10 votes
Accepted

What is the difference between Computational Science and Data Science?

They are not interchangeable. Computational science tends to refer more to HPC, simulation techniques (differential equations, molecular dynamics, etc.), and is usually referred to as scientific ...
Chris Rackauckas's user avatar
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 ...
Julius's user avatar
  • 285
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 ...
Lutz Lehmann's user avatar
  • 6,064
4 votes
Accepted

FFT (Numerical Recipes in FORTRAN 77)

No, it's illegal by the Fortran standard, but that said most compilers will let you get away with it (if the debugging options are not turned on and provided a correct interface is not in scope at the ...
Ian Bush's user avatar
  • 616
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 ...
MPIchael's user avatar
  • 2,935
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 ...
Root of All Things's user avatar
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, ...
Neil Lindquist's user avatar
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 ...
cdalitz's user avatar
  • 481
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 ...
spektr's user avatar
  • 4,248
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 ...
GertVdE's user avatar
  • 6,179
2 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 ...
ajit's user avatar
  • 121
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: ...
Raizen's user avatar
  • 61
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.
Jacob Church's user avatar
2 votes

How are the outcomes that generated from different predictive models combined to get more accurate predictions?

Bagging, Boosting, and Bayesian Model Averaging/Combination are all widely used techniques for doing this. These are discussed in many textbooks on machine learning.
Brian Borchers's user avatar
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 ...
Lutz Lehmann's user avatar
  • 6,064
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....
mathew gunther's user avatar
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 ...
Futurologist's user avatar
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 ...
Wolfgang Bangerth's user avatar
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 ...
Abdullah Ali Sivas's user avatar
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 $...
cdalitz's user avatar
  • 481
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, ...
Anton Menshov's user avatar
  • 8,672
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. ...
gazzar's user avatar
  • 11
1 vote

How are the outcomes that generated from different predictive models combined to get more accurate predictions?

Provided you have raw data you could use in this process, one could use the various different models and treat them as basis functions of sorts that you wish to merge together in a least square sense. ...
spektr's user avatar
  • 4,248
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....
cdalitz's user avatar
  • 481
1 vote

Similarity of two CSV files (or more?)

Useful inclusion measures depend on whether you want to check pairwise similiarity or containment. For similiarity the Jaccard index is intuitive. For containment I would adapt it to ...
PatrickS's user avatar
  • 156
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: ...
Tom's user avatar
  • 111
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 ...
Richmond Newman's user avatar

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