def testPhaseFoldTime(self):
time = np.arange(0, 2, 0.1)
# Simple.
tfold = util.phase_fold_time(time, period=1, t0=0.45)
expected = [
-0.45, -0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45,
-0.45, -0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45
]
self.assertSequenceAlmostEqual(expected, tfold)
# Large t0.
tfold = util.phase_fold_time(time, period=1, t0=1.25)
expected = [
-0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45, -0.45, -0.35,
-0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45, -0.45, -0.35
]
self.assertSequenceAlmostEqual(expected, tfold)
# Negative t0.
tfold = util.phase_fold_time(time, period=1, t0=-1.65)
expected = [
-0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45, -0.45,
-0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45, -0.45
]
self.assertSequenceAlmostEqual(expected, tfold)
# Negative time.
time = np.arange(-3, -1, 0.1)
tfold = util.phase_fold_time(time, period=1, t0=0.55)
expected = [
0.45, -0.45, -0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35,
0.45, -0.45, -0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35
]
self.assertSequenceAlmostEqual(expected, tfold)
def testPhaseFoldTime(self):
time = np.arange(0, 2, 0.1)
# Simple.
tfold = util.phase_fold_time(time, period=1, t0=0.45)
expected = [
-0.45, -0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45, -0.45,
-0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45
]
self.assertSequenceAlmostEqual(expected, tfold)
# Large t0.
tfold = util.phase_fold_time(time, period=1, t0=1.25)
expected = [
-0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45, -0.45, -0.35, -0.25,
-0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45, -0.45, -0.35
]
self.assertSequenceAlmostEqual(expected, tfold)
# Negative t0.
tfold = util.phase_fold_time(time, period=1, t0=-1.65)
expected = [
-0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45, -0.45, -0.35,
-0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45, -0.45
]
self.assertSequenceAlmostEqual(expected, tfold)
# Negative time.
time = np.arange(-3, -1, 0.1)
tfold = util.phase_fold_time(time, period=1, t0=0.55)
expected = [
0.45, -0.45, -0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35, 0.45,
-0.45, -0.35, -0.25, -0.15, -0.05, 0.05, 0.15, 0.25, 0.35
]
self.assertSequenceAlmostEqual(expected, tfold)
def phase_fold_and_sort_light_curve(time, flux, period, t0):
"""Phase folds a light curve and sorts by ascending time.
Args:
time: 1D NumPy array of time values.
flux: 1D NumPy array of flux values.
period: A positive real scalar; the period to fold over.
t0: The center of the resulting folded vector; this value is mapped to 0.
Returns:
folded_time: 1D NumPy array of phase folded time values in
[-period / 2, period / 2), where 0 corresponds to t0 in the original
time array. Values are sorted in ascending order.
folded_flux: 1D NumPy array. Values are the same as the original input
array, but sorted by folded_time.
"""
# Phase fold time.
time = util.phase_fold_time(time, period, t0)
# Sort by ascending time.
sorted_i = np.argsort(time)
time = time[sorted_i]
flux = flux[sorted_i]
return time, flux
def phase_fold_and_sort_light_curve(time, flux, period, t0):
"""Phase folds a light curve and sorts by ascending time.
Args:
time: 1D NumPy array of time values.
flux: 1D NumPy array of flux values.
period: A positive real scalar; the period to fold over.
t0: The center of the resulting folded vector; this value is mapped to 0.
Returns:
folded_time: 1D NumPy array of phase folded time values in
[-period / 2, period / 2), where 0 corresponds to t0 in the original
time array. Values are sorted in ascending order.
folded_flux: 1D NumPy array. Values are the same as the original input
array, but sorted by folded_time.
"""
# Phase fold time.
time = util.phase_fold_time(time, period, t0)
# Sort by ascending time.
sorted_i = np.argsort(time)
time = time[sorted_i]
flux = flux[sorted_i]
return time, flux
def phase_fold_and_sort_light_curve(time, flux, mask, period, t0):
if not len(time):
return np.array([]), np.array([]), np.array([]), np.array([])
# Phase fold time.
time, fold_num = util.phase_fold_time(time, period, t0)
# Sort by ascending time.
sorted_i = np.argsort(time)
time = time[sorted_i]
flux = flux[sorted_i]
mask = mask[sorted_i]
fold_num = fold_num[sorted_i]
return time, flux, fold_num, mask
def get_spline_mask(time, period, t0, tdur):
phase, _ = util.phase_fold_time(time, period, t0)
outtran = (np.abs(phase) > (tdur / 2))
return outtran
