Remove progress bar
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8127ee2c19
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@ -10,7 +10,6 @@ from ..SpectralQty import SpectralQty
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from .PixelMask import PixelMask
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from .PixelMask import PixelMask
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from ...lib.logger import logger
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from ...lib.logger import logger
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import astropy.constants as const
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import astropy.constants as const
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import enlighten
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import os
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import os
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import astropy.io.fits as fits
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import astropy.io.fits as fits
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@ -115,18 +114,11 @@ class Imager(ASensor):
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snr = signal_current.sum() * exp_time / np.sqrt(
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snr = signal_current.sum() * exp_time / np.sqrt(
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(signal_current + background_current + dark_current).sum() * exp_time + (read_noise ** 2).sum())
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(signal_current + background_current + dark_current).sum() * exp_time + (read_noise ** 2).sum())
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# Print information
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# Print information
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if exp_time.size > 1:
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for exp_time_ in exp_time if exp_time.size > 1 else [exp_time]:
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pbar = enlighten.get_manager().counter(**dict(total=len(exp_time), desc='SNR', unit='configurations'))
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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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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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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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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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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 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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return snr.value * u.dimensionless_unscaled
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@ -160,19 +152,11 @@ class Imager(ASensor):
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1 + current_ratio + np.sqrt((1 + current_ratio) ** 2 + 4 * (read_noise ** 2).sum() / snr ** 2)) / (
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1 + current_ratio + np.sqrt((1 + current_ratio) ** 2 + 4 * (read_noise ** 2).sum() / snr ** 2)) / (
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2 * signal_current_tot)
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2 * signal_current_tot)
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# Print information
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# Print information
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if exp_time.size > 1:
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for snr_, exp_time_ in zip(snr, exp_time) if snr.size > 1 else zip([snr], [exp_time]):
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pbar = enlighten.get_manager().counter(**dict(total=len(exp_time), desc='Exposure Time',
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unit='configurations'))
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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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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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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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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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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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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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@u.quantity_input(exp_time="time", snr=u.dimensionless_unscaled, target_brightness=u.mag)
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@ -203,21 +187,13 @@ class Imager(ASensor):
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snr ** 2 + 4 * (exp_time * (background_current.sum() + dark_current.sum()) +
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snr ** 2 + 4 * (exp_time * (background_current.sum() + dark_current.sum()) +
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(read_noise ** 2).sum()))) / (2 * exp_time)
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(read_noise ** 2).sum()))) / (2 * exp_time)
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# Print information
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# Print information
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if exp_time.size > 1:
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for snr_, exp_time_, signal_current_lim_ in zip(snr, exp_time, signal_current_lim) if snr.size > 1 else zip(
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pbar = enlighten.get_manager().counter(**dict(total=len(exp_time), desc='Sensitivity',
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[snr], [exp_time], [signal_current_lim]):
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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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self.__printDetails(signal_current_lim_ * exp_time_, background_current * exp_time_, read_noise,
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dark_current * exp_time_, "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 * signal_current_lim_ / signal_current.sum() * exp_time_,
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self.__output(signal_current * signal_current_lim_ / signal_current.sum() * exp_time_,
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background_current * exp_time_, read_noise, dark_current * exp_time_,
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background_current * exp_time_, read_noise, dark_current * exp_time_,
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"snr_%.2f_texp_%.2f" % (snr_.value, exp_time_.value))
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"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, "SNR=%.2f t_exp=%.2f s: " % (snr.value, exp_time.value))
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self.__output(signal_current * signal_current_lim / signal_current.sum() * exp_time,
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background_current * exp_time, read_noise, dark_current * exp_time,
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"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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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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@u.quantity_input(signal=u.electron, background=u.electron, read_noise=u.electron ** 0.5, dark=u.electron)
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