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Commit d8118d46 authored by Fang Yuedong's avatar Fang Yuedong
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Merge branch 'revert-914004c1' into 'release_v3.0' 

Revert "Merge branch 'milky_way_extinction' into 'release_v3.0'"

See merge request !29
parents 914004c1 64eb7956
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observation_sim/mock_objects/__init__.py
View file @ d8118d46
...@@ -5,4 +5,3 @@ from .Quasar import Quasar ...@@ -5,4 +5,3 @@ from .Quasar import Quasar
from .Star import Star from .Star import Star
from .Stamp import Stamp from .Stamp import Stamp
from .FlatLED import FlatLED from .FlatLED import FlatLED
from .ExtinctionMW import ExtinctionMW
observation_sim/psf/PSFGauss.py
View file @ d8118d46
...@@ -17,7 +17,7 @@ class PSFGauss(PSFModel): ...@@ -17,7 +17,7 @@ class PSFGauss(PSFModel):
self.fwhm = self.fwhmGauss(r=psfRa) self.fwhm = self.fwhmGauss(r=psfRa)
self.sigGauss = psfRa # 80% light radius self.sigGauss = psfRa # 80% light radius
self.sigSpin = sigSpin self.sigSpin = sigSpin
self.psf = galsim.Gaussian(flux=1.0, fwhm=self.fwhm) self.psf = galsim.Gaussian(flux=1.0, fwhm=fwhm)
def perfGauss(self, r, sig): def perfGauss(self, r, sig):
""" """
......
observation_sim/psf/PSFInterpSLS.py
View file @ d8118d46
...@@ -20,10 +20,8 @@ import os ...@@ -20,10 +20,8 @@ import os
from astropy.io import fits from astropy.io import fits
from astropy.modeling.models import Gaussian2D from astropy.modeling.models import Gaussian2D
from scipy import signal, interpolate from scipy import signal
import datetime
import gc
from jax import numpy as jnp
LOG_DEBUG = False # ***# LOG_DEBUG = False # ***#
NPSF = 900 # ***# 30*30 NPSF = 900 # ***# 30*30
...@@ -435,16 +433,7 @@ class PSFInterpSLS(PSFModel): ...@@ -435,16 +433,7 @@ class PSFInterpSLS(PSFModel):
# PSF_int_trans[ids_szero] = 0 # PSF_int_trans[ids_szero] = 0
# print(PSF_int_trans[ids_szero].shape[0],PSF_int_trans.shape) # print(PSF_int_trans[ids_szero].shape[0],PSF_int_trans.shape)
PSF_int_trans = PSF_int_trans/np.sum(PSF_int_trans) PSF_int_trans = PSF_int_trans/np.sum(PSF_int_trans)
###DEBGU
ids_szero = PSF_int_trans<0
n01 = PSF_int_trans[ids_szero].shape[0]
n1 = np.sum(np.isinf(PSF_int_trans))
n2 = np.sum(np.isnan(PSF_int_trans))
if n1>0 or n2>0:
print("DEBUG: PSFInterpSLS, inf:%d, nan:%d, 0 num:%d"%(n1, n2, n01))
####
# from astropy.io import fits # from astropy.io import fits
# fits.writeto(str(bandNo) + '_' + g_order+ '_psf_o.fits', PSF_int_trans) # fits.writeto(str(bandNo) + '_' + g_order+ '_psf_o.fits', PSF_int_trans)
...@@ -490,215 +479,6 @@ class PSFInterpSLS(PSFModel): ...@@ -490,215 +479,6 @@ class PSFInterpSLS(PSFModel):
return PSF_int_trans, PSF_int return PSF_int_trans, PSF_int
def get_PSF_AND_convolve_withsubImg(self, chip, cutImg=None, pos_img_local=[1000, 1000], bandNo=1, g_order='A', grating_split_pos=3685):
"""
Get the PSF at a given image position
Parameters:
chip: A 'Chip' object representing the chip we want to extract PSF from.
pos_img: A 'galsim.Position' object representing the image position.
bandpass: A 'galsim.Bandpass' object representing the wavelength range.
pixSize: The pixels size of psf matrix
findNeighMode: 'treeFind' or 'hoclistFind'
Returns:
PSF: A 'galsim.GSObject'.
"""
order_IDs = {'A': '1', 'B': '0', 'C': '0', 'D': '0', 'E': '0'}
contam_order_sigma = {'C': 0.28032344707964174,
'D': 0.39900182912061344, 'E': 1.1988309797685412} # arcsec
x_start = chip.x_cen/chip.pix_size - chip.npix_x / 2.
y_start = chip.y_cen/chip.pix_size - chip.npix_y / 2.
# print(pos_img.x - x_start)
# pos_img_x = pos_img_local[0] + x_start
# pos_img_y = pos_img_local[1] + y_start
# pos_img = galsim.PositionD(pos_img_x, pos_img_y)
# centerPos_local = cutImg.ncol/2.
if pos_img_local[0] < grating_split_pos:
psf_data = self.grating1_data
else:
psf_data = self.grating2_data
grating_order = order_IDs[g_order]
# if grating_order in ['-2','-1','2']:
# grating_order = '1'
# if grating_order in ['0', '1']:
psf_order = psf_data['order'+grating_order]
psf_order_b = psf_order['band'+str(bandNo)]
psf_b_dat = psf_order_b['band_data']
# pos_p = psf_b_dat[1].data
pos_p = psf_b_dat[1].data/chip.pix_size - np.array([y_start, x_start])
pc_coeff = psf_b_dat[2].data
pcs = psf_b_dat[0].data
npc = 10
m_size = int(pcs.shape[0]**0.5)
sumImg = np.sum(cutImg.array)
tmp_img = cutImg*0
for j in np.arange(npc):
X_ = jnp.hstack((pos_p[:,1].flatten()[:, None], pos_p[:,0].flatten()[:, None]),dtype=np.float32)
Z_ = (pc_coeff[j].astype(np.float32)).flatten()
# print(pc_coeff[j].shape[0], pos_p[:,1].shape[0], pos_p[:,0].shape[0])
cx_len = int(chip.npix_x)
cy_len = int(chip.npix_y)
n_x = jnp.arange(0, cx_len, 1, dtype = int)
n_y = jnp.arange(0, cy_len, 1, dtype = int)
M, N = jnp.meshgrid(n_x, n_y)
# t1=datetime.datetime.now()
# U = interpolate.griddata(X_, Z_, (M[0:cy_len, 0:cx_len],N[0:cy_len, 0:cx_len]),
# method='nearest',fill_value=1.0)
b_img = galsim.Image(cx_len, cy_len)
b_img.setOrigin(0,0)
bounds = cutImg.bounds & b_img.bounds
if bounds.area() == 0:
continue
# ys = cutImg.ymin
# if ys < 0:
# ys = 0
# ye = cutImg.ymin+cutImg.nrow
# if ye >= cy_len-1:
# ye = cy_len-1
# if ye - ys <=0:
# continue
# xs = cutImg.xmin
# if xs < 0:
# xs = 0
# xe = cutImg.xmin+cutImg.ncol
# if xe >= cx_len-1:
# xe = cx_len-1
# if xe - xs <=0:
# continue
ys = bounds.ymin
ye = bounds.ymax+1
xs = bounds.xmin
xe = bounds.xmax+1
U = interpolate.griddata(X_, Z_, (M[ys:ye, xs:xe],N[ys:ye, xs:xe]),
method='nearest',fill_value=1.0)
# t2=datetime.datetime.now()
# print("time interpolate:", t2-t1)
# if U.shape != cutImg.array.shape:
# print('DEBUG:SHAPE',cutImg.ncol,cutImg.nrow,cutImg.xmin, cutImg.ymin)
# continue
img_tmp = cutImg
img_tmp[bounds] = img_tmp[bounds]*U
psf = pcs[:, j].reshape(m_size, m_size)
tmp_img = tmp_img + signal.fftconvolve(img_tmp.array, psf, mode='same', axes=None)
# t3=datetime.datetime.now()
# print("time convole:", t3-t2)
del U
del img_tmp
if np.sum(tmp_img.array)==0:
tmp_img = cutImg
else:
tmp_img = tmp_img/np.sum(tmp_img.array)*sumImg
return tmp_img
def convolveFullImgWithPCAPSF(self, chip, folding_threshold=5.e-3):
keys_L1= chip_utils.getChipSLSGratingID(chip.chipID)
# keys_L2 = ['order-2','order-1','order0','order1','order2']
keys_L2 = ['order0','order1']
keys_L3 = ['w1','w2','w3','w4']
npca = 10
x_start = chip.x_cen/chip.pix_size - chip.npix_x / 2.
y_start = chip.y_cen/chip.pix_size - chip.npix_y / 2.
for i,gt in enumerate(keys_L1):
psfCo = self.grating1_data
if i > 0:
psfCo = self.grating2_data
for od in keys_L2:
psfCo_L2 = psfCo['order1']
if od in ['order-2','order-1','order0','order2']:
psfCo_L2 = psfCo['order0']
for w in keys_L3:
img = chip.img_stack[gt][od][w]
pcs = psfCo_L2['band'+w[1]]['band_data'][0].data
pos_p = psfCo_L2['band'+w[1]]['band_data'][1].data/chip.pix_size - np.array([y_start, x_start])
pc_coeff = psfCo_L2['band'+w[1]]['band_data'][2].data
# print("DEBUG-----------",np.max(pos_p[:,1]),np.min(pos_p[:,1]), np.max(pos_p[:,0]),np.min(pos_p[:,0]))
sum_img = np.sum(img.array)
# coeff_mat = np.zeros([npca, chip.npix_y, chip.npix_x])
# for m in np.arange(chip.npix_y):
# for n in np.arange(chip.npix_x):
# px = n
# py = m
# dist2 = (pos_p[:, 1] - px)*(pos_p[:, 1] - px) + (pos_p[:, 0] - py)*(pos_p[:, 0] - py)
# temp_sort_dist = np.zeros([dist2.shape[0], 2])
# temp_sort_dist[:, 0] = np.arange(0, dist2.shape[0], 1)
# temp_sort_dist[:, 1] = dist2
# # print(temp_sort_dist)
# dits2_sortlist = sorted(temp_sort_dist, key=lambda x: x[1])
# # print(dits2_sortlist)
# nearest4p = np.zeros([4, 3])
# pc_coeff_4p = np.zeros([npca, 4])
# for i in np.arange(4):
# smaller_ids = int(dits2_sortlist[i][0])
# nearest4p[i, 0] = pos_p[smaller_ids, 1]
# nearest4p[i, 1] = pos_p[smaller_ids, 0]
# # print(pos_p[smaller_ids, 1],pos_p[smaller_ids, 0])
# nearest4p[i, 2] = dits2_sortlist[i][1]
# pc_coeff_4p[:, i] = pc_coeff[npca, smaller_ids]
# # idw_dist = 1/(np.sqrt((px-nearest4p[:, 0]) * (px-nearest4p[:, 0]) + (
# # py-nearest4p[:, 1]) * (py-nearest4p[:, 1])))
# idw_dist = 1/(np.sqrt(nearest4p[:, 2]))
# coeff_int = np.zeros(npca)
# for i in np.arange(4):
# coeff_int = coeff_int + pc_coeff_4p[:, i]*idw_dist[i]
# coeff_mat[:, m, n] = coeff_int
m_size = int(pcs.shape[0]**0.5)
tmp_img = np.zeros_like(img.array,dtype=np.float32)
for j in np.arange(npca):
print(gt, od, w, j)
X_ = jnp.hstack((pos_p[:,1].flatten()[:, None], pos_p[:,0].flatten()[:, None]),dtype=np.float32)
Z_ = (pc_coeff[j].astype(np.float32)).flatten()
# print(pc_coeff[j].shape[0], pos_p[:,1].shape[0], pos_p[:,0].shape[0])
sub_size = 4
cx_len = int(chip.npix_x/sub_size)
cy_len = int(chip.npix_y/sub_size)
n_x = jnp.arange(0, chip.npix_x, sub_size, dtype = int)
n_y = jnp.arange(0, chip.npix_y, sub_size, dtype = int)
M, N = jnp.meshgrid(n_x, n_y)
t1=datetime.datetime.now()
# U = interpolate.griddata(X_, Z_, (M[0:cy_len, 0:cx_len],N[0:cy_len, 0:cx_len]),
# method='nearest',fill_value=1.0)
U1 = interpolate.griddata(X_, Z_, (M, N),
method='nearest',fill_value=1.0)
U = np.zeros_like(chip.img.array, dtype=np.float32)
for mi in np.arange(cy_len):
for mj in np.arange(cx_len):
U[mi*sub_size:(mi+1)*sub_size, mj*sub_size:(mj+1)*sub_size]=U1[mi,mj]
t2=datetime.datetime.now()
print("time interpolate:", t2-t1)
img_tmp = img.array*U
psf = pcs[:, j].reshape(m_size, m_size)
tmp_img = tmp_img + signal.fftconvolve(img_tmp, psf, mode='same', axes=None)
t3=datetime.datetime.now()
print("time convole:", t3-t2)
del U
del U1
chip.img = chip.img + tmp_img*sum_img/np.sum(tmp_img)
del tmp_img
gc.collect()
# pixSize = np.rad2deg(self.pixsize*1e-3/28)*3600 #set psf pixsize # pixSize = np.rad2deg(self.pixsize*1e-3/28)*3600 #set psf pixsize
# #
# # assert self.iccd == int(chip.getChipLabel(chipID=chip.chipID)), 'ERROR: self.iccd != chip.chipID' # # assert self.iccd == int(chip.getChipLabel(chipID=chip.chipID)), 'ERROR: self.iccd != chip.chipID'
......
observation_sim/sim_steps/__init__.py
View file @ d8118d46
import os import os
class SimSteps: class SimSteps:
def __init__(self, overall_config, chip_output, all_filters, ra_offset=0., dec_offset=0.): def __init__(self, overall_config, chip_output, all_filters):
self.overall_config = overall_config self.overall_config = overall_config
self.chip_output = chip_output self.chip_output = chip_output
self.all_filters = all_filters self.all_filters = all_filters
self.ra_offset = ra_offset
self.dec_offset = dec_offset
from .prepare_headers import prepare_headers, updateHeaderInfo from .prepare_headers import prepare_headers, updateHeaderInfo
from .add_sky_background import add_sky_background_sci, add_sky_flat_calibration, add_sky_background from .add_sky_background import add_sky_background_sci, add_sky_flat_calibration, add_sky_background
...@@ -18,7 +15,6 @@ class SimSteps: ...@@ -18,7 +15,6 @@ class SimSteps:
from .readout_output import add_prescan_overscan, add_readout_noise, apply_gain, quantization_and_output from .readout_output import add_prescan_overscan, add_readout_noise, apply_gain, quantization_and_output
from .add_LED_flat import add_LED_Flat from .add_LED_flat import add_LED_Flat
SIM_STEP_TYPES = { SIM_STEP_TYPES = {
"scie_obs": "add_objects", "scie_obs": "add_objects",
"sky_background": "add_sky_background", "sky_background": "add_sky_background",
...@@ -35,6 +31,6 @@ SIM_STEP_TYPES = { ...@@ -35,6 +31,6 @@ SIM_STEP_TYPES = {
"readout_noise": "add_readout_noise", "readout_noise": "add_readout_noise",
"gain": "apply_gain", "gain": "apply_gain",
"quantization_and_output": "quantization_and_output", "quantization_and_output": "quantization_and_output",
"led_calib_model": "add_LED_Flat", "led_calib_model":"add_LED_Flat",
"sky_flatField": "add_sky_flat_calibration", "sky_flatField":"add_sky_flat_calibration",
} }
\ No newline at end of file
observation_sim/sim_steps/add_objects.py
View file @ d8118d46
...@@ -145,7 +145,7 @@ def add_objects(self, chip, filt, tel, pointing, catalog, obs_param): ...@@ -145,7 +145,7 @@ def add_objects(self, chip, filt, tel, pointing, catalog, obs_param):
# Get position of object on the focal plane # Get position of object on the focal plane
pos_img, _, _, _, fd_shear = obj.getPosImg_Offset_WCS( pos_img, _, _, _, fd_shear = obj.getPosImg_Offset_WCS(
img=chip.img, fdmodel=fd_model, chip=chip, verbose=False, chip_wcs=chip_wcs, img_header=self.h_ext, ra_offset=self.ra_offset, dec_offset=self.dec_offset) img=chip.img, fdmodel=fd_model, chip=chip, verbose=False, chip_wcs=chip_wcs, img_header=self.h_ext)
# [TODO] For now, only consider objects which their centers (after field distortion) are projected within the focal plane # [TODO] For now, only consider objects which their centers (after field distortion) are projected within the focal plane
# Otherwise they will be considered missed objects # Otherwise they will be considered missed objects
...@@ -194,8 +194,7 @@ def add_objects(self, chip, filt, tel, pointing, catalog, obs_param): ...@@ -194,8 +194,7 @@ def add_objects(self, chip, filt, tel, pointing, catalog, obs_param):
if isUpdated == 1: if isUpdated == 1:
# TODO: add up stats # TODO: add up stats
self.chip_output.cat_add_obj( self.chip_output.cat_add_obj(obj, pos_img, pos_shear)
obj, pos_img, pos_shear, ra_offset=self.ra_offset, dec_offset=self.dec_offset)
pass pass
elif isUpdated == 0: elif isUpdated == 0:
missed_obj += 1 missed_obj += 1
...@@ -217,27 +216,7 @@ def add_objects(self, chip, filt, tel, pointing, catalog, obs_param): ...@@ -217,27 +216,7 @@ def add_objects(self, chip, filt, tel, pointing, catalog, obs_param):
# Unload SED: # Unload SED:
obj.unload_SED() obj.unload_SED()
del obj del obj
# gc.collect() gc.collect()
if chip.survey_type == "spectroscopic" and not self.overall_config["run_option"]["out_cat_only"] and chip.slsPSFOptim:
# from observation_sim.instruments.chip import chip_utils as chip_utils
# gn = chip_utils.getChipSLSGratingID(chip.chipID)[0]
# img1 = np.zeros([2,chip.img.array.shape[0],chip.img.array.shape[1]])
# for id1 in np.arange(2):
# gn = chip_utils.getChipSLSGratingID(chip.chipID)[id1]
# img_i = 0
# for id2 in ['0','1']:
# o_n = "order"+id2
# for id3 in ['1','2','3','4']:
# w_n = "w"+id3
# img1[img_i] = img1[img_i] + chip.img_stack[gn][o_n][w_n].array
# img_i = img_i + 1
# from astropy.io import fits
# fits.writeto('order0.fits',img1[0],overwrite=True)
# fits.writeto('order1.fits',img1[1],overwrite=True)
psf_model.convolveFullImgWithPCAPSF(chip)
del psf_model del psf_model
gc.collect() gc.collect()
......
observation_sim/sim_steps/add_pattern_noise.py
View file @ d8118d46
...@@ -27,7 +27,7 @@ def add_poisson_and_dark(self, chip, filt, tel, pointing, catalog, obs_param): ...@@ -27,7 +27,7 @@ def add_poisson_and_dark(self, chip, filt, tel, pointing, catalog, obs_param):
InputDark=None) InputDark=None)
else: else:
chip.img, _ = chip_utils.add_poisson(img=chip.img, chip.img, _ = chip_utils.add_poisson(img=chip.img,
chip=chip, chip=self,
exptime=exptime, exptime=exptime,
poisson_noise=chip.poisson_noise, poisson_noise=chip.poisson_noise,
dark_noise=0.) dark_noise=0.)
...@@ -81,5 +81,5 @@ def add_bias(self, chip, filt, tel, pointing, catalog, obs_param): ...@@ -81,5 +81,5 @@ def add_bias(self, chip, filt, tel, pointing, catalog, obs_param):
nsecx=chip.nsecx, nsecx=chip.nsecx,
seed=self.overall_config["random_seeds"]["seed_biasNonUniform"]+chip.chipID) seed=self.overall_config["random_seeds"]["seed_biasNonUniform"]+chip.chipID)
elif obs_param["bias_16channel"] == False: elif obs_param["bias_16channel"] == False:
chip.img += chip.bias_level chip.img += self.bias_level
return chip, filt, tel, pointing return chip, filt, tel, pointing
observation_sim/sim_steps/readout_output.py
View file @ d8118d46
...@@ -86,10 +86,10 @@ def quantization_and_output(self, chip, filt, tel, pointing, catalog, obs_param) ...@@ -86,10 +86,10 @@ def quantization_and_output(self, chip, filt, tel, pointing, catalog, obs_param)
fname = os.path.join(self.chip_output.subdir, fname = os.path.join(self.chip_output.subdir,
self.h_prim['FILENAME'] + '.fits') self.h_prim['FILENAME'] + '.fits')
# f_name_size = 68 f_name_size = 68
# if (len(self.h_prim['FILENAME']) > f_name_size): if (len(self.h_prim['FILENAME']) > f_name_size):
# self.updateHeaderInfo(header_flag='prim', keys=['FILENAME'], values=[ self.updateHeaderInfo(header_flag='prim', keys=['FILENAME'], values=[
# self.h_prim['FILENAME'][0:f_name_size]]) self.h_prim['FILENAME'][0:f_name_size]])
hdu1 = fits.PrimaryHDU(header=self.h_prim) hdu1 = fits.PrimaryHDU(header=self.h_prim)
......
submit_jobs.slurm
View file @ d8118d46
#!/bin/bash #!/bin/bash
#SBATCH -J CSSTSim #SBATCH -J CSSTSim
#SBATCH -N 2 #SBATCH -N 1
#SBATCH --ntasks-per-node=6 #SBATCH --ntasks-per-node=6
#SBATCH -p debug #SBATCH -p debug
#SBATCH --mem=96G #SBATCH --mem=60G
module load mpi/hpcx/2.4.1/gcc-7.3.1 module load mpi/hpcx/2.4.1/gcc-7.3.1
date date
...@@ -12,4 +12,4 @@ date ...@@ -12,4 +12,4 @@ date
#限定单节点任务数 #限定单节点任务数
srun hostname -s | sort -n | awk -F"-" '{print $2}' | uniq > pnodes srun hostname -s | sort -n | awk -F"-" '{print $2}' | uniq > pnodes
mpirun -mca pml ucx -x UCX_NET_DEVICES=mlx5_0:1 -machinefile pnodes -np 12 --map-by node python3 /public/home/fangyuedong/project/csst_msc_sim/run_sim.py --config_file config_overall.yaml --catalog C9_Catalog -c /public/home/fangyuedong/project/csst_msc_sim/config mpirun -mca pml ucx -x UCX_NET_DEVICES=mlx5_0:1 -machinefile pnodes -np 6 --map-by node python3 /public/home/fangyuedong/project/csst_msc_sim/run_sim.py --config_file config_overall.yaml --catalog C9_Catalog -c /public/home/fangyuedong/project/csst_msc_sim/config
\ No newline at end of file \ No newline at end of file
tools/get_pointing.py
View file @ d8118d46
...@@ -63,15 +63,10 @@ class Chip(object): ...@@ -63,15 +63,10 @@ class Chip(object):
ycen = self.cen_pix_y ycen = self.cen_pix_y
if pix_scale == None: if pix_scale == None:
pix_scale = self.pix_scale pix_scale = self.pix_scale
# dudx = -np.cos(img_rot.rad) * pix_scale
# dudy = -np.sin(img_rot.rad) * pix_scale
# dvdx = -np.sin(img_rot.rad) * pix_scale
# dvdy = +np.cos(img_rot.rad) * pix_scale
dudx = -np.cos(img_rot.rad) * pix_scale dudx = -np.cos(img_rot.rad) * pix_scale
dudy = +np.sin(img_rot.rad) * pix_scale dudy = -np.sin(img_rot.rad) * pix_scale
dvdx = -np.sin(img_rot.rad) * pix_scale dvdx = -np.sin(img_rot.rad) * pix_scale
dvdy = -np.cos(img_rot.rad) * pix_scale dvdy = +np.cos(img_rot.rad) * pix_scale
# dudx = +np.sin(img_rot.rad) * pix_scale # dudx = +np.sin(img_rot.rad) * pix_scale
# dudy = +np.cos(img_rot.rad) * pix_scale # dudy = +np.cos(img_rot.rad) * pix_scale
...@@ -144,11 +139,12 @@ def getobsPA(ra, dec): ...@@ -144,11 +139,12 @@ def getobsPA(ra, dec):
angle = math.acos(np.dot(l1l2cross,pdl2cross)/(np.linalg.norm(l1l2cross)*np.linalg.norm(pdl2cross))) angle = math.acos(np.dot(l1l2cross,pdl2cross)/(np.linalg.norm(l1l2cross)*np.linalg.norm(pdl2cross)))
angle = (angle)/math.pi*180 angle = (angle)/math.pi*180
angle = angle + 90
if (ra<90 or ra> 270): # if (ra>90 and ra< 270):
angle=-angle # angle=-angle
return angle return angle
# @jit() # @jit()
def getSelectPointingList(center = [60,-40], radius = 2): def getSelectPointingList(center = [60,-40], radius = 2):
points = np.loadtxt('sky.dat') points = np.loadtxt('sky.dat')
...@@ -265,7 +261,7 @@ def findPointingbyChipID(chipID = 8, ra = 60., dec = -40.): ...@@ -265,7 +261,7 @@ def findPointingbyChipID(chipID = 8, ra = 60., dec = -40.):
if __name__ == "__main__": if __name__ == "__main__":
tchip, tra, tdec = 13, 60., -40. tchip, tra, tdec = 8, 60., -40.
pointing = findPointingbyChipID(chipID=tchip, ra=tra, dec=tdec) pointing = findPointingbyChipID(chipID=tchip, ra=tra, dec=tdec)
print("[ra_center, dec_center, image_rot]: ", pointing) print("[ra_center, dec_center, image_rot]: ", pointing)
tools/get_pointing_accuracy.py deleted 100644 → 0
View file @ 914004c1
from pylab import *
import math, sys, numpy as np
import astropy.coordinates as coord
from astropy.coordinates import SkyCoord
from astropy import wcs, units as u
from observation_sim.config.header import ImageHeader
from observation_sim.instruments import Telescope, Chip, FilterParam, Filter, FocalPlane
def transRaDec2D(ra, dec):
x1 = np.cos(dec / 57.2957795) * np.cos(ra / 57.2957795)
y1 = np.cos(dec / 57.2957795) * np.sin(ra / 57.2957795)
z1 = np.sin(dec / 57.2957795)
return np.array([x1, y1, z1])
def ecl2radec(lon_ecl, lat_ecl):
## convert from ecliptic coordinates to equatorial coordinates
c_ecl = SkyCoord(
lon=lon_ecl * u.degree, lat=lat_ecl * u.degree, frame="barycentrictrueecliptic"
)
c_eq = c_ecl.transform_to("icrs")
ra_eq, dec_eq = c_eq.ra.degree, c_eq.dec.degree
return ra_eq, dec_eq
def radec2ecl(ra, dec):
## convert from equatorial coordinates to ecliptic coordinates
c_eq = SkyCoord(ra=ra * u.degree, dec=dec * u.degree, frame="icrs")
c_ecl = c_eq.transform_to("barycentrictrueecliptic")
lon_ecl, lat_ecl = c_ecl.lon.degree, c_ecl.lat.degree
return lon_ecl, lat_ecl
def cal_FoVcenter_1P_equatorial(ra_FieldCenter, dec_FieldCenter, chipID = 1, pa = -23.5):
### [ra_FieldCenter, dec_FieldCenter] is the center ra, dec of calibration fileds, such as: NEP, NGC 6397, etc.
### [ra_ChipCenter, dec_ChipCenter] is the center ra, dec of the Chip center.
### [ra_PointCenter, dec_PointCenter] is the telescope pointing center.
## Calculate PA angle
chip = Chip(chipID)
h_ext = ImageHeader.generateExtensionHeader(
chip=chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=(ra_FieldCenter * u.degree).value,
dec=(dec_FieldCenter * u.degree).value,
pa=pa,
gain=chip.gain,
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
pixel_scale=chip.pix_scale,
pixel_size=chip.pix_size,
xcen=chip.x_cen,
ycen=chip.y_cen,
)
# assume that the telescope point to the sky center; then abtain the chip center under this situation; then calculate the differenc between the assumed telescope center and chip center; then add this difference to the sky center
wcs_h = wcs.WCS(h_ext)
pixs = np.array([[4608, 4616]])
world_point = wcs_h.wcs_pix2world(pixs, 0)
ra_ChipCenter, dec_ChipCenter = world_point[0][0], world_point[0][1]
d_ra = ra_FieldCenter - ra_ChipCenter
d_dec = dec_FieldCenter - dec_ChipCenter
ra_PointCenter = ra_FieldCenter + d_ra
dec_PointCenter = dec_FieldCenter + d_dec
lon_ecl_PointCenter, lat_ecl_PointCenter = radec2ecl(
ra_PointCenter, dec_PointCenter
)
return ra_PointCenter, dec_PointCenter, lon_ecl_PointCenter, lat_ecl_PointCenter
def cal_FoVcenter_1P_ecliptic(lon_ecl_FieldCenter, lat_ecl_FieldCenter, chipID = 1, pa = -23.5):
### [ra_FieldCenter, dec_FieldCenter] is the center ra, dec of calibration fileds, such as: NEP, NGC 6397, etc.
### [ra_ChipCenter, dec_ChipCenter] is the center ra, dec of the Chip center.
### [ra_PointCenter, dec_PointCenter] is the telescope pointing center.
ra_FieldCenter, dec_FieldCenter = ecl2radec(
lon_ecl_FieldCenter, lat_ecl_FieldCenter
)
## Calculate PA angle
chip = Chip(chipID)
h_ext = ImageHeader.generateExtensionHeader(
chip=chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=(ra_FieldCenter * u.degree).value,
dec=(dec_FieldCenter * u.degree).value,
pa=pa,
gain=chip.gain,
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
pixel_scale=chip.pix_scale,
pixel_size=chip.pix_size,
xcen=chip.x_cen,
ycen=chip.y_cen,
)
# assume that the telescope point to the sky center; then abtain the chip center under this situation; then calculate the differenc between the assumed telescope center and chip center; then add this difference to the sky center
wcs_h = wcs.WCS(h_ext)
pixs = np.array([[4608, 4616]])
world_point = wcs_h.wcs_pix2world(pixs, 0)
ra_ChipCenter, dec_ChipCenter = world_point[0][0], world_point[0][1]
d_ra = ra_FieldCenter - ra_ChipCenter
d_dec = dec_FieldCenter - dec_ChipCenter
ra_PointCenter = ra_FieldCenter + d_ra
dec_PointCenter = dec_FieldCenter + d_dec
lon_ecl_PointCenter, lat_ecl_PointCenter = radec2ecl(
ra_PointCenter, dec_PointCenter
)
return ra_PointCenter, dec_PointCenter, lon_ecl_PointCenter, lat_ecl_PointCenter
def getChipCenterRaDec(chipID = 1, p_ra = 60., p_dec = -40.):
chip = Chip(chipID)
h_ext = ImageHeader.generateExtensionHeader(
chip=chip,
xlen=chip.npix_x,
ylen=chip.npix_y,
ra=(p_ra * u.degree).value,
dec=(p_dec * u.degree).value,
pa=pa,
gain=chip.gain,
readout=chip.read_noise,
dark=chip.dark_noise,
saturation=90000,
pixel_scale=chip.pix_scale,
pixel_size=chip.pix_size,
xcen=chip.x_cen,
ycen=chip.y_cen,
)
wcs_h = wcs.WCS(h_ext)
pixs = np.array([[4608, 4616]])
world_point = wcs_h.wcs_pix2world(pixs, 0)
RA_chip, Dec_chip = world_point[0][0], world_point[0][1]
return RA_chip, Dec_chip
if __name__ == '__main__':
ra_input, dec_input = 270.00000, 66.56000 # NEP
pa = 23.5
# chipid = 2
for chipid in np.arange(1,31,1):
ra, dec, lon_ecl, lat_ecl = cal_FoVcenter_1P_equatorial(
ra_input, dec_input,chipID=chipid, pa=pa)
print("chip id is %d, chip center [ra,dec] is [%f, %f], pointing center calculated [ra,dec] is [%f, %f]"%(chipid, ra_input, dec_input, ra, dec))
#for check the result
# testRA, testDec = getChipCenterRaDec(chipID = chipid, p_ra = ra, p_dec = dec)
# print(ra_input-testRA, dec_input-testDec)
tools/target_location_check.py
View file @ d8118d46
...@@ -119,15 +119,10 @@ def getTanWCS(ra, dec, img_rot, pix_scale=0.074): ...@@ -119,15 +119,10 @@ def getTanWCS(ra, dec, img_rot, pix_scale=0.074):
""" """
xcen, ycen = 0, 0 xcen, ycen = 0, 0
img_rot = img_rot * galsim.degrees img_rot = img_rot * galsim.degrees
# dudx = -np.cos(img_rot.rad) * pix_scale
# dudy = -np.sin(img_rot.rad) * pix_scale
# dvdx = -np.sin(img_rot.rad) * pix_scale
# dvdy = +np.cos(img_rot.rad) * pix_scale
dudx = -np.cos(img_rot.rad) * pix_scale dudx = -np.cos(img_rot.rad) * pix_scale
dudy = +np.sin(img_rot.rad) * pix_scale dudy = -np.sin(img_rot.rad) * pix_scale
dvdx = -np.sin(img_rot.rad) * pix_scale dvdx = -np.sin(img_rot.rad) * pix_scale
dvdy = -np.cos(img_rot.rad) * pix_scale dvdy = +np.cos(img_rot.rad) * pix_scale
moscen = galsim.PositionD(x=xcen, y=ycen) moscen = galsim.PositionD(x=xcen, y=ycen)
sky_center = galsim.CelestialCoord( sky_center = galsim.CelestialCoord(
......
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