def get_points(R_proj, num_points, weights): rd = [] dp = [] edp = [] for i in range(len(R_proj) / num_points - 1): r_biweight = bwt_ave(R_proj[num_points * i:num_points * \ (i + 1)]) rd.append(r_biweight[0][0]) if i == 0: r1 = 0. if i > 0: r1 = r2 r2 = R_proj[num_points * (i + 1)] weight = np.sum(weights[num_points * i:num_points * (i + 1)]) dp.append(weight / (np.pi * (r2**2 - r1**2))) edp.append(np.sqrt(num_points) / num_points * weight / \ (np.pi * (r2 ** 2 - r1 ** 2))) return np.array(rd), np.array(dp), np.array(edp)
def get_points(R_proj, num_points, weights): radial_pt = [] density_pt = [] density_pt_err = [] for i in range(len(R_proj) / num_points - 1): r_biweight = bwt_ave(R_proj[num_points * i:num_points * \ (i + 1)]) radial_pt.append(r_biweight[0][0]) if i == 0: r1 = 0. if i > 0: r1 = r2 r2 = R_proj[num_points * (i + 1)] weight = np.sum(weights[num_points * i:num_points * (i + 1)]) density_pt.append(weight / (np.pi * (r2 ** 2 - r1 ** 2))) density_pt_err.append(np.sqrt(num_points) / num_points * weight / \ (np.pi * (r2 ** 2 - r1 ** 2))) return np.array(radial_pt), np.array(density_pt), np.array(density_pt_err)
def get_points(R_proj, num_points, weights): radial_pt = [] density_pt = [] density_pt_err = [] for i in range(len(R_proj) / num_points - 1): r_biweight = bwt_ave(R_proj[num_points * i:num_points * \ (i + 1)]) radial_pt.append(r_biweight[0][0]) if i == 0: r1 = 0. if i > 0: r1 = r2 r2 = R_proj[num_points * (i + 1)] weight = np.sum(weights[num_points * i:num_points * (i + 1)]) density_pt.append(weight / (np.pi * (r2**2 - r1**2))) density_pt_err.append(np.sqrt(num_points) / num_points * weight / \ (np.pi * (r2 ** 2 - r1 ** 2))) return np.array(radial_pt), np.array(density_pt), np.array(density_pt_err)
def get_points(R_proj, num_points, weights): rd = [] dp = [] edp = [] for i in range(len(R_proj) / num_points - 1): r_biweight = bwt_ave(R_proj[num_points * i:num_points * \ (i + 1)]) rd.append(r_biweight[0][0]) if i == 0: r1 = 0. if i > 0: r1 = r2 r2 = R_proj[num_points * (i + 1)] weight = np.sum(weights[num_points * i:num_points * (i + 1)]) dp.append(weight / (np.pi * (r2 ** 2 - r1 ** 2))) edp.append(np.sqrt(num_points) / num_points * weight / \ (np.pi * (r2 ** 2 - r1 ** 2))) return np.array(rd), np.array(dp), np.array(edp)