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Commit 38e2c452 authored by Fang Yuedong's avatar Fang Yuedong
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Merge branch 'master' into 'current_stable_for_tests' 

for tests before release

See merge request !23
parents e0f2b9f7 1c35c0e2
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ObservationSim/MockObject/CatalogBase.py → observation_sim/mock_objects/CatalogBase.py
View file @ 38e2c452
...@@ -5,7 +5,7 @@ import cmath ...@@ -5,7 +5,7 @@ import cmath
from astropy.table import Table from astropy.table import Table
from abc import abstractmethod, ABCMeta from abc import abstractmethod, ABCMeta
from ObservationSim.MockObject._util import integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getABMAG from observation_sim.mock_objects._util import integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getABMAG
class CatalogBase(metaclass=ABCMeta): class CatalogBase(metaclass=ABCMeta):
......
ObservationSim/MockObject/FlatLED.py → observation_sim/mock_objects/FlatLED.py
View file @ 38e2c452
import galsim import galsim
import os, sys import os
import sys
import numpy as np import numpy as np
import time import time
import math import math
...@@ -9,12 +10,11 @@ import astropy.constants as cons ...@@ -9,12 +10,11 @@ import astropy.constants as cons
from astropy.io import fits from astropy.io import fits
from scipy.interpolate import griddata from scipy.interpolate import griddata
from astropy.table import Table from astropy.table import Table
from ObservationSim.MockObject.SpecDisperser import SpecDisperser from observation_sim.mock_objects.SpecDisperser import SpecDisperser
from scipy import interpolate from scipy import interpolate
import gc import gc
from ObservationSim.MockObject.MockObject import MockObject from observation_sim.mock_objects.MockObject import MockObject
# from ObservationSim.Straylight import calculateSkyMap_split_g
try: try:
import importlib.resources as pkg_resources import importlib.resources as pkg_resources
...@@ -27,13 +27,13 @@ except ImportError: ...@@ -27,13 +27,13 @@ except ImportError:
LED_name = ['LED1', 'LED2', 'LED3', 'LED4', 'LED5', 'LED6', 'LED7', 'LED8', 'LED9', 'LED10', 'LED11', 'LED12', 'LED13', LED_name = ['LED1', 'LED2', 'LED3', 'LED4', 'LED5', 'LED6', 'LED7', 'LED8', 'LED9', 'LED10', 'LED11', 'LED12', 'LED13',
'LED14'] 'LED14']
cwaves_name = {'LED1': '275', 'LED2': '310', 'LED3': '430', 'LED4': '505', 'LED5': '545', 'LED6': '590', 'LED7': '670', cwaves_name = {'LED1': '275', 'LED2': '310', 'LED3': '430', 'LED4': '505', 'LED5': '545', 'LED6': '590', 'LED7': '670',
'LED8': '760', 'LED9': '940', 'LED10': '940', 'LED11': '1050', 'LED12': '1050', 'LED8': '760', 'LED9': '940', 'LED10': '940', 'LED11': '1050', 'LED12': '1050',
'LED13': '340', 'LED14': '365'} 'LED13': '340', 'LED14': '365'}
cwaves = {'LED1': 2750, 'LED2': 3100, 'LED3': 4300, 'LED4': 5050, 'LED5': 5250, 'LED6': 5900, 'LED7': 6700, cwaves = {'LED1': 2750, 'LED2': 3100, 'LED3': 4300, 'LED4': 5050, 'LED5': 5250, 'LED6': 5900, 'LED7': 6700,
'LED8': 7600, 'LED9': 8800, 'LED10': 9400, 'LED11': 10500, 'LED12': 15500, 'LED13': 3400, 'LED14': 3650} 'LED8': 7600, 'LED9': 8800, 'LED10': 9400, 'LED11': 10500, 'LED12': 15500, 'LED13': 3400, 'LED14': 3650}
cwaves_fwhm = {'LED1': 110, 'LED2': 120, 'LED3': 200, 'LED4': 300, 'LED5': 300, 'LED6': 130, 'LED7': 210, cwaves_fwhm = {'LED1': 110, 'LED2': 120, 'LED3': 200, 'LED4': 300, 'LED5': 300, 'LED6': 130, 'LED7': 210,
'LED8': 260, 'LED9': 400, 'LED10': 370, 'LED11': 500, 'LED12': 1400, 'LED13': 90, 'LED14': 100} 'LED8': 260, 'LED9': 400, 'LED10': 370, 'LED11': 500, 'LED12': 1400, 'LED13': 90, 'LED14': 100}
# LED_QE = {'LED1': 0.3, 'LED2': 0.4, 'LED13': 0.5, 'LED14': 0.5, 'LED10': 0.4} # LED_QE = {'LED1': 0.3, 'LED2': 0.4, 'LED13': 0.5, 'LED14': 0.5, 'LED10': 0.4}
# e-/ms # e-/ms
# fluxLED = {'LED1': 0.16478729, 'LED2': 0.084220931, 'LED3': 2.263360617, 'LED4': 2.190623489, 'LED5': 0.703504768, # fluxLED = {'LED1': 0.16478729, 'LED2': 0.084220931, 'LED3': 2.263360617, 'LED4': 2.190623489, 'LED5': 0.703504768,
...@@ -43,17 +43,18 @@ cwaves_fwhm = {'LED1': 110, 'LED2': 120, 'LED3': 200, 'LED4': 300, 'LED5': 300, ...@@ -43,17 +43,18 @@ cwaves_fwhm = {'LED1': 110, 'LED2': 120, 'LED3': 200, 'LED4': 300, 'LED5': 300,
# e-/ms # e-/ms
fluxLED = {'LED1': 15, 'LED2': 15, 'LED3': 12.5, 'LED4': 9, 'LED5': 9, fluxLED = {'LED1': 15, 'LED2': 15, 'LED3': 12.5, 'LED4': 9, 'LED5': 9,
'LED6': 9, 'LED7': 9, 'LED8': 9, 'LED9': 9, 'LED10': 12.5, 'LED11': 15, 'LED12':15, 'LED13': 12.5, 'LED6': 9, 'LED7': 9, 'LED8': 9, 'LED9': 9, 'LED10': 12.5, 'LED11': 15, 'LED12': 15, 'LED13': 12.5,
'LED14': 12.5} 'LED14': 12.5}
# fluxLEDL = {'LED1': 10, 'LED2': 10, 'LED3': 10, 'LED4': 10, 'LED5': 10, # fluxLEDL = {'LED1': 10, 'LED2': 10, 'LED3': 10, 'LED4': 10, 'LED5': 10,
# 'LED6': 10, 'LED7': 10, 'LED8': 10, 'LED9': 10, 'LED10': 10, 'LED11': 10, 'LED12':10, 'LED13': 10, # 'LED6': 10, 'LED7': 10, 'LED8': 10, 'LED9': 10, 'LED10': 10, 'LED11': 10, 'LED12':10, 'LED13': 10,
# 'LED14': 10} # 'LED14': 10}
mirro_eff = {'GU':0.61, 'GV':0.8, 'GI':0.8} mirro_eff = {'GU': 0.61, 'GV': 0.8, 'GI': 0.8}
# mirro_eff = {'GU':1, 'GV':1, 'GI':1} # mirro_eff = {'GU':1, 'GV':1, 'GI':1}
class FlatLED(MockObject): class FlatLED(MockObject):
def __init__(self, chip,filt, flatDir = None, logger=None): def __init__(self, chip, filt, flatDir=None, logger=None):
# self.led_type_list = led_type_list # self.led_type_list = led_type_list
self.filt = filt self.filt = filt
self.chip = chip self.chip = chip
...@@ -62,18 +63,19 @@ class FlatLED(MockObject): ...@@ -62,18 +63,19 @@ class FlatLED(MockObject):
self.flatDir = flatDir self.flatDir = flatDir
else: else:
try: try:
with pkg_resources.files('ObservationSim.MockObject.data.led').joinpath("") as ledDir: with pkg_resources.files('observation_sim.mock_objects.data.led').joinpath("") as ledDir:
self.flatDir = ledDir.as_posix() self.flatDir = ledDir.as_posix()
except AttributeError: except AttributeError:
with pkg_resources.path('ObservationSim.MockObject.data.led', "") as ledDir: with pkg_resources.path('observation_sim.mock_objects.data.led', "") as ledDir:
self.flatDir = ledDir.as_posix() self.flatDir = ledDir.as_posix()
### ###
### return LED flat, e/s # return LED flat, e/s
### ###
def getLEDImage(self, led_type='LED1'): def getLEDImage(self, led_type='LED1'):
# cwave = cwaves[led_type] # cwave = cwaves[led_type]
flat = fits.open(os.path.join(self.flatDir, 'model_' + cwaves_name[led_type] + 'nm.fits')) flat = fits.open(os.path.join(self.flatDir, 'model_' +
cwaves_name[led_type] + 'nm.fits'))
xlen = flat[0].header['NAXIS1'] xlen = flat[0].header['NAXIS1']
ylen = 601 ylen = 601
x = np.linspace(0, self.chip.npix_x * 6, xlen) x = np.linspace(0, self.chip.npix_x * 6, xlen)
...@@ -95,21 +97,23 @@ class FlatLED(MockObject): ...@@ -95,21 +97,23 @@ class FlatLED(MockObject):
i = self.chip.rowID - 1 i = self.chip.rowID - 1
j = self.chip.colID - 1 j = self.chip.colID - 1
U = griddata(X_, Z_, ( U = griddata(X_, Z_, (
M[self.chip.npix_y * i:self.chip.npix_y * (i + 1), self.chip.npix_x * j:self.chip.npix_x * (j + 1)], M[self.chip.npix_y * i:self.chip.npix_y *
(i + 1), self.chip.npix_x * j:self.chip.npix_x * (j + 1)],
N[self.chip.npix_y * i:self.chip.npix_y * (i + 1), self.chip.npix_x * j:self.chip.npix_x * (j + 1)]), N[self.chip.npix_y * i:self.chip.npix_y * (i + 1), self.chip.npix_x * j:self.chip.npix_x * (j + 1)]),
method='linear') method='linear')
U = U/np.mean(U) U = U/np.mean(U)
flatImage = U*fluxLED[led_type]*1000 flatImage = U*fluxLED[led_type]*1000
gc.collect() gc.collect()
return flatImage return flatImage
### ###
### return LED flat, e/s # return LED flat, e/s
### ###
def getLEDImage1(self, led_type='LED1'): def getLEDImage1(self, led_type='LED1'):
# cwave = cwaves[led_type] # cwave = cwaves[led_type]
flat = fits.open(os.path.join(self.flatDir, 'model_' + cwaves_name[led_type] + 'nm.fits')) flat = fits.open(os.path.join(self.flatDir, 'model_' +
cwaves_name[led_type] + 'nm.fits'))
xlen = flat[0].header['NAXIS1'] xlen = flat[0].header['NAXIS1']
ylen = 601 ylen = 601
...@@ -120,22 +124,23 @@ class FlatLED(MockObject): ...@@ -120,22 +124,23 @@ class FlatLED(MockObject):
y = np.linspace(0, self.chip.npix_y, int(ylen/5.)) y = np.linspace(0, self.chip.npix_y, int(ylen/5.))
xx, yy = np.meshgrid(x, y) xx, yy = np.meshgrid(x, y)
a1 = flat[0].data[int(ylen*i/5.):int(ylen*i/5.)+int(ylen/5.), int(xlen*j/6.):int(xlen*j/6.)+int(xlen/6.)] a1 = flat[0].data[int(ylen*i/5.):int(ylen*i/5.)+int(ylen/5.),
int(xlen*j/6.):int(xlen*j/6.)+int(xlen/6.)]
# z = np.sin((xx+yy+xx**2+yy**2)) # z = np.sin((xx+yy+xx**2+yy**2))
# fInterp = interp2d(xx, yy, z, kind='linear') # fInterp = interp2d(xx, yy, z, kind='linear')
X_ = np.hstack((xx.flatten()[:, None], yy.flatten()[:, None])) X_ = np.hstack((xx.flatten()[:, None], yy.flatten()[:, None]))
Z_ = a1.flatten() Z_ = a1.flatten()
n_x = np.arange(0, self.chip.npix_x , 1) n_x = np.arange(0, self.chip.npix_x, 1)
n_y = np.arange(0, self.chip.npix_y, 1) n_y = np.arange(0, self.chip.npix_y, 1)
M, N = np.meshgrid(n_x, n_y) M, N = np.meshgrid(n_x, n_y)
U = griddata(X_, Z_, ( U = griddata(X_, Z_, (
M[0:self.chip.npix_y, 0:self.chip.npix_x], M[0:self.chip.npix_y, 0:self.chip.npix_x],
N[0:self.chip.npix_y, 0:self.chip.npix_x ]), N[0:self.chip.npix_y, 0:self.chip.npix_x]),
method='linear') method='linear')
U = U/np.mean(U) U = U/np.mean(U)
flatImage = U*fluxLED[led_type]*1000 flatImage = U*fluxLED[led_type]*1000
gc.collect() gc.collect()
...@@ -143,12 +148,13 @@ class FlatLED(MockObject): ...@@ -143,12 +148,13 @@ class FlatLED(MockObject):
def drawObj_LEDFlat_img(self, led_type_list=['LED1'], exp_t_list=[0.1]): def drawObj_LEDFlat_img(self, led_type_list=['LED1'], exp_t_list=[0.1]):
if len(led_type_list) > len(exp_t_list): if len(led_type_list) > len(exp_t_list):
return np.ones([self.chip.npix_y,self.chip.npix_x]) return np.ones([self.chip.npix_y, self.chip.npix_x])
ledFlat = np.zeros([self.chip.npix_y,self.chip.npix_x]) ledFlat = np.zeros([self.chip.npix_y, self.chip.npix_x])
ledStat = '00000000000000' ledStat = '00000000000000'
ledTimes = [0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0] ledTimes = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
nledStat = '2' nledStat = '2'
for i in np.arange(len(led_type_list)): for i in np.arange(len(led_type_list)):
...@@ -160,8 +166,10 @@ class FlatLED(MockObject): ...@@ -160,8 +166,10 @@ class FlatLED(MockObject):
led_wave = cwaves[led_type] led_wave = cwaves[led_type]
led_fwhm = cwaves_fwhm[led_type] led_fwhm = cwaves_fwhm[led_type]
led_spec = self.gaussian1d_profile_led(led_wave, led_fwhm) led_spec = self.gaussian1d_profile_led(led_wave, led_fwhm)
speci = interpolate.interp1d(led_spec['WAVELENGTH'], led_spec['FLUX']) speci = interpolate.interp1d(
w_list = np.arange(self.filt.blue_limit, self.filt.red_limit, 0.5) #A led_spec['WAVELENGTH'], led_spec['FLUX'])
w_list = np.arange(self.filt.blue_limit,
self.filt.red_limit, 0.5) # A
f_spec = speci(w_list) f_spec = speci(w_list)
ccd_bp = self.chip._getChipEffCurve(self.chip.filter_type) ccd_bp = self.chip._getChipEffCurve(self.chip.filter_type)
...@@ -174,19 +182,21 @@ class FlatLED(MockObject): ...@@ -174,19 +182,21 @@ class FlatLED(MockObject):
# print("DEBUG1:---------------",np.mean(unitFlatImg)) # print("DEBUG1:---------------",np.mean(unitFlatImg))
ledFlat = ledFlat+unitFlatImg*exp_t ledFlat = ledFlat+unitFlatImg*exp_t
ledStat = ledStat[0:int(led_type[3:])-1]+nledStat+ledStat[int(led_type[3:]):] ledStat = ledStat[0:int(led_type[3:])-1] + \
nledStat+ledStat[int(led_type[3:]):]
ledTimes[int(led_type[3:])-1] = exp_t * 1000 ledTimes[int(led_type[3:])-1] = exp_t * 1000
gc.collect() gc.collect()
return ledFlat, ledStat, ledTimes return ledFlat, ledStat, ledTimes
def drawObj_LEDFlat_slitless(self, led_type_list=['LED1'], exp_t_list=[0.1]): def drawObj_LEDFlat_slitless(self, led_type_list=['LED1'], exp_t_list=[0.1]):
if len(led_type_list) != len(exp_t_list): if len(led_type_list) != len(exp_t_list):
return np.ones([self.chip.npix_y,self.chip.npix_x]) return np.ones([self.chip.npix_y, self.chip.npix_x])
ledFlat = np.zeros([self.chip.npix_y,self.chip.npix_x]) ledFlat = np.zeros([self.chip.npix_y, self.chip.npix_x])
ledStat = '00000000000000' ledStat = '00000000000000'
ledTimes = [0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0] ledTimes = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
nledStat = '2' nledStat = '2'
...@@ -213,7 +223,8 @@ class FlatLED(MockObject): ...@@ -213,7 +223,8 @@ class FlatLED(MockObject):
flat_cube=self.chip.flat_cube, led_spec=led_spec) flat_cube=self.chip.flat_cube, led_spec=led_spec)
ledFlat = ledFlat + ledspec_map ledFlat = ledFlat + ledspec_map
ledStat = ledStat[0:int(led_type[3:])-1]+nledStat+ledStat[int(led_type[3:]):] ledStat = ledStat[0:int(led_type[3:])-1] + \
nledStat+ledStat[int(led_type[3:]):]
ledTimes[int(led_type[3:])-1] = exp_t * 1000 ledTimes[int(led_type[3:])-1] = exp_t * 1000
return ledFlat, ledStat, ledTimes return ledFlat, ledStat, ledTimes
...@@ -223,7 +234,6 @@ class FlatLED(MockObject): ...@@ -223,7 +234,6 @@ class FlatLED(MockObject):
elif self.chip.survey_type == "spectroscopic": elif self.chip.survey_type == "spectroscopic":
return self.drawObj_LEDFlat_slitless(led_type_list=led_type_list, exp_t_list=exp_t_list) return self.drawObj_LEDFlat_slitless(led_type_list=led_type_list, exp_t_list=exp_t_list)
def gaussian1d_profile_led(self, xc=5050, fwhm=300): def gaussian1d_profile_led(self, xc=5050, fwhm=300):
sigma = fwhm/2.355 sigma = fwhm/2.355
x_radii = int(5*sigma + 1) x_radii = int(5*sigma + 1)
...@@ -232,9 +242,10 @@ class FlatLED(MockObject): ...@@ -232,9 +242,10 @@ class FlatLED(MockObject):
xlist_[1:-1] = xlist xlist_[1:-1] = xlist
xlist_[0] = 2000 xlist_[0] = 2000
xlist_[-1] = 18000 xlist_[-1] = 18000
ids1 = xlist>xc-fwhm ids1 = xlist > xc-fwhm
ids2 = xlist[ids1]<xc+fwhm ids2 = xlist[ids1] < xc+fwhm
data = np.exp((-(xlist-xc)*(xlist-xc))/(2*sigma*sigma))/(np.sqrt(2*math.pi)*sigma) data = np.exp((-(xlist-xc)*(xlist-xc))/(2*sigma*sigma)) / \
(np.sqrt(2*math.pi)*sigma)
scale = 1/np.trapz(data[ids1][ids2], xlist[ids1][ids2]) scale = 1/np.trapz(data[ids1][ids2], xlist[ids1][ids2])
data_ = np.zeros(len(xlist) + 2) data_ = np.zeros(len(xlist) + 2)
data_[1:-1] = data*scale data_[1:-1] = data*scale
...@@ -242,8 +253,8 @@ class FlatLED(MockObject): ...@@ -242,8 +253,8 @@ class FlatLED(MockObject):
return Table(np.array([xlist_.astype(np.float32), data_.astype(np.float32)]).T, names=('WAVELENGTH', 'FLUX')) return Table(np.array([xlist_.astype(np.float32), data_.astype(np.float32)]).T, names=('WAVELENGTH', 'FLUX'))
def calculateLEDSpec(self, skyMap=None, blueLimit=4200, redLimit=6500, def calculateLEDSpec(self, skyMap=None, blueLimit=4200, redLimit=6500,
conf=[''], pixelSize=0.074, isAlongY=0, conf=[''], pixelSize=0.074, isAlongY=0,
split_pos=3685, flat_cube=None, led_spec=None): split_pos=3685, flat_cube=None, led_spec=None):
conf1 = conf[0] conf1 = conf[0]
conf2 = conf[0] conf2 = conf[0]
...@@ -297,7 +308,8 @@ class FlatLED(MockObject): ...@@ -297,7 +308,8 @@ class FlatLED(MockObject):
sub_x_s = k2 sub_x_s = k2
sub_x_e = sub_x_end_arr[j] sub_x_e = sub_x_end_arr[j]
skyImg_sub = galsim.Image(skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e]) skyImg_sub = galsim.Image(
skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e])
origin_sub = [sub_y_s, sub_x_s] origin_sub = [sub_y_s, sub_x_s]
sub_x_center = (sub_x_s + sub_x_e) / 2. sub_x_center = (sub_x_s + sub_x_e) / 2.
...@@ -321,11 +333,8 @@ class FlatLED(MockObject): ...@@ -321,11 +333,8 @@ class FlatLED(MockObject):
continue continue
fImg[bounds] = fImg[bounds] + ssImg[bounds] fImg[bounds] = fImg[bounds] + ssImg[bounds]
else: else:
# sdp.compute_spec_orders() # sdp.compute_spec_orders()
y_len = skyMap.shape[0] y_len = skyMap.shape[0]
x_len = skyMap.shape[1] x_len = skyMap.shape[1]
...@@ -352,7 +361,8 @@ class FlatLED(MockObject): ...@@ -352,7 +361,8 @@ class FlatLED(MockObject):
sub_x_e = sub_x_end_arr[j] sub_x_e = sub_x_end_arr[j]
# print(i,j,sub_y_s, sub_y_e,sub_x_s,sub_x_e) # print(i,j,sub_y_s, sub_y_e,sub_x_s,sub_x_e)
T1 = time.time() T1 = time.time()
skyImg_sub = galsim.Image(skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e]) skyImg_sub = galsim.Image(
skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e])
origin_sub = [sub_y_s, sub_x_s] origin_sub = [sub_y_s, sub_x_s]
sub_x_center = (sub_x_s + sub_x_e) / 2. sub_x_center = (sub_x_s + sub_x_e) / 2.
...@@ -398,7 +408,8 @@ class FlatLED(MockObject): ...@@ -398,7 +408,8 @@ class FlatLED(MockObject):
T1 = time.time() T1 = time.time()
skyImg_sub = galsim.Image(skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e]) skyImg_sub = galsim.Image(
skyImg.array[sub_y_s:sub_y_e, sub_x_s:sub_x_e])
origin_sub = [sub_y_s, sub_x_s] origin_sub = [sub_y_s, sub_x_s]
sub_x_center = (sub_x_s + sub_x_e) / 2. sub_x_center = (sub_x_s + sub_x_e) / 2.
...@@ -426,14 +437,11 @@ class FlatLED(MockObject): ...@@ -426,14 +437,11 @@ class FlatLED(MockObject):
print('time: %s ms' % ((T2 - T1) * 1000)) print('time: %s ms' % ((T2 - T1) * 1000))
if isAlongY == 1: if isAlongY == 1:
fimg, tmx, tmy = SpecDisperser.rotate90(array_orig=fImg.array, xc=0, yc=0, isClockwise=0) fimg, tmx, tmy = SpecDisperser.rotate90(
array_orig=fImg.array, xc=0, yc=0, isClockwise=0)
else: else:
fimg = fImg.array fimg = fImg.array
# fimg = fimg * pixelSize * pixelSize # fimg = fimg * pixelSize * pixelSize
return fimg return fimg
ObservationSim/MockObject/Galaxy.py → observation_sim/mock_objects/Galaxy.py
View file @ 38e2c452
...@@ -2,9 +2,9 @@ import numpy as np ...@@ -2,9 +2,9 @@ import numpy as np
import galsim import galsim
from astropy.table import Table from astropy.table import Table
from ObservationSim.MockObject._util import eObs, integrate_sed_bandpass, getNormFactorForSpecWithABMAG from observation_sim.mock_objects._util import eObs, integrate_sed_bandpass, getNormFactorForSpecWithABMAG
from ObservationSim.MockObject.SpecDisperser import SpecDisperser from observation_sim.mock_objects.SpecDisperser import SpecDisperser
from ObservationSim.MockObject.MockObject import MockObject from observation_sim.mock_objects.MockObject import MockObject
# import tracemalloc # import tracemalloc
......
ObservationSim/MockObject/MockObject.py → observation_sim/mock_objects/MockObject.py
View file @ 38e2c452
...@@ -6,10 +6,10 @@ from astropy import wcs ...@@ -6,10 +6,10 @@ from astropy import wcs
from astropy.table import Table from astropy.table import Table
import astropy.io.fits as fitsio import astropy.io.fits as fitsio
from ObservationSim.MockObject._util import magToFlux, VC_A, convolveGaussXorders, convolveImg from observation_sim.mock_objects._util import magToFlux, VC_A, convolveGaussXorders, convolveImg
from ObservationSim.MockObject._util import integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, \ from observation_sim.mock_objects._util import integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, \
getABMAG getABMAG
from ObservationSim.MockObject.SpecDisperser import SpecDisperser from observation_sim.mock_objects.SpecDisperser import SpecDisperser
class MockObject(object): class MockObject(object):
...@@ -17,21 +17,21 @@ class MockObject(object): ...@@ -17,21 +17,21 @@ class MockObject(object):
self.param = param self.param = param
for key in self.param: for key in self.param:
setattr(self, key, self.param[key]) setattr(self, key, self.param[key])
if self.param["star"] == 0: if self.param["star"] == 0:
self.type = "galaxy" self.type = "galaxy"
elif self.param["star"] == 1: elif self.param["star"] == 1:
self.type = "star" self.type = "star"
elif self.param["star"] == 2: elif self.param["star"] == 2:
self.type = "quasar" self.type = "quasar"
###mock_stamp_START # mock_stamp_START
elif self.param["star"] == 3: elif self.param["star"] == 3:
self.type = "stamp" self.type = "stamp"
###mock_stamp_END # mock_stamp_END
###for calibration # for calibration
elif self.param["star"] == 4: elif self.param["star"] == 4:
self.type = "calib" self.type = "calib"
###END # END
self.sed = None self.sed = None
self.fd_shear = None self.fd_shear = None
...@@ -72,19 +72,22 @@ class MockObject(object): ...@@ -72,19 +72,22 @@ class MockObject(object):
if verbose: if verbose:
print("\n") print("\n")
print("Before field distortion:\n") print("Before field distortion:\n")
print("x = %.2f, y = %.2f\n" % (self.posImg.x, self.posImg.y), flush=True) print("x = %.2f, y = %.2f\n" %
self.posImg, self.fd_shear = fdmodel.get_distorted(chip=chip, pos_img=self.posImg) (self.posImg.x, self.posImg.y), flush=True)
self.posImg, self.fd_shear = fdmodel.get_distorted(
chip=chip, pos_img=self.posImg)
if verbose: if verbose:
print("After field distortion:\n") print("After field distortion:\n")
print("x = %.2f, y = %.2f\n" % (self.posImg.x, self.posImg.y), flush=True) print("x = %.2f, y = %.2f\n" %
(self.posImg.x, self.posImg.y), flush=True)
x, y = self.posImg.x + 0.5, self.posImg.y + 0.5 x, y = self.posImg.x + 0.5, self.posImg.y + 0.5
self.x_nominal = int(np.floor(x + 0.5)) self.x_nominal = int(np.floor(x + 0.5))
self.y_nominal = int(np.floor(y + 0.5)) self.y_nominal = int(np.floor(y + 0.5))
dx = x - self.x_nominal dx = x - self.x_nominal
dy = y - self.y_nominal dy = y - self.y_nominal
self.offset = galsim.PositionD(dx, dy) self.offset = galsim.PositionD(dx, dy)
# Deal with chip rotation # Deal with chip rotation
if chip_wcs is not None: if chip_wcs is not None:
self.chip_wcs = chip_wcs self.chip_wcs = chip_wcs
...@@ -108,7 +111,8 @@ class MockObject(object): ...@@ -108,7 +111,8 @@ class MockObject(object):
# print("nphotons_tot = ", nphotons_tot) # print("nphotons_tot = ", nphotons_tot)
try: try:
full = integrate_sed_bandpass(sed=self.sed, bandpass=filt.bandpass_full) full = integrate_sed_bandpass(
sed=self.sed, bandpass=filt.bandpass_full)
except Exception as e: except Exception as e:
print(e) print(e)
if self.logger: if self.logger:
...@@ -121,7 +125,7 @@ class MockObject(object): ...@@ -121,7 +125,7 @@ class MockObject(object):
else: else:
folding_threshold = 5.e-3 folding_threshold = 5.e-3
gsp = galsim.GSParams(folding_threshold=folding_threshold) gsp = galsim.GSParams(folding_threshold=folding_threshold)
# Get real image position of object (deal with chip rotation w.r.t its center) # Get real image position of object (deal with chip rotation w.r.t its center)
self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y, self.real_pos = self.getRealPos(chip.img, global_x=self.posImg.x, global_y=self.posImg.y,
img_real_wcs=self.chip_wcs) img_real_wcs=self.chip_wcs)
...@@ -153,7 +157,7 @@ class MockObject(object): ...@@ -153,7 +157,7 @@ class MockObject(object):
# nphotons_sum += nphotons # nphotons_sum += nphotons
# print("nphotons_sub-band_%d = %.2f"%(i, nphotons)) # print("nphotons_sub-band_%d = %.2f"%(i, nphotons))
# Get PSF model # Get PSF model
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass, psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img, bandpass=bandpass,
folding_threshold=folding_threshold) folding_threshold=folding_threshold)
...@@ -166,21 +170,22 @@ class MockObject(object): ...@@ -166,21 +170,22 @@ class MockObject(object):
if np.sum(np.isnan(stamp.array)) > 0: if np.sum(np.isnan(stamp.array)) > 0:
continue continue
stamp.setCenter(x_nominal, y_nominal) stamp.setCenter(x_nominal, y_nominal)
bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1) bounds = stamp.bounds & galsim.BoundsI(
0, chip.npix_x - 1, 0, chip.npix_y - 1)
if bounds.area() > 0: if bounds.area() > 0:
chip.img.setOrigin(0, 0) chip.img.setOrigin(0, 0)
chip.img[bounds] += stamp[bounds] chip.img[bounds] += stamp[bounds]
is_updated = 1 is_updated = 1
chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin) chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
del stamp del stamp
if is_updated == 0: if is_updated == 0:
# Return code 0: object has missed this detector # Return code 0: object has missed this detector
print("obj %s missed"%(self.id)) print("obj %s missed" % (self.id))
if self.logger: if self.logger:
self.logger.info("obj %s missed"%(self.id)) self.logger.info("obj %s missed" % (self.id))
return 0, pos_shear return 0, pos_shear
return 1, pos_shear # Return code 1: draw sucesss return 1, pos_shear # Return code 1: draw sucesss
def addSLStoChipImage(self, sdp=None, chip=None, xOrderSigPlus=None, local_wcs=None): def addSLStoChipImage(self, sdp=None, chip=None, xOrderSigPlus=None, local_wcs=None):
spec_orders = sdp.compute_spec_orders() spec_orders = sdp.compute_spec_orders()
...@@ -193,7 +198,8 @@ class MockObject(object): ...@@ -193,7 +198,8 @@ class MockObject(object):
nan_ids = np.isnan(img_s) nan_ids = np.isnan(img_s)
if img_s[nan_ids].shape[0] > 0: if img_s[nan_ids].shape[0] > 0:
# img_s[nan_ids] = 0 # img_s[nan_ids] = 0
print("DEBUG: before convolveGaussXorders specImg nan num is", img_s[nan_ids].shape[0]) print("DEBUG: before convolveGaussXorders specImg nan num is",
img_s[nan_ids].shape[0])
######################################################### #########################################################
img_s, orig_off = convolveGaussXorders(img_s, xOrderSigPlus[k]) img_s, orig_off = convolveGaussXorders(img_s, xOrderSigPlus[k])
origin_order_x = v[1] - orig_off origin_order_x = v[1] - orig_off
...@@ -219,7 +225,8 @@ class MockObject(object): ...@@ -219,7 +225,8 @@ class MockObject(object):
stamp.wcs = local_wcs stamp.wcs = local_wcs
stamp.setOrigin(origin_order_x, origin_order_y) stamp.setOrigin(origin_order_x, origin_order_y)
bounds = stamp.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1) bounds = stamp.bounds & galsim.BoundsI(
0, chip.npix_x - 1, 0, chip.npix_y - 1)
if bounds.area() == 0: if bounds.area() == 0:
continue continue
chip.img.setOrigin(0, 0) chip.img.setOrigin(0, 0)
...@@ -230,17 +237,18 @@ class MockObject(object): ...@@ -230,17 +237,18 @@ class MockObject(object):
del stamp del stamp
del spec_orders del spec_orders
def addSLStoChipImageWithPSF(self, sdp=None, chip=None, pos_img_local = [1,1], psf_model=None, bandNo = 1, grating_split_pos=3685, local_wcs=None, pos_img=None): def addSLStoChipImageWithPSF(self, sdp=None, chip=None, pos_img_local=[1, 1], psf_model=None, bandNo=1, grating_split_pos=3685, local_wcs=None, pos_img=None):
spec_orders = sdp.compute_spec_orders() spec_orders = sdp.compute_spec_orders()
for k, v in spec_orders.items(): for k, v in spec_orders.items():
img_s = v[0] img_s = v[0]
# print(bandNo,k) # print(bandNo,k)
try: try:
psf, pos_shear = psf_model.get_PSF(chip, pos_img_local = pos_img_local, bandNo = bandNo, galsimGSObject=True, g_order = k, grating_split_pos=grating_split_pos) psf, pos_shear = psf_model.get_PSF(
chip, pos_img_local=pos_img_local, bandNo=bandNo, galsimGSObject=True, g_order=k, grating_split_pos=grating_split_pos)
except: except:
psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img) psf, pos_shear = psf_model.get_PSF(chip=chip, pos_img=pos_img)
psf_img = psf.drawImage(nx=100, ny=100, wcs = local_wcs) psf_img = psf.drawImage(nx=100, ny=100, wcs=local_wcs)
psf_img_m = psf_img.array psf_img_m = psf_img.array
...@@ -263,7 +271,6 @@ class MockObject(object): ...@@ -263,7 +271,6 @@ class MockObject(object):
origin_order_x = v[1] - orig_off[0] origin_order_x = v[1] - orig_off[0]
origin_order_y = v[2] - orig_off[1] origin_order_y = v[2] - orig_off[1]
specImg = galsim.ImageF(img_s) specImg = galsim.ImageF(img_s)
# photons = galsim.PhotonArray.makeFromImage(specImg) # photons = galsim.PhotonArray.makeFromImage(specImg)
# photons.x += origin_order_x # photons.x += origin_order_x
...@@ -278,7 +285,8 @@ class MockObject(object): ...@@ -278,7 +285,8 @@ class MockObject(object):
specImg.wcs = local_wcs specImg.wcs = local_wcs
specImg.setOrigin(origin_order_x, origin_order_y) specImg.setOrigin(origin_order_x, origin_order_y)
bounds = specImg.bounds & galsim.BoundsI(0, chip.npix_x - 1, 0, chip.npix_y - 1) bounds = specImg.bounds & galsim.BoundsI(
0, chip.npix_x - 1, 0, chip.npix_y - 1)
if bounds.area() == 0: if bounds.area() == 0:
continue continue
chip.img.setOrigin(0, 0) chip.img.setOrigin(0, 0)
...@@ -297,7 +305,8 @@ class MockObject(object): ...@@ -297,7 +305,8 @@ class MockObject(object):
norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001 norm_thr_rang_ids = normFilter['SENSITIVITY'] > 0.001
sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'], spectrum=self.sed, sedNormFactor = getNormFactorForSpecWithABMAG(ABMag=self.param['mag_use_normal'], spectrum=self.sed,
norm_thr=normFilter, norm_thr=normFilter,
sWave=np.floor(normFilter[norm_thr_rang_ids][0][0]), sWave=np.floor(
normFilter[norm_thr_rang_ids][0][0]),
eWave=np.ceil(normFilter[norm_thr_rang_ids][-1][0])) eWave=np.ceil(normFilter[norm_thr_rang_ids][-1][0]))
if sedNormFactor == 0: if sedNormFactor == 0:
return 2, None return 2, None
...@@ -331,9 +340,9 @@ class MockObject(object): ...@@ -331,9 +340,9 @@ class MockObject(object):
'D': 5.5684364343742825, 'E': 16.260021029735388} 'D': 5.5684364343742825, 'E': 16.260021029735388}
grating_split_pos_chip = 0 + grating_split_pos grating_split_pos_chip = 0 + grating_split_pos
branges = np.zeros([len(bandpass_list),2]) branges = np.zeros([len(bandpass_list), 2])
if hasattr(psf_model,'bandranges'): if hasattr(psf_model, 'bandranges'):
if psf_model.bandranges is None: if psf_model.bandranges is None:
return 2, None return 2, None
if len(psf_model.bandranges) != len(bandpass_list): if len(psf_model.bandranges) != len(bandpass_list):
...@@ -354,22 +363,24 @@ class MockObject(object): ...@@ -354,22 +363,24 @@ class MockObject(object):
star = star.withFlux(tel.pupil_area * exptime) star = star.withFlux(tel.pupil_area * exptime)
psf_tmp = galsim.Gaussian(sigma=0.002) psf_tmp = galsim.Gaussian(sigma=0.002)
star = galsim.Convolve(psf_tmp, star) star = galsim.Convolve(psf_tmp, star)
starImg = star.drawImage(nx=60, ny=60, wcs=chip_wcs_local, offset=offset) starImg = star.drawImage(
nx=60, ny=60, wcs=chip_wcs_local, offset=offset)
origin_star = [y_nominal - (starImg.center.y - starImg.ymin), origin_star = [y_nominal - (starImg.center.y - starImg.ymin),
x_nominal - (starImg.center.x - starImg.xmin)] x_nominal - (starImg.center.x - starImg.xmin)]
starImg.setOrigin(0,0) starImg.setOrigin(0, 0)
gal_origin = [origin_star[0], origin_star[1]] gal_origin = [origin_star[0], origin_star[1]]
gal_end = [origin_star[0] + starImg.array.shape[0] - 1, origin_star[1] + starImg.array.shape[1] - 1] gal_end = [origin_star[0] + starImg.array.shape[0] -
1, origin_star[1] + starImg.array.shape[1] - 1]
if gal_origin[1] < grating_split_pos_chip < gal_end[1]: if gal_origin[1] < grating_split_pos_chip < gal_end[1]:
subSlitPos = int(grating_split_pos_chip - gal_origin[1] + 1) subSlitPos = int(grating_split_pos_chip - gal_origin[1] + 1)
## part img disperse # part img disperse
subImg_p1 = starImg.array[:, 0:subSlitPos] subImg_p1 = starImg.array[:, 0:subSlitPos]
star_p1 = galsim.Image(subImg_p1) star_p1 = galsim.Image(subImg_p1)
origin_p1 = origin_star origin_p1 = origin_star
star_p1.setOrigin(0,0) star_p1.setOrigin(0, 0)
xcenter_p1 = min(x_nominal, grating_split_pos_chip - 1) - 0 xcenter_p1 = min(x_nominal, grating_split_pos_chip - 1) - 0
ycenter_p1 = y_nominal - 0 ycenter_p1 = y_nominal - 0
...@@ -382,11 +393,12 @@ class MockObject(object): ...@@ -382,11 +393,12 @@ class MockObject(object):
flat_cube=flat_cube) flat_cube=flat_cube)
# self.addSLStoChipImage(sdp=sdp_p1, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local) # self.addSLStoChipImage(sdp=sdp_p1, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear=self.addSLStoChipImageWithPSF(sdp=sdp_p1, chip=chip, pos_img_local = [xcenter_p1,ycenter_p1], pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp_p1, chip=chip, pos_img_local=[xcenter_p1, ycenter_p1],
psf_model=psf_model, bandNo = i+1, grating_split_pos=grating_split_pos, psf_model=psf_model, bandNo=i+1, grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img) local_wcs=chip_wcs_local, pos_img=pos_img)
subImg_p2 = starImg.array[:, subSlitPos + 1:starImg.array.shape[1]] subImg_p2 = starImg.array[:,
subSlitPos + 1:starImg.array.shape[1]]
star_p2 = galsim.Image(subImg_p2) star_p2 = galsim.Image(subImg_p2)
star_p2.setOrigin(0, 0) star_p2.setOrigin(0, 0)
origin_p2 = [origin_star[0], grating_split_pos_chip] origin_p2 = [origin_star[0], grating_split_pos_chip]
...@@ -402,9 +414,9 @@ class MockObject(object): ...@@ -402,9 +414,9 @@ class MockObject(object):
flat_cube=flat_cube) flat_cube=flat_cube)
# self.addSLStoChipImage(sdp=sdp_p2, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local) # self.addSLStoChipImage(sdp=sdp_p2, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear=self.addSLStoChipImageWithPSF(sdp=sdp_p2, chip=chip, pos_img_local=[xcenter_p2, ycenter_p2], pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp_p2, chip=chip, pos_img_local=[xcenter_p2, ycenter_p2],
psf_model=psf_model, bandNo=i + 1, grating_split_pos=grating_split_pos, psf_model=psf_model, bandNo=i + 1, grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img) local_wcs=chip_wcs_local, pos_img=pos_img)
del sdp_p1 del sdp_p1
del sdp_p2 del sdp_p2
...@@ -417,9 +429,9 @@ class MockObject(object): ...@@ -417,9 +429,9 @@ class MockObject(object):
isAlongY=0, isAlongY=0,
flat_cube=flat_cube) flat_cube=flat_cube)
# self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local) # self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear=self.addSLStoChipImageWithPSF(sdp=sdp, chip=chip, pos_img_local=[x_nominal, y_nominal], pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp, chip=chip, pos_img_local=[x_nominal, y_nominal],
psf_model=psf_model, bandNo=i + 1, grating_split_pos=grating_split_pos, psf_model=psf_model, bandNo=i + 1, grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img) local_wcs=chip_wcs_local, pos_img=pos_img)
del sdp del sdp
elif grating_split_pos_chip >= gal_end[1]: elif grating_split_pos_chip >= gal_end[1]:
sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0, sdp = SpecDisperser(orig_img=starImg, xcenter=x_nominal - 0,
...@@ -430,9 +442,9 @@ class MockObject(object): ...@@ -430,9 +442,9 @@ class MockObject(object):
isAlongY=0, isAlongY=0,
flat_cube=flat_cube) flat_cube=flat_cube)
# self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local) # self.addSLStoChipImage(sdp=sdp, chip=chip, xOrderSigPlus=xOrderSigPlus, local_wcs=chip_wcs_local)
pos_shear=self.addSLStoChipImageWithPSF(sdp=sdp, chip=chip, pos_img_local=[x_nominal, y_nominal], pos_shear = self.addSLStoChipImageWithPSF(sdp=sdp, chip=chip, pos_img_local=[x_nominal, y_nominal],
psf_model=psf_model, bandNo=i + 1, grating_split_pos=grating_split_pos, psf_model=psf_model, bandNo=i + 1, grating_split_pos=grating_split_pos,
local_wcs=chip_wcs_local, pos_img = pos_img) local_wcs=chip_wcs_local, pos_img=pos_img)
del sdp del sdp
# del psf # del psf
return 1, pos_shear return 1, pos_shear
...@@ -447,16 +459,15 @@ class MockObject(object): ...@@ -447,16 +459,15 @@ class MockObject(object):
snr_obj = img_flux / sig_obj snr_obj = img_flux / sig_obj
return snr_obj return snr_obj
def drawObj_PSF(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0, def drawObj_PSF(self, tel, pos_img, psf_model, bandpass_list, filt, chip, nphotons_tot=None, g1=0, g2=0,
exptime=150., fd_shear=None, chip_output=None): exptime=150., fd_shear=None, chip_output=None):
if nphotons_tot == None: if nphotons_tot == None:
nphotons_tot = self.getElectronFluxFilt(filt, tel, exptime) nphotons_tot = self.getElectronFluxFilt(filt, tel, exptime)
# print("nphotons_tot = ", nphotons_tot) # print("nphotons_tot = ", nphotons_tot)
try: try:
full = integrate_sed_bandpass(sed=self.sed, bandpass=filt.bandpass_full) full = integrate_sed_bandpass(
sed=self.sed, bandpass=filt.bandpass_full)
except Exception as e: except Exception as e:
print(e) print(e)
if self.logger: if self.logger:
...@@ -504,21 +515,21 @@ class MockObject(object): ...@@ -504,21 +515,21 @@ class MockObject(object):
folding_threshold=folding_threshold) folding_threshold=folding_threshold)
star_temp = psf.withFlux(nphotons) star_temp = psf.withFlux(nphotons)
if i==0: if i == 0:
star = star_temp star = star_temp
else: else:
star = star+star_temp star = star+star_temp
pixelScale = 0.074 pixelScale = 0.074
stamp = star.drawImage(wcs=chip_wcs_local, offset=offset) stamp = star.drawImage(wcs=chip_wcs_local, offset=offset)
#stamp = star.drawImage(nx=256, ny=256, scale=pixelScale) # stamp = star.drawImage(nx=256, ny=256, scale=pixelScale)
if np.sum(np.isnan(stamp.array)) > 0: if np.sum(np.isnan(stamp.array)) > 0:
return None return None
fn = chip_output.subdir + "/psfIDW" fn = chip_output.subdir + "/psfIDW"
os.makedirs(fn, exist_ok=True) os.makedirs(fn, exist_ok=True)
fn = fn + "/ccd_{:}".format(chip.chipID)+"_psf_"+str(self.param['id'])+".fits" fn = fn + "/ccd_{:}".format(chip.chipID) + \
"_psf_"+str(self.param['id'])+".fits"
if fn != None: if fn != None:
if os.path.exists(fn): if os.path.exists(fn):
os.remove(fn) os.remove(fn)
......
ObservationSim/MockObject/Quasar.py → observation_sim/mock_objects/Quasar.py
View file @ 38e2c452
...@@ -6,8 +6,8 @@ import astropy.constants as cons ...@@ -6,8 +6,8 @@ import astropy.constants as cons
from astropy.table import Table from astropy.table import Table
from scipy import interpolate from scipy import interpolate
from ObservationSim.MockObject.MockObject import MockObject from observation_sim.mock_objects.MockObject import MockObject
from ObservationSim.MockObject._util import integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, getABMAG from observation_sim.mock_objects._util import integrate_sed_bandpass, getNormFactorForSpecWithABMAG, getObservedSED, getABMAG
class Quasar(MockObject): class Quasar(MockObject):
......
ObservationSim/MockObject/SpecDisperser/SpecDisperser.py → observation_sim/mock_objects/SpecDisperser/SpecDisperser.py
View file @ 38e2c452
...@@ -97,7 +97,6 @@ class SpecDisperser(object): ...@@ -97,7 +97,6 @@ class SpecDisperser(object):
self.grating_conf_file = conf self.grating_conf_file = conf
self.ignoreBeam = ignoreBeam self.ignoreBeam = ignoreBeam
def compute_spec_orders(self): def compute_spec_orders(self):
all_orders = OrderedDict() all_orders = OrderedDict()
...@@ -121,16 +120,18 @@ class SpecDisperser(object): ...@@ -121,16 +120,18 @@ class SpecDisperser(object):
ytrace_beam, lam_beam = self.grating_conf.get_beam_trace(x=self.xcenter, y=self.ycenter, dx=(dx + xoff), ytrace_beam, lam_beam = self.grating_conf.get_beam_trace(x=self.xcenter, y=self.ycenter, dx=(dx + xoff),
beam=beam) beam=beam)
### Account for pixel centering of the trace # Account for pixel centering of the trace
yfrac_beam = ytrace_beam - floor(ytrace_beam+0.5) yfrac_beam = ytrace_beam - floor(ytrace_beam+0.5)
ysens = lam_beam * 0 ysens = lam_beam * 0
lam_index = argsort(lam_beam) lam_index = argsort(lam_beam)
conf_sens = self.grating_conf.sens[beam] conf_sens = self.grating_conf.sens[beam]
lam_intep = np.linspace(self.band_start, self.band_end, int((self.band_end - self.band_start) / 0.1)) lam_intep = np.linspace(self.band_start, self.band_end, int(
(self.band_end - self.band_start) / 0.1))
thri = interpolate.interp1d(conf_sens['WAVELENGTH'], conf_sens['SENSITIVITY']) thri = interpolate.interp1d(
conf_sens['WAVELENGTH'], conf_sens['SENSITIVITY'])
spci = interpolate.interp1d(self.spec['WAVELENGTH'], self.spec['FLUX']) spci = interpolate.interp1d(self.spec['WAVELENGTH'], self.spec['FLUX'])
beam_thr = thri(lam_intep) beam_thr = thri(lam_intep)
...@@ -138,7 +139,7 @@ class SpecDisperser(object): ...@@ -138,7 +139,7 @@ class SpecDisperser(object):
bean_thr_spec = beam_thr * spec_sample bean_thr_spec = beam_thr * spec_sample
###generate sensitivity file for aXe # generate sensitivity file for aXe
# ysensitivity = lam_beam * 0 # ysensitivity = lam_beam * 0
# #
# ysensitivity[lam_index] = interp.interp_conserve_c(lam_beam[lam_index], lam_intep, # ysensitivity[lam_index] = interp.interp_conserve_c(lam_beam[lam_index], lam_intep,
...@@ -155,7 +156,8 @@ class SpecDisperser(object): ...@@ -155,7 +156,8 @@ class SpecDisperser(object):
sensitivity_beam = ysens sensitivity_beam = ysens
len_spec_x = len(dx) len_spec_x = len(dx)
len_spec_y = int(abs(ceil(ytrace_beam[-1]) - floor(ytrace_beam[0])) + 1) len_spec_y = int(
abs(ceil(ytrace_beam[-1]) - floor(ytrace_beam[0])) + 1)
beam_sh = (self.img_sh[0] + len_spec_y, self.img_sh[1] + len_spec_x) beam_sh = (self.img_sh[0] + len_spec_y, self.img_sh[1] + len_spec_x)
modelf = zeros(product(beam_sh), dtype=float) modelf = zeros(product(beam_sh), dtype=float)
...@@ -169,7 +171,7 @@ class SpecDisperser(object): ...@@ -169,7 +171,7 @@ class SpecDisperser(object):
dypix = cast[int](np.floor(ytrace_beam - dyc[0] + x0[0] + 0.5)) dypix = cast[int](np.floor(ytrace_beam - dyc[0] + x0[0] + 0.5))
frac_ids = yfrac_beam<0 frac_ids = yfrac_beam < 0
dypix[frac_ids] = dypix[frac_ids] - 1 dypix[frac_ids] = dypix[frac_ids] - 1
yfrac_beam[frac_ids] = 1+yfrac_beam[frac_ids] yfrac_beam[frac_ids] = 1+yfrac_beam[frac_ids]
...@@ -199,7 +201,8 @@ class SpecDisperser(object): ...@@ -199,7 +201,8 @@ class SpecDisperser(object):
else: else:
beam_flat = zeros([len(modelf), len(self.flat_cube)]) beam_flat = zeros([len(modelf), len(self.flat_cube)])
sub_flat_cube = zeros([len(self.flat_cube),beam_sh[0], beam_sh[1]]) sub_flat_cube = zeros(
[len(self.flat_cube), beam_sh[0], beam_sh[1]])
sub_flat_cube[0] = sub_flat_cube[0] + 1. sub_flat_cube[0] = sub_flat_cube[0] + 1.
overlap_flag = 1 overlap_flag = 1
...@@ -210,23 +213,28 @@ class SpecDisperser(object): ...@@ -210,23 +213,28 @@ class SpecDisperser(object):
sub_x_e = originOut_x + beam_sh[1] - 1 sub_x_e = originOut_x + beam_sh[1] - 1
beam_x_s = max(sub_x_s, 0) beam_x_s = max(sub_x_s, 0)
if beam_x_s > self.flat_cube[0].shape[1] - 1: overlap_flag = 0 if beam_x_s > self.flat_cube[0].shape[1] - 1:
overlap_flag = 0
if overlap_flag == 1: if overlap_flag == 1:
beam_x_e = min(sub_x_e, self.flat_cube[0].shape[1] - 1) beam_x_e = min(sub_x_e, self.flat_cube[0].shape[1] - 1)
if beam_x_e < 0: overlap_flag = 0 if beam_x_e < 0:
overlap_flag = 0
if overlap_flag == 1: if overlap_flag == 1:
beam_y_s = max(sub_y_s, 0) beam_y_s = max(sub_y_s, 0)
if beam_y_s > self.flat_cube[0].shape[0] - 1: overlap_flag = 0 if beam_y_s > self.flat_cube[0].shape[0] - 1:
overlap_flag = 0
if overlap_flag == 1: if overlap_flag == 1:
beam_y_e = min(sub_y_e, self.flat_cube[0].shape[0] - 1) beam_y_e = min(sub_y_e, self.flat_cube[0].shape[0] - 1)
if beam_y_e < 0: overlap_flag = 0 if beam_y_e < 0:
overlap_flag = 0
if overlap_flag == 1: if overlap_flag == 1:
sub_flat_cube[:,beam_y_s-originOut_y:beam_y_e-originOut_y+1,beam_x_s-originOut_x:beam_x_e-originOut_x+1] = self.flat_cube[:,beam_y_s:beam_y_e+1,beam_x_s:beam_x_e+1] sub_flat_cube[:, beam_y_s-originOut_y:beam_y_e-originOut_y+1, beam_x_s-originOut_x:beam_x_e -
originOut_x+1] = self.flat_cube[:, beam_y_s:beam_y_e+1, beam_x_s:beam_x_e+1]
for i in arange(0, len(self.flat_cube), 1): for i in arange(0, len(self.flat_cube), 1):
beam_flat[:,i] = sub_flat_cube[i].flatten() beam_flat[:, i] = sub_flat_cube[i].flatten()
# beam_flat = zeros([len(modelf), len(self.flat_cube)]) # beam_flat = zeros([len(modelf), len(self.flat_cube)])
# flat_sh = self.flat_cube[0].shape # flat_sh = self.flat_cube[0].shape
# for i in arange(0, beam_sh[0], 1): # for i in arange(0, beam_sh[0], 1):
...@@ -243,7 +251,8 @@ class SpecDisperser(object): ...@@ -243,7 +251,8 @@ class SpecDisperser(object):
flat_index[nonz], yfrac_beam[nonz], flat_index[nonz], yfrac_beam[nonz],
sensitivity_beam[nonz], sensitivity_beam[nonz],
modelf, x0, modelf, x0,
array(self.img_sh, dtype=int64), array(self.img_sh,
dtype=int64),
array(beam_sh, dtype=int64), array(beam_sh, dtype=int64),
beam_flat, beam_flat,
lam_beam[lam_index][nonz]) lam_beam[lam_index][nonz])
...@@ -254,13 +263,15 @@ class SpecDisperser(object): ...@@ -254,13 +263,15 @@ class SpecDisperser(object):
if self.isAlongY == 1: if self.isAlongY == 1:
model, _, _ = rotate90(array_orig=model, isClockwise=0) model, _, _ = rotate90(array_orig=model, isClockwise=0)
return model, originOut_x, originOut_y, dxpix, dypix, lam_beam,ysens return model, originOut_x, originOut_y, dxpix, dypix, lam_beam, ysens
def writerSensitivityFile(self, conffile='', beam='', w=None, sens=None): def writerSensitivityFile(self, conffile='', beam='', w=None, sens=None):
orders = {'A': '1st', 'B': '0st', 'C': '2st', 'D': '-1st', 'E': '-2st'} orders = {'A': '1st', 'B': '0st', 'C': '2st', 'D': '-1st', 'E': '-2st'}
sens_file_name = conffile[0:-5] + '_sensitivity_' + orders[beam] + '.fits' sens_file_name = conffile[0:-5] + \
'_sensitivity_' + orders[beam] + '.fits'
if not os.path.exists(sens_file_name) == True: if not os.path.exists(sens_file_name) == True:
senstivity_out = Table(array([w, sens]).T, names=('WAVELENGTH', 'SENSITIVITY')) senstivity_out = Table(
array([w, sens]).T, names=('WAVELENGTH', 'SENSITIVITY'))
senstivity_out.write(sens_file_name, format='fits') senstivity_out.write(sens_file_name, format='fits')
...@@ -284,7 +295,7 @@ class aXeConf(): ...@@ -284,7 +295,7 @@ class aXeConf():
self.conf_file = conf_file self.conf_file = conf_file
self.count_beam_orders() self.count_beam_orders()
## Global XOFF/YOFF offsets # Global XOFF/YOFF offsets
if 'XOFF' in self.conf.keys(): if 'XOFF' in self.conf.keys():
self.xoff = np.float(self.conf['XOFF']) self.xoff = np.float(self.conf['XOFF'])
else: else:
...@@ -310,11 +321,11 @@ class aXeConf(): ...@@ -310,11 +321,11 @@ class aXeConf():
conf = OrderedDict() conf = OrderedDict()
lines = open(conf_file).readlines() lines = open(conf_file).readlines()
for line in lines: for line in lines:
## empty / commented lines # empty / commented lines
if (line.startswith('#')) | (line.strip() == '') | ('"' in line): if (line.startswith('#')) | (line.strip() == '') | ('"' in line):
continue continue
## split the line, taking out ; and # comments # split the line, taking out ; and # comments
spl = line.split(';')[0].split('#')[0].split() spl = line.split(';')[0].split('#')[0].split()
param = spl[0] param = spl[0]
if len(spl) > 2: if len(spl) > 2:
...@@ -360,13 +371,14 @@ class aXeConf(): ...@@ -360,13 +371,14 @@ class aXeConf():
self.beams.append(beam) self.beams.append(beam)
self.dxlam[beam] = np.arange(self.conf['BEAM{0}'.format(beam)].min(), self.dxlam[beam] = np.arange(self.conf['BEAM{0}'.format(beam)].min(),
self.conf['BEAM{0}'.format(beam)].max(), dtype=int) self.conf['BEAM{0}'.format(beam)].max(), dtype=int)
self.nx[beam] = int(self.dxlam[beam].max() - self.dxlam[beam].min()) + 1 self.nx[beam] = int(self.dxlam[beam].max() -
self.dxlam[beam].min()) + 1
self.sens[beam] = Table.read( self.sens[beam] = Table.read(
'{0}/{1}'.format(os.path.dirname(self.conf_file), self.conf['SENSITIVITY_{0}'.format(beam)])) '{0}/{1}'.format(os.path.dirname(self.conf_file), self.conf['SENSITIVITY_{0}'.format(beam)]))
# self.sens[beam].wave = np.cast[np.double](self.sens[beam]['WAVELENGTH']) # self.sens[beam].wave = np.cast[np.double](self.sens[beam]['WAVELENGTH'])
# self.sens[beam].sens = np.cast[np.double](self.sens[beam]['SENSITIVITY']) # self.sens[beam].sens = np.cast[np.double](self.sens[beam]['SENSITIVITY'])
### Need doubles for interpolating functions # Need doubles for interpolating functions
for col in self.sens[beam].colnames: for col in self.sens[beam].colnames:
data = np.cast[np.double](self.sens[beam][col]) data = np.cast[np.double](self.sens[beam][col])
self.sens[beam].remove_column(col) self.sens[beam].remove_column(col)
...@@ -394,22 +406,22 @@ class aXeConf(): ...@@ -394,22 +406,22 @@ class aXeConf():
Evaluated field-dependent coefficients Evaluated field-dependent coefficients
""" """
## number of coefficients for a given polynomial order # number of coefficients for a given polynomial order
## 1:1, 2:3, 3:6, 4:10, order:order*(order+1)/2 # 1:1, 2:3, 3:6, 4:10, order:order*(order+1)/2
if isinstance(coeffs, float): if isinstance(coeffs, float):
order = 1 order = 1
else: else:
order = int(-1 + np.sqrt(1 + 8 * len(coeffs))) // 2 order = int(-1 + np.sqrt(1 + 8 * len(coeffs))) // 2
## Build polynomial terms array # Build polynomial terms array
## $a = a_0+a_1x_i+a_2y_i+a_3x_i^2+a_4x_iy_i+a_5yi^2+$ ... # $a = a_0+a_1x_i+a_2y_i+a_3x_i^2+a_4x_iy_i+a_5yi^2+$ ...
xy = [] xy = []
for p in range(order): for p in range(order):
for px in range(p + 1): for px in range(p + 1):
# print 'x**%d y**%d' %(p-px, px) # print 'x**%d y**%d' %(p-px, px)
xy.append(xi ** (p - px) * yi ** (px)) xy.append(xi ** (p - px) * yi ** (px))
## Evaluate the polynomial, allowing for N-dimensional inputs # Evaluate the polynomial, allowing for N-dimensional inputs
a = np.sum((np.array(xy).T * coeffs).T, axis=0) a = np.sum((np.array(xy).T * coeffs).T, axis=0)
return a return a
...@@ -445,26 +457,27 @@ class aXeConf(): ...@@ -445,26 +457,27 @@ class aXeConf():
.. math:: dp = (u \sqrt{1+u^2} + \mathrm{arcsinh}\ u) / (4\cdot \mathrm{DYDX}[2]) .. math:: dp = (u \sqrt{1+u^2} + \mathrm{arcsinh}\ u) / (4\cdot \mathrm{DYDX}[2])
""" """
## dp is the arc length along the trace # dp is the arc length along the trace
## $\lambda = dldp_0 + dldp_1 dp + dldp_2 dp^2$ ... # $\lambda = dldp_0 + dldp_1 dp + dldp_2 dp^2$ ...
poly_order = len(dydx) - 1 poly_order = len(dydx) - 1
if (poly_order == 2): if (poly_order == 2):
if np.abs(np.unique(dydx[2])).max() == 0: if np.abs(np.unique(dydx[2])).max() == 0:
poly_order = 1 poly_order = 1
if poly_order == 0: ## dy=0 if poly_order == 0: # dy=0
dp = dx dp = dx
elif poly_order == 1: ## constant dy/dx elif poly_order == 1: # constant dy/dx
dp = np.sqrt(1 + dydx[1] ** 2) * (dx) dp = np.sqrt(1 + dydx[1] ** 2) * (dx)
elif poly_order == 2: ## quadratic trace elif poly_order == 2: # quadratic trace
u0 = dydx[1] + 2 * dydx[2] * (0) u0 = dydx[1] + 2 * dydx[2] * (0)
dp0 = (u0 * np.sqrt(1 + u0 ** 2) + np.arcsinh(u0)) / (4 * dydx[2]) dp0 = (u0 * np.sqrt(1 + u0 ** 2) + np.arcsinh(u0)) / (4 * dydx[2])
u = dydx[1] + 2 * dydx[2] * (dx) u = dydx[1] + 2 * dydx[2] * (dx)
dp = (u * np.sqrt(1 + u ** 2) + np.arcsinh(u)) / (4 * dydx[2]) - dp0 dp = (u * np.sqrt(1 + u ** 2) + np.arcsinh(u)) / \
(4 * dydx[2]) - dp0
else: else:
## high order shape, numerical integration along trace # high order shape, numerical integration along trace
## (this can be slow) # (this can be slow)
xmin = np.minimum((dx).min(), 0) xmin = np.minimum((dx).min(), 0)
xmax = np.maximum((dx).max(), 0) xmax = np.maximum((dx).max(), 0)
xfull = np.arange(xmin, xmax) xfull = np.arange(xmin, xmax)
...@@ -472,11 +485,12 @@ class aXeConf(): ...@@ -472,11 +485,12 @@ class aXeConf():
for i in range(1, poly_order): for i in range(1, poly_order):
dyfull += i * dydx[i] * (xfull - 0.5) ** (i - 1) dyfull += i * dydx[i] * (xfull - 0.5) ** (i - 1)
## Integrate from 0 to dx / -dx # Integrate from 0 to dx / -dx
dpfull = xfull * 0. dpfull = xfull * 0.
lt0 = xfull < 0 lt0 = xfull < 0
if lt0.sum() > 1: if lt0.sum() > 1:
dpfull[lt0] = np.cumsum(np.sqrt(1 + dyfull[lt0][::-1] ** 2))[::-1] dpfull[lt0] = np.cumsum(
np.sqrt(1 + dyfull[lt0][::-1] ** 2))[::-1]
dpfull[lt0] *= -1 dpfull[lt0] *= -1
# #
...@@ -520,10 +534,12 @@ class aXeConf(): ...@@ -520,10 +534,12 @@ class aXeConf():
NORDER = self.orders[beam] + 1 NORDER = self.orders[beam] + 1
xi, yi = x - self.xoff, y - self.yoff xi, yi = x - self.xoff, y - self.yoff
xoff_beam = self.field_dependent(xi, yi, self.conf['XOFF_{0}'.format(beam)]) xoff_beam = self.field_dependent(
yoff_beam = self.field_dependent(xi, yi, self.conf['YOFF_{0}'.format(beam)]) xi, yi, self.conf['XOFF_{0}'.format(beam)])
yoff_beam = self.field_dependent(
xi, yi, self.conf['YOFF_{0}'.format(beam)])
## y offset of trace (DYDX) # y offset of trace (DYDX)
dydx = np.zeros(NORDER) # 0 #+1.e-80 dydx = np.zeros(NORDER) # 0 #+1.e-80
dydx = [0] * NORDER dydx = [0] * NORDER
...@@ -538,7 +554,7 @@ class aXeConf(): ...@@ -538,7 +554,7 @@ class aXeConf():
for i in range(NORDER): for i in range(NORDER):
dy += dydx[i] * (dx - xoff_beam) ** i dy += dydx[i] * (dx - xoff_beam) ** i
## wavelength solution # wavelength solution
dldp = np.zeros(NORDER) dldp = np.zeros(NORDER)
dldp = [0] * NORDER dldp = [0] * NORDER
...@@ -556,7 +572,7 @@ class aXeConf(): ...@@ -556,7 +572,7 @@ class aXeConf():
# ## dp is the arc length along the trace # ## dp is the arc length along the trace
# ## $\lambda = dldp_0 + dldp_1 dp + dldp_2 dp^2$ ... # ## $\lambda = dldp_0 + dldp_1 dp + dldp_2 dp^2$ ...
# if self.conf['DYDX_ORDER_%s' %(beam)] == 0: ## dy=0 # if self.conf['DYDX_ORDER_%s' %(beam)] == 0: ## dy=0
# dp = dx-xoff_beam # dp = dx-xoff_beam
# elif self.conf['DYDX_ORDER_%s' %(beam)] == 1: ## constant dy/dx # elif self.conf['DYDX_ORDER_%s' %(beam)] == 1: ## constant dy/dx
# dp = np.sqrt(1+dydx[1]**2)*(dx-xoff_beam) # dp = np.sqrt(1+dydx[1]**2)*(dx-xoff_beam)
# elif self.conf['DYDX_ORDER_%s' %(beam)] == 2: ## quadratic trace # elif self.conf['DYDX_ORDER_%s' %(beam)] == 2: ## quadratic trace
...@@ -573,7 +589,7 @@ class aXeConf(): ...@@ -573,7 +589,7 @@ class aXeConf():
# dyfull = 0 # dyfull = 0
# for i in range(1, NORDER): # for i in range(1, NORDER):
# dyfull += i*dydx[i]*(xfull-0.5)**(i-1) # dyfull += i*dydx[i]*(xfull-0.5)**(i-1)
# #
# ## Integrate from 0 to dx / -dx # ## Integrate from 0 to dx / -dx
# dpfull = xfull*0. # dpfull = xfull*0.
# lt0 = xfull <= 0 # lt0 = xfull <= 0
...@@ -584,10 +600,10 @@ class aXeConf(): ...@@ -584,10 +600,10 @@ class aXeConf():
# gt0 = xfull >= 0 # gt0 = xfull >= 0
# if gt0.sum() > 0: # if gt0.sum() > 0:
# dpfull[gt0] = np.cumsum(np.sqrt(1+dyfull[gt0]**2)) # dpfull[gt0] = np.cumsum(np.sqrt(1+dyfull[gt0]**2))
# #
# dp = np.interp(dx-xoff_beam, xfull, dpfull) # dp = np.interp(dx-xoff_beam, xfull, dpfull)
## Evaluate dldp # Evaluate dldp
lam = dp * 0. lam = dp * 0.
for i in range(NORDER): for i in range(NORDER):
lam += dldp[i] * dp ** i lam += dldp[i] * dp ** i
...@@ -619,7 +635,8 @@ class aXeConf(): ...@@ -619,7 +635,8 @@ class aXeConf():
if 'XOFF_{0}'.format(beam) not in self.conf.keys(): if 'XOFF_{0}'.format(beam) not in self.conf.keys():
continue continue
xoff = self.field_dependent(x0, x1, self.conf['XOFF_{0}'.format(beam)]) xoff = self.field_dependent(
x0, x1, self.conf['XOFF_{0}'.format(beam)])
dy, lam = self.get_beam_trace(x0, x1, dx=dx, beam=beam) dy, lam = self.get_beam_trace(x0, x1, dx=dx, beam=beam)
xlim = self.conf['BEAM{0}'.format(beam)] xlim = self.conf['BEAM{0}'.format(beam)]
ok = (dx >= xlim[0]) & (dx <= xlim[1]) ok = (dx >= xlim[0]) & (dx <= xlim[1])
...@@ -627,7 +644,8 @@ class aXeConf(): ...@@ -627,7 +644,8 @@ class aXeConf():
alpha=0.5, edgecolor='None') alpha=0.5, edgecolor='None')
plt.text(np.median(dx[ok]), np.median(dy[ok]) + 1, beam, plt.text(np.median(dx[ok]), np.median(dy[ok]) + 1, beam,
ha='center', va='center', fontsize=14) ha='center', va='center', fontsize=14)
print('Beam {0}, lambda=({1:.1f} - {2:.1f})'.format(beam, lam[ok].min(), lam[ok].max())) print('Beam {0}, lambda=({1:.1f} - {2:.1f})'.format(beam,
lam[ok].min(), lam[ok].max()))
plt.grid() plt.grid()
plt.xlabel(r'$\Delta x$') plt.xlabel(r'$\Delta x$')
...@@ -650,7 +668,7 @@ class aXeConf(): ...@@ -650,7 +668,7 @@ class aXeConf():
# Returns # Returns
# ------- # -------
# conf : `~grizli.grismconf.aXeConf` # conf : `~grizli.grismconf.aXeConf`
# Configuration file object. Runs `conf.get_beams()` to read the # Configuration file object. Runs `conf.get_beams()` to read the
# sensitivity curves. # sensitivity curves.
# """ # """
# conf = aXeConf(conf_file) # conf = aXeConf(conf_file)
......
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