def fit_region(coords,
initial_props=None,
try_fit_ellipse=True,
use_ransac=False,
min_in_mask=0.8,
mask=None,
max_resid=None,
ransac_trials=50,
beam_pix=4,
max_rad=1.75,
max_eccent=3.,
image_shape=None,
conv_hull=None,
verbose=False):
'''
Fit a circle or ellipse to the given coordinates.
'''
coords = np.array(coords).copy()
ymean = coords[:, 0].mean()
xmean = coords[:, 1].mean()
# Fitting works better when the points are near the origin
coords[:, 0] -= int(ymean)
coords[:, 1] -= int(xmean)
new_props = np.empty((5, ))
if len(coords) < 3:
raise ValueError("Must have at least 3 points to fit.")
if len(coords) > 5 and try_fit_ellipse:
with catch_warnings():
filterwarnings("ignore", r"Number of calls to function")
filterwarnings("ignore", r"gtol=0.000000 is too small")
if use_ransac:
model, inliers = \
ransac(coords[:, ::-1], EllipseModel, 5,
beam_pix, max_trials=ransac_trials)
else:
model = EllipseModel()
model.estimate(coords[:, ::-1])
dof = len(coords) - 5
# Calculate the model residual
resid = model.residuals(coords[:, ::-1]).sum() / dof
pars = model.params.copy()
pars[0] += int(xmean)
pars[1] += int(ymean)
eccent = pars[2] / float(pars[3])
# Sometimes a < b?? If so, manually correct.
if eccent < 1:
eccent = 1. / eccent
pars[2], pars[3] = pars[3], pars[2]
pars[4] = wrap_to_pi(pars[4] + 0.5 * np.pi)
fail_conds = eccent > max_eccent
if beam_pix is not None and not fail_conds:
fail_conds = fail_conds or \
pars[3] < beam_pix
if max_resid is not None and not fail_conds:
fail_conds = fail_conds or \
resid > max_resid
if initial_props is not None and not fail_conds:
fail_conds = fail_conds or \
pars[2] > max_rad * initial_props[2] or \
not in_ellipse(initial_props[:2][::-1], pars)
if image_shape is not None and not fail_conds:
fail_conds = fail_conds or \
not in_array(pars[:2], image_shape[::-1])
# We require the entire region be inside the array. This
# shouldn't be a big issue for galaxies, but should be revisited
# when testing on galactic emission or incomplete maps.
fail_conds = fail_conds or not \
ellipse_in_array(pars, image_shape[::-1])
if mask is not None and not fail_conds:
# Make sure most of the region falls within the hole mask
fail_conds = fail_conds or \
fraction_in_mask(pars, mask) < min_in_mask
# Now make sure the region is within a region with signal.
# We define this based on the convex hull. It seems
# appropriate to just use min_in_mask, since most of it needs to
# be within the region.
if conv_hull is not None and not fail_conds:
fail_conds = fail_conds or \
fraction_in_mask(pars, conv_hull) < min_in_mask
# The center of the fit should fall within the convex hull mask
y, x = floor_int(pars[1]), floor_int(pars[0])
fail_conds = fail_conds or not conv_hull[y, x]
if fail_conds:
ellip_fail = True
else:
new_props[0] = pars[1]
new_props[1] = pars[0]
new_props[2] = pars[2]
new_props[3] = pars[3]
new_props[4] = pars[4]
ellip_fail = False
else:
ellip_fail = True
# If ellipse fitting is not allowed, or it failed, fit a circle
if ellip_fail:
with catch_warnings():
filterwarnings("ignore", r"Number of calls to function")
filterwarnings("ignore", r"gtol=0.000000 is too small")
if use_ransac:
model, inliers = \
ransac(coords[:, ::-1], CircleModel, 3,
beam_pix, max_trials=ransac_trials)
else:
model = CircleModel()
model.estimate(coords[:, ::-1])
dof = len(coords) - 3
# Calculate the model residual
resid = model.residuals(coords[:, ::-1]).sum() / dof
pars = model.params.copy()
pars[0] += int(xmean)
pars[1] += int(ymean)
fail_conds = False
if beam_pix is not None and not fail_conds:
fail_conds = fail_conds or \
pars[2] < beam_pix
if max_resid is not None and not fail_conds:
fail_conds = fail_conds or \
resid > max_resid
if initial_props is not None and not fail_conds:
fail_conds = fail_conds or \
pars[2] > max_rad * initial_props[2] or \
not in_circle(initial_props[:2][::-1], pars)
if image_shape is not None and not fail_conds:
fail_conds = fail_conds or \
not in_array(pars[:2], image_shape[::-1])
# We require the entire region be inside the array. This
# shouldn't be a big issue for galaxies, but should be revisited
# when testing on galactic emission or incomplete maps.
fail_conds = fail_conds or not \
circle_in_array(pars, image_shape[::-1])
if mask is not None and not fail_conds:
fail_conds = fail_conds or \
fraction_in_mask(pars, mask) < min_in_mask
if conv_hull is not None and not fail_conds:
# Needs to be in convex hull. See ellipse rejections
fail_conds = fail_conds or \
fraction_in_mask(pars, conv_hull) < min_in_mask
# The center of the fit should fall within the convex hull mask
y, x = floor_int(pars[1]), floor_int(pars[0])
fail_conds = fail_conds or not conv_hull[y, x]
if fail_conds:
if verbose:
Warning("All fitting failed.")
return None, None
new_props[0] = pars[1]
new_props[1] = pars[0]
new_props[2] = pars[2]
new_props[3] = pars[2]
new_props[4] = 0.0
props = new_props
return props, resid
def getZoneByLocation(lat, lon, level):
level += 2
h_size = calcHexSize(level)
z_xy = loc2xy(lon, lat)
lon_grid = z_xy.x
lat_grid = z_xy.y
unit_x = 6 * h_size
unit_y = 6 * h_size * H_K
h_pos_x = (lon_grid + lat_grid / H_K) / unit_x
h_pos_y = (lat_grid - H_K * lon_grid) / unit_y
h_x_0 = floor_int(h_pos_x)
h_y_0 = floor_int(h_pos_y)
h_x_q = h_pos_x - h_x_0
h_y_q = h_pos_y - h_y_0
h_x = round_int(h_pos_x)
h_y = round_int(h_pos_y)
if h_y_q > -h_x_q + 1:
if (h_y_q < 2 * h_x_q) and (h_y_q > 0.5 * h_x_q):
h_x = h_x_0 + 1
h_y = h_y_0 + 1
elif h_y_q < -h_x_q + 1:
if (h_y_q > (2 * h_x_q) - 1) and (h_y_q < (0.5 * h_x_q) + 0.5):
h_x = h_x_0
h_y = h_y_0
h_lat = (H_K * h_x * unit_x + h_y * unit_y) / 2
h_lon = (h_lat - h_y * unit_y) / H_K
z_loc = xy2loc(h_lon, h_lat)
z_loc_x = z_loc.lon
z_loc_y = z_loc.lat
if H_BASE - h_lon < h_size:
z_loc_x = 180
h_xy = h_x
h_x = h_y
h_y = h_xy
h_code = ""
code3_x = [0] * (level + 1)
code3_y = [0] * (level + 1)
code3 = ""
code9 = ""
mod_x = h_x
mod_y = h_y
for i in range(level + 1):
h_pow = math.pow(3, level - i)
if mod_x >= ceil_int(h_pow/2):
code3_x[i] = 2
mod_x -= h_pow
elif mod_x <= -ceil_int(h_pow/2):
code3_x[i] = 0
mod_x += h_pow
else:
code3_x[i] = 1
if mod_y >= ceil_int(h_pow/2):
code3_y[i] =2
mod_y -= h_pow
elif mod_y <= -ceil_int(h_pow/2):
code3_y[i] =0
mod_y += h_pow
else:
code3_y[i] = 1
for i in range(len(code3_x)):
code3 += "%s%s" % (code3_x[i], code3_y[i])
code9 += str(int(code3, 3))
h_code += code9
code9 = ""
code3 = ""
h_2 = h_code[3:]
h_1 = h_code[0:3]
h_a1 = floor_int(int(h_1) / 30)
h_a2 = int(h_1) % 30
h_code = (H_KEY[h_a1] + H_KEY[h_a2]) + h_2
return Zone(z_loc_y, z_loc_x, h_x, h_y, h_code)
def fit_region(coords, initial_props=None,
try_fit_ellipse=True, use_ransac=False,
min_in_mask=0.8, mask=None, max_resid=None,
ransac_trials=50, beam_pix=4, max_rad=1.75,
max_eccent=3., image_shape=None, conv_hull=None,
verbose=False):
'''
Fit a circle or ellipse to the given coordinates.
'''
coords = np.array(coords).copy()
ymean = coords[:, 0].mean()
xmean = coords[:, 1].mean()
# Fitting works better when the points are near the origin
coords[:, 0] -= int(ymean)
coords[:, 1] -= int(xmean)
new_props = np.empty((5,))
if len(coords) < 3:
raise ValueError("Must have at least 3 points to fit.")
if len(coords) > 5 and try_fit_ellipse:
with catch_warnings():
filterwarnings("ignore",
r"Number of calls to function")
filterwarnings("ignore",
r"gtol=0.000000 is too small")
if use_ransac:
model, inliers = \
ransac(coords[:, ::-1], EllipseModel, 5,
beam_pix, max_trials=ransac_trials)
else:
model = EllipseModel()
model.estimate(coords[:, ::-1])
dof = len(coords) - 5
# Calculate the model residual
resid = model.residuals(coords[:, ::-1]).sum() / dof
pars = model.params.copy()
pars[0] += int(xmean)
pars[1] += int(ymean)
eccent = pars[2] / float(pars[3])
# Sometimes a < b?? If so, manually correct.
if eccent < 1:
eccent = 1. / eccent
pars[2], pars[3] = pars[3], pars[2]
pars[4] = wrap_to_pi(pars[4] + 0.5 * np.pi)
fail_conds = eccent > max_eccent
if beam_pix is not None and not fail_conds:
fail_conds = fail_conds or \
pars[3] < beam_pix
if max_resid is not None and not fail_conds:
fail_conds = fail_conds or \
resid > max_resid
if initial_props is not None and not fail_conds:
fail_conds = fail_conds or \
pars[2] > max_rad * initial_props[2] or \
not in_ellipse(initial_props[:2][::-1], pars)
if image_shape is not None and not fail_conds:
fail_conds = fail_conds or \
not in_array(pars[:2], image_shape[::-1])
# We require the entire region be inside the array. This
# shouldn't be a big issue for galaxies, but should be revisited
# when testing on galactic emission or incomplete maps.
fail_conds = fail_conds or not \
ellipse_in_array(pars, image_shape[::-1])
if mask is not None and not fail_conds:
# Make sure most of the region falls within the hole mask
fail_conds = fail_conds or \
fraction_in_mask(pars, mask) < min_in_mask
# Now make sure the region is within a region with signal.
# We define this based on the convex hull. It seems
# appropriate to just use min_in_mask, since most of it needs to
# be within the region.
if conv_hull is not None and not fail_conds:
fail_conds = fail_conds or \
fraction_in_mask(pars, conv_hull) < min_in_mask
# The center of the fit should fall within the convex hull mask
y, x = floor_int(pars[1]), floor_int(pars[0])
fail_conds = fail_conds or not conv_hull[y, x]
if fail_conds:
ellip_fail = True
else:
new_props[0] = pars[1]
new_props[1] = pars[0]
new_props[2] = pars[2]
new_props[3] = pars[3]
new_props[4] = pars[4]
ellip_fail = False
else:
ellip_fail = True
# If ellipse fitting is not allowed, or it failed, fit a circle
if ellip_fail:
with catch_warnings():
filterwarnings("ignore",
r"Number of calls to function")
filterwarnings("ignore",
r"gtol=0.000000 is too small")
if use_ransac:
model, inliers = \
ransac(coords[:, ::-1], CircleModel, 3,
beam_pix, max_trials=ransac_trials)
else:
model = CircleModel()
model.estimate(coords[:, ::-1])
dof = len(coords) - 3
# Calculate the model residual
resid = model.residuals(coords[:, ::-1]).sum() / dof
pars = model.params.copy()
pars[0] += int(xmean)
pars[1] += int(ymean)
fail_conds = False
if beam_pix is not None and not fail_conds:
fail_conds = fail_conds or \
pars[2] < beam_pix
if max_resid is not None and not fail_conds:
fail_conds = fail_conds or \
resid > max_resid
if initial_props is not None and not fail_conds:
fail_conds = fail_conds or \
pars[2] > max_rad * initial_props[2] or \
not in_circle(initial_props[:2][::-1], pars)
if image_shape is not None and not fail_conds:
fail_conds = fail_conds or \
not in_array(pars[:2], image_shape[::-1])
# We require the entire region be inside the array. This
# shouldn't be a big issue for galaxies, but should be revisited
# when testing on galactic emission or incomplete maps.
fail_conds = fail_conds or not \
circle_in_array(pars, image_shape[::-1])
if mask is not None and not fail_conds:
fail_conds = fail_conds or \
fraction_in_mask(pars, mask) < min_in_mask
if conv_hull is not None and not fail_conds:
# Needs to be in convex hull. See ellipse rejections
fail_conds = fail_conds or \
fraction_in_mask(pars, conv_hull) < min_in_mask
# The center of the fit should fall within the convex hull mask
y, x = floor_int(pars[1]), floor_int(pars[0])
fail_conds = fail_conds or not conv_hull[y, x]
if fail_conds:
if verbose:
Warning("All fitting failed.")
return None, None
new_props[0] = pars[1]
new_props[1] = pars[0]
new_props[2] = pars[2]
new_props[3] = pars[2]
new_props[4] = 0.0
props = new_props
return props, resid
