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Vyperdatum [definition]
Vyperdatum requires GDAL
which can be installed from the conda's conda-forge channel. Below, we first create a conda environment, install GDAL
and Vperdatum.
conda create -n vd python=3.11
conda activate vd
conda install -c conda-forge gdal=3.8.4
conda install -c conda-forge python-pdal
pip install vyperdatum
Before running vyperdatum, you need to copy NOAA's datum files and the updated proj.db
into the PROJ data directory [download link will be added here]. This process may get automated in the future. The Proj data directory path can be found here:
import pyproj as pp
pp.datadir.get_data_dir()
Vyperdatum offers a Transformer
class to handle the transformation of point and raster data. The Transformer
class applies transformation from crs_from
to crs_to
coordinate reference systems. The transformation steps can be prescribed manually or let the Pipeline
class to infer:
from vyperdatum.transformer import Transformer
from vyperdatum.pipeline import Pipeline
crs_from = "EPSG:6346"
crs_to = "EPSG:6346+NOAA:5224"
tf = Transformer(crs_from=crs_from,
crs_to=crs_to,
steps=["EPSG:6346", "EPSG:6319", "EPSG:6318+NOAA:5224", "EPSG:6346+NOAA:5224"]
# steps=Pipeline(crs_from=crs_from, crs_to=crs_to).transformation_steps()
)
Once an instance of the Transformer
class is created, the transform()
method can be called. Vyperdatum supports all GDAL-supported drivers, variable resolution BAG, LAZ and NPZ point-cloud files.
tf.transform(input_file=<PATH_TO_INPUT_RASTER_FILE>,
output_file=<PATH_TO_OUTPUT_RASTER_FILE>
)
You may also, directly call the file-specific transform methods instead of the generic Transformer.transform()
method:
# dircet point transformation. x, y, z can be arrays, too.
x, y, z = 278881.198, 2719890.433, 0
xt, yt, zt = tf.transform_points(x, y, z, always_xy=True, allow_ballpark=False)
# GDAL-supported raster transform
tf.transform_raster(input_file=<PATH_TO_INPUT_RASTER_FILE>,
output_file=<PATH_TO_OUTPUT_RASTER_FILE>
)
# VRBAG transform
tf.transform_vrbag(input_file=<PATH_TO_INPUT_VRBAG_FILE>,
output_file=<PATH_TO_OUTPUT_VRBAG_FILE>
)
# LAZ transform
tf.transform_laz(input_file=<PATH_TO_INPUT_LAZ_FILE>,
output_file=<PATH_TO_OUTPUT_LAZ_FILE>
)
# NPZ transform
tf.transform_npz(input_file=<PATH_TO_INPUT_NPZ_FILE>,
output_file=<PATH_TO_OUTPUT_NPZ_FILE>
)
For a quick start, more detailed descriptions or search through the API, see Vyperdatums's documentation at: https://vyperdatum.readthedocs.io.
FAQs
Vyperdatum with built-in regional datums, proj.db, and vdatum vector files.
We found that vyperdatum demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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