def disp_delay_inf(freq1=0.184975, DM=0.0):
"""
Accepts lower band-edge frequency and a DM, returns the dispersion delay
in milliseconds realtive to infinite frequncy.
Default: frequency = 184.975 MHz, DM = 0 pc/cm^3
"""
A = e.value ** 2 / (8 * pi ** 2 * m_e.value * c.value * eps0.value)
A = A * (1.0 / 1.0e9) ** 2 * (1e6) * (1e3) * pc.to("m").value
del_t = A * DM * freq ** (-2)
return del_t
def disp_delay(freq1=0.184975, freq2=0.200335, DM=0.0):
"""
Accepts two frequencies as input (low then high, in GHz) as well as a
DM (in pc/cm^3) and reports the delay in milliseconds (ms).
Default frequncies: 184.975 and 200.355 MHz, default DM=0.0 pc/cm^3
"""
# constant from analytic cold plasma dispersion
A = e.value ** 2 / (8 * pi ** 2 * m_e.value * c.value * eps0.value)
# convert into units: GHz^2 cm^3 ms / pc
A = A * (1.0 / 1.0e9) ** 2 * (1e6) * (1e3) * pc.to("m").value
del_t = A * DM * ((freq1) ** (-2) - (freq2) ** (-2))
return del_t
def get_qsfit_M1450(qsfit,alpha_nu=-0.4):
cwave = np.zeros(len(qsfit))
qsfitCont = np.zeros(len(qsfit))
for wv in ['1450','2245','3000','4210','5100']:
contk = 'CONT%s__LUM' % wv
contwk = 'CONT%s__WAVE' % wv
ii = np.where((cwave==0) & ~np.isnan(qsfit[contk]))[0]
if len(ii) > 0:
cwave[ii] = qsfit[contwk][ii]
qsfitCont[ii] = qsfit[contk][ii]
cnu = (cwave*u.Angstrom).to(u.Hz,equivalencies=u.spectral())
cnu1450 = (1450.*u.Angstrom).to(u.Hz,equivalencies=u.spectral())
qsfitLnu1450 = (qsfitCont*1e42/cnu)*(cnu1450/cnu)**alpha_nu
fourpidsqr = 4*np.pi*(10*pc.to('cm').value)**2
qsfitM1450 = -2.5*np.log10(qsfitLnu1450.value/fourpidsqr) - 48.6
return qsfitM1450
def __init__(self,model,dx,nphi=2**12,screen_res=2,\
wavelength=1.3e-3,dpc=8400,rpc=5800,r0 = 'sgra',\
r_outer=10000000,r_inner=12,alpha='kolmogorov',\
anisotropy=2.045,pa=78,match_screen_res=False,live_dangerously=False,think_positive=False):
# set initial members
self.logger = logging.getLogger(self.__class__.__name__)
self.live_dangerously = live_dangerously
self.think_positive = think_positive
self.wavelength = wavelength * 1e-3 # observing wavelength in km
self.dpc = float(dpc) # earth-source distance in pc
self.rpc = float(rpc) # R: source-scatterer distance in pc
self.d = self.dpc - self.rpc # D: earth-scatterer distance in pc
self.m = self.d / self.rpc # magnification factor (D/R)
if r0 == 'sgra':
# major axis (EW) phase coherence length in km
self.r0 = 3136.67 * (1.3e-6 / self.wavelength)
else:
try:
self.r0 = float(r0)
except:
raise ValueError('Bad value for r0')
self.anisotropy = anisotropy # anisotropy for screen = (EW / NS elongation)
self.pa = pa # orientation of major axis, E of N (or CCW of +y)
# Fresnel scale in km
self.rf = sqrt(self.dpc * pc.to(units.km).value /
(2 * pi / self.wavelength) * self.m / (1 + self.m)**2)
# compute pixel scale for image
if match_screen_res:
self.ips = 1
self.screen_dx = screen_res * self.r0
else:
self.screen_dx = screen_res * self.r0 # size of a screen pixel in km
self.ips = int(
ceil(1e-6 * dx * self.d * au.to(units.km).value /
self.screen_dx)) # image pixel / screen pixel
# image arrays
self.dx = 1e6 * self.ips * (self.screen_dx /
(au.to(units.km).value * self.d)
) # image pixel scale in uas
self.nx = int(ceil(model.shape[-1] * dx /
self.dx)) # number of image pixels
self.model = model # source model
self.model_dx = dx # source model resolution
self.iss = np.array([], dtype=np.float64) # scattered image
self.isrc = np.array(
[],
dtype=np.float64) # source image at same scale as scattered image
# screen parameters
if type(nphi) == int:
self.nphi = (nphi, nphi) # size of screen array
else:
self.nphi = nphi
self.nphi = np.asarray(self.nphi)
self.r_inner = r_inner # inner turbulence scale in r0
self.r_outer = r_outer # outer turbulence scale in r0
#self.qmax = 1.*screen_res/r_inner # 1 / inner turbulence scale in pix
#self.qmin = 1.*screen_res/r_outer # 1 / outer tubulence scale in pix
if alpha == 'kolmogorov':
self.alpha = 5. / 3
else:
try:
self.alpha = float(alpha)
except:
raise ValueError('Bad value for alpha')
# use logger to report
self.chatter()
# includes sanity check
self.setModel(self.model,
self.model_dx,
think_positive=self.think_positive)
def __init__(self,model,dx,nphi=2**12,screen_res=2,\
wavelength=1.3e-3,dpc=8400,rpc=5800,r0 = 'sgra',\
r_outer=10000000,r_inner=12,alpha='kolmogorov',\
anisotropy=2.045,pa=78,match_screen_res=False,live_dangerously=False,think_positive=False):
# set initial members
self.logger = logging.getLogger(self.__class__.__name__)
self.live_dangerously = live_dangerously
self.think_positive = think_positive
self.wavelength = wavelength*1e-3 # observing wavelength in km
self.dpc = float(dpc) # earth-source distance in pc
self.rpc = float(rpc) # R: source-scatterer distance in pc
self.d = self.dpc - self.rpc # D: earth-scatterer distance in pc
self.m = self.d/self.rpc # magnification factor (D/R)
if r0 == 'sgra':
# major axis (EW) phase coherence length in km
self.r0 = 3136.67*(1.3e-6/self.wavelength)
else:
try:
self.r0 = float(r0)
except:
raise ValueError('Bad value for r0')
self.anisotropy = anisotropy # anisotropy for screen = (EW / NS elongation)
self.pa = pa # orientation of major axis, E of N (or CCW of +y)
# Fresnel scale in km
self.rf = sqrt(self.dpc*pc.to(units.km).value / (2*pi / self.wavelength) * self.m / (1+self.m)**2)
# compute pixel scale for image
if match_screen_res:
self.ips = 1
self.screen_dx = screen_res * self.r0
else:
self.screen_dx = screen_res * self.r0 # size of a screen pixel in km
self.ips = int(ceil(1e-6*dx*self.d*au.to(units.km).value/self.screen_dx)) # image pixel / screen pixel
# image arrays
self.dx = 1e6 * self.ips * (self.screen_dx / (au.to(units.km).value * self.d)) # image pixel scale in uas
self.nx = int(ceil(model.shape[-1] * dx / self.dx)) # number of image pixels
self.model = model # source model
self.model_dx = dx # source model resolution
self.iss = np.array([],dtype=np.float64) # scattered image
self.isrc = np.array([],dtype=np.float64) # source image at same scale as scattered image
# screen parameters
if type(nphi) == int:
self.nphi = (nphi,nphi) # size of screen array
else:
self.nphi = nphi
self.nphi = np.asarray(self.nphi)
self.r_inner = r_inner # inner turbulence scale in r0
self.r_outer = r_outer # outer turbulence scale in r0
#self.qmax = 1.*screen_res/r_inner # 1 / inner turbulence scale in pix
#self.qmin = 1.*screen_res/r_outer # 1 / outer tubulence scale in pix
if alpha == 'kolmogorov':
self.alpha = 5./3
else:
try:
self.alpha = float(alpha)
except:
raise ValueError('Bad value for alpha')
# use logger to report
self.chatter()
# includes sanity check
self.setModel(self.model,self.model_dx,think_positive=self.think_positive)
