cigvis.utils.surfaceutils module#

utils to process surface, such as create triangular mesh

cigvis.utils.surfaceutils.arbitray_line(data, points, di: float = 1)#: data : SegyNP or np.ndarray points : the points to interpolate a path di : step

cigvis.utils.surfaceutils.extract_data(data, p)#

Parameters#

segy: str: segyfile
pArrayLike: shape is (N, 2)

cigvis.utils.surfaceutils.fill_grid(points: ndarray, shape: List | Tuple, interp: bool = True, method: str = 'cubic', fill: float = -1) → ndarray#

fill points in a grid in shape. If interp, interpolation, this function doesn’t extrapolate, so we fill the edge as fill.

Parameters#

pointsarray-like: shape as (N, 3), N points, each row means (x, y, z) coordinate
shapeList or Tuple: [n1, n2], the grid shape, points will be filled into a n1*n2 grid
interpbool: if True, will interpolate the grid from points, but not extrapolate, this means some edge points will be fill
methodstr: interpolation method
fillfloat: the points can not be interpolated will be filled as fill, default is -1

cigvis.utils.surfaceutils.interp_arb(p: ndarray, d: ndarray) → ndarray#

Interpolates a 1d series in 3d space by linear interpolation.

Parameters#

pArrayLike: (N, 2), each row is [x, y], normalized, i.e., 0 <= x, y <= 1
dArrayLike: shape is (N, 4, n3)

cigvis.utils.surfaceutils.interp_linefirst_impl(volume: ndarray, surf: ndarray, order: int) → ndarray#

interp value of linefirst volume in surf positions

Parameters#

volumearray-like: 3D array, shape as (ni, nx, nt)
surfarray-like: 2D array, shape as (ni, nx), each point means z pos

Returns#

valuearray-like: 2D array, shape as (ni, nx), each point means value in z pos

cigvis.utils.surfaceutils.interp_surf(volume: ndarray, surf: ndarray, order: int = 1) → ndarray#

interp value of volume in surf positions

Parameters#

volumearray-like: 3D array
surfarray-like: 2D array, each point means z/nt pos
orderint: interpolate method, 0 for nearest, 1 for linear

Returns#

valuearray-like: 2D array, each point means value in z/nt pos

cigvis.utils.surfaceutils.interp_timefirst_impl(volume: ndarray, surf: ndarray, order: int) → ndarray#

interp value of timefirst volume in surf positions

Parameters#

volumearray-like: 3D array, shape as (nt, nx, ni)
surfarray-like: 2D array, shape as (nx, ni), each point means z/nt pos

Returns#

valuearray-like: 2D array, shape as (nx, ni), each point means value in z/nt pos

cigvis.utils.surfaceutils.interpolate_path(points, di=1)#: Interpolates a path from the given points with a given step size.

cigvis.utils.surfaceutils.preproc_surf_array2(surf, volume=None, value_type='depth')#: surf shape as (n1, n2)

cigvis.utils.surfaceutils.preproc_surf_array3(surf, value_type='depth')#: surf shape as (n1, n2, 2) or (n1, n2, 4) or (n1, n2, 5)

cigvis.utils.surfaceutils.preproc_surf_pos(surf, shape, volume=None, value_type='depth', interp=True, method='cubic', fill=-1)#: surf shape as (N, 3) or (N, 4) or (N, 6) or (N, 7)