Module gplately.ptt.utils.subduction_teeth

Expand source code
import numpy as np

def tesselate_triangles(shapefilename, tesselation_radians, triangle_base_length, triangle_aspect=1.0):
    """
    Place subduction teeth along line segments within a MultiLineString shapefile
    
    Parameters
    ----------
        shapefilename  : str  path to shapefile
        tesselation_radians : float
        triangle_base_length : float  length of base
        triangle_aspect : float  aspect ratio
            Setting triangle_aspect to -1 reverses the tooth direction
        
    Returns
    -------
        X_points : (n,3) array of triangle x points
        Y_points : (n,3) array of triangle y points
    """

    import shapefile
    shp = shapefile.Reader(shapefilename)

    tesselation_degrees = np.degrees(tesselation_radians)
    triangle_pointsX = []
    triangle_pointsY = []

    for i in range(len(shp)):
        pts = np.array(shp.shape(i).points)

        cum_distance = 0.0
        for p in range(len(pts) - 1):

            A = pts[p]
            B = pts[p+1]

            AB_dist = B - A
            AB_norm = AB_dist / np.hypot(*AB_dist)
            cum_distance += np.hypot(*AB_dist)

            # create a new triangle if cumulative distance is exceeded.
            if cum_distance >= tesselation_degrees:

                C = A + triangle_base_length*AB_norm

                # find normal vector
                AD_dist = np.array([AB_norm[1], -AB_norm[0]])
                AD_norm = AD_dist / np.linalg.norm(AD_dist)

                C0 = A + 0.5*triangle_base_length*AB_norm

                # project point along normal vector
                D = C0 + triangle_base_length*triangle_aspect*AD_norm

                triangle_pointsX.append( [A[0], C[0], D[0]] )
                triangle_pointsY.append( [A[1], C[1], D[1]] )

                cum_distance = 0.0

    shp.close()
    return np.array(triangle_pointsX), np.array(triangle_pointsY)

Functions

def tesselate_triangles(shapefilename, tesselation_radians, triangle_base_length, triangle_aspect=1.0)

Place subduction teeth along line segments within a MultiLineString shapefile

Parameters

shapefilename  : str  path to shapefile
tesselation_radians : float
triangle_base_length : float  length of base
triangle_aspect : float  aspect ratio
    Setting triangle_aspect to -1 reverses the tooth direction

Returns

X_points : (n,3) array of triangle x points
Y_points : (n,3) array of triangle y points
Expand source code
def tesselate_triangles(shapefilename, tesselation_radians, triangle_base_length, triangle_aspect=1.0):
    """
    Place subduction teeth along line segments within a MultiLineString shapefile
    
    Parameters
    ----------
        shapefilename  : str  path to shapefile
        tesselation_radians : float
        triangle_base_length : float  length of base
        triangle_aspect : float  aspect ratio
            Setting triangle_aspect to -1 reverses the tooth direction
        
    Returns
    -------
        X_points : (n,3) array of triangle x points
        Y_points : (n,3) array of triangle y points
    """

    import shapefile
    shp = shapefile.Reader(shapefilename)

    tesselation_degrees = np.degrees(tesselation_radians)
    triangle_pointsX = []
    triangle_pointsY = []

    for i in range(len(shp)):
        pts = np.array(shp.shape(i).points)

        cum_distance = 0.0
        for p in range(len(pts) - 1):

            A = pts[p]
            B = pts[p+1]

            AB_dist = B - A
            AB_norm = AB_dist / np.hypot(*AB_dist)
            cum_distance += np.hypot(*AB_dist)

            # create a new triangle if cumulative distance is exceeded.
            if cum_distance >= tesselation_degrees:

                C = A + triangle_base_length*AB_norm

                # find normal vector
                AD_dist = np.array([AB_norm[1], -AB_norm[0]])
                AD_norm = AD_dist / np.linalg.norm(AD_dist)

                C0 = A + 0.5*triangle_base_length*AB_norm

                # project point along normal vector
                D = C0 + triangle_base_length*triangle_aspect*AD_norm

                triangle_pointsX.append( [A[0], C[0], D[0]] )
                triangle_pointsY.append( [A[1], C[1], D[1]] )

                cum_distance = 0.0

    shp.close()
    return np.array(triangle_pointsX), np.array(triangle_pointsY)