Source code for sorts.radar.scans.plane

#!/usr/bin/env python

'''

'''

import numpy as np

from .scan import Scan

class Plane(Scan):
    '''A uniform sampling of a horizontal plane.
    '''
    def __init__(self, min_elevation=30.0, altitude=200e3, x_size=50e3, y_size=50e3, x_num=20, y_num=20, dwell=0.1, x_offset=0.0, y_offset=0.0):
        super().__init__(coordinates='enu')
        self._dwell = dwell
        self.min_elevation = min_elevation
        self.altitude = altitude
        
        self.x_size = x_size
        self.y_size = y_size
        self.x_num = x_num
        self.y_num = y_num

        k = np.empty((3, x_num*y_num), dtype=np.float64)

        xv, yv = np.meshgrid(
            np.linspace(-x_size*0.5, x_size*0.5, num=self.x_num, endpoint=True) + x_offset,
            np.linspace(-y_size*0.5, y_size*0.5, num=self.y_num, endpoint=True) + y_offset,
            sparse=False, 
            indexing='ij',
         )

        k[0,:] = xv.flatten()
        k[1,:] = yv.flatten()
        k[2,:] = altitude

        k = k/np.linalg.norm(k, axis=0)

        min_z = np.sin(np.radians(min_elevation))
        k = k[:, k[2,:] >= min_z]
        self.num = k.shape[1]
        self.pointings = k


    def dwell(self, t=None):
        if t is None:
            return self._dwell
        else:
            if isinstance(t, float) or isinstance(t, int):
                return self._dwell
            else:
                return np.ones(t.shape, dtype=t.dtype)*self._dwell


    def min_dwell(self):
        return self._dwell


    def cycle(self):
        return self.num*self._dwell


    def pointing(self, t):
        ind = (np.mod(t/self.cycle(), 1)*self.num).astype(np.int)
        return self.pointings[:,ind]