen as a primite first step to talk about uncertainties and measurement errors.
You gave the excellent ...
4
votes
Fitting gauss-hermite-parametrization to data?
You're not providing an initial guess for the parameters, and so optimize.curve_fit is defaulting to [1.,1.,1.,1.]. The solver ...
3
votes
Storing Raw Simulation Data or Truncated Data?
I would recommend keeping the computation in your original precision and reducing the accuracy just when you write, unless the computation is too slow. If you reduce the precision of the computation, ...
3
votes
GPGPU/FPGA programming for Combinatorial Analysis
I am writing a general answer about porting a program running on a CPU to a GPU or FPGA.
Both GPU programs (using say CUDA) and CPU programs are written in high level languages like C, C++. Therefore ...
2
votes
Accepted
Which statistical method should I use for comparing machine run-time of two algorithms?
This is a typical use case for a paired t-test. The idea is to consider only the runtime difference $\Delta t$ for each problem and test for the null hypothesis $E(\Delta t)=0$. For a step-by-step ...
2
votes
How much in depth should I cover Python?
If you understand the basics of Python, you should just try to get your hands dirty using some well known/documented Python libraries for the type of work you want to do.
If you find you don't ...
2
votes
Accepted
Bounds condition for IFT to obtain a $1/f$ time-series
Here the solution, a function to create a randomized time-series starting from a PSD:
...
2
votes
Accepted
Best way of storing numerical data in a compact manner, while leaving it accessible for tools like GnuPlot?
You should be able to store everything in one table and plot from that if your data is tidy. Check out this paper, it's only about 20 pages.
2
votes
Is there a better way to do run time analysis than this?
Welcome to SE SciComp. First of all, I would suggest using Jupyter so that you have access to IPython and its nice timing magics (see %time and %timeit magic function). These magics take into account ...
1
vote
Accepted
Dimensionality reduction between discrete wavelet families
The wavelet transform itself does not reduce dimension. If boundaries are taken in account in some sensible way, the wavelet transform is square and invertible.
The "named" transforms ...
1
vote
How to check experimental data against a theoretical curve? (Python)
Curve_fit works with user defined functions. See copy pasted code from scipy curve_fit web page.
https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html#scipy.optimize....
1
vote
Clustering with points lying along different 3D planes
Observe that any data-point $$x_i = \begin{bmatrix} x_{i1}\\x_{i2}\\x_{i3} \end{bmatrix}$$ can be interpreted as the three-vector pointing from the origin to the point itself (position vector).
For ...
1
vote
Parameter explained by many distributions
Your question is ill-posed.
Take just the data points corresponding to one label. I think that when you say "for each label, we have several data distributions associated to it" that what ...
1
vote
How to extract connected components from persistence diagram?
If you can represent your data as a sparse graph you can use; https://docs.scipy.org/doc/scipy-0.19.0/reference/generated/scipy.sparse.csgraph.connected_components.html
For the cases you are asking ...
1
vote
Spline regularization
As your problem is a local regression problem, I would not use a spline fit, but LO(W)ESS. This estimates $f(x)$ at a sample point $x$ by a weighted least squares fit to the points $x_i$ that are the $...
1
vote
Converting ROOT Tree to HDF5
You might want to give a try to DataHarvester.
This tool claims to support ROOT, HBOOK, HDF, XML, SQLITE and input/output between them.
See the following publication:
W. Waltenberger, G. Richter, ...
1
vote
Python implementation for Frechet Distance
There is a discussion in Tyler Reddy's very recent pycon2017 tutorial on youtube https://youtu.be/ETJc3NfU9aA?t=9540
(at 2:39.00) where he discusses implementing the Frechet Distance in scipy.spatial. ...
1
vote
Accepted
Is resampling more accurate than block average for statistical analysis of data?
I guess that you are not actually interested in the variance, but in a confidence interval for your observable $\theta$. It should be noted that computing the confidence interval from the variance (i....
1
vote
similarity/distance measurement between two ranked sequence
As a starter, I would use the cost of bringing the elements into the same order. Of course this ignores the insertion of missing elements.
A simple solution would be insertion sort:
...
1
vote
Best practice for storing hierarchical simulation data
The use of a database is great for helping you organize/find simulation data (Search by protein, search by simulation parameters). The database should then tell you where to find the relevant ...
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