tdose_utilities.py 文件源码

def build_2D_cov_matrix(sigmax,sigmay,angle,verbose=True):
    """
    Build a covariance matrix for a 2D multivariate Gaussian

    --- INPUT ---
    sigmax          Standard deviation of the x-compoent of the multivariate Gaussian
    sigmay          Standard deviation of the y-compoent of the multivariate Gaussian
    angle           Angle to rotate matrix by in degrees (clockwise) to populate covariance cross terms
    verbose         Toggle verbosity
    --- EXAMPLE OF USE ---
    import tdose_utilities as tu
    covmatrix = tu.build_2D_cov_matrix(3,1,35)

    """
    if verbose: print ' - Build 2D covariance matrix with varinaces (x,y)=('+str(sigmax)+','+str(sigmay)+\
                      ') and then rotated '+str(angle)+' degrees'
    cov_orig      = np.zeros([2,2])
    cov_orig[0,0] = sigmay**2.0
    cov_orig[1,1] = sigmax**2.0

    angle_rad     = (180.0-angle) * np.pi/180.0 # The (90-angle) makes sure the same convention as DS9 is used
    c, s          = np.cos(angle_rad), np.sin(angle_rad)
    rotmatrix     = np.matrix([[c, -s], [s, c]])

    cov_rot       = np.dot(np.dot(rotmatrix,cov_orig),np.transpose(rotmatrix))  # performing rot * cov * rot^T

    return cov_rot
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