Python Bandpass.multiplyThroughputs方法代码示例

# 需要导入模块: from lsst.sims.photUtils import Bandpass [as 别名]
# 或者: from lsst.sims.photUtils.Bandpass import multiplyThroughputs [as 别名]
def buildMirror(mirrorDir, addLosses=True):
    """
    Build a mirror throughput curve.
    Assumes there are *Losses.dat subdirectory with loss files
       and a m*_Ideal.dat file with the mirror throughput.
    Returns a bandpass object.
    If addLosses is True, the *_Ideal.dat file is multiplied by the *_Losses/*.dat files.
    """
    # Read the mirror reflectance curve.
    mirrorfile = glob(os.path.join(mirrorDir, 'm*Ideal.dat'))
    if len(mirrorfile) != 1:
        raise ValueError('Expected a single mirror file in directory %s, found: ' %mirrorDir, mirrorfile)
    mirrorfile = mirrorfile[0]
    mirror = Bandpass()
    mirror.readThroughput(mirrorfile)
    if addLosses:
        loss = _readLosses(mirrorDir)
        wavelen, sb = mirror.multiplyThroughputs(loss.wavelen, loss.sb)
        mirror.setBandpass(wavelen, sb)
    # Verify that no values go significantly below zero.
    belowzero = np.where(mirror.sb < 0)
    # If there are QE values significantly < 0, raise an exception.
    if mirror.sb[belowzero] < belowZeroThreshhold:
        raise ValueError('Found values in mirror response significantly below zero')
    # If they are just small errors in interpolation, set to zero.
    mirror.sb[belowzero] = 0
    return mirror

# 需要导入模块: from lsst.sims.photUtils import Bandpass [as 别名]
# 或者: from lsst.sims.photUtils.Bandpass import multiplyThroughputs [as 别名]
def buildVendorDetector(vendorDir, addLosses=True):
    """
    Builds a detector response from the files in vendorDir, by reading the *_QE.dat
      and *_Losses subdirectory for a single version of the detector.
    Returns a Bandpass object.
    If addLosses is True, the QE curve is multiplied by the losses in the *Losses.dat files.
    If addLosses is False, the QE curve does not have any losses included.
    """
    # Read the QE file.
    qefile = glob(os.path.join(vendorDir, '*_QE.dat'))
    if len(qefile) != 1:
        raise ValueError('Expected a single QE file in this directory, found: ', qefile)
    qefile = qefile[0]
    qe = Bandpass()
    qe.readThroughput(qefile)
    if addLosses:
        loss = _readLosses(vendorDir)
        wavelength, sb = qe.multiplyThroughputs(loss.wavelen, loss.sb)
        qe.setBandpass(wavelength, sb)
    # Verify that no values go significantly below zero.
    belowzero = np.where(qe.sb < 0)
    # If there are QE values significantly < 0, raise an exception.
    if qe.sb[belowzero] < belowZeroThreshhold:
        raise ValueError('Found values in QE response significantly below zero.')
    # If they are just small errors in interpolation, set to zero.
    qe.sb[belowzero] = 0
    return qe

# 需要导入模块: from lsst.sims.photUtils import Bandpass [as 别名]
# 或者: from lsst.sims.photUtils.Bandpass import multiplyThroughputs [as 别名]
def buildLens(lensDir, addLosses=True):
    """
    Build the lens throughput curve from the files in lensDir.
    Returns a bandpass object.
    The coatings for the lens are in *_Coatings, the loss files are in *_Losses.
    The borosilicate glass throughput is in l*_Glass.dat; this file is smoothed using the
     savitzsky_golay function.
    The glass response is multiplied by the coatings and (if addLosses is True),
      also the loss curves.
    """
    lens = Bandpass()
    # Read the glass base file.
    glassfile = glob(os.path.join(lensDir, 'l*_Glass.dat'))
    if len(glassfile) != 1:
        raise ValueError('Expected a single glass file in this directory, found: ', glassfile)
    glassfile = glassfile[0]
    glass = Bandpass()
    glass.readThroughput(glassfile)
    # Smooth the glass response.
    smoothSb = savitzky_golay(glass.sb, 31, 3)
    lens = Bandpass()
    lens.setBandpass(glass.wavelen, smoothSb)
    # Read the broad band antireflective (BBAR) coatings files.
    bbars = _readCoatings(lensDir)
    # Multiply the bbars by the glass.
    wavelen, sb = lens.multiplyThroughputs(bbars.wavelen, bbars.sb)
    lens.setBandpass(wavelen, sb)
    # Add losses.
    if addLosses:
        loss = _readLosses(lensDir)
        wavelen, sb = lens.multiplyThroughputs(loss.wavelen, loss.sb)
        lens.setBandpass(wavelen, sb)
    # Verify that no values go significantly below zero.
    belowzero = np.where(lens.sb < 0)
    # If there are QE values significantly < 0, raise an exception.
    if lens.sb[belowzero] < belowZeroThreshhold:
        raise ValueError('Found values in lens throughput significantly below zero.')
    # If they are just small errors in interpolation, set to zero.
    lens.sb[belowzero] = 0
    return lens