%matplotlib notebook
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from astropy.io import ascii
# Read database
database=ascii.read('database.csv',format='csv',delimiter=',')
# Create new figure frame
plt.figure(figsize=(8,6))
# Load SFR and Mass in Python arrays
x=np.array([float(i) for i in database['log M']])
y=np.array([float(i) for i in database['SFR']])
# Load uncertainties in Python arrays
xerrinf=np.array([float(i) for i in database['log M inf']])
xerrsup=np.array([float(i) for i in database['log M sup']])
yerrinf=np.array([float(i) for i in database['SFR inf']])
yerrsup=np.array([float(i) for i in database['SFR sup']])
# redshift
z=np.array([float(i) for i in database['redshift']])
# names
names=[str(i) for i in database['name']]
# Calculate log SFR
y_log=np.log10(y)
yerr_log_inf=yerrinf/(y*np.log(10))
yerr_log_sup=yerrsup/(y*np.log(10))
# Scatter plot of SFR-Mass. Change symbol for specific objects
for i in range(len(x)):
if names[i] in ['GRB061121','GRB080605','GRB080607','GRB080805','GRB100814A','GRB120119A']:
marker='*'
size=350
else:
marker='s'
size=50
plt.scatter(x[i],y_log[i],c=z[i],cmap=plt.cm.Blues,marker=marker,vmin=0,vmax=3,s=size)
# Nice way to get errorbar and colorbar
# Constrain the colorbar between 0 and 3
norm = matplotlib.colors.Normalize(vmin=0,vmax=3)
# choose a colormap
c_m = matplotlib.cm.Blues
# create a ScalarMappable and initialize a data structure
s_m = matplotlib.cm.ScalarMappable(cmap=c_m, norm=norm)
s_m.set_array([])
# Create a mask to filter nan values
mask_real=(np.isfinite(y)==True) & (np.isfinite(x)==True)
#Plot errorbars for our candidates
plt.errorbar(x[mask_real],y_log[mask_real],xerr=[xerrinf[mask_real],xerrsup[mask_real]],
yerr=[yerr_log_inf[mask_real],yerr_log_sup[mask_real]],color=s_m.to_rgba(z[mask_real]),
fmt='o',ms=0,markeredgewidth=0,alpha=0.8)
# Add MS star forming galaxies
M=np.logspace(7,11.5,100)
redshift=np.array([0.5,1.5,3])
m=np.log10(M/1e9)
m0=0.5
m1=0.36
a0=1.5
a1=0.3
a2=2.5
for zz in redshift:
r=np.log10(1+zz)
log10SFR=m-m0+a0*r-a1*(np.maximum(0,m-m1-a2*r))**2
plt.plot(np.log10(M),log10SFR,color='grey',ls='-',alpha=0.8)
if zz==1.5:plt.plot(np.log10(M),(log10SFR)+np.log10(4),color='grey',ls='--',lw=1,alpha=0.8)
# Locations to plot text
l1 = np.array((11., 1.41))
l2 = np.array((11., 2.03))
l3 = np.array((11.15, 2.35))
l4 = np.array((10.85, 2.55))
# Rotate angle
th = plt.text(l1[0], l1[1], 'MS z = 0.5', fontsize=14,rotation=4, rotation_mode='anchor',color='grey',alpha=0.8)
th = plt.text(l2[0], l2[1], 'MS z = 1.5', fontsize=14,rotation=20, rotation_mode='anchor',color='grey',alpha=0.8)
th = plt.text(l3[0], l3[1], 'MS z = 3', fontsize=14,rotation=30, rotation_mode='anchor',color='grey',alpha=0.8)
th = plt.text(l4[0], l4[1], '4x MS z = 1.5', fontsize=14,rotation=25, rotation_mode='anchor',color='grey',alpha=0.8)
# Set legend with only one point. Change legend size
#plt.legend(loc='lower right',numpoints=1,prop={'size':18})
# Create colorbar on the right side of figure
cbar=plt.colorbar(fraction=0.046, pad=0.04)
cbar.ax.tick_params(labelsize=19)
cbar.ax.set_ylabel('z', rotation=180,size=20)
# Fix x and y axis limits
plt.xlim(9,11.5)
plt.ylim(0,3)
# Change label names size
plt.tick_params(labelsize=19)
# Label names
plt.xlabel(r'log$_{10}$ M$_{*}$ [M$_{\odot}$]',size=22)
plt.ylabel(r'log$_{10}$ SFR [M$_{\odot}$ yr$^{-1}$]',size=22)
# Plot grid with main ticks only
plt.grid(True, which='major', color='grey', linestyle='-',alpha=0.4)
# Automatically adjusts plot so that the (sub)plot(s) fits in to the figure area
plt.tight_layout()
#plt.savefig('MS.png')
There are at least two libraries which can be used to stack images to create a movie: ffmpeg and Libav.
fmpeg needs to be downloaded here https://ffmpeg.org/download.html
Some documentation: https://ffmpeg.org/documentation.html
Libav is installed by default on Ubuntu, I do not know about other OS. You can download it here: https://libav.org/download/
Documentation: https://libav.org/documentation/
import os
cd Images/
# With ffmpeg
os.system("ffmpeg -f image2 -r 10 -s 1920x1080 -i image_%d.png -vcodec mpeg4 -b:v 1000k -y grb170817A_movie.mp4")
# with avconv
# here we start at the image 8 with the command -start_number 8
os.system("avconv -r 10 -start_number 8 -i image_%d.png -b:v 1000k test_avconv.mp4")