Chris Lovell christopherlovell

## pyximport_numpy.py
import pyximport
import numpy as np
pyximport.install(setup_args={'include_dirs': np.get_include()})

## Fitting Distributions with R.R
n <- 50
m <- 50
set.seed(1)
mu <- -0.4
sig <- 0.12
x <- matrix(data=rlnorm(n*m, mu, sig), nrow=m)

library(fitdistrplus)
## Fit a log-normal distribution to the 50 random data set
f <- apply(x, 2,  fitdist, "lnorm")

## tmux_cheatsheet.markdown

      
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                henrik
                / tmux_cheatsheet.markdown
            
            
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              March 3, 2012 19:47
            
              
                tmux cheatsheet
              
          
    tmux cheatsheet

As configured in my dotfiles.
start new:
tmux

start new with session name:

  
## gh-pages.md

      
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                ramnathv
                / gh-pages.md
            
            
              Created
              March 28, 2012 15:37
            
              
                Creating a clean gh-pages branch
              
          
    Creating a clean gh-pages branch

This is the sequence of steps to follow to create a root gh-pages branch. It is based on a question at [SO]
cd /path/to/repo-name
git symbolic-ref HEAD refs/heads/gh-pages
rm .git/index
git clean -fdx
echo "My GitHub Page" &gt; index.html


## part1.rst

      
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                phn
                / part1.rst
            
            
              Created
              July 5, 2012 17:15
            
              
                Astropython.org PyFits tutorial
              
          
    PyFITS: FITS files in Python

In this article, we provide examples of using the python module
PyFITS for working with FITS data. We first go through a brief


## _chi2.c
#include <Python.h>
#include <numpy/arrayobject.h>
#include "chi2.h"

/* Docstrings */
static char module_docstring[] =
    "This module provides an interface for calculating chi-squared using C.";
static char chi2_docstring[] =
    "Calculate the chi-squared of some data given a model.";

## gist:4582705
"""making a dataframe"""
df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))

"""quick way to create an interesting data frame to try things out"""
df = pd.DataFrame(np.random.randn(5, 4), columns=['a', 'b', 'c', 'd'])

"""convert a dictionary into a DataFrame"""
"""make the keys into columns"""
df = pd.DataFrame(dic, index=[0])

## Automatic Voigt Profile Fitting.ipynb

      
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              January 15, 2024 07:14
            
              
                My attempt to create an automatic Voigt Profile Fitting program using PyMC and barak python libraries.
              
          
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## discrete_cmap.py
# By Jake VanderPlas
# License: BSD-style

import matplotlib.pyplot as plt
import numpy as np


def discrete_cmap(N, base_cmap=None):
    """Create an N-bin discrete colormap from the specified input map"""

## tokenizer.R
ngrams.tokenizer <- function(x, n = 2) {
  trim <- function(x) gsub("(^\\s+|\\s+$)", "", x)
  terms <- strsplit(trim(x), split = "\\s+")[[1]]
  ngrams <- vector()
  if (length(terms) >= n) {
    for (i in n:length(terms)) {
      ngram <- paste(terms[(i-n+1):i], collapse = " ")
      ngrams <- c(ngrams,ngram)
    }
  }
	import pyximport
	import numpy as np
	pyximport.install(setup_args={'include_dirs': np.get_include()})
	n <- 50
	m <- 50
	set.seed(1)
	mu <- -0.4
	sig <- 0.12
	x <- matrix(data=rlnorm(n*m, mu, sig), nrow=m)

	library(fitdistrplus)
	## Fit a log-normal distribution to the 50 random data set
	f <- apply(x, 2, fitdist, "lnorm")
	#include <Python.h>
	#include <numpy/arrayobject.h>
	#include "chi2.h"

	/* Docstrings */
	static char module_docstring[] =
	"This module provides an interface for calculating chi-squared using C.";
	static char chi2_docstring[] =
	"Calculate the chi-squared of some data given a model.";
	"""making a dataframe"""
	df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))

	"""quick way to create an interesting data frame to try things out"""
	df = pd.DataFrame(np.random.randn(5, 4), columns=['a', 'b', 'c', 'd'])

	"""convert a dictionary into a DataFrame"""
	"""make the keys into columns"""
	df = pd.DataFrame(dic, index=[0])
	# By Jake VanderPlas
	# License: BSD-style

	import matplotlib.pyplot as plt
	import numpy as np


	def discrete_cmap(N, base_cmap=None):
	"""Create an N-bin discrete colormap from the specified input map"""
	ngrams.tokenizer <- function(x, n = 2) {
	trim <- function(x) gsub("(^\\s+\|\\s+$)", "", x)
	terms <- strsplit(trim(x), split = "\\s+")[[1]]
	ngrams <- vector()
	if (length(terms) >= n) {
	for (i in n:length(terms)) {
	ngram <- paste(terms[(i-n+1):i], collapse = " ")
	ngrams <- c(ngrams,ngram)
	}
	}