'omega_lambda_0': 0.714,
'omega_k_0': 0.0,
'h': 0.696
}
VCV = pd.read_csv('VCV_z03.dat', sep='|', skiprows=4)
distance = []
RA_AGN = []
DEC_AGN = []
name = []
flux = []
j = 0
for i in range(len(VCV)):
if VCV.values[i][2] > 0 and VCV.values[i][2] < .03:
RA, DEC = np.rad2deg(
astroconvert.gal2eq(np.deg2rad(VCV.values[i][4]),
np.deg2rad(VCV.values[i][5])))
RA2 = float("{0:.2f}".format(float(RA)))
DEC2 = float("{0:.2f}".format(float(DEC)))
RA_AGN.append(RA2)
DEC_AGN.append(DEC2)
D = cd.comoving_distance(VCV.values[i][2], **cosmo)
D2 = float("{0:.2f}".format(float(D)))
distance.append(D2)
name.append(VCV.values[i][1])
flux.append(100.0)
j += 1
sorted_index, sorted_d = zip(
*sorted([(i, e) for i, e in enumerate(distance)], key=lambda x: x[1]))
RA_AGN_sorted = [RA_AGN[i] for i in sorted_index]
DEC_AGN_sorted = [DEC_AGN[i] for i in sorted_index]
distance_sorted = [distance[i] for i in sorted_index]
l_Obs=l_Obs[l_Obs!=0]
b_Obs=Data[:,8]*((Data[:,2]>=E_min) & (Data[:,2]<E_max) & (Data[:,1]<theta_max_deg ) & (Data[:,1]>=theta_min_deg ))*1;
b_Obs=b_Obs[b_Obs!=0]
E_Obs=Data[:,2]*((Data[:,2]>=E_min) & (Data[:,2]<E_max) & (Data[:,1]<theta_max_deg ) & (Data[:,1]>=theta_min_deg ))*1;
E_Obs=E_Obs[E_Obs!=0]
Zenith_Obs=Data[:,1]*((Data[:,2]>=E_min) & (Data[:,2]<E_max) & (Data[:,1]<theta_max_deg ) & (Data[:,1]>=theta_min_deg ))*1;
Zenith_Obs=Zenith_Obs[Zenith_Obs!=0]
RA_Obs=np.zeros(l_Obs.size)
DEC_Obs=np.zeros(l_Obs.size)
for k in range(l_Obs.size):
l=l_Obs[k]
b=b_Obs[k]
x2,y2=astroconvert.gal2eq(np.deg2rad(l),np.deg2rad(b))
RA_Obs[k]=np.rad2deg(x2)
DEC_Obs[k]=np.rad2deg(y2)
Zenith_Datos=Zenith_Obs
E_Datos=E_Obs
RA_Datos=RA_Obs
DEC_Datos=DEC_Obs
print DEC_Datos.size, "events with for E>=", E_min, "EeV and zenith <", theta_max_deg, "degree"
np.savetxt("Zenith_Datos", Zenith_Datos,fmt='%.2f')
np.savetxt("E_Datos", E_Datos,fmt='%.2f')
np.savetxt("RA_Datos", RA_Datos,fmt='%.2f')
np.savetxt("DEC_Datos", DEC_Datos,fmt='%.2f')
##################### Plot events
def makeplot(ra,dec,specid,where='',figtype='cart',ellipses='no',saveplot=''):
""" Makes a plot of RA and DEC.
where is a string specifying which data from mysql to grab.
ONLY include columns from table 'config'. do not include
the word 'where' at the beginning or the semicolon at the
end. all other common mysql syntax rules apply.
figtype is the figure type. default is 'cart' for cartesian
coordinates. 'sky' plots the ra and dec as a Mollweide
projection
if ellipses='yes', the spectra are plotted as individual ellipses
of fixed size corresponding to ALFA beam width (only for Cartesian
coordinate axis)
saveplot allows you to save the figure by specifying the
file name as a string. if left empty, the figure is not
saved.
returns a figure"""
import jd2gd, command
#Determine values to include in figure
var1 = min(specid)
var2 = max(specid)
var3 = len(specid)
#Get time info from database
cmd = command.generate('obstime','config',where=where)
data = MySQLFunction.mysqlcommand(cmd)
#Create list
day = numpy.asarray([data[x][0] for x in xrange(len(data))])
#Determine start and end dates
start = min(day)
end = max(day)
#Create Gregorian date from obstime
start = jd2gd.caldate(start)
end = jd2gd.caldate(end)
dates = ['January','February','March','April','May','June','July',
'August','September','October','November','December']
start = [str(start[x]) for x in range(len(start))]
end = [str(end[x]) for x in range(len(end))]
#Insert zeros to make formatting nice
if float(start[2])<10:
start[2] = '0' + start[2]
if float(start[3])<10:
start[3] = '0' + start[3]
if float(start[4])<10:
start[4] = '0' + start[4]
if float(start[5])<10:
start[5] = '0' + start[5]
if float(end[2])<10:
end[2] = '0' + end[2]
if float(end[3])<10:
end[3] = '0' + end[3]
if float(end[4])<10:
end[4] = '0' + end[4]
if float(end[5])<10:
end[5] = '0' + end[5]
#Compile date strings
date1 = start[0]+' '+dates[int(start[1])-1]+' '+start[2]+' '+start[3]+':'+start[4]+':'+start[5][:4]
date2 = end[0]+' '+dates[int(end[1])-1]+' '+end[2]+' '+end[3]+':'+end[4]+':'+end[5][:4]
#Which fig type?
patches=[]
if figtype=='cart':
#Initialize figure
fig=pylab.figure(figsize=(12,7))
ax1 = fig.add_axes([0.1, 0.12, 0.85, 0.75])
#Plot data
if ellipses=='yes':
for x,y in zip(ra,dec):
circle=matplotlib.patches.Ellipse((x,y),width=.0038888,height=.058333,facecolor='b',edgecolor='b')
patches.append(circle)
p=matplotlib.collections.PatchCollection(patches)
ax1.add_collection(p)
else: ax1.scatter(ra,dec,s=.1,label='spectra')
else:
#Convert RA to degrees
length = len(ra)
ra = [ra[x]*15 for x in range(length)]
#Convert arrays to radians
ra = [math.radians(ra[x]) for x in range(length)]
dec = [math.radians(dec[x]) for x in range(length)]
#Adjust ra scale
ra = [ra[x]-numpy.pi for x in range(length)]
#Create figure
fig = pylab.figure(figsize=(12,7))
ax1 = fig.add_axes([.1,.12,.70,.85],projection='mollweide')
#Plot data
ax1.scatter(ra,dec,label='spectra',marker='+',c='b')
#Set xtick labels
ax1.set_xticklabels(['2','4','6','8','10','12','14','16','18','20','22'])
#Create galactic plane lines
#Create l,b arrays
b = [math.radians(5)]*360 + [math.radians(-5)]*360
l = list(numpy.linspace(0,2*numpy.pi,360))*2
#Pass l,b pairs to gal2eq
bounds = []
for x in range(720):
bounds.append(astroconvert.gal2eq(l[x],b[x]))
#Separate into component arrays
ra_bounds = [bounds[x][0] for x in range(720)]
dec_bounds = [bounds[x][1] for x in range(720)]
#Convert to deg if necessary, and plot
if figtype=='sky':
ra_bounds = [ra_bounds[x]-numpy.pi for x in range(720)]
ax1.scatter(ra_bounds,dec_bounds,edgecolor='none',c='r',label='galactic plane')
else:
ra_bounds = [math.degrees(ra_bounds[x])/15 for x in range(720)]
dec_bounds = [math.degrees(dec_bounds[x]) for x in range(720)]
ax1.plot(ra_bounds,dec_bounds,'r',label='galactic plane')
#Set axis limits
ax1.set_xlim(0, 24)
ax1.set_ylim(0, 40)
#Set axis labels and title
pylab.xlabel('RA (hours)')
pylab.ylabel('Dec (degrees)')
pylab.title('Right Ascension and Declination')
#Add legend
ax1.legend(bbox_to_anchor=(0,0,1,1),loc=0)
#Add text to figure
pylab.figtext(0.1,.97,'First Specid: %d' %var1)
pylab.figtext(0.1,.945,'Last Specid: %d' %var2)
pylab.figtext(0.1,.92,'Count: %d spectra' %var3)
pylab.figtext(0.95,.97,' Start: %s' %date1, ha='right')
pylab.figtext(0.95,.945,'End: %s' %date2, ha='right')
#Include grid
pylab.grid(True)
#Save figure?
if saveplot!='':
pylab.savefig('%s'%saveplot)
return fig
if (Type != 'Desviacion_GAL'):
cb = m.colorbar(im, "right", size="3%", pad='3%')
else:
cb = m.colorbar(im, "right", size="3%", pad='6%')
#m.contour(XX,YY,Overlap_Datos_Gal)
#main_ax.set_title('Zenithal Acceptance between 55 and 80 deg')
main_ax.title.set_fontsize(15)
# PLANO G
phi_G = np.linspace(0, 2 * np.pi, num=400)
theta_G = np.linspace(0, 0, num=400)
x1 = np.zeros(theta_G.size)
y1 = np.zeros(theta_G.size)
for k in range(theta_G.size):
x1[k], y1[k] = astroconvert.gal2eq(phi_G[k], theta_G[k])
x1[k] = np.rad2deg(x1[k])
y1[k] = np.rad2deg(y1[k])
x2 = np.sort(x1, axis=0)
sort_indices = np.argsort(x1, axis=0)
y2 = y1[sort_indices]
x3, y3 = m(x2, y2)
if (Type != 'Desviacion_GAL'):
m.plot(x3, y3, color='w', linewidth=3.0, linestyle="--")
# PLANO SG
phi_SG = np.linspace(0, 360, num=400, endpoint=False)
theta_SG = np.linspace(0, 0, num=400, endpoint=False)
x1 = np.zeros(theta_SG.size)
y1 = np.zeros(theta_SG.size)
x2 = np.zeros(theta_SG.size)
def allsky_plot(ra,dec,color='False',header='False',saveplot=''):
"""Plots a 2D histogram of pointing data,
with a color scale giving the relative counts. One ra value
and one dec value are supplied for each continuous pointing.
Inputs:
ra: array of RA values for pointings in db
dec: array of DEC values for pointings in db
color: whether or not to generate a color plot, default='False'
header: whether or not to include header information, default='False'
saveplot: string to specify name of plot
Output is a figure"""
#Perform histogramming
x,y,data=histogram2d(ra,dec,dtype='Equatorial')
#Create figure/axes
fig = pylab.figure(figsize=(12,7))
if header=='False':
ax1 = fig.add_axes([.1,.12,.90,.85])
else: ax1=fig.add_axes([.1,.12,.90,.75])
#Add plot
if color=='False':
mesh=ax1.pcolormesh(x,y,data,cmap=pylab.get_cmap('gray_r'))
elif color=='True':
mesh=ax1.pcolormesh(x,y,data,cmap=pylab.get_cmap('spectral_r'))
fig.colorbar(mesh)
ax1.set_ylabel('Declination')
ax1.set_xlabel('Right Ascension')
pylab.grid(True)
#Add galactic plane
#Create l,b arrays
b = [math.radians(5)]*360 + [math.radians(-5)]*360
l = list(numpy.linspace(0,2*numpy.pi,360))*2
#Pass l,b pairs to gal2eq
bounds = []
for x in range(720):
bounds.append(astroconvert.gal2eq(l[x],b[x]))
#Separate into component arrays
ra_bounds = [bounds[x][0] for x in range(720)]
dec_bounds = [bounds[x][1] for x in range(720)]
#Convert to deg if necessary, and plot
ra_bounds = [math.degrees(ra_bounds[x])/15 for x in range(720)]
dec_bounds = [math.degrees(dec_bounds[x]) for x in range(720)]
ax1.plot(ra_bounds,dec_bounds,'k--',label='galactic plane')
ax1.legend(bbox_to_anchor=(0,0,1,1),loc=0)
#Fix axes
ax1.set_xlim(min(ra),max(ra))
ax1.set_ylim(min(dec),max(dec))
#Add more info
if header!='False':
pylab.figtext(0.1,.95,'# Spectra: %d' %len(specid))
pylab.figtext(0.1,.93,'Max Count: %d' %numpy.max(data))
return fig
