def generate_view(time, flux, num_bins, bin_width, t_min, t_max,
normalize=True):
"""Generates a view of a phase-folded light curve using a median filter.
Args:
time: 1D array of time values, sorted in ascending order.
flux: 1D array of flux values.
num_bins: The number of intervals to divide the time axis into.
bin_width: The width of each bin on the time axis.
t_min: The inclusive leftmost value to consider on the time axis.
t_max: The exclusive rightmost value to consider on the time axis.
normalize: Whether to center the median at 0 and minimum value at -1.
Returns:
1D NumPy array of size num_bins containing the median flux values of
uniformly spaced bins on the phase-folded time axis.
"""
view = median_filter.median_filter(time, flux, num_bins, bin_width, t_min,
t_max)
if normalize:
view -= np.median(view)
view /= np.abs(np.min(view))
return view
def generate_view(time, flux, num_bins, bin_width, t_min, t_max,
normalize=True):
"""Generates a view of a phase-folded light curve using a median filter.
Args:
time: 1D array of time values, sorted in ascending order.
flux: 1D array of flux values.
num_bins: The number of intervals to divide the time axis into.
bin_width: The width of each bin on the time axis.
t_min: The inclusive leftmost value to consider on the time axis.
t_max: The exclusive rightmost value to consider on the time axis.
normalize: Whether to center the median at 0 and minimum value at -1.
Returns:
1D NumPy array of size num_bins containing the median flux values of
uniformly spaced bins on the phase-folded time axis.
"""
view = median_filter.median_filter(time, flux, num_bins, bin_width, t_min,
t_max)
if normalize:
view -= np.median(view)
view /= np.abs(np.min(view))
return view
def testWideBins(self):
x = np.array([-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6])
y = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13])
result = median_filter.median_filter(x,
y,
num_bins=5,
bin_width=6,
x_min=-7,
x_max=7)
np.testing.assert_array_equal([3, 4.5, 6.5, 8.5, 10.5], result)
def testBucketBoundaries(self):
x = np.array([-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6])
y = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13])
result = median_filter.median_filter(x,
y,
num_bins=5,
bin_width=2,
x_min=-5,
x_max=5)
np.testing.assert_array_equal([2.5, 4.5, 6.5, 8.5, 10.5], result)
def testNarrowBins(self):
x = np.array([-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6])
y = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13])
result = median_filter.median_filter(x,
y,
num_bins=5,
bin_width=1,
x_min=-4.5,
x_max=4.5)
np.testing.assert_array_equal([3, 5, 7, 9, 11], result)
def testEmptyBins(self):
x = np.array([-1, 0, 1])
y = np.array([1, 2, 3])
result = median_filter.median_filter(x,
y,
num_bins=5,
bin_width=2,
x_min=-5,
x_max=5)
np.testing.assert_array_equal([2, 2, 1.5, 3, 2], result)
def testMedian(self):
x = np.array([-4, -2, -2, 0, 0, 0, 2, 2, 2, 2, 3, 3, 3, 3, 3])
y = np.array([0, -1, 1, 4, 5, 6, 2, 2, 4, 4, 1, 1, 1, 1, -1])
result = median_filter.median_filter(x,
y,
num_bins=5,
bin_width=2,
x_min=-5,
x_max=5)
np.testing.assert_array_equal([0, 0, 5, 3, 1], result)
def testMultiSizeBins(self):
# Construct bins with size 0, 1, 2, 3, 4, 5, 10, respectively.
x = np.array([
1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6,
6
])
y = np.array([
0, -1, 1, 4, 5, 6, 2, 2, 4, 4, 1, 1, 1, 1, -1, 1, 2, 3, 4, 5, 6, 7, 8,
9, 10
])
result = median_filter.median_filter(
x, y, num_bins=7, bin_width=1, x_min=0, x_max=7)
np.testing.assert_array_equal([3, 0, 0, 5, 3, 1, 5.5], result)
def testMultiSizeBins(self):
# Construct bins with size 0, 1, 2, 3, 4, 5, 10, respectively.
x = np.array([
1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6,
6
])
y = np.array([
0, -1, 1, 4, 5, 6, 2, 2, 4, 4, 1, 1, 1, 1, -1, 1, 2, 3, 4, 5, 6, 7, 8,
9, 10
])
result = median_filter.median_filter(
x, y, num_bins=7, bin_width=1, x_min=0, x_max=7)
np.testing.assert_array_equal([3, 0, 0, 5, 3, 1, 5.5], result)
def testNarrowBins(self):
x = np.array([-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6])
y = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13])
result = median_filter.median_filter(
x, y, num_bins=5, bin_width=1, x_min=-4.5, x_max=4.5)
np.testing.assert_array_equal([3, 5, 7, 9, 11], result)
def testErrors(self):
# x size less than 2.
x = [1]
y = [2]
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=1, x_min=0, x_max=2)
# x and y not the same size.
x = [1, 2]
y = [4, 5, 6]
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=1, x_min=0, x_max=2)
# x_min not less than x_max.
x = [1, 2, 3]
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=1, x_min=-1, x_max=-1)
# x_min greater than the last element of x.
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=0.25, x_min=3.5, x_max=4)
# bin_width nonpositive.
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=0, x_min=1, x_max=3)
# bin_width greater than or equal to x_max - x_min.
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=1, x_min=1.5, x_max=2.5)
# num_bins less than 2.
x = [1, 2, 3]
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=1, bin_width=1, x_min=0, x_max=2)
def testDefaultArgs(self): x = np.array([-4, -2, -2, 0, 0, 0, 2, 2, 2, 2, 3, 3, 3, 3, 3]) y = np.array([7, -1, 3, 4, 5, 6, 2, 2, 4, 4, 1, 1, 1, 1, -1]) result = median_filter.median_filter(x, y, num_bins=5) np.testing.assert_array_equal([7, 1, 5, 2, 3], result)
def testDefaultArgs(self): x = np.array([-4, -2, -2, 0, 0, 0, 2, 2, 2, 2, 3, 3, 3, 3, 3]) y = np.array([7, -1, 3, 4, 5, 6, 2, 2, 4, 4, 1, 1, 1, 1, -1]) result = median_filter.median_filter(x, y, num_bins=5) np.testing.assert_array_equal([7, 1, 5, 2, 3], result)
def testEmptyBins(self):
x = np.array([-1, 0, 1])
y = np.array([1, 2, 3])
result = median_filter.median_filter(
x, y, num_bins=5, bin_width=2, x_min=-5, x_max=5)
np.testing.assert_array_equal([2, 2, 1.5, 3, 2], result)
def testWideBins(self):
x = np.array([-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6])
y = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13])
result = median_filter.median_filter(
x, y, num_bins=5, bin_width=6, x_min=-7, x_max=7)
np.testing.assert_array_equal([3, 4.5, 6.5, 8.5, 10.5], result)
def testMedian(self):
x = np.array([-4, -2, -2, 0, 0, 0, 2, 2, 2, 2, 3, 3, 3, 3, 3])
y = np.array([0, -1, 1, 4, 5, 6, 2, 2, 4, 4, 1, 1, 1, 1, -1])
result = median_filter.median_filter(
x, y, num_bins=5, bin_width=2, x_min=-5, x_max=5)
np.testing.assert_array_equal([0, 0, 5, 3, 1], result)
def testBucketBoundaries(self):
x = np.array([-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6])
y = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13])
result = median_filter.median_filter(
x, y, num_bins=5, bin_width=2, x_min=-5, x_max=5)
np.testing.assert_array_equal([2.5, 4.5, 6.5, 8.5, 10.5], result)
def testErrors(self):
# x size less than 2.
x = [1]
y = [2]
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=1, x_min=0, x_max=2)
# x and y not the same size.
x = [1, 2]
y = [4, 5, 6]
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=1, x_min=0, x_max=2)
# x_min not less than x_max.
x = [1, 2, 3]
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=1, x_min=-1, x_max=-1)
# x_min greater than the last element of x.
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=0.25, x_min=3.5, x_max=4)
# bin_width nonpositive.
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=0, x_min=1, x_max=3)
# bin_width greater than or equal to x_max - x_min.
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=2, bin_width=1, x_min=1.5, x_max=2.5)
# num_bins less than 2.
x = [1, 2, 3]
with self.assertRaises(ValueError):
median_filter.median_filter(
x, y, num_bins=1, bin_width=1, x_min=0, x_max=2)
