volant-via-sdk 1.5191.1

SDK and utilities for the Via API

Volant Via SDK

SDK and utilities for the Via API

Installation

Run pip install volant-via-sdk

Basic Usage

import volant_via_sdk

credentials = volant_via_sdk.Credentials(username="username", password="password")
client = volant_via_sdk.Client(credentials=credentials)

chart_georeference = client.cost_datasets.get_chart_georeference("bath")

Further Information

Auth

An authentication token is automatically retrieved when any request is made with the credentials provided when instantiating the client, no manual authentication is required.

Autogenerated Types

Autogenerated types are accessible through the top-level namespace as a convenience, they may not be the most ergonomic to use but provide a typed interface to access the underlying API.

from volant_via_sdk import types

Cost Datasets Examples

From GeoTiff

Creating a Cost Dataset using a DEM. This example will produce a cost field that favours flight in area of low terrain elevation.

import os

import rasterio

from volant_via_sdk import Client, Credentials
from volant_via_sdk.services.cost_datasets import Georeference

# Open a GeoTiff (Stored locally as "example.tif")
# An example tif could be obtained from services such as OpenTopography:
# https://portal.opentopography.org/API/globaldem?demtype=NASADEM&south=51.33&north=51.42&west=-2.45&east=-2.28&outputFormat=GTiff&API_Key=demoapikeyot2022
with rasterio.open("./example.tif") as src:
    example_raster_data = src.read(1)
    src_georeference = Georeference(crs=src.crs, shape=[src.height, src.width], affine_transform=src.transform)

# Setup the client using credentials
client = Client(credentials=Credentials(username=os.environ["USERNAME"], password=os.environ["PASSWORD"]))

# Get the georeference for the desired chart
chart_georeference = client.cost_datasets.get_chart_georeference("bath")

# Reproject the downloaded raster data to fit the chart bounds and projection
reprojected_example_raster = client.cost_datasets.reproject_to_chart(
    src_raster=example_raster_data, src_georeference=src_georeference, chart_georeference=chart_georeference
)

# Cost Datasets cannot contain any negative values!
reprojected_example_raster[reprojected_example_raster < 0] = 0

# Upload the raster as a Cost Dataset
persisted_cost_dataset = client.cost_datasets.create_cost_dataset_from_raster_data(
    raster=reprojected_example_raster, georeference=chart_georeference, name="Example Cost Dataset", chart_id="bath"
)

From Arbitrary Data

Creating a cost dataset from an arbitrary grid of data.

import os

import numpy as np

from volant_via_sdk import Client, Credentials

# Setup the client using credentials
client = Client(credentials=Credentials(username=os.environ["USERNAME"], password=os.environ["PASSWORD"]))

# Get the georeference for the desired chart
chart_georeference = client.cost_datasets.get_chart_georeference("bath")

# Build a grid of data from the chart's shape (no reprojection required as it will already match)
raster_grid = np.zeros(chart_georeference.shape, dtype=np.float32)
# Create a stripe across the north side and left side. Note that Cost Datasets expect a North-Down representation such
# that (0, 0) is the NW corner.
raster_grid[20:30, :] = 1
raster_grid[:, 20:30] = 2

client.cost_datasets.create_cost_dataset_from_raster_data(
    raster=raster_grid, georeference=chart_georeference, name="Example Cost Dataset", chart_id="bath"
)