py_eddy_tracker.observations.groups.GroupEddiesObservations

class py_eddy_tracker.observations.groups.GroupEddiesObservations(size=0, track_extra_variables=None, track_array_variables=0, array_variables=None, only_variables=None, raw_data=False)

Bases: EddiesObservations, ABC

Methods

add_fields	Add a new field.
add_rotation_type
align_on	Align the variable indices of two datasets.
append	Merge.
basic_formula_ellipse_major_axis	Give major axis in km with a given latitude
bins_stat	param str,array xname: variable to compute stats on
box_display	Return values evenly spaced with few numbers
build_var_list
circle_contour	Set contours as circles from radius and center data.
coherence	Check coherence between two datasets.
compare_units
concatenate
contains	Return index of contour containing (x,y)
copy
copy_data_to_zarr	Copy with buffer for zarr.
cost_function	Return the cost function between two obs.
cost_function_common_area	How does it work on x bound ?
create_particles	Create particles inside contour (Default : speed contour).
create_variable
create_variable_zarr
display	Plot the speed and effective (dashed) contour of the eddies
display_color	Plot colored contour of eddies
distance	Use haversine distance for distance matrix between every self and other eddies.
empty_dataset
extract_with_area	Extract geographically with a bounding box.
extract_with_mask	Extract a subset of observations.
field_table	Produce description table of the fields available in this object
fill_coherence	_summary_
filled	param matplotlib.axes.Axes ax: matplotlib axe used to draw
filled_by_interpolation	Fill selected values by interpolation
first_obs	Get first obs of each trajectory.
fix_next_previous_obs
fixed_ellipsoid_mask
format_label
from_array
from_netcdf
from_zarr
get_color	Return colors as a cyclic list
get_filters_zarr	Get filters to store in zarr for known variable
get_infos
get_missing_indices	Find indexes where observations are missing
grid_box_stat	Get percentile of eddies in each bin
grid_count	Count the eddies in each bin (use all pixels in each contour)
grid_stat	Return the mean of the eddies' variable in each bin
hist	Build histograms.
index	Return obs from self at the index.
insert_observations	Insert other obs in self at the given index.
insert_virtual	Insert virtual observations on segments where observations are missing
inside	True for each point inside the effective contour of an eddy
intern
interp_grid	Interpolate a grid on a center or contour with mean, min or max method
is_convex	Get flag of the eddy's convexity
iter_on	Yield observation group for each bin.
keep_tracks_by_date	Find tracks that exist at date date and lasted at least nb_days after.
last_obs	Get Last obs of each trajectory.
load_file	Load the netcdf or the zarr file.
load_from_netcdf	Load data from netcdf.
load_from_zarr	Load data from zarr.
mask_from_polygons	Return mask for all observations in one of polygons list
mask_function
match	Return index and score computed on the effective contour.
merge	Merge two datasets.
merge_filters	Compute an intersection between all filters after to evaluate each of them
merge_particle_result	Copy local result in merged result with global indexation
needed_variable
netcdf_create_dimensions
new_like
obs_dimension
parse_varname
particle_candidate_atlas	Select particles within eddies, advect them, return target observation and associated percentages
post_process_link
propagate	Fill virtual obs (C).
re_reference_index	Shift index with ref
remove_fields	Copy with fields listed remove
reset
scatter	Scatter data.
set_global_attr_netcdf
set_global_attr_zarr
shifted_ellipsoid_degrees_mask
solve_conflict
solve_first
solve_function
solve_simultaneous	Deduce link from cost matrix.
time_sub_sample	Time sub sampling
to_netcdf
to_zarr
tracking	Track obs between self and other
write_file	Write a netcdf or zarr with eddy obs.
zarr_dimension

Attributes

track_extra_variables
track_array_variables
array_variables
only_variables
observations
sign_type
raw_data
period_
COLORS
ELEMENTS
NB_COLORS
dtype	Return dtype to build numpy array.
elements	Return all the names of the variables.
fields
global_attr
nb_days	Return period in days covered by the dataset
obs	Return observations.
period	Give the time coverage.
shape
sign_legend
time_datetime64
tracks

array_variables

classmethod fill_coherence(network, i_targets, percents, i_origin, i_end, start_intern, end_intern, **kwargs)

_summary_

Parameters:

• i_targets (array) – global target

• percents (array) –

• i_origin (array) – indices of origins

• i_end (array) – indices of ends

• start_intern (bool) – Use intern or extern contour at injection

• end_intern (bool) – Use intern or extern contour at end of advection

filled_by_interpolation(mask)

Fill selected values by interpolation

Parameters:

mask (array(bool)) – True if must be filled by interpolation

Track in python

Track in python

Correspondances

Correspondances

abstract fix_next_previous_obs()

abstract get_missing_indices(dt)

Find indexes where observations are missing

insert_virtual()

Insert virtual observations on segments where observations are missing

keep_tracks_by_date(date, nb_days)

Find tracks that exist at date date and lasted at least nb_days after.

Parameters:

• date (int,float) – date where the tracks must exist

• nb_days (int,float) – number of times the tracks must exist. Can be negative

If nb_days is negative, it searches a track that exists at the date, but existed at least nb_days before the date

static merge_particle_result(i_targets, percents, i_local_targets, local_percents, i_origin, i_end)

Copy local result in merged result with global indexation

Parameters:

• i_targets (array) – global target

• percents (array) –

• i_local_targets (array) – local index target

• local_percents (array) –

• i_origin (array) – indices of origins

• i_end (array) – indices of ends

observations

only_variables

particle_candidate_atlas(cube, space_step, dt, start_intern=False, end_intern=False, callback_coherence=None, finalize_coherence=None, **kwargs)

Select particles within eddies, advect them, return target observation and associated percentages

Parameters:

• cube (GridCollection) – GridCollection with speed for particles

• space_step (float) – step between 2 particles

• dt (int) – duration of advection

• start_intern (bool) – Use intern or extern contour at injection, defaults to False

• end_intern (bool) – Use intern or extern contour at end of advection, defaults to False

• kwargs (dict) – dict of params given to advection

• callback_coherence (func) – if None we will use cls.fill_coherence

• finalize_coherence (func) – to apply on results of callback_coherence

Return (np.array,np.array):

return target index and percent associate

period_

raw_data

sign_type

track_array_variables

track_extra_variables