# Disclaimer: I'm sure there are many better ways to do the things listed
# here - all I can say is these work!
#
# import some libraries we might need

import numpy
import math

# matplotlib is documented at matplotlib.sourceforge.net
# In particular, there are many helpful examples and a gallery which do
# 90% of what you'd ever need. 

import matplotlib.pyplot as plt


# Step 1: define the object fig

fig = plt.figure(figsize=(7,7))

# Step 2: read in data

data1 = numpy.loadtxt('uv_cii_highz.txt')
data2 = numpy.loadtxt('uv_cii_lowz.csv',delimiter=',')
data3 = numpy.loadtxt('uv_cii_agn.csv',delimiter=',')
data4 = numpy.loadtxt('fir_fit.txt')

uv_hiz = data1[:,0]
cii_hiz= data1[:,1]

uv_lowz= data2[:,0]
cii_lowz= data2[:,2]

uv_agn = data3[:,0]
cii_agn= data3[:,2]

uv_fir = data4[:,0]
cii_fir= data4[:,1]


# Step 3: define a subplot using the add_subplot method
# (in this case the only one). An axis instance is returned, which
# can be further operated on, as we'll see.
# 111 is 1 row by 1 column, first position

x11 = 19.0
x12 = 23.0

ax1 = fig.add_subplot(111,autoscale_on=False, xlim=(x11,x12),ylim = (32,38))

# Axis labeling is one weak point, I can't find much to do the fancy
# font changes etc that you sometimes need, though limited subscripting
# and superscripting does seem to be supported

ax1.set_xlabel('Log$_{10}$(Ultraviolet luminosity (W/Hz))')
ax1.set_ylabel('Log$_{10}$(L$_{[CII]}$ (W))')

# to make two plots side-by side
# ax1 = fig.add_subplot(121,autoscale_on=False, xlim=(0,1),ylim = (0,1))
# ax2 = fig.add_subplot(122,autoscale_on=False, xlim=(0,1),ylim = (0,1))

# It's also possible to have different axis scales on the top and bottom,
# or left and right, axes by defining an ax2 object as the twin of ax1

x21 = 19.0-21.15
x22 = 22.0-21.15

ax2 = ax1.twiny()
ax2.set_autoscale_on=False
ax2.set_ylim(32,38)
ax2.set_xlim(x21,x22)
ax2.set_xlabel('Approximate star formation rate (solar masses/yr)')


# plot
# Note marker codes are typically two letters, the first is the color,
# the second the symbol shape (e.g. bo = blue dot). See online help for
# all the options. The edge color is determined by a separate keyword.

ax1.plot(uv_hiz,cii_hiz,'bo',markersize=10.0,markeredgecolor='b', label='High redshift objects')

ax1.plot(uv_lowz,cii_lowz,'r^',markersize=10.0,markeredgecolor='r', label='Low redshift galaxies')

ax1.plot(uv_agn,cii_agn,'gx',markersize=10.0,markeredgecolor='r', label='Low redshift AGN')

ax1.plot(uv_fir,cii_fir,'k--')

# add a legend. The legend text is determined by the label arguments
# to the "plot" method

ax1.legend(loc=4,scatterpoints=1,numpoints=1)


# save as postscript

plt.savefig('test.eps',dpi=72,facecolor='w',edgecolor='w',orientation='portrait',transparent=False,format='eps')

# to show the plot, type plt.show()