def BackgroundProfile(binsz):
    background, mask, signifiance = Run(correlation_radius = correlation_radius, significance_threshold=significance_threshold, mask_dilation_radius=mask_dilation_radius, number_of_iterations=50, data_image = data_image)
    background = background[1]
    glats = np.arange(LatLow, LatHigh+binsz, binsz)    
    glat_bounds = Table()
    glat_bounds['CHANNEL'] = np.arange(len(glats) - 1)
    glat_bounds['GLAT_MIN'] = np.float64(glats[:-1])
    glat_bounds['GLAT_MAX'] = np.float64(glats[1:])
    data = compute_latitude_profile(glat_bounds = glat_bounds, binsz=binsz, image=background, datatype=2, emission=4, tev=0)
    return data
def GeneralProfile(binsz, filename):
    """This should be improved to avoid hard-coded filenames"""
    data_image = fits.open(filename)
    data_image= data_image[1]
    glats = np.arange(LatLow, LatHigh+binsz, binsz)    
    glat_bounds = Table()
    glat_bounds['CHANNEL'] = np.arange(len(glats) - 1)
    glat_bounds['GLAT_MIN'] = np.float64(glats[:-1])
    glat_bounds['GLAT_MAX'] = np.float64(glats[1:])
    data = compute_latitude_profile(glat_bounds = glat_bounds, binsz=binsz, image=data_image, datatype=2, emission=4, tev=0)
    return data
示例#3
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def GeneralProfile(binsz, filename):
    """This should be improved to avoid hard-coded filenames"""
    data_image = fits.open(filename)
    data_image = data_image[1]
    glats = np.arange(LatLow, LatHigh + binsz, binsz)
    glat_bounds = Table()
    glat_bounds['CHANNEL'] = np.arange(len(glats) - 1)
    glat_bounds['GLAT_MIN'] = np.float64(glats[:-1])
    glat_bounds['GLAT_MAX'] = np.float64(glats[1:])
    data = compute_latitude_profile(glat_bounds=glat_bounds,
                                    binsz=binsz,
                                    image=data_image,
                                    datatype=2,
                                    emission=4,
                                    tev=0)
    return data
示例#4
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def BackgroundProfile(binsz):
    background, mask, signifiance = Run(
        correlation_radius=correlation_radius,
        significance_threshold=significance_threshold,
        mask_dilation_radius=mask_dilation_radius,
        number_of_iterations=50,
        data_image=data_image)
    background = background[1]
    glats = np.arange(LatLow, LatHigh + binsz, binsz)
    glat_bounds = Table()
    glat_bounds['CHANNEL'] = np.arange(len(glats) - 1)
    glat_bounds['GLAT_MIN'] = np.float64(glats[:-1])
    glat_bounds['GLAT_MAX'] = np.float64(glats[1:])
    data = compute_latitude_profile(glat_bounds=glat_bounds,
                                    binsz=binsz,
                                    image=background,
                                    datatype=2,
                                    emission=4,
                                    tev=0)
    return data