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cdim_maskfrac.py
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#########################################################################
##
## CDIM observation time calculator
## Mike Zemcov ([email protected])
##
## Changelog:
## v1, June 2017, first (extremely simplistic) version.
##
#########################################################################
#!/usr/bin/python
import sys
import numpy as np
import pylab as pl
import matplotlib.pyplot as plt
from scipy import constants as cst
from scipy.optimize import curve_fit
from scipy.signal import savgol_filter
from mpl_toolkits.mplot3d import Axes3D
def func(x, a, b, c):
return a*(x/b)**(-0.75)*np.exp(-x/b)+c
verbose = 2 # control verbosity
if verbose == 2:
fig=plt.figure(figsize=(6.5,5))
ax = fig.add_subplot(1,1,1)
countfiles = ["counts_U.csv","counts_B.csv","g_data_all.sorted.txt","r_data_all.sorted.txt","counts_R.csv","i_data_all.sorted.txt","counts_I.csv","z_data_all.sorted.txt","Y_data_all.sorted.txt","j_data_all.sorted.txt","counts_H.csv","counts_K.csv","counts_36.csv","counts_45.csv","counts_58.csv","counts_80.csv"]
countlambda = np.asarray([0.36,0.438,0.467,0.560,0.641,0.680,0.798,0.892,1.02,1.24,1.63,2.19,3.6,4.5,5.8,8.0])
countzero = [1790,4063,3631,3631,3064,3631,2416,3631,3631,3631,1021,640,3631,3631,3631,3631]
countmag = np.arange(5,25,0.5)
countcolors = plt.cm.rainbow(np.linspace(0, 1, len(countlambda)))
abzero = 3631
Apert = 1.0 # Aperture in m
lmax = 7.5 # maximum wavelength, microns
lmin = 0.75 # minimum wavelength, microns
fnum = 3.74/Apert # fnumber
Pitch = 18. # detector pixel pitch, um
n_width = 2.5; # number of FWHM to cut out for each masked source
rtoa = 3600.*180./np.pi # constant radians to arcsec
# angle subtended by each pixel
th_pix = rtoa*(Pitch*1.e-6)/(Apert*fnum)
# array of wavelengths
cdim_lambda = np.arange(lmin,lmax,0.1)
# this is the diffraction limit at each wavelength in arcsec
diffraction_limit = 1.03 * (cdim_lambda * 1e-6) / Apert * rtoa
# this is how many FWHM we would cut for each source based on
# the difftraction limt
dl_safety = n_width * diffraction_limit
# make a copy we can do things with
cut_width = dl_safety
# everywhere the pixel size is larger than the number of pixels
# we would cut, turn into the pixel size
whpl = np.where(cut_width < th_pix)
cut_width[whpl] = th_pix
# now the previous number is in width, we want in area
cut_area = np.pi * (cut_width / 2)**2
# and fix to the closest integer
cut_area_fix = np.ceil(cut_area)
for counter, lam in enumerate(cut_area):
if cut_area[counter] <= 1:
cut_area_fix[counter] = 3
if cut_area[counter] > 1 and cut_area[counter] <= 4:
cut_area_fix[counter] = 4
if cut_area[counter] > 4 and cut_area[counter] <= 9:
cut_area_fix[counter] = 9
if cut_area[counter] > 9 and cut_area[counter] <= 16:
cut_area_fix[counter] = 16
if cut_area[counter] > 16 and cut_area[counter] <= 25:
cut_area_fix[counter] = 25
if verbose == 2:
ax.plot(cdim_lambda,diffraction_limit,linestyle='-',label='Diffraction Limit, FWHM')
ax.plot(cdim_lambda,np.repeat(th_pix,np.size(cdim_lambda)),linestyle='-',label='Pixel Size')
ax.plot(cdim_lambda,cut_width,linestyle='-',label='Cut Function')
ax.set_xlabel(r'$\lambda$ ($\mu$m)')
ax.set_ylabel(r'Width (arcsec)')
ax.set_xlim([0.75,7.5])
plt.legend(loc=2)
plt.tight_layout()
plt.savefig('cdim_maskfrac_width.pdf')
#plt.show()
if verbose == 2:
fig=plt.figure(figsize=(6.5,5))
ax = fig.add_subplot(1,1,1)
#print cdim_lambda
#print cut_area_fix
#print np.size(cdim_lambda)
magsurf = np.zeros([18,len(countfiles)])
#fluxes = 15.**(np.arange(-10,-1))
xmagab = np.arange(13,31)
markmag = np.array([31,30,29,30,32,29,26,26,26,26])
#markmag = np.array([26,26,26,26,26,26,26,26,26,26])
for ifile,thisfile in enumerate(countfiles):
my_data = np.genfromtxt("lookup/"+thisfile, delimiter=',')
thiscountmag = my_data[:,0]
thiscountcount = my_data[:,1]
ymagab = -2.5*np.log10(countzero[ifile]*10**(-thiscountmag/2.5)/abzero)
try:
popt, pcov = curve_fit(func,ymagab,np.log10(thiscountcount), p0=(10,10,0))
except RuntimeError:
print("Error - curve_fit failed")
popt = [0,0,0]
#interpcount = np.polyfit(ymagab,np.log10(thiscountcount),2)
#fitcount = interpcount[0] * xmagab**2 + interpcount[1] * xmagab + interpcount[2]
fitcount = func(xmagab, *popt)
ax.plot(ymagab,np.log10(thiscountcount),marker='o',linestyle='',color=countcolors[ifile])
ax.plot(xmagab,fitcount,linestyle='-',color=countcolors[ifile],label=countlambda[ifile].astype('str')+r' $\mu$m')
plt.show(block=False)
#print popt
#_ = raw_input("Press [enter] to continue.")
#interpcount = 10**(interpcount)
#print interpcount
#print ymagab
#whpl = np.where(xmagab >= markmag[ifile])
#wheq = np.where(np.abs(xmagab-markmag[ifile]) == np.min(np.abs(xmagab-markmag[ifile])))
#fitcount[whpl] = fitcount[wheq]
magsurf[:,ifile] = fitcount
ax.set_xlim([13,30])
ax.set_xlabel('Mag (AB)')
ax.set_ylabel('N(>M) (deg$^{-2}$)')
plt.legend(loc=4,fontsize=8)
plt.savefig('cdim_maskfrac_counts.pdf')
#plt.show()
npersd = np.interp(cdim_lambda,countlambda,magsurf[len(xmagab)-1,:])
cut_as = cut_area * 10**(npersd)
numberperslice = (3600./th_pix)**2
cut_frac = savgol_filter(cut_as / numberperslice,17,1)
if verbose == 2:
fig=plt.figure(figsize=(6.5,5))
ax = fig.add_subplot(1,1,1)
ax.plot(cdim_lambda,cut_frac,linestyle='-')
ax.set_xlabel(r'$\lambda$ ($\mu$m)')
ax.set_ylabel(r'Fraction of Pixels Lost at m$_{\rm AB}=27$')
ax.set_xlim([0.75,7.5])
#plt.legend(loc=2)
#plt.tight_layout()
#plt.show()
plt.savefig('cdim_maskfrac_pixlost.pdf')
### return