Source code for verde.datasets.synthetic

# pylint: disable=abstract-method
Generators of synthetic datasets.
import numpy as np

from ..base import BaseGridder
from ..coordinates import check_region

[docs]class CheckerBoard(BaseGridder): r""" Generate synthetic data in a checkerboard pattern. The mathematical model is: .. math:: f(e, n) = a \sin\left(\frac{2\pi}{w_e} e\right) \cos\left(\frac{2\pi}{w_n} n\right) in which :math:`e` is the easting coordinate, :math:`n` is the northing coordinate, :math:`a` is the amplitude, and :math:`w_e` and :math:`w_n` are the wavelengths in the east and north directions, respectively. Parameters ---------- amplitude : float The amplitude of the checkerboard undulations. region : tuple The boundaries (``[W, E, S, N]``) of the region used to generate the synthetic data. w_east : float The wavelength in the east direction. Defaults to half of the West-East size of the evaluating region. w_north : float The wavelength in the north direction. Defaults to half of the South-North size of the evaluating region. Examples -------- >>> synth = CheckerBoard() >>> # Default values for the wavelengths are selected automatically >>> print(synth.w_east_, synth.w_north_) 2500.0 2500.0 >>> # Checkerboard.grid produces an xarray.Dataset with data on a regular grid >>> grid = synth.grid(shape=(11, 6)) >>> type(grid) <class 'xarray.core.dataset.Dataset'> >>> # scatter and profile generate pandas.DataFrame objects >>> table = synth.scatter() >>> print(sorted(table.columns)) ['easting', 'northing', 'scalars'] >>> profile = synth.profile(point1=(0, 0), point2=(2500, -2500), size=100) >>> print(sorted(profile.columns)) ['distance', 'easting', 'northing', 'scalars'] """ def __init__( self, amplitude=1000, region=(0, 5000, -5000, 0), w_east=None, w_north=None ): self.amplitude = amplitude self.w_east = w_east self.w_north = w_north self.region = region @property def w_east_(self): "Use half of the E-W extent" if self.w_east is None: return (self.region[1] - self.region[0]) / 2 return self.w_east @property def w_north_(self): "Use half of the N-S extent" if self.w_north is None: return (self.region[3] - self.region[2]) / 2 return self.w_north @property def region_(self): "Used to fool the BaseGridder methods" check_region(self.region) return self.region
[docs] def predict(self, coordinates): """ Evaluate the checkerboard function on a given set of points. Parameters ---------- coordinates : tuple of arrays Arrays with the coordinates of each data point. Should be in the following order: (easting, northing, vertical, ...). Only easting and northing will be used, all subsequent coordinates will be ignored. Returns ------- data : array The evaluated checkerboard function. """ easting, northing = coordinates[:2] data = ( self.amplitude * np.sin((2 * np.pi / self.w_east_) * easting) * np.cos((2 * np.pi / self.w_north_) * northing) ) return data