Tom Gilliss gilliss

## MarginalizeMesh.py
"""
Marginalize a 2-dimensional distribution evaluated over a numpy meshgrid.

-The Distribution class holds the distribution, the marginalization method,
and the grid parameters to be used for the integration.
-The Marginalize() method allows specification of the axis you would like to marginalize.
The marginalization is done via simple grid integration, using rectangular Riemann
sum approximation of integral.

There is similar code in scipy's scipy/stats/tests/test_multivariate.py::test_marginalization()

## chstwo.py
"""
A chi-square test for the difference between two data sets.

_count() method is from SciPy's https://github.com/scipy/scipy/blob/v0.14.0/scipy/stats/stats.py#L3467

A version of this function is in NRC, and related functions are in SciPy:
        NRC: chstwo(bins1, bins2, nbins, knstrn, df, chsq, prob)
        SciPy: power_divergence(f_obs, f_exp=None, ddof=0, axis=0, lambda_=None)
"""
import numpy as np

## barh_left_right.py
"""
Plotting a matplotlib.pyplot.barh from the left or right of axes

Ref:
    https://matplotlib.org/api/_as_gen/matplotlib.pyplot.barh.html
    https://matplotlib.org/examples/lines_bars_and_markers/barh_demo.html
"""
import numpy as np
import matplotlib.pyplot as plt

## AxisBinLabelsROOT.cc
/*
Code to change the strings used for TAxis bin labels in ROOT.
Ref:
  https://root.cern.ch/doc/master/classTAxis.html
*/

#include <map>
#include <string>
#include <iostream>

## CustomColorList.py
"""
Create a custom list of colors for use in data visualization
"""

import matplotlib.pyplot as plt
import numpy as np

# create n data points
n = 20
xData = np.linspace(0,n,n)

## SaveNumpy.py
"""
Save and access numpy arrays, as single arrays in .npy files, and as multiple arrays in .npz files
Ref:
    https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.save.html
    https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.savez.html
"""

import numpy as np
import glob
import os

## MixtureModelScipyOptimize.py
"""
Use scipy.optimize.fmin (simplex algorithm) to find optimal weights for components of a simple mixture model.
"""

import numpy as np
import scipy.stats as stats
from scipy.optimize import fmin

#############
# Generate data

## json_module.py
"""
Write, read, and print using the json module.
"""

import json
import os

# Create dictionary
d = {'first': 1, 'second': 2, 'third': 3}
file_path = './tmp_file.json'

## ip_problem.py
def isSectionValid(s):
    """
    Inputs:
        s = string of chars with 1<=len(s)<=3
    Output:
        True or False for valid or invalid
    Description:
        Leading digit of section must not be 0 if length of section > 1. Value
        of section must be within [0,255]. If section fails either of these
        requirements, section is invalid.

## argparse_module.py
"""
A simple example using argparse to sum or find max of a list of numbers,
and optionally multiply result by some factor.

Examples:
    $ python basic_argparse.py 1 2 3 4
    $ python basic_argparse.py --mult 10 --max 1 2 3 4
    $ python basic_argparse.py --max --mult 10 1 2 3 4

Ref:
	"""
	Marginalize a 2-dimensional distribution evaluated over a numpy meshgrid.

	-The Distribution class holds the distribution, the marginalization method,
	and the grid parameters to be used for the integration.
	-The Marginalize() method allows specification of the axis you would like to marginalize.
	The marginalization is done via simple grid integration, using rectangular Riemann
	sum approximation of integral.

	There is similar code in scipy's scipy/stats/tests/test_multivariate.py::test_marginalization()
	"""
	A chi-square test for the difference between two data sets.

	_count() method is from SciPy's https://github.com/scipy/scipy/blob/v0.14.0/scipy/stats/stats.py#L3467

	A version of this function is in NRC, and related functions are in SciPy:
	NRC: chstwo(bins1, bins2, nbins, knstrn, df, chsq, prob)
	SciPy: power_divergence(f_obs, f_exp=None, ddof=0, axis=0, lambda_=None)
	"""
	import numpy as np
	"""
	Plotting a matplotlib.pyplot.barh from the left or right of axes

	Ref:
	https://matplotlib.org/api/_as_gen/matplotlib.pyplot.barh.html
	https://matplotlib.org/examples/lines_bars_and_markers/barh_demo.html
	"""
	import numpy as np
	import matplotlib.pyplot as plt
	/*
	Code to change the strings used for TAxis bin labels in ROOT.
	Ref:
	https://root.cern.ch/doc/master/classTAxis.html
	*/

	#include <map>
	#include <string>
	#include <iostream>
	"""
	Create a custom list of colors for use in data visualization
	"""

	import matplotlib.pyplot as plt
	import numpy as np

	# create n data points
	n = 20
	xData = np.linspace(0,n,n)
	"""
	Save and access numpy arrays, as single arrays in .npy files, and as multiple arrays in .npz files
	Ref:
	https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.save.html
	https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.savez.html
	"""

	import numpy as np
	import glob
	import os
	"""
	Use scipy.optimize.fmin (simplex algorithm) to find optimal weights for components of a simple mixture model.
	"""

	import numpy as np
	import scipy.stats as stats
	from scipy.optimize import fmin

	#############
	# Generate data
	"""
	Write, read, and print using the json module.
	"""

	import json
	import os

	# Create dictionary
	d = {'first': 1, 'second': 2, 'third': 3}
	file_path = './tmp_file.json'
	def isSectionValid(s):
	"""
	Inputs:
	s = string of chars with 1<=len(s)<=3
	Output:
	True or False for valid or invalid
	Description:
	Leading digit of section must not be 0 if length of section > 1. Value
	of section must be within [0,255]. If section fails either of these
	requirements, section is invalid.
	"""
	A simple example using argparse to sum or find max of a list of numbers,
	and optionally multiply result by some factor.

	Examples:
	$ python basic_argparse.py 1 2 3 4
	$ python basic_argparse.py --mult 10 --max 1 2 3 4
	$ python basic_argparse.py --max --mult 10 1 2 3 4

	Ref: