CODEWITHSUNDEEP
pythonpython-3.xnumpymatplotlib
rrigaud
rrigaud

Reputation: 31

Plotting negative values using matplotlib scatter

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')

enter image description here

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!

Upvotes: 0

Views: 1648

Answers (1)

Diziet Asahi
Diziet Asahi

Reputation: 40747

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

Upvotes: 2

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