Documentation
Guides
One guide per module. Each one explains the main functions, shows examples with their real output and links every name to the API reference.
Getting started
| Guide | Covers | NumPy / SciPy |
|---|---|---|
| Getting started | Install scidart, import it and run your first computation. |
NumDart
| Guide | Covers | NumPy / SciPy |
|---|---|---|
| Arrays | Array, Array2d and ArrayComplex, element-wise math and evenly spaced samples. | numpy.ndarray, numpy.linspace, numpy.arange |
| Linear algebra | Solve linear systems, invert matrices and use the QR, LU and SVD decompositions. | numpy.linalg |
| Polynomial fitting | Least squares polynomial fits with one input (PolyFit) or several inputs and outputs (PolyFitMultivariate). | numpy.polyfit, sklearn PolynomialFeatures |
| Statistics | Mean, median, mode, variance and standard deviation of a sample. | numpy.mean, numpy.median, scipy.stats.mode |
| Calculus | Numerical integration with the trapezoidal and Simpson rules, cumulative integrals and derivatives. | scipy.integrate.trapezoid, scipy.integrate.simpson |
| Interpolation | Parabolic interpolation to find a peak between samples. | |
| Complex numbers | The Complex type and its operations. | |
| Random arrays | Uniform random arrays for tests and simulations. | |
| Constants | Mathematical and physical constants and unit conversion factors. | scipy.constants |
SciDart
| Guide | Covers | NumPy / SciPy |
|---|---|---|
| Fourier transform | FFT, inverse FFT, real FFT, frequency bins and spectra in dB. | scipy.fft |
| Signal processing | FIR filter design, filtering, peaks, window functions and convolution. | scipy.signal |
| Special functions | Error functions and the modified Bessel function of order zero. | scipy.special |
| Normal distribution | Density, cumulative probability, quantiles, intervals and random samples of a normal distribution. | scipy.stats.norm |
| Root finding | Roots of scalar functions and of systems of nonlinear equations. | scipy.optimize.root_scalar, scipy.optimize.root |