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Commit 4c36363e authored by Wei Chengliang's avatar Wei Chengliang
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Merge branch 'develop' of https://csst-tb.bao.ac.cn/code/csst-sims/csst_msc_sim into develop

parents 3351be22 3515cc73
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observation_sim/mock_objects/SpecDisperser/SpecDisperser.py
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...@@ -50,8 +50,21 @@ def rotate90(array_orig=None, xc=0, yc=0, isClockwise=0): ...@@ -50,8 +50,21 @@ def rotate90(array_orig=None, xc=0, yc=0, isClockwise=0):
class SpecDisperser(object): class SpecDisperser(object):
def __init__(self, orig_img=None, xcenter=0, ycenter=0, origin=[100, 100], tar_spec=None, band_start=6200, def __init__(
band_end=10000, isAlongY=0, conf='../param/CONF/csst.conf', gid=0, flat_cube=None, ignoreBeam=[]): self,
orig_img=None,
xcenter=0,
ycenter=0,
origin=[100, 100],
tar_spec=None,
band_start=6200,
band_end=10000,
isAlongY=0,
conf="../param/CONF/csst.conf",
gid=0,
flat_cube=None,
ignoreBeam=[],
):
""" """
orig_img: normal image,galsim image orig_img: normal image,galsim image
xcenter, ycenter: the center of galaxy in orig_img xcenter, ycenter: the center of galaxy in orig_img
...@@ -66,23 +79,21 @@ class SpecDisperser(object): ...@@ -66,23 +79,21 @@ class SpecDisperser(object):
# self.img_y = orig_img.shape[0] # self.img_y = orig_img.shape[0]
# 5 orders, A, B , # 5 orders, A, B ,
orderName=["A","B","C","D","E"] orderName = ["A", "B", "C", "D", "E"]
self.orig_img_orders = OrderedDict() self.orig_img_orders = OrderedDict()
if isinstance(orig_img, list): if isinstance(orig_img, list):
orig_img_list = orig_img orig_img_list = orig_img
list_len = len(orig_img_list) list_len = len(orig_img_list)
if list_len < 5: if list_len < 5:
for i in np.arange(5-list_len): for i in np.arange(5 - list_len):
orig_img_list.append(orig_img_list[list_len-1]) orig_img_list.append(orig_img_list[list_len - 1])
for i, k in enumerate(orig_img_list): for i, k in enumerate(orig_img_list):
self.orig_img_orders[orderName[i]] = k self.orig_img_orders[orderName[i]] = k
if isinstance(orig_img, galsim.Image): if isinstance(orig_img, galsim.Image):
for i in np.arange(5): for i in np.arange(5):
self.orig_img_orders[orderName[i]] = orig_img self.orig_img_orders[orderName[i]] = orig_img
orig_img_one = self.orig_img_orders["A"] orig_img_one = self.orig_img_orders["A"]
self.thumb_img = np.abs(orig_img_one.array) self.thumb_img = np.abs(orig_img_one.array)
...@@ -99,8 +110,12 @@ class SpecDisperser(object): ...@@ -99,8 +110,12 @@ class SpecDisperser(object):
self.flat_cube = flat_cube self.flat_cube = flat_cube
if self.isAlongY == 1: if self.isAlongY == 1:
for order in orderName: for order in orderName:
self.orig_img_orders[order], self.thumb_x, self.thumb_y = rotate90(array_orig=self.orig_img_orders[order], xc=orig_img_one.center.x, self.orig_img_orders[order], self.thumb_x, self.thumb_y = rotate90(
yc=orig_img_one.center.y, isClockwise=1) array_orig=self.orig_img_orders[order],
xc=orig_img_one.center.x,
yc=orig_img_one.center.y,
isClockwise=1,
)
# self.thumb_img, self.thumb_x, self.thumb_y = rotate90(array_orig=self.thumb_img, xc=orig_img_one.center.x, # self.thumb_img, self.thumb_x, self.thumb_y = rotate90(array_orig=self.thumb_img, xc=orig_img_one.center.x,
# yc=orig_img_one.center.y, isClockwise=1) # yc=orig_img_one.center.y, isClockwise=1)
...@@ -139,6 +154,7 @@ class SpecDisperser(object): ...@@ -139,6 +154,7 @@ class SpecDisperser(object):
from .disperse_c import interp from .disperse_c import interp
from .disperse_c import disperse from .disperse_c import disperse
# from MockObject.disperse_c import disperse # from MockObject.disperse_c import disperse
self.thumb_img = np.abs(self.orig_img_orders[beam].array) self.thumb_img = np.abs(self.orig_img_orders[beam].array)
self.thumb_x = self.orig_img_orders[beam].center.x self.thumb_x = self.orig_img_orders[beam].center.x
...@@ -146,22 +162,21 @@ class SpecDisperser(object): ...@@ -146,22 +162,21 @@ class SpecDisperser(object):
self.img_sh = self.orig_img_orders[beam].array.shape self.img_sh = self.orig_img_orders[beam].array.shape
dx = self.grating_conf.dxlam[beam] dx = self.grating_conf.dxlam[beam]
xoff = 0 xoff = 0
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(
beam=beam) x=self.xcenter, y=self.ycenter, dx=(dx + xoff), 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( lam_intep = np.linspace(self.band_start, self.band_end, int((self.band_end - self.band_start) / 0.1))
(self.band_end - self.band_start) / 0.1))
thri = interpolate.interp1d( thri = interpolate.interp1d(conf_sens["WAVELENGTH"], conf_sens["SENSITIVITY"])
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)
spec_sample = spci(lam_intep) spec_sample = spci(lam_intep)
...@@ -179,14 +194,14 @@ class SpecDisperser(object): ...@@ -179,14 +194,14 @@ class SpecDisperser(object):
# #
# self.writerSensitivityFile(conffile = self.grating_conf_file, beam = beam, w = lam_beam[lam_index], sens = ysensitivity[lam_index]) # self.writerSensitivityFile(conffile = self.grating_conf_file, beam = beam, w = lam_beam[lam_index], sens = ysensitivity[lam_index])
ysens[lam_index] = interp.interp_conserve_c(lam_beam[lam_index], lam_intep, bean_thr_spec, integrate=1, left=0, ysens[lam_index] = interp.interp_conserve_c(
right=0) lam_beam[lam_index], lam_intep, bean_thr_spec, integrate=1, left=0, right=0
)
sensitivity_beam = ysens sensitivity_beam = ysens
len_spec_x = len(dx) len_spec_x = len(dx)
len_spec_y = int( len_spec_y = int(abs(ceil(ytrace_beam[-1]) - floor(ytrace_beam[0])) + 1)
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)
...@@ -196,7 +211,7 @@ class SpecDisperser(object): ...@@ -196,7 +211,7 @@ class SpecDisperser(object):
dxpix = dx - dx[0] + x0[1] dxpix = dx - dx[0] + x0[1]
dyc = cast[int](np.floor(ytrace_beam+0.5)) dyc = cast[int](np.floor(ytrace_beam + 0.5))
# 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))
dypix = dyc - dyc[0] + x0[0] dypix = dyc - dyc[0] + x0[0]
...@@ -204,7 +219,7 @@ class SpecDisperser(object): ...@@ -204,7 +219,7 @@ class SpecDisperser(object):
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]
flat_index = idx[dypix, dxpix] flat_index = idx[dypix, dxpix]
...@@ -231,9 +246,8 @@ class SpecDisperser(object): ...@@ -231,9 +246,8 @@ 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( sub_flat_cube = zeros([len(self.flat_cube), beam_sh[0], beam_sh[1]])
[len(self.flat_cube), beam_sh[0], beam_sh[1]]) sub_flat_cube[0] = sub_flat_cube[0] + 1.0
sub_flat_cube[0] = sub_flat_cube[0] + 1.
overlap_flag = 1 overlap_flag = 1
...@@ -260,33 +274,38 @@ class SpecDisperser(object): ...@@ -260,33 +274,38 @@ class SpecDisperser(object):
overlap_flag = 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 - sub_flat_cube[
originOut_x+1] = self.flat_cube[:, beam_y_s:beam_y_e+1, beam_x_s:beam_x_e+1] :,
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):
# for j in arange(0, beam_sh[1], 1): # for j in arange(0, beam_sh[1], 1):
# k = i * beam_sh[1] + j # k = i * beam_sh[1] + j
# if originOut_y + i >= flat_sh[0] or originOut_y + i < 0 or originOut_x + j>= flat_sh[1] or originOut_x+j < 0: # if originOut_y + i >= flat_sh[0] or originOut_y + i < 0 or originOut_x + j>= flat_sh[1] or originOut_x+j < 0:
# temp_bf = np.zeros_like(self.flat_cube[:, 0, 0]) # temp_bf = np.zeros_like(self.flat_cube[:, 0, 0])
# temp_bf[0] = 1.0 # temp_bf[0] = 1.0
# beam_flat[k] = temp_bf # beam_flat[k] = temp_bf
# else: # else:
# beam_flat[k] = self.flat_cube[:, originOut_y + i, originOut_x + j] # beam_flat[k] = self.flat_cube[:, originOut_y + i, originOut_x + j]
status = disperse.disperse_grism_object(self.thumb_img.astype(np.float32), status = disperse.disperse_grism_object(
flat_index[nonz], self.thumb_img.astype(np.float32),
yfrac_beam[nonz], flat_index[nonz],
sensitivity_beam[nonz], yfrac_beam[nonz],
modelf, x0, sensitivity_beam[nonz],
array(self.img_sh, modelf,
dtype=int64), x0,
array(beam_sh, dtype=int64), array(self.img_sh, dtype=int64),
beam_flat, array(beam_sh, dtype=int64),
lam_beam[lam_index][nonz]) beam_flat,
lam_beam[lam_index][nonz],
)
model = modelf.reshape(beam_sh) model = modelf.reshape(beam_sh)
# n1 = np.sum(np.isinf(model)) # n1 = np.sum(np.isinf(model))
...@@ -296,27 +315,25 @@ class SpecDisperser(object): ...@@ -296,27 +315,25 @@ class SpecDisperser(object):
# if n1>0 or n2 > 0: # if n1>0 or n2 > 0:
# print("DEBUG: SpecDisperser, inf:%d, nan:%d--------%d,%d"%(n1, n2, n3, n4)) # print("DEBUG: SpecDisperser, inf:%d, nan:%d--------%d,%d"%(n1, n2, n3, n4))
# print(dypix) # print(dypix)
# n1 = np.sum(np.isinf(self.thumb_img.astype(np.float32))) # n1 = np.sum(np.isinf(self.thumb_img.astype(np.float32)))
# n2 = np.sum(np.isnan(self.thumb_img.astype(np.float32))) # n2 = np.sum(np.isnan(self.thumb_img.astype(np.float32)))
# n3 = np.sum(np.isinf(yfrac_beam)) # n3 = np.sum(np.isinf(yfrac_beam))
# n4 = np.sum(np.isnan(yfrac_beam)) # n4 = np.sum(np.isnan(yfrac_beam))
# n5 = np.sum(np.isinf(sensitivity_beam)) # n5 = np.sum(np.isinf(sensitivity_beam))
# n6 = np.sum(np.isnan(sensitivity_beam)) # n6 = np.sum(np.isnan(sensitivity_beam))
# print("DEBUG: SpecDisperser, innput ---inf:%d, nan:%d, yfrac_beam:%d/%d, sensitivity_beam:%d/%d"%(n1, n2, n3, n4, n5, n6)) # print("DEBUG: SpecDisperser, innput ---inf:%d, nan:%d, yfrac_beam:%d/%d, sensitivity_beam:%d/%d"%(n1, n2, n3, n4, n5, n6))
self.beam_flux[beam] = sum(modelf) self.beam_flux[beam] = sum(modelf)
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] + \ sens_file_name = conffile[0:-5] + "_sensitivity_" + orders[beam] + ".fits"
'_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( senstivity_out = Table(array([w, sens]).T, names=("WAVELENGTH", "SENSITIVITY"))
array([w, sens]).T, names=('WAVELENGTH', 'SENSITIVITY')) senstivity_out.write(sens_file_name, format="fits")
senstivity_out.write(sens_file_name, format='fits')
""" """
...@@ -324,8 +341,8 @@ Demonstrate aXe trace polynomials. ...@@ -324,8 +341,8 @@ Demonstrate aXe trace polynomials.
""" """
class aXeConf(): class aXeConf:
def __init__(self, conf_file='WFC3.IR.G141.V2.5.conf'): def __init__(self, conf_file="WFC3.IR.G141.V2.5.conf"):
"""Read an aXe-compatible configuration file """Read an aXe-compatible configuration file
Parameters Parameters
...@@ -340,17 +357,17 @@ class aXeConf(): ...@@ -340,17 +357,17 @@ class aXeConf():
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:
self.xoff = 0. self.xoff = 0.0
if 'YOFF' in self.conf.keys(): if "YOFF" in self.conf.keys():
self.yoff = np.float(self.conf['YOFF']) self.yoff = np.float(self.conf["YOFF"])
else: else:
self.yoff = 0. self.yoff = 0.0
def read_conf_file(self, conf_file='WFC3.IR.G141.V2.5.conf'): def read_conf_file(self, conf_file="WFC3.IR.G141.V2.5.conf"):
"""Read an aXe config file, convert floats and arrays """Read an aXe config file, convert floats and arrays
Parameters Parameters
...@@ -366,11 +383,11 @@ class aXeConf(): ...@@ -366,11 +383,11 @@ class aXeConf():
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:
value = np.cast[float](spl[1:]) value = np.cast[float](spl[1:])
...@@ -385,22 +402,20 @@ class aXeConf(): ...@@ -385,22 +402,20 @@ class aXeConf():
return conf return conf
def count_beam_orders(self): def count_beam_orders(self):
"""Get the maximum polynomial order in DYDX or DLDP for each beam """Get the maximum polynomial order in DYDX or DLDP for each beam"""
"""
self.orders = {} self.orders = {}
for beam in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J']: for beam in ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J"]:
order = 0 order = 0
while 'DYDX_{0:s}_{1:d}'.format(beam, order) in self.conf.keys(): while "DYDX_{0:s}_{1:d}".format(beam, order) in self.conf.keys():
order += 1 order += 1
while 'DLDP_{0:s}_{1:d}'.format(beam, order) in self.conf.keys(): while "DLDP_{0:s}_{1:d}".format(beam, order) in self.conf.keys():
order += 1 order += 1
self.orders[beam] = order - 1 self.orders[beam] = order - 1
def get_beams(self): def get_beams(self):
"""Get beam parameters and read sensitivity curves """Get beam parameters and read sensitivity curves"""
"""
import os import os
from collections import OrderedDict from collections import OrderedDict
from astropy.table import Table, Column from astropy.table import Table, Column
...@@ -413,12 +428,13 @@ class aXeConf(): ...@@ -413,12 +428,13 @@ class aXeConf():
for beam in self.orders: for beam in self.orders:
if self.orders[beam] > 0: if self.orders[beam] > 0:
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)].max(), dtype=int) self.conf["BEAM{0}".format(beam)].min(), 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'])
...@@ -505,7 +521,7 @@ class aXeConf(): ...@@ -505,7 +521,7 @@ class aXeConf():
# $\lambda = dldp_0 + dldp_1 dp + dldp_2 dp^2$ ... # $\lambda = dldp_0 + dldp_1 dp + dldp_2 dp^2$ ...
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
...@@ -515,10 +531,9 @@ class aXeConf(): ...@@ -515,10 +531,9 @@ class aXeConf():
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)) / \ dp = (u * np.sqrt(1 + u**2) + np.arcsinh(u)) / (4 * dydx[2]) - dp0
(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)
...@@ -530,11 +545,10 @@ class aXeConf(): ...@@ -530,11 +545,10 @@ class aXeConf():
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 * 0.0
lt0 = xfull < 0 lt0 = xfull < 0
if lt0.sum() > 1: if lt0.sum() > 1:
dpfull[lt0] = np.cumsum( dpfull[lt0] = np.cumsum(np.sqrt(1 + dyfull[lt0][::-1] ** 2))[::-1]
np.sqrt(1 + dyfull[lt0][::-1] ** 2))[::-1]
dpfull[lt0] *= -1 dpfull[lt0] *= -1
# #
...@@ -548,7 +562,7 @@ class aXeConf(): ...@@ -548,7 +562,7 @@ class aXeConf():
return dp return dp
def get_beam_trace(self, x=507, y=507, dx=0., beam='A'): def get_beam_trace(self, x=507, y=507, dx=0.0, beam="A"):
"""Get an aXe beam trace for an input reference pixel and list of output x pixels `dx` """Get an aXe beam trace for an input reference pixel and list of output x pixels `dx`
Parameters Parameters
...@@ -578,18 +592,16 @@ class aXeConf(): ...@@ -578,18 +592,16 @@ 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( xoff_beam = self.field_dependent(xi, yi, self.conf["XOFF_{0}".format(beam)])
xi, yi, self.conf['XOFF_{0}'.format(beam)]) yoff_beam = self.field_dependent(xi, yi, self.conf["YOFF_{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
for i in range(NORDER): for i in range(NORDER):
if 'DYDX_{0:s}_{1:d}'.format(beam, i) in self.conf.keys(): if "DYDX_{0:s}_{1:d}".format(beam, i) in self.conf.keys():
coeffs = self.conf['DYDX_{0:s}_{1:d}'.format(beam, i)] coeffs = self.conf["DYDX_{0:s}_{1:d}".format(beam, i)]
dydx[i] = self.field_dependent(xi, yi, coeffs) dydx[i] = self.field_dependent(xi, yi, coeffs)
# $dy = dydx_0+dydx_1 dx+dydx_2 dx^2+$ ... # $dy = dydx_0+dydx_1 dx+dydx_2 dx^2+$ ...
...@@ -603,14 +615,20 @@ class aXeConf(): ...@@ -603,14 +615,20 @@ class aXeConf():
dldp = [0] * NORDER dldp = [0] * NORDER
for i in range(NORDER): for i in range(NORDER):
if 'DLDP_{0:s}_{1:d}'.format(beam, i) in self.conf.keys(): if "DLDP_{0:s}_{1:d}".format(beam, i) in self.conf.keys():
coeffs = self.conf['DLDP_{0:s}_{1:d}'.format(beam, i)] coeffs = self.conf["DLDP_{0:s}_{1:d}".format(beam, i)]
dldp[i] = self.field_dependent(xi, yi, coeffs) dldp[i] = self.field_dependent(xi, yi, coeffs)
self.eval_input = {'x': x, 'y': y, 'beam': beam, 'dx': dx} self.eval_input = {"x": x, "y": y, "beam": beam, "dx": dx}
self.eval_output = {'xi': xi, 'yi': yi, 'dldp': dldp, 'dydx': dydx, self.eval_output = {
'xoff_beam': xoff_beam, 'yoff_beam': yoff_beam, "xi": xi,
'dy': dy} "yi": yi,
"dldp": dldp,
"dydx": dydx,
"xoff_beam": xoff_beam,
"yoff_beam": yoff_beam,
"dy": dy,
}
dp = self.evaluate_dp(dx - xoff_beam, dydx) dp = self.evaluate_dp(dx - xoff_beam, dydx)
# ## dp is the arc length along the trace # ## dp is the arc length along the trace
...@@ -648,13 +666,13 @@ class aXeConf(): ...@@ -648,13 +666,13 @@ class aXeConf():
# 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 * 0.0
for i in range(NORDER): for i in range(NORDER):
lam += dldp[i] * dp ** i lam += dldp[i] * dp**i
return dy, lam return dy, lam
def show_beams(self, beams=['E', 'D', 'C', 'B', 'A']): def show_beams(self, beams=["E", "D", "C", "B", "A"]):
""" """
Make a demo plot of the beams of a given configuration file Make a demo plot of the beams of a given configuration file
""" """
...@@ -663,45 +681,42 @@ class aXeConf(): ...@@ -663,45 +681,42 @@ class aXeConf():
x0, x1 = 507, 507 x0, x1 = 507, 507
dx = np.arange(-800, 1200) dx = np.arange(-800, 1200)
if 'WFC3.UV' in self.conf_file: if "WFC3.UV" in self.conf_file:
x0, x1 = 2073, 250 x0, x1 = 2073, 250
dx = np.arange(-1200, 1200) dx = np.arange(-1200, 1200)
if 'G800L' in self.conf_file: if "G800L" in self.conf_file:
x0, x1 = 2124, 1024 x0, x1 = 2124, 1024
dx = np.arange(-1200, 1200) dx = np.arange(-1200, 1200)
s = 200 # marker size s = 200 # marker size
fig = plt.figure(figsize=[10, 3]) fig = plt.figure(figsize=[10, 3])
plt.scatter(0, 0, marker='s', s=s, color='black', edgecolor='0.8', plt.scatter(0, 0, marker="s", s=s, color="black", edgecolor="0.8", label="Direct")
label='Direct')
for beam in beams: for beam in beams:
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( xoff = self.field_dependent(x0, x1, self.conf["XOFF_{0}".format(beam)])
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])
plt.scatter(dx[ok] + xoff, dy[ok], c=lam[ok] / 1.e4, marker='s', s=s, plt.scatter(dx[ok] + xoff, dy[ok], c=lam[ok] / 1.0e4, marker="s", s=s, alpha=0.5, edgecolor="None")
alpha=0.5, edgecolor='None') plt.text(np.median(dx[ok]), np.median(dy[ok]) + 1, beam, ha="center", va="center", fontsize=14)
plt.text(np.median(dx[ok]), np.median(dy[ok]) + 1, beam, print("Beam {0}, lambda=({1:.1f} - {2:.1f})".format(beam, lam[ok].min(), lam[ok].max()))
ha='center', va='center', fontsize=14)
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"$\Delta x$")
plt.ylabel(r'$\Delta y$') plt.ylabel(r"$\Delta y$")
cb = plt.colorbar(pad=0.01, fraction=0.05) cb = plt.colorbar(pad=0.01, fraction=0.05)
cb.set_label(r'$\lambda\,(\mu\mathrm{m})$') cb.set_label(r"$\lambda\,(\mu\mathrm{m})$")
plt.title(self.conf_file) plt.title(self.conf_file)
plt.tight_layout() plt.tight_layout()
plt.savefig('{0}.pdf'.format(self.conf_file)) plt.savefig("{0}.pdf".format(self.conf_file))
# def load_grism_config(conf_file): # def load_grism_config(conf_file):
# """Load parameters from an aXe configuration file # """Load parameters from an aXe configuration file
# Parameters # Parameters
......
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