The following are code examples for showing how to use . They are extracted from open source Python projects. You can vote up the examples you like or vote down the exmaples you don’t like. You can also save this page to your account.
Example 1
def masked_matrix(matrix, all_zero=False):
"""
Returns masked version of HicMatrix. By default, all entries in zero-count
rows and columns are masked.
:param matrix: A numpy 2D matrix
:param all_zero: Mask ALL zero-count entries
:returns: MaskedArray with zero entries masked
"""
if all_zero:
return np.ma.MaskedArray(matrix, mask=np.isclose(matrix, 0.))
col_zero = np.isclose(np.sum(matrix, axis=0), 0.)
row_zero = np.isclose(np.sum(matrix, axis=1), 0.)
mask = np.zeros(matrix.shape, dtype=np.bool_)
mask[:, col_zero] = np.True_
mask[row_zero, :] = np.True_
return np.ma.MaskedArray(matrix, mask=mask) Example 2
def test_logical(self):
f = np.False_
t = np.True_
s = "xyz"
self.assertTrue((t and s) is s)
self.assertTrue((f and s) is f) Example 3
def test_bitwise_or(self):
f = np.False_
t = np.True_
self.assertTrue((t | t) is t)
self.assertTrue((f | t) is t)
self.assertTrue((t | f) is t)
self.assertTrue((f | f) is f) Example 4
def test_bitwise_and(self):
f = np.False_
t = np.True_
self.assertTrue((t & t) is t)
self.assertTrue((f & t) is f)
self.assertTrue((t & f) is f)
self.assertTrue((f & f) is f) Example 5
def test_bitwise_xor(self):
f = np.False_
t = np.True_
self.assertTrue((t ^ t) is f)
self.assertTrue((f ^ t) is t)
self.assertTrue((t ^ f) is t)
self.assertTrue((f ^ f) is f) Example 6
def test_logical(self):
f = np.False_
t = np.True_
s = "xyz"
self.assertTrue((t and s) is s)
self.assertTrue((f and s) is f) Example 7
def test_bitwise_or(self):
f = np.False_
t = np.True_
self.assertTrue((t | t) is t)
self.assertTrue((f | t) is t)
self.assertTrue((t | f) is t)
self.assertTrue((f | f) is f) Example 8
def test_bitwise_and(self):
f = np.False_
t = np.True_
self.assertTrue((t & t) is t)
self.assertTrue((f & t) is f)
self.assertTrue((t & f) is f)
self.assertTrue((f & f) is f) Example 9
def test_bitwise_xor(self):
f = np.False_
t = np.True_
self.assertTrue((t ^ t) is f)
self.assertTrue((f ^ t) is t)
self.assertTrue((t ^ f) is t)
self.assertTrue((f ^ f) is f) Example 10
def _recalc_display_image_minmax(self):
finite_mask = np.isfinite(self.display_image)
if finite_mask.max() is np.True_:
self._display_image_min = self.display_image[finite_mask].min()
self._display_image_max = self.display_image[finite_mask].max()
else:
self._display_image_min = 0.
self._display_image_max = 0. Example 11
def _recalc_display_image_minmax(self):
finite_mask = np.isfinite(self.display_image)
if finite_mask.max() is np.True_:
self._display_image_min = self.display_image[finite_mask].min()
self._display_image_max = self.display_image[finite_mask].max()
else:
self._display_image_min = 0.
self._display_image_max = 0. Example 12
def test_logical(self):
f = np.False_
t = np.True_
s = "xyz"
self.assertTrue((t and s) is s)
self.assertTrue((f and s) is f) Example 13
def test_bitwise_or(self):
f = np.False_
t = np.True_
self.assertTrue((t | t) is t)
self.assertTrue((f | t) is t)
self.assertTrue((t | f) is t)
self.assertTrue((f | f) is f) Example 14
def test_bitwise_and(self):
f = np.False_
t = np.True_
self.assertTrue((t & t) is t)
self.assertTrue((f & t) is f)
self.assertTrue((t & f) is f)
self.assertTrue((f & f) is f) Example 15
def test_bitwise_xor(self):
f = np.False_
t = np.True_
self.assertTrue((t ^ t) is f)
self.assertTrue((f ^ t) is t)
self.assertTrue((t ^ f) is t)
self.assertTrue((f ^ f) is f) Example 16
def test_logical(self):
f = np.False_
t = np.True_
s = "xyz"
self.assertTrue((t and s) is s)
self.assertTrue((f and s) is f) Example 17
def test_bitwise_or(self):
f = np.False_
t = np.True_
self.assertTrue((t | t) is t)
self.assertTrue((f | t) is t)
self.assertTrue((t | f) is t)
self.assertTrue((f | f) is f) Example 18
def test_bitwise_and(self):
f = np.False_
t = np.True_
self.assertTrue((t & t) is t)
self.assertTrue((f & t) is f)
self.assertTrue((t & f) is f)
self.assertTrue((f & f) is f) Example 19
def test_bitwise_xor(self):
f = np.False_
t = np.True_
self.assertTrue((t ^ t) is f)
self.assertTrue((f ^ t) is t)
self.assertTrue((t ^ f) is t)
self.assertTrue((f ^ f) is f) Example 20
def test_logical(self):
f = np.False_
t = np.True_
s = "xyz"
self.assertTrue((t and s) is s)
self.assertTrue((f and s) is f) Example 21
def test_bitwise_or(self):
f = np.False_
t = np.True_
self.assertTrue((t | t) is t)
self.assertTrue((f | t) is t)
self.assertTrue((t | f) is t)
self.assertTrue((f | f) is f) Example 22
def test_bitwise_and(self):
f = np.False_
t = np.True_
self.assertTrue((t & t) is t)
self.assertTrue((f & t) is f)
self.assertTrue((t & f) is f)
self.assertTrue((f & f) is f) Example 23
def test_bitwise_xor(self):
f = np.False_
t = np.True_
self.assertTrue((t ^ t) is f)
self.assertTrue((f ^ t) is t)
self.assertTrue((t ^ f) is t)
self.assertTrue((f ^ f) is f) Example 24
def test_logical(self):
f = np.False_
t = np.True_
s = "xyz"
self.assertTrue((t and s) is s)
self.assertTrue((f and s) is f) Example 25
def test_bitwise_or(self):
f = np.False_
t = np.True_
self.assertTrue((t | t) is t)
self.assertTrue((f | t) is t)
self.assertTrue((t | f) is t)
self.assertTrue((f | f) is f) Example 26
def test_bitwise_and(self):
f = np.False_
t = np.True_
self.assertTrue((t & t) is t)
self.assertTrue((f & t) is f)
self.assertTrue((t & f) is f)
self.assertTrue((f & f) is f) Example 27
def test_bitwise_xor(self):
f = np.False_
t = np.True_
self.assertTrue((t ^ t) is f)
self.assertTrue((f ^ t) is t)
self.assertTrue((t ^ f) is t)
self.assertTrue((f ^ f) is f) Example 28
def test_logical(self):
f = np.False_
t = np.True_
s = "xyz"
self.assertTrue((t and s) is s)
self.assertTrue((f and s) is f) Example 29
def test_bitwise_or(self):
f = np.False_
t = np.True_
self.assertTrue((t | t) is t)
self.assertTrue((f | t) is t)
self.assertTrue((t | f) is t)
self.assertTrue((f | f) is f) Example 30
def test_bitwise_and(self):
f = np.False_
t = np.True_
self.assertTrue((t & t) is t)
self.assertTrue((f & t) is f)
self.assertTrue((t & f) is f)
self.assertTrue((f & f) is f) Example 31
def test_bitwise_xor(self):
f = np.False_
t = np.True_
self.assertTrue((t ^ t) is f)
self.assertTrue((f ^ t) is t)
self.assertTrue((t ^ f) is t)
self.assertTrue((f ^ f) is f) Example 32
def aperture_phot(im, x, y, star_radius, sky_inner_radius, sky_outer_radius,
return_distances=False):
"""
im - 2-d numpy array
x,y - coordinates of center of star
star_radius - radius of photometry circle
sky_inner_radius, sky_outer_radius - defines annulus for determining sky
(if sky_inner_radius > sky_outer_radius, aperture_phot flips them)
----
Note that this is a very quick-and-dirty aperture photometry routine.
No error checking.
No partial pixels.
Many ways this could fail and/or give misleading results.
Not to be used within 12 hours of eating food.
Use only immediately after a large meal.
----
returns dictionary with:
flux - sky-subtracted flux inside star_radius
sky_per_pixel - sky counts per pixel determined from sky annulus
sky_per_pixel_err - estimated 1-sigma uncertainty in sky_per_pixel
sky_err - estimated 1-sigma uncertainty in sky subtraction from flux
n_star_pix - number of pixels in star_radius
n_sky_pix - number of pixels in sky annulus
x - input x
y - input y
star_radius - input star_radius
sky_inner_radius - input sky_inner_radius
sky_outer_radius - input sky_outer_radius
"""
if np.isnan(x) or np.isnan(y):
return {'error-msg':'One or both of x/y were NaN.', 'x':x, 'y':y, 'star_radius': star_radius,
'sky_inner_radius': sky_inner_radius, 'sky_outer_radius': sky_outer_radius,
'n_star_pix':0, 'n_sky_pix':0, 'sky_per_pixel':np.nan, 'sky_per_pixel_err':np.nan,
'flux':np.nan, 'sky_err':np.nan, 'distances':[]}
if sky_inner_radius > sky_outer_radius:
sky_inner_radius, sky_outer_radius = sky_outer_radius, sky_inner_radius
output = {'x': x, 'y': y, 'star_radius': star_radius,
'sky_inner_radius': sky_inner_radius, 'sky_outer_radius': sky_outer_radius}
xdist = np.outer(np.ones(im.shape[0]), np.arange(im.shape[1]) - x)
ydist = np.outer(np.arange(im.shape[0]) - y, np.ones(im.shape[1]))
dist = np.sqrt(xdist**2 + ydist**2)
star_mask = dist <= star_radius
star_pixels = im[star_mask]
sky_pixels = im[(dist >= sky_inner_radius) & (dist <= sky_outer_radius)]
output['n_star_pix'] = star_pixels.size
output['n_sky_pix'] = sky_pixels.size
finite_mask = np.isfinite(sky_pixels)
if finite_mask.max() is np.True_:
sky_per_pixel, median, stddev = sigma_clipped_stats(sky_pixels[finite_mask])
else:
sky_per_pixel, median, stddev = np.nan, np.nan, np.inf
sky_per_pixel_err = stddev/np.sqrt(finite_mask.sum())
output['sky_per_pixel'] = sky_per_pixel
# TODO: check that are doing sky_per_pixel_err right. In one quick test seemed high (but maybe wasn't a good test)
output['sky_per_pixel_err'] = sky_per_pixel_err
output['flux'] = star_pixels.sum() - sky_per_pixel*star_pixels.size
output['sky_err'] = sky_per_pixel_err*np.sqrt(star_pixels.size)
if return_distances:
output['distances'] = dist
return output Example 33
def aperture_phot(im, x, y, star_radius, sky_inner_radius, sky_outer_radius,
return_distances=False):
"""
im - 2-d numpy array
x,y - coordinates of center of star
star_radius - radius of photometry circle
sky_inner_radius, sky_outer_radius - defines annulus for determining sky
(if sky_inner_radius > sky_outer_radius, aperture_phot flips them)
----
Note that this is a very quick-and-dirty aperture photometry routine.
No error checking.
No partial pixels.
Many ways this could fail and/or give misleading results.
Not to be used within 12 hours of eating food.
Use only immediately after a large meal.
----
returns dictionary with:
flux - sky-subtracted flux inside star_radius
sky_per_pixel - sky counts per pixel determined from sky annulus
sky_per_pixel_err - estimated 1-sigma uncertainty in sky_per_pixel
sky_err - estimated 1-sigma uncertainty in sky subtraction from flux
n_star_pix - number of pixels in star_radius
n_sky_pix - number of pixels in sky annulus
x - input x
y - input y
star_radius - input star_radius
sky_inner_radius - input sky_inner_radius
sky_outer_radius - input sky_outer_radius
"""
if np.isnan(x) or np.isnan(y):
return {'error-msg':'One or both of x/y were NaN.', 'x':x, 'y':y, 'star_radius': star_radius,
'sky_inner_radius': sky_inner_radius, 'sky_outer_radius': sky_outer_radius,
'n_star_pix':0, 'n_sky_pix':0, 'sky_per_pixel':np.nan, 'sky_per_pixel_err':np.nan,
'flux':np.nan, 'sky_err':np.nan, 'distances':[]}
if sky_inner_radius > sky_outer_radius:
sky_inner_radius, sky_outer_radius = sky_outer_radius, sky_inner_radius
output = {'x': x, 'y': y, 'star_radius': star_radius,
'sky_inner_radius': sky_inner_radius, 'sky_outer_radius': sky_outer_radius}
xdist = np.outer(np.ones(im.shape[0]), np.arange(im.shape[1]) - x)
ydist = np.outer(np.arange(im.shape[0]) - y, np.ones(im.shape[1]))
dist = np.sqrt(xdist**2 + ydist**2)
star_mask = dist <= star_radius
star_pixels = im[star_mask]
sky_pixels = im[(dist >= sky_inner_radius) & (dist <= sky_outer_radius)]
output['n_star_pix'] = star_pixels.size
output['n_sky_pix'] = sky_pixels.size
finite_mask = np.isfinite(sky_pixels)
if finite_mask.max() is np.True_:
sky_per_pixel, median, stddev = sigma_clipped_stats(sky_pixels[finite_mask])
else:
sky_per_pixel, median, stddev = np.nan, np.nan, np.inf
sky_per_pixel_err = stddev/np.sqrt(finite_mask.sum())
output['sky_per_pixel'] = sky_per_pixel
# TODO: check that are doing sky_per_pixel_err right. In one quick test seemed high (but maybe wasn't a good test)
output['sky_per_pixel_err'] = sky_per_pixel_err
output['flux'] = star_pixels.sum() - sky_per_pixel*star_pixels.size
output['sky_err'] = sky_per_pixel_err*np.sqrt(star_pixels.size)
if return_distances:
output['distances'] = dist
return output 