Skip to main content

dnplot 💻

dnplot is a tool designed for the visualization of dnora objects, such as 🌬️ wind, 🌊 wave and ocean current data.

dnplot Visualization

Quick Installation 🚀

Ready to dive in? You can easily install dnplot using pip:

$ pip install dnplot 

Examples

To quickly visualize the wave data outputted by SWAN to a netcdf file:

import dnplot
from dnora.wavegrid import WaveGrid

data = WaveGrid.from_netcdf('model_output.nc')
point = data.sel(lon=5.25, lat=62.3, method='nearest') # Pick just one point

# The dict could be a dnora ModelRun object containing the data
plot = dnplot.Matplotlib({'wavegrid': data, 'waveseries': point})

# default value for var=["hs", ("tm01", "tm02"), "dirm"] 
plot.waveseries(var=['hs', ('tp','tm01'), 'dirp']) 
plot.wavegrid('hs', contour=False)
Screenshot from 2025-10-14 14-09-08 Screenshot from 2025-10-14 12-49-05

To interactively compare spectra from a model with several locations with buoy measurements:

import dnora as dn
import dnplot

model = dn.modelrun.ModelRun(year=2020)
model.import_spectra(filename="nora3.nc", name="NORA3")
model.spectra_to_1d()

buoy = dn.modelrun.ModelRun(year=2020, month=2, day=5)
buoy.import_spectra1d(filename="spec_E39_D_1h.nc", name="Breisundet")

plot = dnplot.Plotly(buoy, model)
plot.spectra()
Screenshot from 2025-10-14 12-34-48

Docs 📚

Looking for more details? Our documentation (currently under development) provides information about the package, its features, and how to use it. Explore it here.

Metadata

Release files for dnplot 0.4.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for dnplot 0.4.3
File Size Uploaded Provenance
dnplot-0.4.3.tar.gz 21.8 MB Without provenance Details

Release files / dnplot-0.4.3.tar.gz

Download URL dnplot-0.4.3.tar.gz
Size 21.8 MB
Tags Source
SHA-256 checksum
How to use checksums
634bf9f55ff065363a71a38bf978be2605a940254fc0680feab2c00b2d1af7fc
BLAKE2b-256 checksum
How to use checksums
c1deb66acf5cfac975e997873fdf90f045dc875f232c0eb7aad7641f5379bfce
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.3

Security for dnplot 0.4.3

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page