benjaminrose

import numpy as np
import matplotlib.pyplot as plt

def ScatterToContour(x,y, bins=[10,10]):
	'''
	x is the x location of the points
	y is the y location of the points
	len(x) needs to equal len(y)
	bins determins the refinement of the histogram and line edges.
	All contour plot perameters (levels, ect.) are defined outside 

benjaminrose

'this still needs better testing, espcially to work with numpy'
'needs to work with degrees and radians'

def convert(x):
	'x is a list, would like it to work with numpy'
	ind = x>180
	for i,j in enumerate(ind):
		if j:
			l[i]-=360
	return x

benjaminrose

import matplotlib.pyplot as plt
import numpy as np #casue it rocks

# get random values to plot
#needs to be in radians from (-pi,pi) & (-pi/2, pi/2)
a = np.random.rand(100)*2*np.pi - np.pi
d = np.random.rand(100)*np.pi - np.pi/2
#todo(make values astropy.cooridnates and use wrap_at(180*u.degree). Allows for more varriable data.

#make figure

benjaminrose

% \documentclass[apj, iop]{emulateapj}
  % use for a preview of the final version
\documentclass[manuscript]{aastex}
  %[manuscript] = defualt, and how you submit
  %[preprint] = one-column, single-spaced document 
  %[preprint2] = double-column, single-spaced document
  
\usepackage{graphicx}% Include figure files
\usepackage{color}%for preprints
\usepackage{hyperref}

benjaminrose

import numpy as np

#create random data
data1 = np.random.rand(10)
data2 = np.random.rand(10)
data3 = np.random.rand(10)

#stack data into one ojbect
data_list = np.dstack((data1, data2, data3))

benjaminrose

benjaminrose

benjaminrose

benjaminrose

benjaminrose