MMesch

#!/usr/bin/env python
"""
Robust non-linear feature estimation with scikit-learn applied to
the Fourier Transform.
"""

from matplotlib import pyplot as plt
import numpy as np
from sklearn.base import TransformerMixin
from sklearn.pipeline import make_pipeline

MMesch

#!/usr/bin/env python
"""
Robust B-Spline regression with scikit-learn
"""

import matplotlib.pyplot as plt
import numpy as np
import scipy.interpolate as si
from sklearn.base import TransformerMixin
from sklearn.pipeline import make_pipeline

MMesch

#!/usr/bin/env python

"""
ND Bspline basis class for Python
"""

import numpy as np
import scipy.interpolate as si
import matplotlib.pyplot as plt
import itertools

MMesch

#!/usr/bin/env python

"""
2D BSpline Regression with Scikitlearn.
"""

import matplotlib.pyplot as plt
import numpy as np
import scipy.interpolate as si
import itertools

MMesch

#!/usr/bin/env python

"""Mini implementation of continuous wavelet transform (Morlet wavelet)."""

import numpy as np
import matplotlib.pyplot as plt


def continuous_wavelet_transform(signal, frequencies, time_step=1.0,
                                 wavelet_width=5):

MMesch

"some basic options
set shiftwidth=4
set expandtab
set nowrap
set colorcolumn=80

"let &colorcolumn=join(range(80, 999), ",")

" autopep 8 when hitting gq
au FileType python setlocal formatprg=autopep8\ -

MMesch

var plot_tree = function(data, chart){
    // set some layout variables
    var positionInfo = chart.getBoundingClientRect();
    var el_height = positionInfo.height;
    var el_width = positionInfo.width;

    var margin = {top: 20, right: 20, bottom: 30, left: 40},
        svg_width = el_width - margin.left - margin.right,
        svg_height = el_height - margin.top - margin.bottom;
    

MMesch

Visualization of scikit-learn decision trees. Hover with the mouse over the paths to see the decision rules and a histogram of the classes that remain at a certain node in the tree. Checkout this repository to see how to use it in python and also directly in the jupyter notebook.

MMesch

Visualization of the time-dependent correlation matrix of the food production of 245 countries from the united nations.

MMesch

Python Refactoring Strategies

project structure and workflow

git and CI

check if git and CI are setup

folder tree