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Verbs#

In this notebook we will describe the different verbs that semantique offers. Remember that result instructions in query recipes can be formulated by combining basic building blocks into processing chains. These processing chains start with a reference. For a description of those, see the References notebook. At the query recipe construction stage, the reference is nothing more than a small piece of text. When executing the recipe, the query processor solves this reference and evaluates it internally into a multi-dimensional array filled with data values. Several actions can then be applied to this array. These actions are all labeled with an action word that should intuitively describe the operation they are performing. That is why we call them verbs. The same building blocks can also be used when constructing a set of mapping rules according to semantiques native mapping configuration.

Prepare#

Import packages:

[1]:

import semantique as sq

[2]:

import geopandas as gpd
import pandas as pd
import numpy as np
import xarray as xr
import json
import copy

Set the context of query execution:

[3]:

# Load a mapping.
with open("files/mapping.json", "r") as file:
    mapping = sq.mapping.Semantique(json.load(file))

# Represent an EO data cube.
with open("files/layout_gtiff.json", "r") as file:
    dc = sq.datacube.GeotiffArchive(json.load(file), src = "files/layers_gtiff.zip")

# Set the spatio-temporal extent.
space = sq.SpatialExtent(gpd.read_file("files/footprint.geojson"))
time = sq.TemporalExtent("2019-01-01", "2020-12-31")

# Collect the full context.
# Including additional configuration parameters.
context = {
    "datacube": dc,
    "mapping": mapping,
    "space": space,
    "time": time,
    "crs": 3035,
    "tz": "UTC",
    "spatial_resolution": [-1800, 1800]
}