wavy.collocation_module

Module that should take care of collocation of points or swaths
Needs input from modules that retrieve from observational platforms and models

Attributes

`model_dict`
`insitu_dict`
`variable_def`

Classes

collocation_class

draft of envisioned collocation class object

Functions

`collocate_observations`(co1, co2[, twin, dist_max])	Collocates observations from two wavy objects, keeping only closest
`collocation_fct`(obs_lons, obs_lats, model_lons, model_lats)
`get_model_filename`(nID, d, leadtime, **kwargs)
`find_valid_fc_dates_for_model_and_leadtime`(fc_dates, ...)	Finds valid dates that are close to desired dates at a precision
`check_if_file_is_valid`(fc_date, model, leadtime, **kwargs)
`get_closest_date`(overdetermined_lst, target_lst)
`adjust_dict_for_idx`(indict, idx, excl_keys_lst)
`validate_collocated_values`(dtime, obs, mods, **kwargs)

Module Contents

wavy.collocation_module.model_dict

wavy.collocation_module.insitu_dict

wavy.collocation_module.variable_def

wavy.collocation_module.collocate_observations(co1, co2, twin=5, dist_max=200)

Collocates observations from two wavy objects, keeping only closest data from the second dataset within a given time range around each observation from the first given dataset.

Args:

co1 (insitu_class or satellite_class object): first observation dataset: the data from the second dataset will be collocated around this one.
co2 (insitu_class or satellite_class object): second observation: dataset

twin (int): time window length in minutes dist_max (int | float): Maximum distance

accepted to collocate data, in km

Returns:

tuple (co1_filter (insitu_class or satellite_class object),

co2_filter (insitu_class or satellite_class object)): first and: second objects given as inputs, with data filtered to keep only collocated observations

wavy.collocation_module.collocation_fct(obs_lons, obs_lats, model_lons, model_lats)

wavy.collocation_module.get_model_filename(nID, d, leadtime, **kwargs)

wavy.collocation_module.find_valid_fc_dates_for_model_and_leadtime(fc_dates, model, leadtime, colloc_time_method, **kwargs): Finds valid dates that are close to desired dates at a precision of complete hours

wavy.collocation_module.check_if_file_is_valid(fc_date, model, leadtime, **kwargs)

wavy.collocation_module.get_closest_date(overdetermined_lst, target_lst)

wavy.collocation_module.adjust_dict_for_idx(indict, idx, excl_keys_lst)

class wavy.collocation_module.collocation_class(oco=None, model=None, poi=None, leadtime=None, varalias=None, **kwargs)

Bases: wavy.quicklookmod.quicklook_class_sat

draft of envisioned collocation class object

varalias = None

varalias_obs

varalias_mod = None

model = None

leadtime = None

oco = None

nID

obstype = ''

units

stdvarname

region

sd

ed

twin

distlim

method

colloc_time_method

nproc

res

populate(**kwargs)

_build_xr_dataset(results_dict, **kwargs)

_drop_duplicates(**kwargs)

_collocate_field(mco, tmp_dict, **kwargs): Some info

_collocate_track(**kwargs): Some info

_collocate_centered_model_value(time, lon, lat, **kwargs)

_collocate_regridded_model(**kwargs)

collocate(**kwargs)

get obs value for model value for given: temporal and spatial constraints

validate_collocated_values(**kwargs)

wavy.collocation_module.validate_collocated_values(dtime, obs, mods, **kwargs)