Python SpectralCube.moment1方法代码示例

# 需要导入模块: from spectral_cube import SpectralCube [as 别名]
# 或者: from spectral_cube.SpectralCube import moment1 [as 别名]
# Create a synthetic X-dimension in km/s
xarr = np.linspace(50, 70, 41) # km/s

# Define a line width, which will vary across our image
# It will increase from 1 km/s to 4 km/s over the X-direction (RA)
sigma = np.outer(np.linspace(1,1.5,2), np.ones(4)).T

# Define a line center, which will vary in the opposite direction,
# along increasing Y-direction (declination)
centroid = np.outer(np.ones(2), np.linspace(58, 62, 4)).T

data = np.exp(-(np.tile(xarr, (2, 4, 1)).T - centroid)**2 / (2.*sigma**2))
cube = SpectralCube(data=data, wcs=mywcs)

# Sanity checks: do the moments accurately recover the inputs?
assert (np.abs(cube.moment1().to(u.km/u.s).value - centroid).max()) < 1e-5
assert (np.abs(cube.moment2().to(u.km**2/u.s**2).value - sigma**2).max()) < 1e-5

# Create a pyspeckit cube
pcube = pyspeckit.Cube(cube=cube)

# For convenience, convert the X-axis to km/s
# (WCSLIB automatically converts to m/s even if you give it km/s)
pcube.xarr.convert_to_unit(u.km/u.s)

# Set up the fitter by doing a preliminary fit
pcube.specfit(fittype='gaussian', guesses='moments')

# Fit each spectrum with a gaussian
# First, assemble the guesses:
guesses = np.array([cube.max(axis=0).value,

# 需要导入模块: from spectral_cube import SpectralCube [as 别名]
# 或者: from spectral_cube.SpectralCube import moment1 [as 别名]
class SimCube(object):
    '''
    A wrapping class to prepare a simulated spectral data cube for
    comparison with another cube.
    '''

    def __init__(self, cube, beam=None, mask=None, method="MAD", compute=True):

        # Initialize cube object
        self.cube = SpectralCube.read(cube)

        if mask is not None:
            _check_mask(mask)
        self.mask = mask

        if beam is not None:
            _check_beam(mask)

        # Initialize noise object
        self.noise = Noise(self.cube, beam=beam, method=method)

    def add_noise(self):
        '''
        Use Noise to add synthetic noise to the data. Then update
        SpectralCube.
        '''

        # Create the noisy cube
        self.noise.get_noise_cube()
        noise_data = self.noise.noise_cube +\
            self.cube.filled_data[:]

        # Update SpectralCube object
        self._update(data=noise_data)

        return self

    def clean_cube(self, algorithm=None):
        raise NotImplementedError("")

    def apply_mask(self, mask=None):
        '''
        Check if the given mask is acceptable abd apply to
        SpectralCube.
        '''

        # Update mask
        if mask is not None:
            _check_mask(mask)
            self.mask = mask

        # Create the mask, auto masking nan values
        default_mask = np.isfinite(self.cube.filled_data[:])
        if self.mask is not None:
            self.mask = CompositeMask(default_mask, self.mask)
        else:
            self.mask = default_mask

        # Apply mask to spectral cube object
        self.cube = self.cube.with_mask(mask)

        return self

    def _update(self, data=None, wcs=None, beam=None, method="MAD"):
        '''
        Helper function to update classes.
        '''

        # Check if we need a new SpectralCube
        if data is None and wcs is None:
            pass
        else:
            if data is None:
                data = self.cube.unmasked_data[:]
            if wcs is None:
                wcs = self.cube.wcs
            # Make new SpectralCube object
            self.cube = SpectralCube(data=data, wcs=wcs)

        if beam is not None:
            _check_beam(beam)
            self.noise = Noise(self.cube, beam=beam, method=method)

    def compute_properties(self):
        '''
        Use SpectralCube to compute the moments. Also compute the integrated
        intensity based on the noise properties from Noise.
        '''

        self._moment0 = self.cube.moment0().value

        self._moment1 = self.cube.moment1().value

        self._moment2 = self.cube.moment2().value

        _get_int_intensity(self)

        return self

    @property
#.........这里部分代码省略.........

# 需要导入模块: from spectral_cube import SpectralCube [as 别名]
# 或者: from spectral_cube.SpectralCube import moment1 [as 别名]
class ObsCube(object):
    """
    A wrapping class of SpectralCube which prepares observational data cubes
    to be compared to any other data cube.

    Parameters
    ----------

    cube : str
        Path to file.
    mask : numpy.ndarray, any mask class from spectral_cube, optional
        Mask to be applied to the cube.
    algorithm : {NAME HERE}, optional
        Name of the cleaning algorithm to use.

    Example
    -------
    ```
    from turbustat.cube_tools import ObsCube

    cube = ObsCube("data.fits")
    cube.apply_cleaning(algorithm="SUPERAWESOMECLEANING")

    ```
    """
    def __init__(self, cube, mask=None, algorithm=None, beam=None):
        super(ObsCube, self).__init__()
        self.cube = sc.SpectralCube.read(cube)

        self.algorithm = algorithm

        # Make sure mask is an accepted type
        if mask is not None:
            _check_mask(mask)
        self.mask = mask

        if beam is not None:
            _check_beam(beam)
        self.noise = Noise(self.cube, beam=beam)

    def clean_cube(self, algorithm=None):
        raise NotImplementedError("")

    def apply_mask(self, mask=None):
        '''
        Check if the given mask is acceptable abd apply to
        SpectralCube.
        '''

        # Update mask
        if mask is not None:
            _check_mask(mask)
            self.mask = mask

        # Create the mask, auto masking nan values
        default_mask = np.isfinite(self.cube.filled_data[:])
        if self.mask is not None:
            self.mask = CompositeMask(default_mask, self.mask)
        else:
            self.mask = default_mask

        # Apply mask to spectral cube object
        self.cube = self.cube.with_mask(mask)

        return self

    def _update(self, data=None, wcs=None, beam=None, method="MAD"):
        '''
        Helper function to update classes.
        '''

        # Check if we need a new SpectralCube
        if data is None and wcs is None:
            pass
        else:
            if data is None:
                data = self.cube.unmasked_data[:]
            if wcs is None:
                wcs = self.cube.wcs
            # Make new SpectralCube object
            self.cube = SpectralCube(data=data, wcs=wcs)

        if beam is not None:
            _check_beam(beam)
            self.noise = Noise(self.cube, beam=beam, method=method)

    def compute_properties(self):
        '''
        Use SpectralCube to compute the moments. Also compute the integrated
        intensity based on the noise properties from Noise.
        '''

        self._moment0 = self.cube.moment0().value

        self._moment1 = self.cube.moment1().value

        self._moment2 = self.cube.moment2().value

        _get_int_intensity(self)

#.........这里部分代码省略.........