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  2. LMS color space - Wikipedia

    en.wikipedia.org/wiki/LMS_color_space

    The above development has the advantage of basing the new X F Y F Z F color matching functions on the physiologically-based LMS cone response functions. In addition, it offers a one-to-one relationship between the LMS chromaticity coordinates and the new X F Y F Z F chromaticity coordinates, which was not the case for the CIE 1931 color ...

  3. Matplotlib - Wikipedia

    en.wikipedia.org/wiki/Matplotlib

    Matplotlib-animation [11] capabilities are intended for visualizing how certain data changes. However, one can use the functionality in any way required. These animations are defined as a function of frame number (or time). In other words, one defines a function that takes a frame number as input and defines/updates the matplotlib-figure based ...

  4. Radar chart - Wikipedia

    en.wikipedia.org/wiki/Radar_chart

    The radar chart is a chart and/or plot that consists of a sequence of equi-angular spokes, called radii, with each spoke representing one of the variables. The data length of a spoke is proportional to the magnitude of the variable for the data point relative to the maximum magnitude of the variable across all data points.

  5. Bar chart - Wikipedia

    en.wikipedia.org/wiki/Bar_chart

    A bar chart or bar graph is a chart or graph that presents categorical data with rectangular bars with heights or lengths proportional to the values that they represent. The bars can be plotted vertically or horizontally. A vertical bar chart is sometimes called a column chart and has been identified as the prototype of charts. [1]

  6. Lambda calculus - Wikipedia

    en.wikipedia.org/wiki/Lambda_calculus

    The examples 1 and 2 denote different terms, differing only in where the parentheses are placed. They have different meanings: example 1 is a function definition, while example 2 is a function application. The lambda variable x is a placeholder in both examples. Here, example 1 defines a function .

  7. Kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Kernel_density_estimation

    Kernel density estimation of 100 normally distributed random numbers using different smoothing bandwidths.. In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights.

  8. Principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Principal_component_analysis

    MATLAB – The SVD function is part of the basic system. In the Statistics Toolbox, the functions princomp and pca (R2012b) give the principal components, while the function pcares gives the residuals and reconstructed matrix for a low-rank PCA approximation. Matplotlib – Python library have a PCA package in the .mlab module.

  9. Convolution - Wikipedia

    en.wikipedia.org/wiki/Convolution

    As changes, the weighting function () emphasizes different parts of the input function (); If is a positive value, then () is equal to () that slides or is shifted along the -axis toward the right (toward +) by the amount of , while if is a negative value, then () is equal to () that slides or is shifted toward the left (toward ) by the amount ...