modify unittest name spec & straylight

tests/test_SpecDisperse.py

+import unittest
+from ObservationSim.MockObject.SpecDisperser import rotate90, SpecDisperser
+
+from ObservationSim.Config import ChipOutput, Config
+from ObservationSim.Instrument import Telescope, Chip, FilterParam, Filter, FocalPlane
+from ObservationSim.MockObject import MockObject, Star
+from ObservationSim.PSF import PSFGauss
+
+import numpy as np
+import galsim
+from astropy.table import Table
+from scipy import interpolate
+
+import matplotlib.pyplot as plt
+
+from lmfit.models import LinearModel, GaussianModel
+
+from ObservationSim.Config.Header import generateExtensionHeader
+import math
+import yaml
+
+
+def getAngle132(x1=0, y1=0, z1=0, x2=0, y2=0, z2=0, x3=0, y3=0, z3=0):
+    cosValue = 0;
+    angle = 0;
+
+    x11 = x1 - x3;
+    y11 = y1 - y3;
+    z11 = z1 - z3;
+
+    x22 = x2 - x3;
+    y22 = y2 - y3;
+    z22 = z2 - z3;
+
+    tt = np.sqrt((x11 * x11 + y11 * y11 + z11 * z11) * (x22 * x22 + y22 * y22 + z22 * z22));
+    if (tt == 0):
+        return 0;
+
+    cosValue = (x11 * x22 + y11 * y22 + z11 * z22) / tt;
+
+    if (cosValue > 1):
+        cosValue = 1;
+    if (cosValue < -1):
+        cosValue = -1;
+    angle = math.acos(cosValue);
+    return angle * 360 / (2 * math.pi);
+
+
+def fit_SingleGauss(xX, yX, contmX, iHa0):
+    background = LinearModel(prefix='line_')
+    pars = background.make_params(intercept=yX.max(), slope=0)
+    pars = background.guess(yX, x=xX)
+
+    gauss = GaussianModel(prefix='g_')
+    pars.update(gauss.make_params())
+    pars['g_center'].set(iHa0, min=iHa0 - 3, max=iHa0 + 3)
+    pars['g_amplitude'].set(50, min=0)
+    pars['g_sigma'].set(12, min=0.0001)
+
+    mod = gauss + background
+    init = mod.eval(pars, x=xX)
+    outX = mod.fit(yX, pars, x=xX)
+    compsX = outX.eval_components(x=xX)
+    # print(outX.fit_report(min_correl=0.25))
+    # print outX.params['g_center']
+    outX.fit_report(min_correl=0.25)
+    # print(outX.fit_report(min_correl=0.25))
+    line_slopeX = float(outX.fit_report(min_correl=0.25).split('line_slope:')[1].split('+/-')[0]) * contmX
+    err_line_slopeX = float(
+        outX.fit_report(min_correl=0.25).split('line_slope:')[1].split('+/-')[1].split('(')[0]) * contmX
+
+    line_interceptX = float(outX.fit_report(min_correl=0.25).split('line_intercept:')[1].split('+/-')[0]) * contmX
+    err_line_interceptX = float(
+        outX.fit_report(min_correl=0.25).split('line_intercept:')[1].split('+/-')[1].split('(')[0]) * contmX
+
+    sigmaX = float(outX.fit_report(min_correl=0.25).split('g_sigma:')[1].split('+/-')[0])
+    err_sigmaX = float(outX.fit_report(min_correl=0.25).split('g_sigma:')[1].split('+/-')[1].split('(')[0])
+
+    fwhmX = float(outX.fit_report(min_correl=0.25).split('g_fwhm:')[1].split('+/-')[0])
+    err_fwhmX = float(outX.fit_report(min_correl=0.25).split('g_fwhm:')[1].split('+/-')[1].split('(')[0])
+
+    centerX = float(outX.fit_report(min_correl=0.25).split('g_center:')[1].split('+/-')[0])
+    err_centerX = float(outX.fit_report(min_correl=0.25).split('g_center:')[1].split('+/-')[1].split('(')[0])
+
+    return sigmaX, err_sigmaX, fwhmX, err_fwhmX, centerX, err_centerX
+
+def produceObj(x,y,chip, ra, dec, pa):
+    pos_img = galsim.PositionD(chip.bound.xmin + x, chip.bound.ymin + y)
+
+    param = {}
+    param["star"] = 1
+    param["id"] = 1
+    param["ra"] = chip.img.wcs.posToWorld(pos_img).ra.deg
+    param["dec"] = chip.img.wcs.posToWorld(pos_img).dec.deg
+    param["z"] = 0
+    param["sed_type"] = 1
+    param["model_tag"] = 1
+    param["mag_use_normal"] = 10
+
+    obj = Star(param)
+
+    header_wcs = generateExtensionHeader(
+        xlen=chip.npix_x,
+        ylen=chip.npix_y,
+        ra=ra,
+        dec=dec,
+        pa=pa,
+        gain=chip.gain,
+        readout=chip.read_noise,
+        dark=chip.dark_noise,
+        saturation=90000,
+        psize=chip.pix_scale,
+        row_num=chip.rowID,
+        col_num=chip.colID,
+        extName='raw')
+
+    pos_img, offset, local_wcs, _ = obj.getPosImg_Offset_WCS(img=chip.img, chip=chip, img_header=header_wcs)
+    wave = np.arange(2500, 11000.5, 0.5)
+    # sedLen = wave.shape[0]
+    flux = pow(wave, -2) * 1e8
+    flux[200] = flux[200] * 10
+    flux[800] = flux[800] * 30
+    flux[2000] = flux[2000] * 5
+
+    obj.sed = Table(np.array([wave, flux]).T,
+                    names=('WAVELENGTH', 'FLUX'))
+    return obj, pos_img
+
+
+class TestSpecDisperse(unittest.TestCase):
+
+    def __init__(self, methodName='runTest',conff = '', throughputf = ''):
+        super(TestSpecDisperse,self).__init__(methodName)
+        self.conff = conff
+        self.throughputf = throughputf
+
+    def test_rotate901(self):
+        m = np.array([[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14,15],[16,17,18,19,20],[21,22,23,24,25]])
+        m1 = np.array([[21,16,11,6,1],[22,17,12,7,2],[23,18,13,8,3],[24,19,14,9,4],[25,20,15,10,5]])
+        m2 = np.array([[5,10,15,20,25],[4,9,14,19,24],[3,8,13,18,23],[2,7,12,17,22],[1,6,11,16,21]])
+        xc = 2
+        yc = 2
+        isClockwise = 0
+        m1, xc1, yc1 = rotate90(array_orig=m, xc=xc, yc=yc, isClockwise=isClockwise)
+        self.assertTrue(xc1-xc == 0)
+        self.assertTrue(yc1-yc == 0)
+        self.assertTrue(np.sum(m-m1) == 0)
+
+    def test_rotate902(self):
+        m = np.array([[1,2,3,4,5],[6,7,8,9,10],[11,12,13,14,15],[16,17,18,19,20],[21,22,23,24,25]])
+        m1 = np.array([[21,16,11,6,1],[22,17,12,7,2],[23,18,13,8,3],[24,19,14,9,4],[25,20,15,10,5]])
+        m2 = np.array([[5,10,15,20,25],[4,9,14,19,24],[3,8,13,18,23],[2,7,12,17,22],[1,6,11,16,21]])
+        xc = 2
+        yc = 2
+        isClockwise =1
+        m1, xc1, yc1 = rotate90(array_orig=m, xc=xc, yc=yc, isClockwise=isClockwise)
+        self.assertTrue(xc1-xc == 0)
+        self.assertTrue(yc1-yc == 0)
+        self.assertTrue(np.sum(m-m2) == 0)
+
+
+    def test_Specdistperse1(self):
+        star = galsim.Gaussian(fwhm=0.39)
+        g_img = galsim.Image(100, 100, scale=0.074)
+        starImg = star.drawImage(image=g_img)
+
+        wave = np.arange(6200, 10000.5, 0.5)
+        # sedLen = wave.shape[0]
+        flux = pow(wave, -2) * 1e8
+        # flux[200] = flux[200] * 10
+        # flux[800] = flux[800] * 30
+        # flux[2000] = flux[2000] * 5
+
+        sed = Table(np.array([wave, flux]).T,
+                    names=('WAVELENGTH', 'FLUX'))
+        conff = self.conff
+        throughput_f = self.throughputf
+        thp = Table.read(throughput_f)
+        thp_i = interpolate.interp1d(thp['WAVELENGTH'], thp['SENSITIVITY'])
+        sdp = SpecDisperser(orig_img=starImg, xcenter=0, ycenter=0, origin=[100, 100], tar_spec=sed, band_start=6200,
+                            band_end=10000, isAlongY=0, conf=conff, gid=0)
+        spec = sdp.compute_spec_orders()
+        Aimg = spec['A'][0]
+        wave_pix = spec['A'][5]
+        wave_pos = spec['A'][3]
+        sens = spec['A'][6]
+        sh = Aimg.shape
+        spec_pix = np.zeros(sh[1])
+        for i in range(sh[1]):
+            spec_pix[i] = sum(Aimg[:, i])
+        # figure()
+        # imshow(Aimg)
+
+        wave_flux = np.zeros(wave_pix.shape[0])
+        for i in np.arange(1, wave_pix.shape[0] - 1):
+            w = wave_pix[i]
+            thp_w = thp_i(w)
+            deltW = (w - wave_pix[i - 1]) / 2 + (wave_pix[i + 1] - w) / 2
+            f = spec_pix[wave_pos[0] - 1 + i]
+
+            if 6200 <= w <= 10000:
+                f = f / thp_w
+            else:
+                f = 0
+            wave_flux[i] = f / deltW
+        sed_i = interpolate.interp1d(sed['WAVELENGTH'], sed['FLUX'])
+        ids = wave_pix < 9700
+        ids1 = wave_pix[ids] > 6500
+        print('Spec disperse flux test')
+        self.assertTrue(np.mean((wave_flux[ids][ids1] - sed_i(wave_pix[ids][ids1]))/sed_i(wave_pix[ids][ids1]))<0.004)
+        plt.figure()
+        plt.plot(wave_pix, wave_flux)
+        plt.plot(sed['WAVELENGTH'], sed['FLUX'])
+        plt.xlim(6200, 10000)
+        plt.ylim(1, 3)
+        plt.yscale('log')
+        plt.xlabel('$\lambda$')
+        plt.ylabel('$F\lambda$')
+        plt.legend(['extracted', 'input'])
+        plt.show()
+
+    def test_Specdistperse2(self):
+
+        psf_fwhm = 0.39
+        pix_scale = 0.074
+        star = galsim.Gaussian(fwhm=psf_fwhm)
+        g_img = galsim.Image(100, 100, scale=pix_scale)
+        starImg = star.drawImage(image=g_img)
+
+        wave = np.arange(6200, 10000.5, 0.5)
+        # sedLen = wave.shape[0]
+        flux = pow(wave, -2) * 1e8
+        flux[200] = flux[200] * 10
+        flux[800] = flux[800] * 30
+        flux[2000] = flux[2000] * 5
+
+        sed = Table(np.array([wave, flux]).T,
+                    names=('WAVELENGTH', 'FLUX'))
+        conff = self.conff
+        throughput_f = self.throughputf
+        thp = Table.read(throughput_f)
+        thp_i = interpolate.interp1d(thp['WAVELENGTH'], thp['SENSITIVITY'])
+        sdp = SpecDisperser(orig_img=starImg, xcenter=0, ycenter=0, origin=[100, 100], tar_spec=sed, band_start=6200,
+                            band_end=10000, isAlongY=0, conf=conff, gid=0)
+        spec = sdp.compute_spec_orders()
+        Aimg = spec['A'][0]
+        wave_pix = spec['A'][5]
+        wave_pos = spec['A'][3]
+        sens = spec['A'][6]
+        sh = Aimg.shape
+        spec_pix = np.zeros(sh[1])
+        for i in range(sh[1]):
+            spec_pix[i] = sum(Aimg[:, i])
+        # figure()
+        # imshow(Aimg)
+
+        wave_flux = np.zeros(wave_pix.shape[0])
+        for i in np.arange(1, wave_pix.shape[0] - 1):
+            w = wave_pix[i]
+            thp_w = thp_i(w)
+            deltW = (w - wave_pix[i - 1]) / 2 + (wave_pix[i + 1] - w) / 2
+            f = spec_pix[wave_pos[0] - 1 + i]
+
+            if 6200 <= w <= 10000:
+                f = f / thp_w
+            else:
+                f = 0
+            wave_flux[i] = f / deltW
+        sed_i = interpolate.interp1d(sed['WAVELENGTH'], sed['FLUX'])
+        input_em_lam = 6600
+        ids = wave_pix < input_em_lam+200
+        ids1 = wave_pix[ids] > input_em_lam-200
+        deltLamda_pix = (max(wave_pix[ids][ids1]) - min(wave_pix[ids][ids1])) / (wave_pix[ids][ids1].shape[0] - 1)
+        _, _, fwhmx, fwhmx_err, center, center_err = fit_SingleGauss(wave_pix[ids][ids1], wave_flux[ids][ids1], 1.0, 6600)
+
+        print('Emission line position and shape test')
+
+        self.assertTrue(input_em_lam-center < deltLamda_pix)
+
+        self.assertTrue(fwhmx/deltLamda_pix*pix_scale - psf_fwhm  < np.abs(0.01))
+        # print('error is ',np.mean((wave_flux[ids][ids1] - sed_i(wave_pix[ids][ids1]))/sed_i(wave_pix[ids][ids1])))
+        # self.assertTrue(np.mean((wave_flux[ids][ids1] - sed_i(wave_pix[ids][ids1]))/sed_i(wave_pix[ids][ids1]))<0.004)
+        plt.figure()
+        plt.plot(wave_pix, wave_flux)
+        plt.plot(sed['WAVELENGTH'], sed['FLUX'])
+        plt.xlim(6200, 10000)
+        plt.ylim(1, 75)
+        plt.yscale('log')
+        plt.xlabel('$\lambda$')
+        plt.ylabel('$F\lambda$')
+        plt.legend(['extracted', 'input'])
+        plt.show()
+
+    def test_Specdistperse3(self):
+
+        psf_fwhm = 0.39
+        pix_scale = 0.074
+        star = galsim.Gaussian(fwhm=psf_fwhm)
+        g_img = galsim.Image(100, 100, scale=pix_scale)
+        starImg = star.drawImage(image=g_img)
+
+        wave = np.arange(6200, 10000.5, 0.5)
+        # sedLen = wave.shape[0]
+        flux = pow(wave, -2) * 1e8
+        flux[200] = flux[200] * 10
+        flux[800] = flux[800] * 30
+        flux[2000] = flux[2000] * 5
+
+        sed = Table(np.array([wave, flux]).T,
+                    names=('WAVELENGTH', 'FLUX'))
+        conff = self.conff
+        throughput_f = self.throughputf
+        thp = Table.read(throughput_f)
+        thp_i = interpolate.interp1d(thp['WAVELENGTH'], thp['SENSITIVITY'])
+        sdp = SpecDisperser(orig_img=starImg, xcenter=0, ycenter=0, origin=[100, 100], tar_spec=sed, band_start=6200,
+                            band_end=8000, isAlongY=0, conf=conff, gid=0)
+        sdp1 = SpecDisperser(orig_img=starImg, xcenter=0, ycenter=0, origin=[100, 100], tar_spec=sed, band_start=8000,
+                             band_end=10000, isAlongY=0, conf=conff, gid=0)
+        spec = sdp.compute_spec_orders()
+        spec1 = sdp1.compute_spec_orders()
+        Aimg = spec['A'][0] + spec1['A'][0]
+        wave_pix = spec['A'][5]
+        wave_pos = spec['A'][3]
+        sens = spec['A'][6]
+        sh = Aimg.shape
+        spec_pix = np.zeros(sh[1])
+        for i in range(sh[1]):
+            spec_pix[i] = sum(Aimg[:, i])
+
+
+        wave_flux = np.zeros(wave_pix.shape[0])
+        for i in np.arange(1, wave_pix.shape[0] - 1):
+            w = wave_pix[i]
+            thp_w = thp_i(w)
+            deltW = (w - wave_pix[i - 1]) / 2 + (wave_pix[i + 1] - w) / 2
+            f = spec_pix[wave_pos[0] - 1 + i]
+
+            if 6200 <= w <= 10000:
+                f = f / thp_w
+            else:
+                f = 0
+            wave_flux[i] = f / deltW
+
+        sdp2 = SpecDisperser(orig_img=starImg, xcenter=0, ycenter=0, origin=[100, 100], tar_spec=sed, band_start=6200,
+                             band_end=10000, isAlongY=0, conf=conff, gid=0)
+
+        spec2 = sdp2.compute_spec_orders()
+        Aimg2 = spec2['A'][0]
+
+        spec_pix2 = np.zeros(sh[1])
+        for i in range(sh[1]):
+            spec_pix2[i] = sum(Aimg2[:, i])
+
+        wave_flux2 = np.zeros(wave_pix.shape[0])
+        for i in np.arange(1, wave_pix.shape[0] - 1):
+            w = wave_pix[i]
+            thp_w = thp_i(w)
+            deltW = (w - wave_pix[i - 1]) / 2 + (wave_pix[i + 1] - w) / 2
+            f = spec_pix2[wave_pos[0] - 1 + i]
+
+            if 6200 <= w <= 10000:
+                f = f / thp_w
+            else:
+                f = 0
+            wave_flux2[i] = f / deltW
+
+        r1_i = interpolate.interp1d(wave_pix, wave_flux2)
+        r2_i = interpolate.interp1d(wave_pix, wave_flux)
+
+        print('Spec Splicing test')
+        self.assertTrue(r1_i(8000)-r2_i(8000) < np.abs(0.0001))
+
+        # self.assertTrue(fwhmx/deltLamda_pix*pix_scale - psf_fwhm  < np.abs(0.01))
+        # print('error is ',np.mean((wave_flux[ids][ids1] - sed_i(wave_pix[ids][ids1]))/sed_i(wave_pix[ids][ids1])))
+        # self.assertTrue(np.mean((wave_flux[ids][ids1] - sed_i(wave_pix[ids][ids1]))/sed_i(wave_pix[ids][ids1]))<0.004)
+        plt.figure()
+        plt.plot(wave_pix, wave_flux2)
+        plt.plot(wave_pix, wave_flux)
+        # plt.plot(sed['WAVELENGTH'], sed['FLUX'])
+        plt.xlim(6200, 10000)
+        plt.ylim(1, 4)
+        plt.yscale('log')
+        plt.xlabel('$\lambda$')
+        plt.ylabel('$F\lambda$')
+        plt.legend(['one spec', 'split in 8000 A'])
+        plt.show()
+
+
+
+    def test_double_disperse(self):
+        work_dir = "/public/home/fangyuedong/CSST_unittest/CSST/test/"
+        # data_dir = "/Volumes/Extreme SSD/SimData/"
+        data_dir = "/data/simudata/CSSOSDataProductsSims/data/"
+        configFn = '/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/csst-simulation/config/config_C6.yaml'
+        normFilterFn = "/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/csst-simulation/Catalog/data/SLOAN_SDSS.g.fits"
+        norm_star = Table.read(normFilterFn)
+        with open(configFn, "r") as stream:
+            try:
+                config = yaml.safe_load(stream)
+                for key, value in config.items():
+                    print(key + " : " + str(value))
+            except yaml.YAMLError as exc:
+                print(exc)
+        # config = Config.read_config(configFn)
+        # path_dict = Config.config_dir(config,work_dir=work_dir, data_dir=data_dir)
+
+
+        filter_param = FilterParam()
+        focal_plane = FocalPlane(survey_type=config["obs_setting"]["survey_type"])
+        chip = Chip(1, config=config)
+        filter_id, filter_type = chip.getChipFilter()
+        filt = Filter(filter_id=filter_id, filter_type=filter_type, filter_param=filter_param,
+                      ccd_bandpass=chip.effCurve)
+        tel = Telescope()
+
+        psf_model = PSFGauss(chip=chip)
+
+
+        wcs_fp = focal_plane.getTanWCS(float(config["obs_setting"]["ra_center"]), float(config["obs_setting"]["dec_center"]), float(config["obs_setting"]["image_rot"]) * galsim.degrees, chip.pix_scale)
+        chip.img = galsim.ImageF(chip.npix_x, chip.npix_y)
+        chip.img.setOrigin(chip.bound.xmin, chip.bound.ymin)
+        chip.img.wcs = wcs_fp
+
+        obj, pos_img = produceObj(2000,4500, chip,float(config["obs_setting"]["ra_center"]), float(config["obs_setting"]["dec_center"]), float(config["obs_setting"]["image_rot"]))
+        obj.drawObj_slitless(
+            tel=tel,
+            pos_img=pos_img,
+            psf_model=psf_model,
+            bandpass_list=filt.bandpass_sub_list,
+            filt=filt,
+            chip=chip,
+            g1=0,
+            g2=0,
+            exptime=150,
+            normFilter=norm_star)
+
+        obj, pos_img = produceObj(3685, 6500, chip,float(config["obs_setting"]["ra_center"]), float(config["obs_setting"]["dec_center"]), float(config["obs_setting"]["image_rot"]))
+        obj.drawObj_slitless(
+            tel=tel,
+            pos_img=pos_img,
+            psf_model=psf_model,
+            bandpass_list=filt.bandpass_sub_list,
+            filt=filt,
+            chip=chip,
+            g1=0,
+            g2=0,
+            exptime=150,
+            normFilter=norm_star)
+
+        obj, pos_img = produceObj(5000, 2500, chip, float(config["obs_setting"]["ra_center"]), float(config["obs_setting"]["dec_center"]), float(config["obs_setting"]["image_rot"]))
+        obj.drawObj_slitless(
+            tel=tel,
+            pos_img=pos_img,
+            psf_model=psf_model,
+            bandpass_list=filt.bandpass_sub_list,
+            filt=filt,
+            chip=chip,
+            g1=0,
+            g2=0,
+            exptime=150,
+            normFilter=norm_star)
+
+        print('Spec double disperse test')
+        from astropy.io import fits
+        fits.writeto('test.fits',chip.img.array, overwrite = True)
+
+        # plt.figure()
+        # plt.imshow(chip.img.array)
+        # plt.show()
+
+    def test_SLSImage_rotation(self):
+        from astropy.wcs import WCS
+        configFn = '/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/csst-simulation/config/config_C6.yaml'
+
+        with open(configFn, "r") as stream:
+            try:
+                config = yaml.safe_load(stream)
+                for key, value in config.items():
+                    print(key + " : " + str(value))
+            except yaml.YAMLError as exc:
+                print(exc)
+        chip = Chip(1, config=config)
+
+        ra=float(config["obs_setting"]["ra_center"])
+        dec=float(config["obs_setting"]["dec_center"])
+        pa=float(config["obs_setting"]["image_rot"])
+
+        header_wcs1 = generateExtensionHeader(
+            xlen=chip.npix_x,
+            ylen=chip.npix_y,
+            ra=ra,
+            dec=dec,
+            pa=pa,
+            gain=chip.gain,
+            readout=chip.read_noise,
+            dark=chip.dark_noise,
+            saturation=90000,
+            psize=chip.pix_scale,
+            row_num=chip.rowID,
+            col_num=chip.colID,
+            extName='raw', center_rot=0)
+
+        center = np.array([chip.npix_x / 2, chip.npix_y / 2])
+        h_wcs1 = WCS(header_wcs1)
+        x1, y1 = center + [100,0]
+        sky_1 = h_wcs1.pixel_to_world(x1,y1)
+
+        rot_angle = 1
+        header_wcs2 = generateExtensionHeader(
+            xlen=chip.npix_x,
+            ylen=chip.npix_y,
+            ra=ra,
+            dec=dec,
+            pa=pa,
+            gain=chip.gain,
+            readout=chip.read_noise,
+            dark=chip.dark_noise,
+            saturation=90000,
+            psize=chip.pix_scale,
+            row_num=chip.rowID,
+            col_num=chip.colID,
+            extName='raw', center_rot=rot_angle)
+
+        h_wcs2 = WCS(header_wcs2)
+        x2, y2 = h_wcs2.world_to_pixel(sky_1)
+        angle = getAngle132(x1,y1,0,x2,y2,0,center[0],center[1],0)
+        print(angle)
+        self.assertTrue(rot_angle - angle < np.abs(0.001))
+
+        rot_angle = 10
+        header_wcs2 = generateExtensionHeader(
+            xlen=chip.npix_x,
+            ylen=chip.npix_y,
+            ra=ra,
+            dec=dec,
+            pa=pa,
+            gain=chip.gain,
+            readout=chip.read_noise,
+            dark=chip.dark_noise,
+            saturation=90000,
+            psize=chip.pix_scale,
+            row_num=chip.rowID,
+            col_num=chip.colID,
+            extName='raw', center_rot=rot_angle)
+
+        h_wcs2 = WCS(header_wcs2)
+        x2, y2 = h_wcs2.world_to_pixel(sky_1)
+        angle = getAngle132(x1, y1, 0, x2, y2, 0, center[0], center[1], 0)
+        print(angle)
+        self.assertTrue(rot_angle - angle < np.abs(0.001))
+
+        rot_angle = 50
+        header_wcs2 = generateExtensionHeader(
+            xlen=chip.npix_x,
+            ylen=chip.npix_y,
+            ra=ra,
+            dec=dec,
+            pa=pa,
+            gain=chip.gain,
+            readout=chip.read_noise,
+            dark=chip.dark_noise,
+            saturation=90000,
+            psize=chip.pix_scale,
+            row_num=chip.rowID,
+            col_num=chip.colID,
+            extName='raw', center_rot=rot_angle)
+
+        h_wcs2 = WCS(header_wcs2)
+        x2, y2 = h_wcs2.world_to_pixel(sky_1)
+        angle = getAngle132(x1, y1, 0, x2, y2, 0, center[0], center[1], 0)
+        print(angle)
+        self.assertTrue(rot_angle - angle < np.abs(0.001))
+
+
+        chip = Chip(27, config=config)
+
+        ra = float(config["obs_setting"]["ra_center"])
+        dec = float(config["obs_setting"]["dec_center"])
+        pa = float(config["obs_setting"]["image_rot"])
+
+        header_wcs1 = generateExtensionHeader(
+            xlen=chip.npix_x,
+            ylen=chip.npix_y,
+            ra=ra,
+            dec=dec,
+            pa=pa,
+            gain=chip.gain,
+            readout=chip.read_noise,
+            dark=chip.dark_noise,
+            saturation=90000,
+            psize=chip.pix_scale,
+            row_num=chip.rowID,
+            col_num=chip.colID,
+            extName='raw', center_rot=0)
+
+        center = np.array([chip.npix_x / 2, chip.npix_y / 2])
+        h_wcs1 = WCS(header_wcs1)
+        x1, y1 = center + [100, 0]
+        sky_1 = h_wcs1.pixel_to_world(x1, y1)
+
+        rot_angle = 1
+        header_wcs2 = generateExtensionHeader(
+            xlen=chip.npix_x,
+            ylen=chip.npix_y,
+            ra=ra,
+            dec=dec,
+            pa=pa,
+            gain=chip.gain,
+            readout=chip.read_noise,
+            dark=chip.dark_noise,
+            saturation=90000,
+            psize=chip.pix_scale,
+            row_num=chip.rowID,
+            col_num=chip.colID,
+            extName='raw', center_rot=rot_angle)
+
+        h_wcs2 = WCS(header_wcs2)
+        x2, y2 = h_wcs2.world_to_pixel(sky_1)
+        angle = getAngle132(x1, y1, 0, x2, y2, 0, center[0], center[1], 0)
+        print(angle)
+        self.assertTrue(rot_angle - angle < np.abs(0.001))
+
+        rot_angle = 10
+        header_wcs2 = generateExtensionHeader(
+            xlen=chip.npix_x,
+            ylen=chip.npix_y,
+            ra=ra,
+            dec=dec,
+            pa=pa,
+            gain=chip.gain,
+            readout=chip.read_noise,
+            dark=chip.dark_noise,
+            saturation=90000,
+            psize=chip.pix_scale,
+            row_num=chip.rowID,
+            col_num=chip.colID,
+            extName='raw', center_rot=rot_angle)
+
+        h_wcs2 = WCS(header_wcs2)
+        x2, y2 = h_wcs2.world_to_pixel(sky_1)
+        angle = getAngle132(x1, y1, 0, x2, y2, 0, center[0], center[1], 0)
+        print(angle)
+        self.assertTrue(rot_angle - angle < np.abs(0.001))
+
+        rot_angle = 50
+        header_wcs2 = generateExtensionHeader(
+            xlen=chip.npix_x,
+            ylen=chip.npix_y,
+            ra=ra,
+            dec=dec,
+            pa=pa,
+            gain=chip.gain,
+            readout=chip.read_noise,
+            dark=chip.dark_noise,
+            saturation=90000,
+            psize=chip.pix_scale,
+            row_num=chip.rowID,
+            col_num=chip.colID,
+            extName='raw', center_rot=rot_angle)
+
+        h_wcs2 = WCS(header_wcs2)
+        x2, y2 = h_wcs2.world_to_pixel(sky_1)
+        angle = getAngle132(x1, y1, 0, x2, y2, 0, center[0], center[1], 0)
+        print(angle)
+        self.assertTrue(rot_angle - angle < np.abs(0.001))
+
+
+
+
+if __name__ == '__main__':
+    conff='/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/csst-simulation/ObservationSim/Instrument/data/sls_conf/CSST_GI2.conf'
+    throughputf='/Users/zhangxin/Work/SlitlessSim/CSST_SIM/CSST_C6/csst-simulation/ObservationSim/Instrument/data/sls_conf/GI.Throughput.1st.fits'
+
+    suit = unittest.TestSuite()
+    case1 = TestSpecDisperse('test_Specdistperse1',conff,throughputf)
+    suit.addTest(case1)
+    case2 = TestSpecDisperse('test_Specdistperse2', conff, throughputf)
+    suit.addTest(case2)
+    case3 = TestSpecDisperse('test_Specdistperse3', conff, throughputf)
+    suit.addTest(case3)
+    case4 = TestSpecDisperse('test_double_disperse', conff, throughputf)
+    suit.addTest(case4)
+    case5 = TestSpecDisperse('test_SLSImage_rotation')
+    suit.addTest(case5)
+
+    unittest.TextTestRunner(verbosity=2).run(suit)
+    # runner = unittest.TextTestRunner()
+    # runner.run(suit)
\ No newline at end of file

tests/test_Straylight.py

+import unittest
+from ObservationSim.Straylight import Straylight
+
+import numpy as np
+import math
+import astropy.constants as cons
+import galsim
+from astropy.table import Table
+from scipy import interpolate
+
+import matplotlib.pyplot as plt
+
+hubbleAverZodiacal = {'nuv':0.0035,'u':0.0163,'g':0.1109,'r':0.1471,'i':0.1568,'z':0.0953,'y':0.0283}
+hubbleAverEarthShine = {'nuv':0.00024,'u':0.0051,'g':0.0506,'r':0.0591,'i':0.0568,'z':0.0315,'y':0.0090}
+
+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 getAngle132(x1=0, y1=0, z1=0, x2=0, y2=0, z2=0, x3=0, y3=0, z3=0):
+    cosValue = 0;
+    angle = 0;
+
+    x11 = x1 - x3;
+    y11 = y1 - y3;
+    z11 = z1 - z3;
+
+    x22 = x2 - x3;
+    y22 = y2 - y3;
+    z22 = z2 - z3;
+
+    tt = np.sqrt((x11 * x11 + y11 * y11 + z11 * z11) * (x22 * x22 + y22 * y22 + z22 * z22));
+    if (tt == 0):
+        return 0;
+
+    cosValue = (x11 * x22 + y11 * y22 + z11 * z22) / tt;
+
+    if (cosValue > 1):
+        cosValue = 1;
+    if (cosValue < -1):
+        cosValue = -1;
+    angle = math.acos(cosValue);
+    return angle * 360 / (2 * math.pi);
+
+def calculateAnglePwithEarth(sat = np.array([0,0,0]), pointing = np.array([0,0,0]), sun = np.array([0,0,0])):
+    modSat = np.sqrt(sat[0]*sat[0] + sat[1]*sat[1]+sat[2]*sat[2])
+    modPoint = np.sqrt(pointing[0]*pointing[0] + pointing[1]*pointing[1] + pointing[2]*pointing[2])
+    withLocalZenithAngle = (pointing[0] * sat[0] + pointing[1] * sat[1] + pointing[2] * sat[2]) / (modPoint*modSat)
+
+    innerM_sat_sun = sat[0] * sun[0] + sat[1] * sun[1] + sat[2] * sun[2]
+    cosAngle = innerM_sat_sun / (modSat * cons.au.value/1000)
+    isInSunSide = 1
+    if (cosAngle < -0.3385737): #cos109.79
+        isInSunSide = -1;
+    elif cosAngle >= -0.3385737 and cosAngle <= 0.3385737:
+        isInSunSide = 0;
+
+    return math.acos(withLocalZenithAngle)*180/math.pi,isInSunSide
+
+class TestStraylight(unittest.TestCase):
+
+    def __init__(self, methodName='runTest',datFn = '', filter = 'i', grating = "GI"):
+        super(TestStraylight,self).__init__(methodName)
+        self.pointingData = np.loadtxt(datFn, dtype=np.double)
+        self.filter = filter
+        self.grating = grating
+
+
+    def test_EarthShineFilter(self):
+        d_sh = self.pointingData.shape
+        sl_e_pix = np.zeros([d_sh[0],3],dtype=np.double)
+
+        for i in np.arange(d_sh[0]):
+            # if i > 50:
+            #     continue
+            ju = self.pointingData[i, 5]
+            # pointing = transRaDec2D(self.pointingData[i, 0], self.pointingData[i, 1])
+            # print(ju, pointing, surveylist[i,3:9])
+            sl = Straylight(jtime=ju, sat_pos=self.pointingData[i, 6:9], pointing_radec=np.array([self.pointingData[i, 0], self.pointingData[i, 1]]),sun_pos=self.pointingData[i,9:12])
+            e1, py = sl.calculateEarthShineFilter(filter=self.filter)
+            earthZenithAngle, isInSunSide = calculateAnglePwithEarth(sat=self.pointingData[i, 6:9], pointing= sl.pointing, sun=self.pointingData[i,9:12])
+            # e2, _ = sl.calculateZodiacalFilter2(filter='i', sun_pos=sl.sun_pos)
+            # e3 = sl.calculateStarLightFilter(filter='i', pointYaxis=py)
+            # e_all = sl.calculateStrayLightFilter(filter='i')
+            # s_pix, spec = sl.calculateStrayLightGrating(grating='GI')
+            sl_e_pix[i,0] = e1
+            sl_e_pix[i, 1] = earthZenithAngle
+            sl_e_pix[i, 2] = isInSunSide
+        median  = np.median(sl_e_pix[:,0])
+        print(' average Earthshine %s: %e' % (self.filter, median))
+        self.assertTrue(median-hubbleAverEarthShine[self.filter] < 0.1)
+        plt.figure()
+        ids1 = sl_e_pix[:, 2] == 1
+        ids2 = sl_e_pix[:, 2] != 1
+        plt.plot(sl_e_pix[ids1, 0], sl_e_pix[ids1, 1], 'r.')
+        plt.plot(sl_e_pix[ids2, 0], sl_e_pix[ids2, 1], 'b.')
+        plt.legend(['In Sun Side', 'In Earths shadow'])
+        plt.xlabel('straylight-earthshine(e-/pixel/s)')
+        plt.ylabel('Angle with local zenith(degree)')
+        plt.show()
+
+    def test_ZodiacalFilter(self):
+        d_sh = self.pointingData.shape
+        sl_e_pix = np.zeros([d_sh[0],2],dtype=np.double)
+
+        for i in np.arange(d_sh[0]):
+            ju = self.pointingData[i, 5]
+            sl = Straylight(jtime=ju, sat_pos=self.pointingData[i, 6:9], pointing_radec=np.array([self.pointingData[i, 0], self.pointingData[i, 1]]),sun_pos=self.pointingData[i,9:12])
+            e1, _ = sl.calculateZodiacalFilter2(filter=self.filter, sun_pos=sl.sun_pos)
+            sl_e_pix[i,0] = e1
+            sl_e_pix[i,1] = getAngle132(x1=self.pointingData[i,9], y1=self.pointingData[i,10], z1=self.pointingData[i,11], x2=sl.pointing[0],
+                                        y2=sl.pointing[1], z2=sl.pointing[2], x3=0, y3=0, z3=0)
+        plt.figure()
+        plt.plot(sl_e_pix[:, 0], sl_e_pix[:, 1], 'r.')
+        plt.xlabel('straylight-zodiacal(e-/pixel/s)')
+        plt.ylabel('Angle between pointing and sun(degree)')
+        plt.show()
+        median  = np.median(sl_e_pix[:,0])
+        print(' average Zodiacal %s: %f' % (self.filter, median))
+        self.assertTrue(median-hubbleAverZodiacal[self.filter] < 0.1)
+
+    def test_StarFilter(self):
+        d_sh = self.pointingData.shape
+        sl_e_pix = np.zeros(d_sh[0],dtype=np.double)
+
+        tnum = 10
+        for i in np.arange(tnum):
+            # if i > 50:
+            #     continue
+            ju = self.pointingData[i, 5]
+            # pointing = transRaDec2D(self.pointingData[i, 0], self.pointingData[i, 1])
+            # print(ju, pointing, surveylist[i,3:9])
+            sl = Straylight(jtime=ju, sat_pos=self.pointingData[i, 6:9], pointing_radec=np.array([self.pointingData[i, 0], self.pointingData[i, 1]]),sun_pos=self.pointingData[i,9:12])
+            e1, py = sl.calculateEarthShineFilter(filter=self.filter)
+            # e2, _ = sl.calculateZodiacalFilter2(filter='i', sun_pos=sl.sun_pos)
+            e3 = sl.calculateStarLightFilter(filter=self.filter, pointYaxis=py)
+            # e_all = sl.calculateStrayLightFilter(filter='i')
+            # s_pix, spec = sl.calculateStrayLightGrating(grating='GI')
+            sl_e_pix[i] = e3
+        median  = np.median(sl_e_pix[0:tnum])
+        print(' average Earthshine %s: %e' % (self.filter, median))
+        self.assertTrue(median-hubbleAverEarthShine[self.filter] < 0.2)
+
+    def test_GratingStraylight(self):
+        d_sh = self.pointingData.shape
+        sl_e_pix = np.zeros(d_sh[0],dtype=np.double)
+
+        tnum = 10
+        for i in np.arange(tnum):
+            # if i > 50:
+            #     continue
+            ju = self.pointingData[i, 5]
+            # pointing = transRaDec2D(self.pointingData[i, 0], self.pointingData[i, 1])
+            # print(ju, pointing, surveylist[i,3:9])
+            sl = Straylight(jtime=ju, sat_pos=self.pointingData[i, 6:9], pointing_radec=np.array([self.pointingData[i, 0], self.pointingData[i, 1]]),sun_pos=self.pointingData[i,9:12])
+            # e1, py = sl.calculateEarthShineFilter(filter=self.filter)
+            # e2, _ = sl.calculateZodiacalFilter2(filter='i', sun_pos=sl.sun_pos)
+            # e3 = sl.calculateStarLightFilter(filter=self.filter, pointYaxis=py)
+            # e_all = sl.calculateStrayLightFilter(filter='i')
+            s_pix, spec = sl.calculateStrayLightGrating(grating=self.grating)
+            sl_e_pix[i] = s_pix
+        plt.figure()
+        plt.plot(spec['WAVELENGTH'], spec['FLUX'], 'r')
+        plt.xlabel('WAVELENGTH')
+        plt.ylabel('F$\lambda$(erg/s/cm2/A/arcsec2)')
+        plt.xlim(2000,10000)
+        plt.show()
+        median  = np.median(sl_e_pix[0:tnum])
+        print(' average Earthshine %s: %e' % (self.grating, median))
+        self.assertTrue(median < 0.8)
+
+
+
+
+
+if __name__ == '__main__':
+
+    suit = unittest.TestSuite()
+    # case1 = TestStraylight('test_EarthShineFilter',datFn = 'Straylight_test.dat', filter = 'i')
+    # suit.addTest(case1)
+    # case2 = TestStraylight('test_ZodiacalFilter',datFn = 'Straylight_test.dat',filter = 'i')
+    # suit.addTest(case2)
+    # case3 = TestStraylight('test_StarFilter', datFn='Straylight_test.dat', filter='i')
+    # suit.addTest(case3)
+    case4 = TestStraylight('test_GratingStraylight', datFn='Straylight_test.dat', grating = 'GI')
+    suit.addTest(case4)
+    unittest.TextTestRunner(verbosity=2).run(suit)
\ No newline at end of file