Write result to files
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@ -11,6 +11,8 @@ from .PixelMask import PixelMask
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import astropy.constants as const
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from logging import info, warning, debug, getLogger
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import enlighten
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import os
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import astropy.io.fits as fits
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class Imager(ASensor):
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@ -118,9 +120,13 @@ class Imager(ASensor):
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for exp_time_ in pbar(exp_time):
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self.__printDetails(signal_current * exp_time_, background_current * exp_time_, read_noise,
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dark_current * exp_time_, "t_exp=%.2f s: " % exp_time_.value)
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self.__output(signal_current * exp_time_, background_current * exp_time_, read_noise,
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dark_current * exp_time_, "texp_%.2f" % exp_time_.value)
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else:
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self.__printDetails(signal_current * exp_time, background_current * exp_time, read_noise,
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dark_current * exp_time, "t_exp=%.2f s: " % exp_time.value)
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self.__output(signal_current * exp_time, background_current * exp_time, read_noise,
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dark_current * exp_time, "texp_%.2f" % exp_time.value)
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# Return the value of the SNR, ignoring the physical units (electrons^0.5)
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return snr.value * u.dimensionless_unscaled
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@ -159,9 +165,13 @@ class Imager(ASensor):
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for snr_, exp_time_ in pbar(zip(snr, exp_time)):
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self.__printDetails(signal_current * exp_time_, background_current * exp_time_, read_noise,
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dark_current * exp_time_, "SNR=%.2f: " % snr_.value)
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self.__output(signal_current * exp_time_, background_current * exp_time_, read_noise,
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dark_current * exp_time_, "snr_%.2f" % snr_.value)
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else:
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self.__printDetails(signal_current * exp_time, background_current * exp_time, read_noise,
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dark_current * exp_time, "SNR=%.2f: " % snr.value)
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self.__output(signal_current * exp_time, background_current * exp_time, read_noise,
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dark_current * exp_time, "snr_%.2f" % snr.value)
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return exp_time
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@u.quantity_input(exp_time="time", snr=u.dimensionless_unscaled, target_brightness=u.mag)
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@ -196,12 +206,14 @@ class Imager(ASensor):
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unit='configurations'))
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for snr_, exp_time_, signal_current_lim_ in pbar(zip(snr, exp_time, signal_current_lim)):
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self.__printDetails(signal_current_lim_ * exp_time_, background_current * exp_time_, read_noise,
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dark_current * exp_time_,
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"SNR=%.2f t_exp=%.2f s: " % (snr_.value, exp_time_.value))
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dark_current * exp_time_, "SNR=%.2f t_exp=%.2f s: " % (snr_.value, exp_time_.value))
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self.__output(signal_current_lim_ * exp_time_, background_current * exp_time_, read_noise,
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dark_current * exp_time_, "snr_%.2f_texp_%.2f" % (snr_.value, exp_time_.value))
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else:
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self.__printDetails(signal_current_lim * exp_time, background_current * exp_time, read_noise,
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dark_current * exp_time,
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"SNR=%.2f t_exp=%.2f s: " % (snr.value, exp_time.value))
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dark_current * exp_time, "SNR=%.2f t_exp=%.2f s: " % (snr.value, exp_time.value))
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self.__output(signal_current_lim * exp_time, background_current * exp_time, read_noise,
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dark_current * exp_time, "snr_%.2f_texp_%.2f" % (snr.value, exp_time.value))
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return target_brightness - 2.5 * np.log10(signal_current_lim / signal_current.sum()) * u.mag
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@u.quantity_input(signal=u.electron, background=u.electron, read_noise=u.electron ** 0.5, dark=u.electron)
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@ -220,6 +232,8 @@ class Imager(ASensor):
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The read noise in electrons.
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dark : Quantity
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The electrons from the dark current in electrons.
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prefix : str
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The prefix to be used for printing
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Returns
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-------
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@ -241,7 +255,7 @@ class Imager(ASensor):
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@u.quantity_input(signal=u.electron, background=u.electron, read_noise=u.electron ** 0.5, dark=u.electron)
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def __output(self, signal: u.Quantity, background: u.Quantity, read_noise: u.Quantity,
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dark: u.Quantity, prefix: str = ""):
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dark: u.Quantity, name: str):
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"""
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Write the signal and the noise in electrons to files.
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@ -255,11 +269,55 @@ class Imager(ASensor):
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The read noise in electrons.
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dark : Quantity
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The electrons from the dark current in electrons.
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name : str
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The name of the configuration.
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Returns
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-------
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"""
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pass
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# Concatenate the paths
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path = os.path.join(self.__common_conf.output.path, name)
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try:
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os.mkdir(path)
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except FileExistsError:
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warning("Output directory '" + path + "' already exists.")
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# Calculate the indices of nonzero values and create a bounding rectangle
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y, x = np.nonzero(signal)
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y_min = min(y)
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y_max = max(y)
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x_min = min(x)
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x_max = max(x)
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# Write arrays to file
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if self.__common_conf.output.format.lower() == "csv":
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mes = "Range reduced to nonzero values.\nThe origin is in the top left corner, starting with 0.\n" + \
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"Column index range: %d - %d\nRow index range: %d - %d\n" % (y_min, y_max, x_min, x_max)
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np.savetxt(os.path.join(path, "signal.csv"), signal[y_min:(y_max + 1), x_min:(x_max + 1)].value,
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delimiter=",", header="Signal in electrons\n" + mes)
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np.savetxt(os.path.join(path, "background.csv"), background[y_min:(y_max + 1), x_min:(x_max + 1)].value,
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delimiter=",", header="Background in electrons\n" + mes)
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np.savetxt(os.path.join(path, "read_noise.csv"), read_noise[y_min:(y_max + 1), x_min:(x_max + 1)].value,
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delimiter=",", header="Read noise in electrons\n" + mes)
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np.savetxt(os.path.join(path, "dark_noise.csv"), dark[y_min:(y_max + 1), x_min:(x_max + 1)].value,
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delimiter=",", header="Dark noise in electrons\n" + mes)
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elif self.__common_conf.output.format.lower() == "fits":
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mes = "Range reduced to nonzero values. The origin is in the top left corner, starting with 0. " + \
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"Column index range: %d - %d Row index range: %d - %d " % (y_min, y_max, x_min, x_max)
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hdu = fits.PrimaryHDU(header=fits.Header(dict(COMMENT="Simulation data created by ESBO-ETC.",
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TELESCOP="ESBO-ETC")))
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signal_hdu = fits.ImageHDU(signal[y_min:(y_max + 1), x_min:(x_max + 1)].value, name="signal",
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header=fits.Header(dict(COMMENT="Signal in electrons. " + mes,
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TELESCOP="ESBO-ETC")))
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background_hdu = fits.ImageHDU(background[y_min:(y_max + 1), x_min:(x_max + 1)].value, name="background",
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header=fits.Header(dict(COMMENT="Background in electrons. " + mes,
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TELESCOP="ESBO-ETC")))
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read_noise_hdu = fits.ImageHDU(read_noise[y_min:(y_max + 1), x_min:(x_max + 1)].value, name="read noise",
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header=fits.Header(dict(COMMENT="Read noise in electrons. " + mes,
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TELESCOP="ESBO-ETC")))
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dark_hdu = fits.ImageHDU(dark[y_min:(y_max + 1), x_min:(x_max + 1)].value, name="dark noise",
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header=fits.Header(dict(COMMENT="Dark noise in electrons. " + mes,
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TELESCOP="ESBO-ETC")))
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hdul = fits.HDUList([hdu, signal_hdu, background_hdu, read_noise_hdu, dark_hdu])
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hdul.writeto(os.path.join(path, "results.fits"), overwrite=True)
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def __exposePixels(self) -> Tuple[u.Quantity, u.Quantity, u.Quantity, u.Quantity]:
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"""
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