Source code for opendrift.readers.basereader.variables

from datetime import timedelta
import numpy as np
import pyproj
from bisect import bisect_left
from abc import abstractmethod
import logging
logger = logging.getLogger(__name__)

from opendrift.timer import Timeable
from opendrift.errors import OutsideSpatialCoverageError, OutsideTemporalCoverageError, VariableNotCoveredError
from .consts import standard_names, vector_pairs_xy


[docs] class ReaderDomain(Timeable): """ Projection, spatial and temporal domain of reader. """ name = None proj4 = None proj = None lon = None lat = None xmin = None xmax = None ymin = None ymax = None zmin = -np.inf zmax = np.inf delta_x = None delta_y = None shape = None ## Temporal start_time = None end_time = None time_step = None times = None """Setting this to `True` overrides temporal and spatial bounds checks. Also useful for readers that are constant and do not have a temporal dimension.""" always_valid = False
[docs] def center(self): """ Returns center of reader (in lon, lat) """ if any(xx is None for xx in [self.xmin, self.xmax, self.ymin, self.ymax]): return None, None x = self.xmin + (self.xmax - self.xmin) / 2 y = self.ymin + (self.ymax - self.ymin) / 2 lo, la = self.xy2lonlat(x, y) return(lo[0], la[0])
[docs] def rotate_vectors(self, reader_x, reader_y, u_component, v_component, proj_from, proj_to): if isinstance(u_component, list): # Looping recursively over ensemble members uout = [] vout = [] for ucomp, vcomp in zip(u_component, v_component): ucomprot, vcomprot = self.rotate_vectors( reader_x, reader_y, ucomp, vcomp, proj_from, proj_to) uout.append(ucomprot) vout.append(vcomprot) return uout, vout """Rotate vectors from one crs to another.""" if type(proj_from) is str: proj_from = pyproj.Proj(proj_from) if type(proj_from) is not pyproj.Proj: proj_from = pyproj.Proj('+proj=latlong +R=6370997.0 +ellps=WGS84') reader_x, reader_y = self.xy2lonlat(reader_x, reader_y) if type(proj_to) is str: proj_to = pyproj.Proj(proj_to) if proj_from.crs.is_geographic: delta_y = .1 # 0.1 degree northwards else: delta_y = 10 # 10 m along y-axis transformer = pyproj.Transformer.from_proj(proj_from, proj_to) x2, y2 = transformer.transform(reader_x, reader_y) x2_delta, y2_delta = transformer.transform(reader_x, reader_y + delta_y) if proj_to.crs.is_geographic: geod = pyproj.Geod(ellps='WGS84') rot_angle_vectors_rad = np.radians( geod.inv(x2, y2, x2_delta, y2_delta)[0]) else: rot_angle_vectors_rad = np.arctan2(x2_delta - x2, y2_delta - y2) logger.debug('Rotating vectors between %s and %s degrees.' % (np.degrees(rot_angle_vectors_rad).min(), np.degrees(rot_angle_vectors_rad).max())) rot_angle_rad = -rot_angle_vectors_rad u_rot = (u_component * np.cos(rot_angle_rad) - v_component * np.sin(rot_angle_rad)) v_rot = (u_component * np.sin(rot_angle_rad) + v_component * np.cos(rot_angle_rad)) return u_rot, v_rot
[docs] def xy2lonlat(self, x, y): """Calculate x,y in own projection from given lon,lat (scalars/arrays). """ x = np.atleast_1d(x) y = np.atleast_1d(y) if self.proj.crs.is_geographic: if 'ob_tran' in str(self.proj4): logger.debug('NB: Converting degrees to radians ' + 'due to ob_tran srs') x = np.radians(np.array(x)) y = np.radians(np.array(y)) return self.proj(x, y, inverse=True) else: return x, y else: return self.proj(x, y, inverse=True)
[docs] def lonlat2xy(self, lon, lat): """ Calculate lon,lat from given x,y (scalars/arrays) in own projection. """ lon = np.atleast_1d(lon) lat = np.atleast_1d(lat) if 'ob_tran' in str(self.proj4): x, y = self.proj(lon, lat, inverse=False) return np.degrees(x), np.degrees(y) elif self.proj.crs.is_geographic: return lon, lat else: x, y = self.proj(lon, lat, inverse=False) return x, y
[docs] def y_azimuth(self, lon, lat): """Calculate azimuth orientation of the y-axis of the reader CRS.""" x0, y0 = self.lonlat2xy(lon, lat) distance = 1000.0 # Create points 1 km away to determine azimuth lon_2, lat_2 = self.xy2lonlat(x0, y0 + distance) geod = pyproj.Geod(ellps='WGS84') # Define an ellipsoid y_az = geod.inv(lon_2, lat_2, lon, lat, radians=False) return y_az[0]
[docs] def pixel_size(self): # Find typical pixel size (e.g. for calculating size of buffer) if self.delta_x is not None: pixelsize = self.delta_x if self.proj.crs.is_geographic is True or \ ('ob_tran' in self.proj4) or \ ('longlat' in self.proj4) or \ ('latlon' in self.proj4): pixelsize = pixelsize * 111000 # deg to meters else: pixelsize = None # Pixel size not defined return pixelsize
[docs] def _coverage_unit_(self): return "degrees"
[docs] def __repr__(self): """String representation of the current reader.""" outStr = '===========================\n' outStr += 'Reader: ' + self.name + '\n' outStr += 'Projection: \n ' + self.proj4 + '\n' outStr += 'Coverage: [%s]\n' % self._coverage_unit_() shape = self.shape if shape is None: outStr += ' xmin: %f xmax: %f\n' % (self.xmin, self.xmax) outStr += ' ymin: %f ymax: %f\n' % (self.ymin, self.ymax) else: outStr += ' xmin: %f xmax: %f step: %g numx: %i\n' % \ (self.xmin, self.xmax, self.delta_x or 0, shape[0]) outStr += ' ymin: %f ymax: %f step: %g numy: %i\n' % \ (self.ymin, self.ymax, self.delta_y or 0, shape[1]) corners = self.xy2lonlat([self.xmin, self.xmin, self.xmax, self.xmax], [self.ymax, self.ymin, self.ymax, self.ymin]) outStr += ' Corners (lon, lat):\n' outStr += ' (%6.2f, %6.2f) (%6.2f, %6.2f)\n' % \ (corners[0][0], corners[1][0], corners[0][2], corners[1][2]) outStr += ' (%6.2f, %6.2f) (%6.2f, %6.2f)\n' % \ (corners[0][1], corners[1][1], corners[0][3], corners[1][3]) if hasattr(self, 'z'): np.set_printoptions(suppress=True) outStr += 'Vertical levels [m]: \n ' + str(self.z) + '\n' elif hasattr(self, 'sigma'): outStr += 'Vertical levels [sigma]: \n ' + str(self.sigma) + '\n' else: outStr += 'Vertical levels [m]: \n Not specified\n' outStr += 'Available time range:\n' outStr += ' start: ' + str(self.start_time) + \ ' end: ' + str(self.end_time) + \ ' step: ' + str(self.time_step) + '\n' if self.start_time is not None and self.time_step is not None: outStr += ' %i times (%i missing)\n' % ( self.expected_time_steps, self.missing_time_steps) if hasattr(self, 'realizations') and self.realizations is not None: outStr += 'Variables (%i ensemble members):\n' % len( self.realizations) else: outStr += 'Variables:\n' for variable in self.variables: if variable in self.derived_variables: outStr += ' ' + variable + ' - derived from ' + \ str(self.derived_variables[variable]) + '\n' else: outStr += ' ' + variable + '\n' outStr += '===========================\n' outStr += self.performance() return outStr
[docs] def covers_positions_xy(self, x, y, z=0): """ Return indices of input points covered by reader. Arguments in native projection of reader. """ x = np.atleast_1d(x) y = np.atleast_1d(y) z = np.atleast_1d(z) if self.global_coverage(): # We need only check north-south and z coverage indices = np.where((y >= self.ymin) & (y <= self.ymax) & (z >= self.zmin) & (z <= self.zmax))[0] else: xx = x if self.proj.crs.is_geographic: xx = self.modulate_longitude(x) indices = np.where((xx >= self.xmin) & (xx <= self.xmax) & (y >= self.ymin) & (y <= self.ymax) & (z >= self.zmin) & (z <= self.zmax))[0] try: return indices, x[indices], y[indices] except Exception as ex: logger.exception(ex) return indices, x, y
[docs] def modulate_longitude(self, lons): """ Modulate the input longitude to the domain supported by the reader. """ yy = np.array([self.ymin, self.ymax, self.ymax, self.ymin]) xx = np.array([self.xmin, self.xmin, self.xmax, self.xmax]) exlons, _lats = self.xy2lonlat(xx, yy) if np.min(exlons) < 0: # Reader domain is from -180 to 180 or somewhere in between. assert np.max(exlons) <= 180.1 lons = np.mod(lons+180, 360) - 180 else: # Reader domain is from 0 to 360 or somewhere in between. assert np.max(exlons) <= 360.1 lons = np.mod(lons, 360) return lons
[docs] def covers_positions(self, lon, lat, z=0): """Return indices of input points covered by reader.""" x, y = self.lonlat2xy(lon, lat) return self.covers_positions_xy(x, y, z)
[docs] def global_coverage(self): """Return True if global coverage east-west""" dx = self.delta_x if self.delta_x is not None else 0 if self.proj.crs.is_geographic is True: if (self.xmin - 2*dx <= 0) and (self.xmax + 2*dx >= 360): return True # Global 0 to 360 if (self.xmin - 2*dx <= -180) and (self.xmax + 2*dx >= 180): return True # Global -180 to 180 return False
[docs] def domain_grid(self, npoints=1000): """Return arrays of lon,lat points spread evenly over reader domain.""" numx = np.floor(np.sqrt(npoints)) numy = np.floor(np.sqrt(npoints)) x = np.linspace(self.xmin, self.xmax - self.delta_x, numx) y = np.linspace(self.ymin, self.ymax - self.delta_y, numy) x, y = np.meshgrid(x, y) lons, lats = self.xy2lonlat(x, y) return lons, lats
[docs] def coverage_string(self): """Coverage of reader to be reported as string for debug output""" corners = self.xy2lonlat([self.xmin, self.xmin, self.xmax, self.xmax], [self.ymax, self.ymin, self.ymax, self.ymin]) return '%.2f-%.2fE, %.2f-%.2fN' % (np.min( corners[0]), np.max(corners[0]), np.min( corners[1]), np.max(corners[1]))
[docs] def check_arguments(self, variables, time, x, y, z): """Check validity of arguments input to method get_variables. Checks that requested positions and time are within coverage of this reader, and that it can provide the requested variable(s). Returns the input arguments, possibly modified/corrected (below) Arguments: See function get_variables for definition. Returns: variables: same as input, but converted to list if given as string. time: same as input, or start_time of reader if given as None. x, y, z: same as input, but converted to ndarrays if given as scalars. outside: boolean array which is True for any particles outside the spatial domain covered by this reader. Raises: ValueError: - if requested time is outside coverage of reader. - if all requested positions are outside coverage of reader. """ # Check time if time is None: time = self.start_time # Use first timestep, if not given # Convert variables to list and x,y to ndarrays if isinstance(variables, str): variables = [variables] x = np.atleast_1d(x) y = np.atleast_1d(y) if z is not None: z = np.asarray(z) for variable in variables: if variable not in self.variables: raise VariableNotCoveredError('Variable not available: ' + variable + '\nAvailable parameters are: ' + str(self.variables)) if (self.start_time is not None and time < self.start_time) and self.always_valid is False: raise OutsideTemporalCoverageError('Requested time (%s) is before first available ' 'time (%s) of %s' % (time, self.start_time, self.name)) if (self.end_time is not None and time > self.end_time) and self.always_valid is False: raise OutsideTemporalCoverageError('Requested time (%s) is after last available ' 'time (%s) of %s' % (time, self.end_time, self.name)) if self.global_coverage(): outside = np.where(~np.isfinite(x + y) | (y < self.ymin) | (y > self.ymax))[0] else: outside = np.where(~np.isfinite(x + y) | (x < self.xmin) | (x > self.xmax) | (y < self.ymin) | (y > self.ymax))[0] if np.size(outside) == np.size(x): lon, lat = self.xy2lonlat(x, y) raise OutsideSpatialCoverageError(('Argcheck: all %s particles (%.2f-%.2fE, ' + '%.2f-%.2fN) are outside domain of %s (%s)') % (len(lon), lon.min(), lon.max(), lat.min(), lat.max(), self.name, self.coverage_string())) return variables, time, x, y, z, outside
[docs] def covers_time(self, time): if self.always_valid is True: return True if self.start_time is None: return True # No time limitations of reader if (time < self.start_time) or (time > self.end_time): return False else: return True
[docs] def nearest_time(self, time): """Return nearest times before and after the requested time. Returns: nearest_time: datetime time_before: datetime time_after: datetime indx_nearest: int indx_before: int indx_after: int """ if self.start_time == self.end_time: return self.start_time, self.start_time, None, 0, 0, 0 if self.start_time is None: return None, None, None, None, None, None if self.times is not None: # Time as array, possibly with holes indx_before = np.max((0, bisect_left(self.times, time) - 1)) if len(self.times) > 1 and self.times[indx_before + 1] == time: # Correction needed when requested time exists in times indx_before = indx_before + 1 time_before = self.times[indx_before] indx_after = np.minimum(indx_before + 1, len(self.times) - 1) # At the end time_after = self.times[indx_after] if (time - time_before) < (time_after - time): indx_nearest = indx_before else: indx_nearest = indx_after nearest_time = self.times[indx_nearest] else: # Time step is constant (no holes) if self.time_step is None: return None, None, None, None, None, None indx = float((time - self.start_time).total_seconds()) / \ float(self.time_step.total_seconds()) indx_nearest = int(round(indx)) nearest_time = self.start_time + indx_nearest * self.time_step indx_before = int(np.floor(indx)) time_before = self.start_time + indx_before * self.time_step indx_after = int(np.ceil(indx)) time_after = self.start_time + indx_after * self.time_step return nearest_time, time_before, time_after,\ indx_nearest, indx_before, indx_after
################################################################ # Methods to derive environment variables from others available ################################################################
[docs] def land_binary_mask_from_ocean_depth(env): env['land_binary_mask'] = np.float32(env['sea_floor_depth_below_sea_level'] <= 0)
[docs] def wind_from_speed_and_direction(env, in_name, out_name): if 'wind_from_direction' in env: wfd = env['wind_from_direction'] else: wfd = -env['wind_to_direction'] north_wind = -env['wind_speed']*np.cos(np.radians(wfd)) east_wind = -env['wind_speed']*np.sin(np.radians(wfd)) env['x_wind'] = east_wind env['y_wind'] = north_wind
# Rotating might be necessary generally #x,y = np.meshgrid(env['x'], env['y']) #env['x_wind'], env['y_wind'] = self.rotate_vectors( # x, y, # east_wind, north_wind, # None, self.proj)
[docs] def vector_from_speed_and_direction(env, in_name, out_name): # TODO: assuming here lonlat or Mercator projection !!NB!! wfd = env[in_name[1]] env[out_name[0]] = env[in_name[0]]*np.cos(np.radians(wfd)) env[out_name[1]] = env[in_name[0]]*np.sin(np.radians(wfd))
[docs] def reverse_direction(env, in_name, out_name): env[out_name[0]] = env[in_name[0]]
[docs] def magnitude_from_components(env, in_name, out_name): env[out_name[0]] = np.sqrt( env[in_name[0]]**2 + env[in_name[1]]**2)
################################################################
[docs] class Variables(ReaderDomain): """ Handles reading and interpolation of variables. """ variables = None derived_variables = None name = None buffer = 0 def __init__(self): if self.derived_variables is None: self.derived_variables = {} if self.variables is None: self.variables = [] # Deriving environment variables from other available variables self.environment_mappings = { #'wind_from_speed_and_direction': { # 'input': ['wind_speed', 'wind_from_direction'], # 'output': ['x_wind', 'y_wind'], # 'method': wind_from_speed_and_direction, # #lambda reader, env: reader.wind_from_speed_and_direction(env)}, # 'active': True}, #'wind_from_speed_and_direction_to': { # 'input': ['wind_speed', 'wind_to_direction'], # 'output': ['x_wind', 'y_wind'], # 'method': wind_from_speed_and_direction, # #lambda reader, env: reader.wind_from_speed_and_direction(env)}, # 'active': True}, 'land_binary_mask_from_ocean_depth': { 'input': ['sea_floor_depth_below_sea_level'], 'output': ['land_binary_mask'], 'method': land_binary_mask_from_ocean_depth, 'active': False} } # Add automatically mappings from xcomp,ycomp <-> magnitude,direction for vector_pair in vector_pairs_xy: #if len(vector_pair) > 4: # TODO: temporarily disabling this test, as one test is failing, # as direction_to is automatically calculated from direction_from #self.environment_mappings[vector_pair[3]] = { # 'input': [vector_pair[4]], # 'output': [vector_pair[3]], # 'method': reverse_direction, # 'active': True # } #self.environment_mappings[vector_pair[4]] = { # 'input': [vector_pair[3]], # 'output': [vector_pair[4]], # 'method': reverse_direction, # 'active': True # } if len(vector_pair) >= 4: self.environment_mappings[str(vector_pair[0:2])] = { 'input': [vector_pair[2], vector_pair[3]], 'output': [vector_pair[0], vector_pair[1]], 'method': vector_from_speed_and_direction, 'active': True } if len(vector_pair) > 2: self.environment_mappings[vector_pair[2]] = { 'input': [vector_pair[0], vector_pair[1]], 'output': [vector_pair[2]], 'method': magnitude_from_components, 'active': True } super().__init__()
[docs] def activate_environment_mapping(self, mapping_name): if mapping_name not in self.environment_mappings: raise ValueError('Available environment mappings: ' + str(self.environment_mappings)) em = self.environment_mappings[mapping_name] em['active'] = True if not all(item in em['output'] for item in self.variables) and \ all(item in self.variables for item in em['input']): for v in em['output']: if v not in self.variables: logger.debug('Adding variable mapping: %s -> %s' % (em['input'], v)) self.variables.append(v) self.derived_variables[v] = em['input']
[docs] def __calculate_derived_environment_variables__(self, env): for m in self.environment_mappings: em = self.environment_mappings[m] if em['active'] is False: continue if not all(item in em['output'] for item in self.variables) and \ all(item in env for item in em['input']): for v in em['output']: logger.debug('Calculating variable mapping: %s -> %s' % (em['input'], v)) em['method'](env, em['input'], em['output'])
[docs] def set_buffer_size(self, max_speed, time_coverage=None): ''' Adjust buffer to minimise data block size needed to cover elements. The buffer size is calculated from the maximum anticpated speed. Seeding over a large area or over longer time can easily cause particles to be located outside the block. This is not critical, but causes interpolation to be one-sided in time for the relevant particles. Args: max_speed (m/s): the maximum speed anticipated for particles. time_coverage (timedelta): the time span to cover ''' self.buffer = 0 pixelsize = self.pixel_size() if pixelsize is not None: if self.time_step is not None: time_step_seconds = self.time_step.total_seconds() else: if time_coverage is None: logger.warning('Assuming time step of 1 hour for ' + self.name) time_step_seconds = 3600 # 1 hour if not given else: time_step_seconds = time_coverage.total_seconds() time_step_seconds = abs(time_step_seconds) self.buffer = int( np.ceil(max_speed * time_step_seconds / pixelsize)) + 2 logger.debug('Setting buffer size %i for reader %s, assuming ' 'a maximum average speed of %g m/s and time span of %s' % (self.buffer, self.name, max_speed,timedelta(seconds=time_step_seconds)))
[docs] def __check_env_coordinates__(self, env): """ Make sure x and y are floats (and not e.g. int64) """ if 'x' in env.keys(): env['x'] = np.array(env['x'], dtype=np.float32) env['y'] = np.array(env['y'], dtype=np.float32)
[docs] @staticmethod def __check_variable_array__(name, variable): """ Ensure arrays are not masked arrays and that values are within valid ranges. """ # Convert any masked arrays to NumPy arrays if isinstance(variable, np.ma.MaskedArray): variable = variable.astype(np.float32) variable = variable.filled(np.nan) # Mask values outside valid_min, valid_max (self.standard_names) if name in standard_names.keys(): logger.debug("Checking %s for invalid values" % name) if isinstance(variable, list): logger.debug( 'Min-max checking for ensemble data (%i members)' % (len(variable))) # Recursive return [ Variables.__check_variable_array__(name, v) for v in variable ] # with np.errstate(invalid='ignore'): invalid_indices = np.logical_and( np.isfinite(variable), np.logical_or(variable < standard_names[name]['valid_min'], variable > standard_names[name]['valid_max'])) if np.sum(invalid_indices) > 0: invalid_values = variable[invalid_indices] logger.warning( 'Invalid values (%s to %s) found for %s, replacing with NaN' % (invalid_values.min(), invalid_values.max(), name)) logger.warning('(allowed range: [%s, %s])' % (standard_names[name]['valid_min'], standard_names[name]['valid_max'])) variable[invalid_indices] = np.nan return variable
[docs] def __check_env_arrays__(self, env): """ Ensure arrays are not masked arrays and that values are within valid ranges. .. seealso:: Disabled in `StructuredReader` because variables are valided before entered into interpolator: :meth:`.structured.StructuredReader.__check_env_arrays__` """ variables = [ var for var in env.keys() if var not in ['x', 'y', 'time'] ] for variable in variables: env[variable] = self.__check_variable_array__( variable, env[variable]) return env
[docs] @abstractmethod def _get_variables_interpolated_(self, variables, profiles, profiles_depth, time, reader_x, reader_y, z): """ This method _must_ be implemented by every reader. Usually by subclassing one of the reader types (e.g. :class:`structured.StructuredReader`). Arguments are in _native projection_ of reader. .. seealso: * :meth:`get_variables_interpolated_xy`. * :meth:`get_variables_interpolated`. """ pass
[docs] def get_variables_interpolated_xy(self, variables, profiles=None, profiles_depth=None, time=None, x=None, y=None, z=None, rotate_to_proj=None): """ Get variables in native projection of reader. .. seealso:: * :meth:`get_variables_interpolated`. * :meth:`_get_variables_interpolated_`. """ self.timer_start('total') # Raise error if time not not within coverage of reader if not self.covers_time(time): raise OutsideTemporalCoverageError('%s is outside time coverage (%s - %s) of %s' % (time, self.start_time, self.end_time, self.name)) self.timer_start('preparing') x = np.atleast_1d(x) numx = len(x) # To check later if all points were covered y = np.atleast_1d(y) z = np.atleast_1d(z) if z is not None else np.zeros((1, )) assert numx == len(y), "x, y, and z must have the same length" assert len(z) == 1 or numx == len( z), "x, y, and z must have the same length" ind_covered, xx, yy = self.covers_positions_xy(x, y, z) if len(ind_covered) == 0: lon, lat = self.xy2lonlat(x, y) raise OutsideSpatialCoverageError( ('All %s particles (%.2f-%.2fE, %.2f-%.2fN) ' + 'are outside domain of %s (%s)') % (len(x), lon.min(), lon.max(), lat.min(), lat.max(), self.name, self.coverage_string())) x = xx y = yy self.timer_end('preparing') # Make copy of z to avoid modifying original array if len(z) == 1 and len(x) > 1: z = z.copy() * np.ones(x.shape) z = z.copy()[ind_covered] logger.debug('Fetching variables from ' + self.name) self.timer_start('reading') # Filter derived variables derived = [] derived_input = [] for var in variables: if var in self.derived_variables: logger.debug("Scheduling %s to be derived from %s" % (var, self.derived_variables[var])) derived_input.extend(self.derived_variables[var]) derived.append(var) for v in derived: variables.remove(v) variables.extend(list(set(derived_input))) env, env_profiles = self._get_variables_interpolated_( variables, profiles, profiles_depth, time, x, y, z) # Calculate derived variables if len(derived) > 0: self.__calculate_derived_environment_variables__(env) variables.extend(derived) for e in [env, env_profiles]: if e is not None: self.__check_env_coordinates__(e) self.__check_env_arrays__(e) self.timer_end('reading') # Rotating vectors fields if rotate_to_proj is not None: if self.proj.crs.is_geographic and 'ob_tran' not in self.proj4: logger.debug('Reader projection is latlon - ' 'rotation of vectors is not needed.') else: vector_pairs = [] for var in variables: for vector_pair in vector_pairs_xy: if var in vector_pair[0:2]: counterpart = list(set(vector_pair[0:2]) - set([var]))[0] if counterpart in variables: vector_pairs.append(vector_pair[0:2]) else: logger.warning( 'Missing component of vector pair, cannot rotate:' + counterpart) # Extract unique vector pairs vector_pairs = [ list(x) for x in set(tuple(x) for x in vector_pairs) ] if len(vector_pairs) > 0: self.timer_start('rotating vectors') for vector_pair in vector_pairs: env[vector_pair[0]], env[vector_pair[1]] = \ self.rotate_vectors(x, y, env[vector_pair[0]], env[vector_pair[1]], self.proj, rotate_to_proj) if profiles is not None and vector_pair[0] in profiles: env_profiles[vector_pair[0]], env_profiles[vector_pair[1]] = \ self.rotate_vectors (x, y, env_profiles[vector_pair[0]], env_profiles[vector_pair[1]], self.proj, rotate_to_proj) self.timer_end('rotating vectors') # Masking non-covered pixels self.timer_start('masking') if len(ind_covered) != numx: logger.debug('Masking %i elements outside coverage' % (numx - len(ind_covered))) for var in variables: tmp = np.nan * np.ones(numx) tmp[ind_covered] = env[var].copy() env[var] = np.ma.masked_invalid(tmp) # Filling also in missing columns # for env_profiles outside coverage if env_profiles is not None and var in env_profiles.keys(): tmp = np.nan * np.ones((env_profiles[var].shape[0], numx)) tmp[:, ind_covered] = env_profiles[var].copy() env_profiles[var] = np.ma.masked_invalid(tmp) self.timer_end('masking') self.timer_end('total') return env, env_profiles
[docs] def get_variables_interpolated(self, variables, profiles=None, profiles_depth=None, time=None, lon=None, lat=None, z=None, rotate_to_proj=None): """ `get_variables_interpolated` is the main interface to :class:`opendrift.basemodel.OpenDriftSimulation`, and is responsible for returning variables at the correct positions. Readers should implement :meth:`_get_variables_interpolated_`. Arguments: variables: string, or list of strings (standard_name) of requested variables. These must be provided by reader. profiles: List of variable names that should be returned for the range in `profiles_depth`. profiles_depth: A range [z-start, z-end] for which to return values for profile-variables. The exact z-depth are given by the reader and returned as `z` variable in `env_profiles`. time: datetime or None, time at which data are requested. Can be None (default) if reader/variable has no time dimension (e.g. climatology or landmask). lon: longitude, 1d array. lat: latitude, 1d array, same length as lon. z: float or ndarray; vertical position (in meters, positive up) of requested points. either scalar or same length as lon, lat. default: 0 m (unless otherwise documented by reader) block: bool, see return below rotate_to_proj: N/A Returns: (env, env_profiles) Interpolated variables at x, y and z. `env` contains values at a fixed depth (`z`), while `env_profiles` contains depth-profiles in the range `profile_depth` for the variables listed in `profiles` for each element (in `x`, `y`). The exact depth is determined by the reader and specified in `env_profiles['z']`. Thus variables in `env_profiles` are not interpolated in z-direction. .. seealso:: :meth:`get_variables_interpolated_xy`. """ assert set(variables).issubset(self.variables), f"{variables} is not subset of {self.variables}" lon = self.modulate_longitude(lon) x, y = self.lonlat2xy(lon, lat) env, env_profiles = self.get_variables_interpolated_xy( variables, profiles, profiles_depth, time, x, y, z, rotate_to_proj) return env, env_profiles