Colormap with colored quiver

Question

I am plotting a map with arrows on top of it. These arrows represent winddirections, average windspeed (per direction) and the occurence (per direction).

The direction is indicated by the direction of the arrow. The length of the arrow indicated the average windspeed in that direction. The color of the arrow indicates the occurence of winds in such a direction.

This all works fine with the script below:

windData = pd.read_csv(src+'.txt'), sep='\t', names=['lat', 'lon', 'wind_dir_start', 'wind_dir_end', 'total_num_data_points','num_data_points', 'avg_windspeed']).dropna()

# plot map
m = Basemap(llcrnrlon=minLon, llcrnrlat=minLat, urcrnrlon=maxLon, urcrnrlat=maxLat, resolution='i')
Left, Bottom = m(minLon, minLat)
Right, Top = m(maxLon, maxLat)

# get x y
x, y = m(windData['lon'], windData['lat'])

# angles
angleStart = -windData['wind_start']+90
angleStart[angleStart<0] = np.radians(angleStart[angleStart<0]+360.)

angleEnd = -windData['wind_end']+90
angleEnd[angleEnd<0] = np.radians(angleEnd[angleEnd<0]+360.)

angle = angleStart + math.radians(binSize/2.)

xux = np.cos(angle) * windData['avg_windspeed']
yuy = np.sin(angle) * windData['avg_windspeed']

# occurence
occurence = (windData['num_data_points']/windData['total_num_data_points'])

xi = np.linspace(minLon, maxLon, 300)
yi = np.linspace(minLat, maxLat, 300)

# plotting
## xux and yuy are used negatively because they are measured as "coming from" and displayed as "going to"
# To make things more readable I left a threshold for the occurence out
# I usually plot x, y, xux, yuy and the colors as var[occurence>threshold]
Q = m.quiver(x, y, -xux, -yuy, scale=75, zorder=6, color=cm.jet, width=0.0003*Width, cmap=cm.jet)
qk = plt.quiverkey(Q, 0.5, 0.92, 3, r'$3 \frac{m}{s}$', labelpos='S', fontproperties={'weight': 'bold'})
m.scatter(x, y, c='k', s=20*np.ones(len(x)), zorder=10, vmin=4.5, vmax=39.)

This plot shows the arrows well, but now I want to add a colormap that indicates the percentage of occurence next to the plot. How would I do this?

Answer 1

OK

Usual imports, plus import matplotlib

%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np

Fake the data to be plotted (tx for the MCVE)

NP = 10
np.random.seed(1)
x = np.random.random(NP)
y = np.random.random(NP)
angle = 1.07+np.random.random(NP) # NE to NW
velocity = 1.50+np.random.random(NP)
o = np.random.random(NP)
occurrence = o/np.sum(o)
dx = np.cos(angle)*velocity
dy = np.sin(angle)*velocity

Create a mappable so that Matplotib has no reason to complain "RuntimeError: No mappable was found to use for colorbar creation."

norm = matplotlib.colors.Normalize()
norm.autoscale(occurrence)
cm = matplotlib.cm.copper

sm = matplotlib.cm.ScalarMappable(cmap=cm, norm=norm)
sm.set_array([])

and plot the data

plt.quiver(x, y, dx, dy, color=cm(norm(o)))
plt.colorbar(sm)
plt.show()

References:

1. A logarithmic colorbar in matplotlib scatter plot ,

2. Drawing a colorbar aside a line plot, using Matplotlib and

3. Different colours for arrows in quiver plot.

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P.S. In recent (for sure in 3.+) Matplotlib releases the cm.set_array incantation is no more necessary

Answer 2

Do you want the colorbar to show the different wind speeds? If so, it might be sufficient to place plt.colorbar() between the lines Q = m.quiver(...) and qk = ....