Quick-view a RHI sweep in polar or cartesian reference systems#

import numpy as np
import matplotlib.pyplot as pl
import wradlib as wrl
import warnings

    get_ipython().run_line_magic("matplotlib inline")
/home/runner/micromamba-root/envs/wradlib-tests/lib/python3.11/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
  from .autonotebook import tqdm as notebook_tqdm

Read a RHI polar data set from University Bonn XBand radar#

filename = wrl.util.get_wradlib_data_file("hdf5/2014-06-09--185000.rhi.mvol")
data1, metadata = wrl.io.read_gamic_hdf5(filename)
img = data1["SCAN0"]["ZH"]["data"]
# mask data array for better presentation
mask_ind = np.where(img <= np.nanmin(img))
img[mask_ind] = np.nan
img = np.ma.array(img, mask=np.isnan(img))

r = metadata["SCAN0"]["r"]
th = metadata["SCAN0"]["el"]
az = metadata["SCAN0"]["az"]
site = (

Inspect the data set a little

print("Shape of polar array: %r\n" % (img.shape,))
print("Some meta data of the RHI file:")
print("\tdatetime: %r" % (metadata["SCAN0"]["Time"],))
Shape of polar array: (450, 667)

Some meta data of the RHI file:
        datetime: '2014-06-09T18:50:01.000Z'

The simplest way to plot this dataset#

ax, pm = wrl.vis.plot_rhi(img)
txt = pl.title("Simple RHI - Rays/Bins")
ax, pm = wrl.vis.plot_rhi(img)
ax.set_ylim(0, 200)
txt = pl.title("Simple RHI - Rays/Bins - with ylimits")
ax, pm = wrl.vis.plot_rhi(img, r=r, th=th)
ax.set_ylim(0, 15000)
txt = pl.title("Simple RHI - Range vs. Height")
ax, pm = wrl.vis.plot_rhi(img, r=r, th=th, rf=1e3)
ax.set_ylim(0, 15)
txt = pl.title("Simple RHI - Range vs. Height (km)")

More decorations and annotations#

You can annotate these plots by using standard matplotlib methods.

ax, pm = wrl.vis.plot_rhi(img, r=r, th=th, rf=1e3)
ylabel = ax.set_xlabel("Ground Range [km]")
ylabel = ax.set_ylabel("Height [km]")
title = ax.set_title("RHI manipulations/colorbar")
# you can now also zoom - either programmatically or interactively
xlim = ax.set_xlim(25, 40)
ylim = ax.set_ylim(0, 15)
# as the function returns the axes- and 'mappable'-objects colorbar needs, adding a colorbar is easy
cb = pl.colorbar(pm, ax=ax)