sisppeo.products package¶

Submodules¶

sisppeo.products.l3 module¶

This module gathers classes related to L3 products.

In this module are defined L3 products : the abstract class L3Product and its child classes L3AlgoProduct and L3MaskProduct. Basically, these classes wrap a well formated xarray Dataset and offer a few useful methods.

Example:

S2_ndvi = L3AlgoProduct(dataset)
S2_ndvi.plot()
S2_ndvi.save(path_to_file)

s2cloudless_mask = L3MaskProduct(dataset)
s2cloudless_mask.save(path_to_file)

class sisppeo.products.l3.L3AlgoProduct(dataset)[source]¶

Bases: sisppeo.products.l3.L3Product

An L3Product embedding data obtained by using a wc/land algorithm.

dataset¶

A dataset containing processed data.

Type: xarray.core.dataset.Dataset

property algo¶: Returns the name of the algorithm used to get this dataset.

classmethod from_file(filename)[source]¶

save(filename)[source]¶: See base class.

class sisppeo.products.l3.L3MaskProduct(dataset)[source]¶

Bases: sisppeo.products.l3.L3Product

An L3Product embedding data obtained by using a mask algorithm.

dataset¶

A dataset containing processed data.

Type: xarray.core.dataset.Dataset

classmethod from_file(filename)[source]¶

property mask¶: Returns the name of the mask used to get this dataset.

save(filename)[source]¶: See base class.

class sisppeo.products.l3.L3Product(dataset)[source]¶

Bases: abc.ABC, sisppeo.utils.products.CoordinatesMixin

Abstract class inherited by both L3AlgoProduct and L3MaskProduct.

dataset¶

A dataset containing processed data.

Type: xarray.core.dataset.Dataset

property data_vars¶: Returns a list of DataArrays corresponding to variables.

dataset¶

abstract classmethod from_file(filename)[source]¶

Loads and returns a L3Product from file.

Parameters: filename – The path to the L3Product (saved as a netCDF file).

plot(data_var)[source]¶

Plots a given variable.

data_var: The name of the variable/DataArray of interest (e.g., a: band, aCDOM, etc).

property product_type¶: Returns the product_type of the product used to get this dataset.

abstract save(filename)[source]¶

Saves this product into a netCDF file.

Parameters: filename – Path of the output file.

property title¶: Returns the title of the underlying dataset.

sisppeo.products.l3.mask_product(l3_algo, l3_masks, lst_mask_type, inplace=False)[source]¶

Masks an L3AlgoProduct.

Masks an L3AlgoProduct with one or more L3MaskProducts. It can be used for instance to get rid of clouds or to extract only water areas.

Parameters

l3_algo – The L3AlgoProduct to be masked.
l3_masks – The mask or list of masks to use.
lst_mask_type – The type of the input mask (or the list of the types of input masks). Can either be ‘IN’ or ‘OUT’, indicating if the corresponding mask is inclusive or exclusive.
inplace – If True, do operation inplace and return None.

Returns

A masked L3AlgoProduct.

sisppeo.products.timeseries module¶

This module contains the TimeSeries class.

A TimeSeries object is a new kind of product, made from either L1, L2, or L3 products, and allowing one to build a time series:

Masks can be used to clip data.
Basic statistics can be calculated.
Generic plots can easily be made.

Example:

paths = [<first S2_ESA_L2A product>, <second S2_ESA_L2A product>, ...,
       <n-th S2_ESA_L2A product>]
mask_paths = [
    [<first water_mask>, <second water_mask>, ..., <n-th water_mask>],
    [<first mask2>
config = {
    'paths': paths,
    'product_type': 'S2_ESA_L2A',
    'requested_bands': ['B2', 'B3', 'B4', 'B5', 'B6'],
    'wkt': wkt,
    'srid': 4326,
}
S2L2A_ts = factory.create('TS', **config)
S2L2A_ts.compute_stats(<filename>)
S2L2A_ts.plot()

class sisppeo.products.timeseries.TimeSeries(dataset)[source]¶

Bases: sisppeo.utils.products.CoordinatesMixin

A ‘L4’ product, made from either L1, L2, or L3 products.

This product contain one or more DataArrays (e.g., one for ndwi, one for each band extracted…). Each DataArrays is a data cube (i.e. 3D: x, y, time). It allows one to study time series of data, and compute and plot statistics over time and/or space.

dataset¶

A dataset containing one or more 3D-dataarrays.

Type: xarray.core.dataset.Dataset

compute_stats(filename, plot=True)[source]¶

Computes (and save on disk) statistics about embedded data at each date.

Parameters

filename – The path of the output product (a CSV file).
plot – A boolean flag that indicates if computed statistics should be plotted or not.

property data_vars¶: Returns a list of DataArrays corresponding to variables.

dataset¶

property end_date¶: Return the end date.

classmethod from_file(filename)[source]¶

Load a TimeSeries object from disk.

Parameters: filename – The path of the netCDF file.
Returns: time, x, y).
Return type: A TimeSeries object (i.e. a 3D dataset

classmethod from_files(paths)[source]¶

Load and merge a list of L3 products from disk.

Parameters: paths – A list of paths (to L3 products saved as netCDF files).
Returns: time, x, y).
Return type: A TimeSeries object (i.e. a 3D dataset

classmethod from_l3products(lst)[source]¶

Load and merge a list of L3 products.

Parameters: lst – A list of L3 products (loaded in memory).
Returns: time, x, y).
Return type: A TimeSeries object (i.e. a 3D dataset

get_max_map(var, plot=True, filename=None, save=False, savefig=False, fmt='jpeg')[source]¶

Gets the map of (temporal) max values for a given data_var.

Compute a map (a dataarray of dimension N * M) from a dataarray of dimension t * N * M. Each pixel of this map is the max value of the N * M t-vectors.

Parameters

var – The name of the dataarray to use.
plot – A boolean flag that indicates if the figure should be plotted or not.
filename – Optional; The path of the output product (a figure and/or a netCDF file).
save – Optional; A boolean flag that indicates if the mean map should be saved on disk or not.
savefig – Optional; A boolean flag that indicates if the figure should be saved or not.
fmt – The format of the static image that is saved on disk. Can be either “png”, “jpeg”, “webp”, “svg” or “pdf”.

Returns

A map (a dataarray of dimension N * M) of max values for a given data_var.

get_mean_map(var, plot=True, filename=None, save=False, savefig=False, fmt='jpeg')[source]¶

Gets the map of (temporal) mean values for a given data_var.

Compute a map (a DataArray of dimension N * M) from a DataArray of dimension t * N * M. Each pixel of this map is the mean value of the N * M t-vectors.

Parameters

var – The name of the DataArray to use.
plot – A boolean flag that indicates if the figure should be plotted or not.
filename – Optional; The path of the output product (a figure and/or a netCDF file).
save – Optional; A boolean flag that indicates if the mean map should be saved on disk or not.
savefig – Optional; A boolean flag that indicates if the figure should be saved or not.
fmt – The format of the static image that is saved on disk. Can be either “png”, “jpeg”, “webp”, “svg” or “pdf”.

Returns

A map (a dataarray of dimension N * M) of mean values for a given data_var.

get_min_map(var, plot=True, filename=None, save=False, savefig=False, fmt='jpeg')[source]¶

Gets the map of (temporal) min values for a given data_var.

Compute a map (a dataarray of dimension N * M) from a dataarray of dimension t * N * M. Each pixel of this map is the min value of the N * M t-vectors.

Parameters

var – The name of the dataarray to use.
plot – A boolean flag that indicates if the figure should be plotted or not.
filename – Optional; The path of the output product (a figure and/or a netCDF file).
save – Optional; A boolean flag that indicates if the mean map should be saved on disk or not.
savefig – Optional; A boolean flag that indicates if the figure should be saved or not.
fmt – The format of the static image that is saved on disk. Can be either “png”, “jpeg”, “webp”, “svg” or “pdf”.

Returns

A map (a dataarray of dimension N * M) of min values for a given data_var.

plot_1d(lst_coordinates, data_var='all', buffer=None, epsg=4326, mode='xy', filename=None, fmt='jpeg')[source]¶

Plots time series of data_var(s) for one or more given points.

Parameters

lst_coordinates – A tuple of coordinates (x, y) that locates the point to extract (/a list of tuples of coordinates, locating points of interest).
data_var – Optional; A variable (e.g. “aCDOM”) or a list of variables to plot.
buffer –
epsg –
mode –
filename – Optional; If a filename is provided, the figure will be saved using this path.
fmt – The format of the exported figure. Can be either “png”, “jpeg”, “webp”, “svg” or “pdf”.

plot_2d(data_vars='all', filename=None, fmt='jpeg')[source]¶

Plots timelapse as a mosaic (one per data_var).

For each data_var, create a figure composed of multiples subplots, each one of them being a image of the given data_var at a given date.

Parameters

data_vars – A variable (e.g. “aCDOM”) or a list for variables to plot. If ‘all’, creates a figure for each variable (i.e. DataArray) embedded into this dataset.
filename – Optional; If a filename is provided, the figure will be saved using this path.
fmt – The format of the exported figure. Can be either “png”, “jpeg”, “webp”, “svg” or “pdf”.

plot_hists(data_vars='all', dates='all', plot=True, filename=None, fmt='jpeg')[source]¶

Plots an histogram (per data_var, per date).

For each data_var, at each date, plots an histogram using the right array of values.

Parameters

data_vars – The name of the dataarray to plot. If ‘all’, create a figure for each dataarray (i.e. for each data_var in data_vars).
dates – The wanted date. If ‘all’, create a histogram for each date.
plot – A boolean flag that indicates if the figure should be plotted or not.
filename – Optional; The path of the output figure.
fmt – The format of the static image that is saved on disk. Can be either “png”, “jpeg”, “webp”, “svg” or “pdf”.

plot_stats_maps(data_vars='all', filename=None, savefig=False, fmt='jpeg')[source]¶

Plots a figure of stats (temporal mean/min/max) map (one per data_var).

For each data_var, create a figure composed of 3 subplots : a mean-, min-, and max-map. See ‘get_mean_map’, ‘get_min_map’, and ‘get_max_map’ for more information about what the so-called maps are.

Parameters

data_vars – The name of the dataarray to plot. If ‘all’, create a figure for each dataarray (i.e. for each data_var in data_vars).
filename – Optional; The path of the output figure.
savefig – Optional; A boolean flag that indicates if the figure should be saved or not.
fmt – The format of the static image that is saved on disk. Can be either “png”, “jpeg”, “webp”, “svg” or “pdf”.

save(filename)[source]¶: See base class.

property start_date¶: Return the start date.

timelapse(data_vars, filename, out_res=None, write_time=True)[source]¶

Creates a timelapse and save it on disk (as a GIF file).

Parameters

data_vars – The data_var(s) to plot; 1 for a grayscale image, and a list of 3 for a RGB one.
filename – The path of the output gif.
out_res – The resolution of the timelapse; must be coarser than the one of the time series.
write_time – If True, the corresponding date will be written on each frame.

property title¶: Returns the title of the underlying dataset.

sisppeo.products.timeseries.cond_resample(arr, in_res, out_res)[source]¶: See resample_band_array(…).

sisppeo.products.timeseries.mask_time_series(ts_algo, ts_masks, lst_mask_type, inplace=False)[source]¶

Masks time series of L3AlgoProducts.

Masks a TimeSeries made of L3AlgoProducts with one (or multiple ones) made of L3MaskProducts. It can be used for instance to get rid of clouds or to extract only water areas.

Parameters

ts_algo – The TimeSeries to be masked.
ts_masks – The TimeSeries or list of TimeSeries to use as mask (/list of masks).
lst_mask_type – The type of the input mask (or the list of the types of input masks). Can either be ‘IN’ or ‘OUT’, indicating if the corresponding mask is inclusive or exclusive.
inplace – If True, do operation inplace and return None.

Returns

A masked TimeSeries.

sisppeo.products package¶

Submodules¶

sisppeo.products.l3 module¶

sisppeo.products.timeseries module¶

Module contents¶