Plotting negative values using matplotlib scatter

Question

I want to plot scatter points corresponding to 6 different datasets over global maps of the Earth. The problem is that some of these quantities have negative values and they don't appear in the maps. I have tried to overcome this problem by taking absolute values of the data and multiplying (or taking the power of) them by some factors, but nothing seems to work the way I want. The problem is that the datasets have very different ranges. Ideally, I want them all to have the same scale so everything will be more organized, but I don't know how to do this.

I created some synthetic data to illustrate this issue

import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from mpl_toolkits.basemap import Basemap, addcyclic, shiftgrid
from matplotlib.pyplot import cm

np.random.seed(100)

VarReTx = np.random.uniform(low=-0.087, high=0.0798, size=(52,))
VarReTy = np.random.uniform(low=-0.076, high=0.1919, size=(52,))
VarImTx = np.random.uniform(low=-0.0331, high=0.0527, size=(52,))
VarImTy = np.random.uniform(low=-0.0311, high=0.2007, size=(52,))
eTx = np.random.uniform(low=0.0019, high=0.0612, size=(52,))
eTx = np.random.uniform(low=0.0031, high=0.0258, size=(52,))
obslat = np.array([18.62,   -65.25,   -13.8,     -7.95,   -23.77,    51.84,    40.14,    58.07,
 -12.1875, -35.32,    36.37,   -46.43,    40.957,  -43.474,   38.2 ,    37.09,
  48.17,     0.6946,  13.59,    28.32,    51.,     -25.88,   -34.43,    21.32,
 -12.05,    52.27,    36.23,   -12.69,    31.42,     5.21,   -22.22,    36.1,
  14.38,   -54.5,     43.91,    61.16,    48.27,    52.07,    54.85,    45.403,
  52.971,  -17.57,   -51.7,     18.11,    39.55,    47.595,   22.79,   -37.067,
  -1.2,     32.18,    51.933,   48.52])
obslong = np.array([-287.13,    -64.25,   -171.78,    -14.38,   -226.12,   -339.21,   -105.24,
 -321.77,   -263.1664, -210.64,   -233.146,  -308.13,   -359.667,  -187.607,
  -77.37,   -119.72,   -348.72,   -287.8463, -215.13,    -16.43,     -4.48,
 -332.29,   -340.77,   -158.,      -75.33,   -255.55,   -219.82,   -227.53,
 -229.12,    -52.73,   -245.9,    -256.16,    -16.97,   -201.05,   -215.81,
  -45.442,  -117.12,   -347.32,   -276.77,    -75.552,  -201.752,  -149.58,
  -57.89,    -66.15,     -4.35,    -52.677,  -354.47,    -12.315,   -48.5,
 -110.73,    -10.25,   -123.42,  ])

fig, ([ax1, ax2], [ax3, ax4], [eax1, eax2]) = plt.subplots(3,2, figsize=(24,23))
matplotlib.rc('xtick', labelsize=12) 
matplotlib.rc('ytick', labelsize=12)

plots = [ax1, ax2, ax3, ax4, eax1, eax2]
Vars = [VarReTx, VarReTy, VarImTx, VarImTy, eTx, eTy]
titles = [r'$\Delta$ ReTx', r'$\Delta$ ReTy', r'$\Delta$ ImTx', r'$\Delta$ ImTy', 'Error (X)', 'Error (Y)']
colors = iter(cm.jet(np.reshape(np.linspace(0.0, 1.0, len(plots)), ((len(plots), 1)))))

for j in range(len(plots)):
    c3 = next(colors)
    lat = np.arange(-91, 91, 0.5)
    long = np.arange(-0.1, 360.1, 0.5)
    longrid, latgrid = np.meshgrid(long, lat)   
    plots[j].set_title(titles[j], fontsize=48, y=1.05)
    condmap = Basemap(projection='robin', llcrnrlat=-90, urcrnrlat=90,\
                                    llcrnrlon=-180, urcrnrlon=180, resolution='c', lon_0=0, ax=plots[j])
    maplong, maplat = condmap(longrid, latgrid)
    condmap.drawcoastlines()
    condmap.drawmapboundary(fill_color='white') 
    parallels = np.arange(-90, 90, 15)
    condmap.drawparallels(parallels,labels=[False,True,True,False], fontsize=15)
    x,y = condmap(obslong, obslat)
    w = []

    for m in range(obslong.size):
        w.append(Vars[j][m])
    w = np.array(w)

    condmap.scatter(x, y, s = w*1e+4, c=c3)
    r = np.linspace(np.min(Vars[j]), np.max(Vars[j]), 4)

    for n in r:
        condmap.scatter([], [], c=c3, s=n*1e+4, label=str(np.round(n, 4)))
    plots[j].legend(bbox_to_anchor=(0., -0.2, 1., .102), loc='lower left',
                   ncol=4, mode="expand", borderaxespad=0., fontsize=16, frameon = False)

plt.show()
plt.close('all')

As you can see in the map, negative data does not are not being exhibited. I want they all to appear in the maps and that all the scatter plots have the same scale in their respective ranges. Thanks!

When I look at that map, I see plenty of data. How can I find out which of the dots is missing? — ImportanceOfBeingErnest
– ImportanceOfBeingErnest, Commented Aug 10, 2019 at 21:24

Diziet Asahi · Accepted Answer · 2019-08-11 12:14:55Z

2

It looks like you are trying to map your dataset to dot size. Obviously you cannot have negative size dots, so that won't work.

Instead, you need to normalize your dataset to a strictly positive range and use those normalized values for the size parameter. A simple way to do this would be to use matplotlib.colors.Normalize(vmin, vmax), which allows you to map any values in the interval [vmin, vmax] to the interval [0,1].

If you want to have a shared scale for all your datasets, first find the global min and max, and use that to instantiate your normalization, then normalize each dataset when plotting:

datasets = [VarReTx,VarReTy,VarImTx,VarImTy,eTx,eTx]

min_val = min([d.min() for d in datasets])
max_val = max([d.max() for d in datasets])

norm = matplotlib.colors.Normalize(vmin=min_val, vmax=max_val)
plt.scatter(x,y,s=norm(VarReTx)*100) # choose appropiate scaling factor instead of 100 to get nicely sized dots

edited Aug 11, 2019 at 12:14

answered Aug 11, 2019 at 11:48

Diziet Asahi

41k8 gold badges67 silver badges85 bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

Diziet Asahi Over a year ago

You're welcome. If you think that your question has been answered, considering accepting the answer using the check mark on the left to close the topic

Collectives™ on Stack Overflow

Plotting negative values using matplotlib scatter

1 Answer 1

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related