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matlab2tikz / matlab2tikz

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ConstantLine (xline yline) unsupported

4
LeoBay
LeoBay commented Jan 8, 2020

ConstantLine was introduced in 2018b:
https://de.mathworks.com/help/matlab/ref/matlab.graphics.chart.decoration.constantline-properties.html

when using for example:
xline(4)
This error appears:
`Error using matlab2tikz>handleAllChildren (line 730)
I don't know how to handle this object: constantline
Error in matlab2tikz>drawAxes (line 880)
[m2t, childrenEnvs] = handleAllChildren(m2

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+0.0.1 HG2 feature request good first issue

casadi / casadi

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CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.

python c-plus-plus library modular optimization matlab mathematics nonlinear octave numerical-calculations scientific-computing derivatives code-generation parameter-estimation academic-project optimal-control symbolic-manipulation algorithmic-differentation nonlinear-programming
  • Updated Sep 8, 2020
  • C++

TheAlgorithms / MATLAB-Octave

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Add more algorithms!

9
cozek
cozek commented Oct 10, 2019

This repo needs more algorithms. If you see any missing algorithms, kindly contribute.
Hackotberfest participants are welcome!
I will list some of the algorithms that are up for grabs. However, please check if the algorithm
is already in our repo before you begin working.
Feel free to help me add more items to the list. If you have any questions, ask away!

Some Guidelines:

  1. Please
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good first issue hacktoberfest help wanted

liquidSVM / liquidSVM

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Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

python c-plus-plus machine-learning r apache-spark matlab svm ml regression octave classification rstats r-package quantile-regression expectile-regression
  • Updated Feb 20, 2020
  • C++

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