"""
heatmap demo
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from freeplot.base import FreePlot
titles = ("S", "h", "a", "n")
row_labels = ('c', 'u', 't', 'e')
col_labels = ('l', 'r', 'i', 'g')
# shape: 1, 4; figsize: 9, 2
fp = FreePlot((1, 4), (9, 2), titles=titles, dpi=100, sharey=True)
for title in titles:
data = np.random.rand(4, 4)
df = pd.DataFrame(data, index=col_labels, columns=row_labels)
fp.heatmap(df,
index=title,
annot=True,
fmt=".4f",
cbar=False,
linewidth=0.5)
fp.set(Xlabel="X")
fp.set_label('Y', index=(0, 0), axis='y')
fp.savefig("heatmap_demo.pdf", format="pdf", tight_layout=False)
# plt.show()
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from freeplot.base import FreePlot
titles = ("S", "h", "a", "n")
labels = ("sin", "cos", "x")
fp = FreePlot((1, 4), (9.5, 2), titles=titles, dpi=100, sharey=True)
nums = 20
x = np.linspace(-10, 10, nums)
y1 = np.sin(x)
y2 = np.cos(x)
y3 = x
ys = (y1, y2, y3)
for title in titles:
for i, y in enumerate(ys):
y = y + np.random.randn(nums)
fp.lineplot(x, y, index=title, label=labels[i])
fp.set_title(y=1.)
fp.set_label("y", axis='y')
fp.set(Xlabel="x")
fp[0, 0].legend()
# fp.savefig("line_demo.pdf", format="pdf", tight_layout=False)
plt.show()
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from freeplot.base import FreePlot
from scipy.stats import multivariate_normal
normal = multivariate_normal
titles = ("S", "h", "a", "n")
labels = ("sin", "cos", "x")
# shape: 1, 4; figsize: 9.5, 2
fp = FreePlot((1, 4), (9.5, 2), titles=titles, dpi=100, sharey=True)
nums = 100
means = ((0, 0), (5, 5), (-5, -5))
cov = (2, 1, 1)
for title in titles:
for i, mean in enumerate(means):
data = normal.rvs(mean, cov[i], size=nums)
fp.scatterplot(data[:, 0], data[:, 1], index=title, label=labels[i])
fp.set_title(y=1.)
fp.set_label("Y", index=(0, 0), axis='y')
fp.set_label("X", index=None, axis='x')
fp[0, 0].legend()
# fp.savefig("scatter_demo.pdf", format="pdf", tight_layout=False)
plt.show()