Source code for pyrocko.model.gnss

# - GPLv3
# The Pyrocko Developers, 21st Century
# ---|P------/S----------~Lg----------

import logging
import math
import numpy as num
from collections import OrderedDict

import pyrocko.orthodrome as od

from pyrocko.guts import (Object, Float, String, List, StringChoice,
from pyrocko.model import Location

guts_prefix = 'pf.gnss'
logger = logging.getLogger('pyrocko.model.gnss')

[docs]class GNSSComponent(Object): ''' Component of a GNSSStation ''' unit = StringChoice.T( choices=['mm', 'cm', 'm'], help='Unit of displacement', default='m') shift = Float.T( default=0., help='Component\'s shift in unit') sigma = Float.T( default=0., help='One sigma uncertainty of the measurement') def __add__(self, other): if not isinstance(other, self.__class__): raise AttributeError('Other has to be of instance %s' % self.__class__) comp = self.__class__() comp.shift = self.shift + other.shift comp.sigma = math.sqrt(self.sigma**2 + other.sigma**2) return comp def __iadd__(self, other): self.shift += other.shift self.sigma = math.sqrt(self.sigma**2 + other.sigma**2) return self
[docs]class GNSSStation(Location): ''' Representation of a GNSS station during a campaign measurement For more information see ''' code = String.T( help='Four letter station code', optional=True) style = StringChoice.T( choices=['static', 'rapid_static', 'kinematic'], default='static') survey_start = DateTimestamp.T( optional=True, help='Survey start time') survey_end = DateTimestamp.T( optional=True, help='Survey end time') correlation_ne = Float.T( default=0., help='North-East component correlation') correlation_eu = Float.T( default=0., help='East-Up component correlation') correlation_nu = Float.T( default=0., help='North-Up component correlation') north = GNSSComponent.T( optional=True) east = GNSSComponent.T( optional=True) up = GNSSComponent.T( optional=True) def __eq__(self, other): try: return self.code == other.code except AttributeError: return False def get_covariance_matrix(self): components = self.components.values() ncomponents = self.ncomponents covar = num.zeros((ncomponents, ncomponents)) for ic1, comp1 in enumerate(components): for ic2, comp2 in enumerate(components): corr = self._get_comp_correlation(comp1, comp2) covar[ic1, ic2] = corr * comp1.sigma * comp2.sigma # This floating point operation is inaccurate: # corr * comp1.sigma * comp2.sigma != corr * comp2.sigma * comp1.sigma # # Hence this identity covar[num.tril_indices_from(covar, k=-1)] = \ covar[num.triu_indices_from(covar, k=1)] return covar def get_correlation_matrix(self): components = self.components.values() ncomponents = self.ncomponents corr = num.zeros((ncomponents, ncomponents)) corr[num.diag_indices_from(corr)] = num.array( [c.sigma for c in components]) for ic1, comp1 in enumerate(components): for ic2, comp2 in enumerate(components): if comp1 is comp2: continue corr[ic1, ic2] = self._get_comp_correlation(comp1, comp2) # See comment at get_covariance_matrix corr[num.tril_indices_from(corr, k=-1)] = \ corr[num.triu_indices_from(corr, k=1)] return corr def get_displacement_data(self): return num.array([c.shift for c in self.components.values()]) def get_component_mask(self): return num.array( [False if self.__getattribute__(name) is None else True for name in ('north', 'east', 'up')], dtype=bool) @property def components(self): return OrderedDict( [(name, self.__getattribute__(name)) for name in ('north', 'east', 'up') if self.__getattribute__(name) is not None]) @property def ncomponents(self): return len(self.components) def _get_comp_correlation(self, comp1, comp2): if comp1 is comp2: return 1. s = self correlation_map = { (s.north, s.east): s.correlation_ne, (s.east, s.up): s.correlation_eu, (s.north, s.up): s.correlation_nu } return correlation_map.get( (comp1, comp2), correlation_map.get((comp2, comp1), False))
[docs]class GNSSCampaign(Object): stations = List.T( GNSSStation.T(), help='List of GNSS campaign measurements') name = String.T( help='Campaign name', default='Unnamed campaign') survey_start = DateTimestamp.T( optional=True) survey_end = DateTimestamp.T( optional=True) def __init__(self, *args, **kwargs): Object.__init__(self, *args, **kwargs) self._cov_mat = None self._cor_mat = None def add_station(self, station): self._cor_mat = None self._cov_mat = None return self.stations.append(station) def remove_station(self, station_code): try: station = self.get_station(station_code) self.stations.remove(station) self._cor_mat = None self._cov_mat = None except ValueError: logger.warning('Station {} does not exist in campaign, ' 'do nothing.'.format(station_code)) def get_station(self, station_code): for sta in self.stations: if sta.code == station_code: return sta raise ValueError('Could not find station %s' % station_code) def get_center_latlon(self): return od.geographic_midpoint_locations(self.stations) def get_radius(self): coords = self.coordinates return od.distance_accurate50m( coords[:, 0].min(), coords[:, 1].min(), coords[:, 0].max(), coords[:, 1].max()) / 2. def get_covariance_matrix(self): if self._cov_mat is None: ncomponents = self.ncomponents cov_arr = num.zeros((ncomponents, ncomponents)) idx = 0 for ista, sta in enumerate(self.stations): ncomp = sta.ncomponents cov_arr[idx:idx+ncomp, idx:idx+ncomp] = \ sta.get_covariance_matrix() idx += ncomp self._cov_mat = cov_arr return self._cov_mat def get_correlation_matrix(self): if self._cor_mat is None: ncomponents = self.ncomponents cor_arr = num.zeros((ncomponents, ncomponents)) idx = 0 for ista, sta in enumerate(self.stations): ncomp = sta.ncomponents cor_arr[idx:idx+ncomp, idx:idx+ncomp] = \ sta.get_correlation_matrix() idx += ncomp self._cor_mat = cor_arr return self._cor_mat def get_component_mask(self): return num.concatenate( [s.get_component_mask() for s in self.stations]) def dump(self, *args, **kwargs): self.regularize() return Object.dump(self, *args, **kwargs) @property def coordinates(self): return num.array([loc.effective_latlon for loc in self.stations]) @property def nstations(self): return len(self.stations) @property def ncomponents(self): return sum([s.ncomponents for s in self.stations])