Commit 0149014e authored by yuedong0607's avatar yuedong0607
Browse files

fix calls in SpecDisperser.py

parent 04dd8634

observation_sim/instruments/chip/chip_utils.py

+1 −0
Original line number Diff line number Diff line
@@ -2,6 +2,7 @@ import os 
import galsim

import ctypes

import numpy as np

from scipy import stats

from astropy.io import fits



from observation_sim.instruments.chip import effects

observation_sim/mock_objects/SpecDisperser/SpecDisperser.py

+15 −15
Original line number Diff line number Diff line
@@ -163,10 +163,10 @@ class SpecDisperser(object): 
        )



        # Account for pixel centering of the trace

        yfrac_beam = ytrace_beam - floor(ytrace_beam + 0.5)

        yfrac_beam = ytrace_beam - np.floor(ytrace_beam + 0.5)



        ysens = lam_beam * 0

        lam_index = argsort(lam_beam)

        lam_index = np.argsort(lam_beam)

        conf_sens = self.grating_conf.sens[beam]



        lam_intep = np.linspace(
@@ -199,19 +199,19 @@ class SpecDisperser(object): 
        sensitivity_beam = ysens



        len_spec_x = len(dx)

        len_spec_y = int(abs(ceil(ytrace_beam[-1]) - floor(ytrace_beam[0])) + 1)

        len_spec_y = int(abs(np.ceil(ytrace_beam[-1]) - np.floor(ytrace_beam[0])) + 1)



        beam_sh = (self.img_sh[0] + len_spec_y, self.img_sh[1] + len_spec_x)

        modelf = zeros(product(beam_sh), dtype=float)

        modelf = np.zeros(np.product(beam_sh), dtype=float)

        model = modelf.reshape(beam_sh)

        idx = np.arange(modelf.size, dtype=int64).reshape(beam_sh)

        x0 = array((self.thumb_y, self.thumb_x), dtype=int64)

        idx = np.arange(modelf.size, dtype=np.int64).reshape(beam_sh)

        x0 = np.array((self.thumb_y, self.thumb_x), dtype=np.int64)



        dxpix = dx - dx[0] + x0[1]



        dyc = cast[int](np.floor(ytrace_beam + 0.5))

        dyc = np.cast[int](np.floor(ytrace_beam + 0.5))



        # dypix = cast[int](np.floor(ytrace_beam - dyc[0] + x0[0] + 0.5))

        # dypix = np.cast[int](np.floor(ytrace_beam - dyc[0] + x0[0] + 0.5))

        dypix = dyc - dyc[0] + x0[0]



        frac_ids = yfrac_beam < 0
@@ -223,7 +223,7 @@ class SpecDisperser(object): 


        nonz = sensitivity_beam != 0



        origin_in = zeros_like(self.origin)

        origin_in = np.zeros_like(self.origin)

        dx0_in = dx[0]

        dy0_in = dyc[0]

        if self.isAlongY == 1:
@@ -242,9 +242,9 @@ class SpecDisperser(object): 
        if self.flat_cube is None:

            beam_flat = None

        else:

            beam_flat = zeros([len(modelf), len(self.flat_cube)])

            beam_flat = np.zeros([len(modelf), len(self.flat_cube)])



            sub_flat_cube = zeros([len(self.flat_cube), beam_sh[0], beam_sh[1]])

            sub_flat_cube = np.zeros([len(self.flat_cube), beam_sh[0], beam_sh[1]])

            sub_flat_cube[0] = sub_flat_cube[0] + 1.0



            overlap_flag = 1
@@ -278,7 +278,7 @@ class SpecDisperser(object): 
                    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 np.arange(0, len(self.flat_cube), 1):

                beam_flat[:, i] = sub_flat_cube[i].flatten()

        #            beam_flat = zeros([len(modelf), len(self.flat_cube)])

        #            flat_sh = self.flat_cube[0].shape
@@ -299,8 +299,8 @@ class SpecDisperser(object): 
            sensitivity_beam[nonz],

            modelf,

            x0,

            array(self.img_sh, dtype=int64),

            array(beam_sh, dtype=int64),

            np.array(self.img_sh, dtype=np.int64),

            np.array(beam_sh, dtype=np.int64),

            beam_flat,

            lam_beam[lam_index][nonz],

        )
@@ -331,7 +331,7 @@ class SpecDisperser(object): 
        sens_file_name = conffile[0:-5] + "_sensitivity_" + orders[beam] + ".fits"

        if os.path.exists(sens_file_name) is False:

            senstivity_out = Table(

                array([w, sens]).T, names=("WAVELENGTH", "SENSITIVITY")

                np.array([w, sens]).T, names=("WAVELENGTH", "SENSITIVITY")

            )

            senstivity_out.write(sens_file_name, format="fits")

observation_sim/sim_steps/add_ghost.py

+1 −0
Original line number Diff line number Diff line 
import galsim

import traceback



from observation_sim.mock_objects import Ghost

from observation_sim.psf import FieldDistortion

pyproject.toml

+2 −1
Original line number Diff line number Diff line
@@ -71,12 +71,13 @@ include = ["observation_sim*"] 
testpaths = ["tests"]



[tool.ruff]

preview = true

line-length = 88

target-version = "py311"



[tool.ruff.lint]

select = ["E", "F", "W"]  # E/W = PEP8, F = pyflakes

ignore = ["E501"]        # example: ignore line length if using black

ignore = ["E501", "E203"]        # example: ignore line length if using black



[tool.ruff.format]

quote-style = "double"