def mo_matrix(mock, obs, opts):
"""
Function to determine the mass-observable matrix.
"""
n_mass_bins = comp.num_bins(opts.mass_bin[0], opts.mass_bin[1], opts.mass_bin[2])
n_proxy_bins = comp.num_bins(opts.proxy_bin[0], opts.proxy_bin[1], opts.proxy_bin[2])
mass_x = comp.x_vals(n_mass_bins, opts.mass_bin[0], opts.mass_bin[2])
proxy_x = comp.x_vals(n_proxy_bins, opts.proxy_bin[0], opts.proxy_bin[2])
matrix = np.zeros((n_proxy_bins, n_mass_bins))
clusters = find_matches(mock, obs, opts)
for cluster in clusters:
proxy_bin = n_proxy_bins - 1 - \
comp.find_bin(np.log10(cluster.proxy), opts.proxy_bin[0], opts.proxy_bin[2])
for i in range(n_proxy_bins):
if proxy_bin == i and opts.z_bin[0] <= cluster.z < opts.z_bin[1]:
matrix[proxy_bin] += comp.scale(cluster.hist, min(cluster.hist),
np.sum(cluster.hist))
for i in range(n_proxy_bins):
matrix[i] = comp.scale(matrix[i], min(matrix[i]), np.sum(matrix[i]))
return matrix, mass_x, proxy_x
def mo_matrix(mock, obs, opts):
n_mass_bins = comp.num_bins(opts.mass_bin[0], opts.mass_bin[1], opts.mass_bin[2])
n_proxy_bins = comp.num_bins(opts.proxy_bin[0], opts.proxy_bin[1], opts.proxy_bin[2])
mass_index = np.floor((mock.mass - opts.mass_bin[0]) / opts.mass_bin[2]).astype('int')
proxy_index = np.floor((obs.proxy - opts.proxy_bin[0]) / opts.proxy_bin[2]).astype('int')
mass_hist = np.zeros(n_mass_bins)
for i in mass_index:
mass_hist[i] += 1
mass_x = comp.x_vals(n_mass_bins, opts.mass_bin[0], opts.mass_bin[2])
proxy_x = comp.x_vals(n_proxy_bins, opts.proxy_bin[0], opts.proxy_bin[2])
matrix = np.zeros((n_proxy_bins, n_mass_bins))
index, dists = find_matches(mock, obs, 2.0 * opts.delta_z)
tag_index = halo_tag(mock, np.copy(index))
mass_hist2 = np.zeros(n_mass_bins)
for i in mass_index[tag_index]:
mass_hist2[i] += 1
print_matches(mock, obs, index, opts)
for i in range(obs.size):
for j in range(len(index[i])):
matrix[proxy_index[i], mass_index[index[i][j]]] += dists[i][j]
return np.nan_to_num(np.flipud(matrix)), mass_hist, mass_hist2, mass_x, proxy_x
def mo_matrix(mock, obs, opts):
"""
Function to determine the mass-observable matrix.
"""
n_mass_bins = comp.num_bins(opts.mass_bin[0], opts.mass_bin[1],
opts.mass_bin[2])
n_proxy_bins = comp.num_bins(opts.proxy_bin[0], opts.proxy_bin[1],
opts.proxy_bin[2])
mass_x = comp.x_vals(n_mass_bins, opts.mass_bin[0], opts.mass_bin[2])
proxy_x = comp.x_vals(n_proxy_bins, opts.proxy_bin[0], opts.proxy_bin[2])
matrix = np.zeros((n_proxy_bins, n_mass_bins))
clusters = find_matches(mock, obs, opts)
for cluster in clusters:
proxy_bin = n_proxy_bins - 1 - \
comp.find_bin(np.log10(cluster.proxy), opts.proxy_bin[0], opts.proxy_bin[2])
for i in range(n_proxy_bins):
if proxy_bin == i and opts.z_bin[0] <= cluster.z < opts.z_bin[1]:
matrix[proxy_bin] += comp.scale(cluster.hist,
min(cluster.hist),
np.sum(cluster.hist))
for i in range(n_proxy_bins):
matrix[i] = comp.scale(matrix[i], min(matrix[i]), np.sum(matrix[i]))
return matrix, mass_x, proxy_x
def mo_matrix(mock, obs, matches, opts):
index, weights, mock_index = matches
n_z_bins = comp.num_bins(opts.z_bin[0], opts.z_bin[1], opts.z_bin[2])
n_mass_bins = comp.num_bins(opts.mass_bin[0], opts.mass_bin[1], opts.mass_bin[2])
n_proxy_bins = comp.num_bins(opts.proxy_bin[0], opts.proxy_bin[1], opts.proxy_bin[2])
z_index = np.floor((mock.z - opts.z_bin[0]) / opts.z_bin[2]).astype('int')
mass_index = np.floor((mock.mass - opts.mass_bin[0]) / opts.mass_bin[2]).astype('int')
proxy_index = np.floor((obs.proxy - opts.proxy_bin[0]) / opts.proxy_bin[2]).astype('int')
z_x = comp.x_vals(n_z_bins, opts.z_bin[0], opts.z_bin[2])
mass_x = comp.x_vals(n_mass_bins, opts.mass_bin[0], opts.mass_bin[2])
proxy_x = comp.x_vals(n_proxy_bins, opts.proxy_bin[0], opts.proxy_bin[2])
matrix = np.zeros((n_z_bins, n_mass_bins, n_proxy_bins))
hm_matrix = np.zeros((n_z_bins, n_mass_bins))
for i in range(len(mass_index)):
hm_matrix[z_index[i], mass_index[i]] += 1
mock_matched = mock[mock_index]
for i in range(mock_matched.size):
if opts.unique:
matrix[z_index[i], mass_index[i], proxy_index[index[i]]] += 1
else:
for j in range(len(index[i])):
matrix[z_index[i], mass_index[i], proxy_index[index[i][j]]] += weights[i][j]
return matrix, hm_matrix, (z_x, mass_x, proxy_x)
