Polar plots

We leverage the polar axes functionality in Matplotlib to construct polar plots.

A simple polar plot

%matplotlib inline
import numpy as np
import scipp as sc
import plopp as pp
import matplotlib.pyplot as plt
plt.ioff()

<contextlib.ExitStack at 0x7f2e500f7010>

# Make some spiral data
N = 150
r = sc.linspace('theta', 0, 10, N, unit='m')
theta = sc.linspace('theta', 0, 12, N, unit='rad')
da = sc.DataArray(data=r, coords={'theta': theta})

# Construct figure axes with Matplotlib
fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})

# Make the plot and tweak the axes
polar1d = pp.plot(da, ax=ax, grid=True)
polar1d

Plotting a sector

Plotting data whose angular coordinate does not wrap around \(2\pi\) is also possible.

# Make data
N = 50
r = np.random.normal(loc=50, scale=5, size=N)
theta = np.radians(np.linspace(180, 200, N))
da = sc.DataArray(
    data=sc.array(dims=['theta'], values=r, unit='m'),
    coords={'theta': sc.array(dims=['theta'], values=theta, unit='rad')},
)

# Make axes and plot
fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
ax.set_rorigin(0)
pp.plot(da, ax=ax, grid=True)

Polar image plots

It is also possible to plot 2d data on polar axes:

da = pp.data.data2d(binedges=True, unit='K')
da.coords['x'] = sc.linspace('x', 0, 2 * np.pi, da.sizes['x'] + 1, unit='rad')

fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
pp.plot(da, ax=ax)

Interactive polar plot

It is also possible to use Plopp’s interactive visualizations with supplied axes:

%matplotlib widget
plt.ioff()  # Prevent the figure from showing up twice

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# Make data
N = 50
r = np.random.normal(loc=50, scale=5, size=(N, N))
theta = np.radians(np.linspace(180, 200, N))
phi = np.radians(np.linspace(0, 90, N))
da = sc.DataArray(
    data=sc.array(dims=['phi', 'theta'], values=r, unit='m'),
    coords={
        'theta': sc.array(dims=['theta'], values=theta, unit='rad'),
        'phi': sc.array(dims=['phi'], values=phi, unit='rad'),
    },
)

# Make axes
fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
ax.set_rorigin(0)

# Use slicer plot
pp.slicer(da, ax=ax, grid=True, autoscale=False)