I am planning to plot a Taylor diagram in Python, using the easy_mpl library. I used the following code and was able to generate a Taylor diagram:
import numpy as np
from easy_mpl import taylor_plot
import pandas as pd
import matplotlib.pyplot as plt
from easy_mpl.utils import version_info
version_info()
df = pd.read_csv("G:\Python\Taylor_plot.csv")
data = df.to_numpy()
observations = data[:, 0]
simulations = {"Model-1": data[:, 1],
"Model-3": data[:, 2],
"Model-3": data[:, 3],
"Model-4": data[:, 4],
"Model-5": data[:,5],
"Model-6": data[:,6],
"Model-7": data[:,7],
"Model-8": data[:,8],}
_ = taylor_plot(observations=observations,
simulations=simulations,
plot_bias=True,
cont_kws={'colors': '#1A74A5', 'linewidths': 1.5},
grid_kws={'axis': 'x', 'color': '#5CB994', 'lw': 2.0, 'ls': 'dotted'},
marker_kws={'markersize': 10, 'markeredgewidth': 1.0,
'markeredgecolor': 'black', 'lw': 0.0},
title="Taylor Plot")
I noticed that Models 7 and 8 are missing from the plot. I hypothesized that their values might be negative or outside the first quadrant.
Therefore, I would like to know how to add other quadrants to the Taylor diagram to show negative correlation values.
This is a sample from the data I used:
[[2.614 0.282 0.901 0.254 0.42 0.785 0.4871 0.6842 1.0216]
[3.141 0.265 0.717 0.245 0.46 0.6122 0.5516 0.6457 0.5939]
[0.563 0.282 0.661 0.252 1.81 0.636 0.4983 0.6041 0.5376]
[2.343 0.292 0.563 0.289 0.6 0.4559 0.515 0.4323 0.65 ]
[0.893 0.276 0.538 0.248 0.37 0.3996 0.4455 0.3962 0.5438]
[0.426 0.253 0.637 0.248 0.42 0.5251 0.4136 0.4809 0.5804]
[8.563 0.39 1.192 0.308 0.61 1.0787 1.1276 0.8346 0.5782]
[2.213 0.499 1.587 0.279 0.88 1.2618 1.6147 1.1937 1.0943]
[3.065 1.728 1.728 4.059 1.1 1.4816 1.5246 1.275 3.4991]
[9.223 2.045 2.045 8.701 0.86 2.1728 4.8029 2.3691 0.9047]]
This is an example of the figure I would like to plot: same figure but in R
