Source code for rubin_sim.phot_utils.bandpass

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__all__ = ("Bandpass", "rubin_bandpasses")

import gzip
import os
import warnings

import numpy as np
import scipy.interpolate as interpolate

from rubin_sim.data import get_data_dir

from .physical_parameters import PhysicalParameters
from .sed import Sed


[docs] def rubin_bandpasses(): """Return the standard expected Rubin filter bandpasses.""" filterlist = ["u", "g", "r", "i", "z", "y"] dd = get_data_dir() filter_dict = {} for f in filterlist: filter_dict[f] = Bandpass() filter_dict[f].read_throughput(os.path.join(dd, "throughputs", "baseline", f"total_{f}.dat")) return filter_dict
[docs] class Bandpass: """ Hold and use telescope throughput curves. Parameters ---------- wavelen : `np.ndarray`, (N,) Wavelength array in nm. sb : `np.ndarray`, (N,) Throughput array (fraction, 0-1). sampling_warning : `float` If wavelength sampling lower than this, throw a warning because it might provide accurate magnitudes due to how magnitudes are calculated in Sed (nm). """ def __init__(self, wavelen=None, sb=None, sampling_warning=0.2): self._phys_params = PhysicalParameters() self.sampling_warning = sampling_warning self.wavelen = None self.sb = None self.phi = None self.bandpassname = None if (wavelen is not None) and (sb is not None): self.set_bandpass(wavelen, sb) return
[docs] def set_bandpass(self, wavelen, sb): """ Populate bandpass data with wavelen/sb arrays. Phi set to None. Parameters ---------- wavelen : `np.ndarray`, (N,) Wavelength array in nm. sb : `np.ndarray`, (N,) Throughput array (fraction, 0-1). Raises ------ ValueError Raised if ``wavelen`` and ``sb`` have different length. """ # Check data type. if (isinstance(wavelen, np.ndarray) is False) or (isinstance(sb, np.ndarray) is False): raise ValueError("Wavelen and sb arrays must be numpy arrays.") # Check data matches in length. if len(wavelen) != len(sb): raise ValueError("Wavelen and sb arrays must have the same length.") self.wavelen = np.copy(wavelen) self.phi = None self.sb = np.copy(sb) self.bandpassname = "FromArrays"
[docs] def imsim_bandpass(self, imsimwavelen=500.0, wavelen_min=300, wavelen_max=1150, wavelen_step=0.1): """ Populate bandpass data with sb=0 everywhere except at imsimwavelen. Sets wavelen/sb, with grid min/max/step as Parameters. """ # Set up arrays. self.wavelen = np.arange( wavelen_min, wavelen_max + wavelen_step, wavelen_step, dtype="float", ) self.phi = None # Set sb. self.sb = np.zeros(len(self.wavelen), dtype="float") self.sb[abs(self.wavelen - imsimwavelen) < wavelen_step / 2.0] = 1.0 self.bandpassname = "IMSIM"
[docs] def read_throughput(self, filename): """ Populate bandpass data with data (wavelen/sb) read from file. Sets wavelen/sb. Does NOT set phi. """ # Set self values to None in case of file read error. self.wavelen = None self.phi = None self.sb = None # Check for filename error. # If given list of filenames, # pass to (and return from) read_throughputList. if isinstance(filename, list): warnings.warn( "Was given list of files, instead of a single file. Using read_throughputList instead" ) self.read_throughput_list(component_list=filename) # Filename is single file, now try to open file and read data. try: if filename.endswith(".gz"): f = gzip.open(filename, "rt") else: f = open(filename, "r") except IOError: try: if filename.endswith(".gz"): f = open(filename[:-3], "r") else: f = gzip.open(filename + ".gz", "rt") except IOError: raise IOError("The throughput file %s does not exist" % (filename)) # The throughput file should have [wavelength(A), throughput(Sb)] wavelen = [] sb = [] for line in f: if line.startswith("#") or line.startswith("$") or line.startswith("!"): continue values = line.split() if len(values) < 2: continue if (values[0] == "$") or (values[0] == "#") or (values[0] == "!"): continue wavelen.append(float(values[0])) sb.append(float(values[1])) f.close() self.bandpassname = filename # Set up wavelen/sb. self.wavelen = np.array(wavelen, dtype="float") self.sb = np.array(sb, dtype="float") # Check that wavelength is monotonic increasing and # non-repeating in wavelength. (Sort on wavelength). if len(self.wavelen) != len(np.unique(self.wavelen)): raise ValueError("The wavelength values in file %s are non-unique." % (filename)) # Sort values. p = self.wavelen.argsort() self.wavelen = self.wavelen[p] self.sb = self.sb[p]
[docs] def read_throughput_list( self, component_list=( "detector.dat", "lens1.dat", "lens2.dat", "lens3.dat", "m1.dat", "m2.dat", "m3.dat", "atmos_std.dat", ), root_dir=".", wavelen_min=300, wavelen_max=1150, wavelen_step=0.1, ): """ Populate bandpass data by reading from a series of files containing wavelen/Sb data. Multiplies throughputs (sb) from each file to give a final bandpass throughput. Sets wavelen/sb, with grid min/max/step as Parameters. Does NOT set phi. """ # ComponentList = names of files in that directory. # A typical component list of all files to build final component list, # including filter, might be: # ['detector.dat', 'lens1.dat', 'lens2.dat', 'lens3.dat', # 'm1.dat', 'm2.dat', 'm3.dat', 'atmos_std.dat', 'ideal_g.dat'] # # Set up wavelen/sb on grid. self.wavelen = np.arange( wavelen_min, wavelen_max + wavelen_step / 2.0, wavelen_step, dtype="float", ) self.phi = None self.sb = np.ones(len(self.wavelen), dtype="float") # Set up a temporary bandpass object to hold data from each file. tempbandpass = Bandpass() for component in component_list: # Read data from file. with warnings.catch_warnings(): warnings.simplefilter("ignore") tempbandpass.read_throughput(os.path.join(root_dir, component)) tempbandpass.resample_bandpass( wavelen_min=wavelen_min, wavelen_max=wavelen_max, wavelen_step=wavelen_step, ) # Multiply self by new sb values. self.sb = self.sb * tempbandpass.sb self.bandpassname = "".join(component_list)
def get_bandpass(self): wavelen = np.copy(self.wavelen) sb = np.copy(self.sb) return wavelen, sb # utilities
[docs] def check_use_self(self, wavelen, sb): """ Simple utility to check if should be using self.wavelen/sb or passed arrays. Useful for other methods in this class. Also does data integrity check on wavelen/sb if not self. """ update_self = False if (wavelen is None) or (sb is None): # Then one of the arrays was not passed - check if true for both. if (wavelen is not None) or (sb is not None): # Then only one of the arrays was passed - raise exception. raise ValueError("Must either pass *both* wavelen/sb pair, or use self defaults") # Okay, neither wavelen or sb was passed in - using self only. update_self = True else: # Both of the arrays were passed in - check their validity. if (isinstance(wavelen, np.ndarray) is False) or (isinstance(sb, np.ndarray) is False): raise ValueError("Must pass wavelen/sb as numpy arrays") if len(wavelen) != len(sb): raise ValueError("Must pass equal length wavelen/sb arrays") return update_self
[docs] def resample_bandpass( self, wavelen=None, sb=None, wavelen_min=300, wavelen_max=1150, wavelen_step=0.1, ): """ Resamples wavelen/sb (or self.wavelen/sb) onto grid defined by min/max/step. Either returns wavelen/sb (if given those arrays) or updates wavelen / Sb in self. If updating self, resets phi to None. """ # Check wavelength limits. wavelen_min = wavelen_min wavelen_max = wavelen_max wavelen_step = wavelen_step # Is method acting on self.wavelen/sb or passed in wavelen/sb? update_self = (wavelen is None) & (sb is None) if update_self: wavelen = self.wavelen sb = self.sb # Now, on with the resampling. if (wavelen.min() > wavelen_max) or (wavelen.max() < wavelen_min): raise Exception("No overlap between known wavelength range and desired wavelength range.") # Set up gridded wavelength. wavelen_grid = np.arange(wavelen_min, wavelen_max + wavelen_step / 2.0, wavelen_step, dtype="float") # Do the interpolation of wavelen/sb onto the grid. # (note wavelen/sb type failures will die here). f = interpolate.interp1d(wavelen, sb, fill_value=0, bounds_error=False) sb_grid = f(wavelen_grid) # Update self values if necessary. if update_self: self.phi = None self.wavelen = wavelen_grid self.sb = sb_grid return return wavelen_grid, sb_grid
# more complicated bandpass functions
[docs] def sb_tophi(self): """ Calculate and set phi - the normalized system response. This function only updates self.phi. """ # The definition of phi = (Sb/wavelength)/\int(Sb/wavelength)dlambda. self.phi = self.sb / self.wavelen # Normalize phi so that the integral of phi is 1. norm = np.trapz(self.phi, x=self.wavelen) self.phi = self.phi / norm return
[docs] def multiply_throughputs(self, wavelen_other, sb_other): """ Multiply self.sb by another wavelen/sb pair, return wavelen/sb arrays. The returned arrays will be gridded like this bandpass. This method does not affect self. """ # Resample wavelen_other/sb_other to match this bandpass. if not np.all(self.wavelen == wavelen_other): wavelen_other, sb_other = self.resample_bandpass( wavelen=wavelen_other, sb=sb_other, wavelen_min=self.wavelen.min(), wavelen_max=self.wavelen.max(), wavelen_step=self.wavelen[1] - self.wavelen[0], ) # Make new memory copy of wavelen. wavelen_new = np.copy(self.wavelen) # Calculate new transmission - this is also new memory. sb_new = self.sb * sb_other return wavelen_new, sb_new
[docs] def calc_zp_t(self, photometric_parameters): """ Calculate the instrumental zeropoint for a bandpass. Parameters ---------- photometric_parameters : `PhotometricParameters` Details about the photometric response of the telescope. Defaults to LSST values. """ # ZP_t is the magnitude of a (F_nu flat) source which produced # 1 count per second. # This is often also known as the 'instrumental zeropoint'. # Set gain to 1 if want to explore photo-electrons rather than adu. # The typical LSST exposure time is 15s and this is default here, # but typical zp_t definition is for 1s. # SED class uses flambda in ergs/cm^2/s/nm, so need effarea in cm^2. # # Check dlambda value for integral. self.wavelen[1] - self.wavelen[0] # Set up flat source of arbitrary brightness, # but where the units of fnu are Jansky (for AB mag zeropoint = -8.9). flatsource = Sed() flatsource.set_flat_sed() adu = flatsource.calc_adu(self, phot_params=photometric_parameters) # Scale fnu so that adu is 1 count/expTime. flatsource.fnu = flatsource.fnu * (1 / adu) # Now need to calculate AB magnitude of the source with this fnu. if self.phi is None: self.sb_tophi() zp_t = flatsource.calc_mag(self) return zp_t
[docs] def calc_eff_wavelen(self): """ Calculate effective wavelengths for filters. """ # This is useful for summary numbers for filters. # Calculate effective wavelength of filters. if self.phi is None: self.sb_tophi() effwavelenphi = (self.wavelen * self.phi).sum() / self.phi.sum() effwavelensb = (self.wavelen * self.sb).sum() / self.sb.sum() return effwavelenphi, effwavelensb
[docs] def write_throughput(self, filename, print_header=None, write_phi=False): """ Write throughput to a file. """ # Useful if you build a throughput up from components # and need to record the combined value. f = open(filename, "w") # Print header. if print_header is not None: if not print_header.startswith("#"): print_header = "#" + print_header f.write(print_header) if write_phi: if self.phi is None: self.sb_tophi() print("# Wavelength(nm) Throughput(0-1) Phi", file=f) else: print("# Wavelength(nm) Throughput(0-1)", file=f) # Loop through data, printing out to file. for i in range(0, len(self.wavelen), 1): if write_phi: print(self.wavelen[i], self.sb[i], self.phi[i], file=f) else: print(self.wavelen[i], self.sb[i], file=f) f.close()