ogrisel

import numpy as np
try:
    import tensorflow as tf
except ImportError:
    tf = None
from time import perf_counter


def timeit(func, *args, **kwargs):
    durations = []

fkguo

#=
This julia script converts fortran 90 code into julia.
It uses naive regex replacements to do as much as possible,
but the output WILL need further cleanup.

Known conversion problems such as GOTO are commented and marked with FIXME

Most variable declaration lines are entirely deleted, which may or
may not be useful. 

JeffBezanson

using Images
import Base.Threads: @threads, @spawn

function escapetime(z; maxiter=80)
    c = z
    for n = 1:maxiter
        if abs(z) > 2
            return n-1
        end
        z = z^2 + c

mroavi

using Plots, Distributions
theme(:juno) # sets theme and resets all attributes of the Plots package
gr(
    xlims=[-10,10],
    ylims=[-10,10],
    aspect_ratio=:equal,
    framestyle=:grid,
    fillalpha=0.3,
    leg=false,
    size=(1200,800),

theogf

using Makie
using MakieLayout
using LinearAlgebra, Distances
using Distributions



α = MixtureModel([Normal(0.2, 0.05), Normal(0.6, 0.06), Normal(0.8, 0.04)], [0.3, 0.5, 0.2])
# β = Normal(0.3, 0.09)
β = Laplace(0.5, 0.1)

fperez

Polyglot Data Science with IPython & friends

Author: Fernando Pérez.

A demonstration of how to use Python, Julia, Fortran and R cooperatively to analyze data, in the same process.

This is supported by the IPython kernel and a few extensions that take advantage of IPython's magic system to provide low-level integration between Python and other languages.

See the companion notebook for data preparation and setup.

rafaeltuelho

My Openshift Cheatsheet

Project Quotes, Limits and Templates

• Cluster Quota

oc create clusterquota env-qa \
    --project-label-selector environment=qa \
    --hard pods=10,services=5
    
oc create clusterquota user-qa \

agramfort

"""
This module implements the Lowess function for nonparametric regression.

Functions:
lowess Fit a smooth nonparametric regression curve to a scatterplot.

For more information, see

William S. Cleveland: "Robust locally weighted regression and smoothing
scatterplots", Journal of the American Statistical Association, December 1979,