class ImageMeter:
def __init__(self, *meters: TrackMeter, title: str = ""):
from freeplot.base import FreePlot
self.meters = list(meters)
self.title = title
self.fp = FreePlot(shape=(1, 1),
figsize=(2.2, 2),
titles=(title, ),
dpi=300)
# self.fp.set_label("Val", axis='y')
# self.fp.set_label("T", axis='x')
self.fp.set_title(y=1.)
def add(self, *meters: TrackMeter) -> None:
self.meters += list(meters)
def plot(self) -> None:
for meter in self.meters:
x = meter.timeline
y = meter.history
self.fp.lineplot(x, y, label=meter.name)
self.fp[0].legend()
self.fp.savefig
plt.tight_layout()
def save(self, writter: 'SummaryWriter', postfix: str = '') -> None:
filename = f"{self.title}{postfix}"
writter.add_figure(filename, self.fp.fig)
def imagemeter(*imgs):
rows = len(imgs)
cols = imgs[0].shape[0]
fp = FreePlot((rows, cols), (cols, rows), dpi=100)
for row in range(rows):
for col in range(cols):
fp.imageplot(imgs[row][col], index=row * cols + col)
return fp.fig
def __init__(self, *meters: TrackMeter, title: str = ""):
from freeplot.base import FreePlot
self.meters = list(meters)
self.title = title
self.fp = FreePlot(shape=(1, 1),
figsize=(2.2, 2),
titles=(title, ),
dpi=300)
# self.fp.set_label("Val", axis='y')
# self.fp.set_label("T", axis='x')
self.fp.set_title(y=1.)
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()
# inset zoom demo
from freeplot.base import FreePlot
fp = FreePlot((1, 1), (5, 4))
fp.lineplot([1, 2, 3], [4, 5, 6], label='a')
fp.lineplot([1, 2, 3], [3, 5, 7], label='b')
axins, patch, lines = fp.inset_axes(xlims=(1.9, 2.1),
ylims=(4.9, 5.1),
bounds=(0.1, 0.7, 0.2, 0.2),
index=(0, 0),
style='line')
fp.lineplot([1, 2, 3], [4, 5, 6], index=axins)
fp.lineplot([1, 2, 3], [3, 5, 7], index=axins)
# for line in lines:
# line.set({'linewidth':5, 'alpha': 0.7})
fp.show()
"""
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
from freeplot.zoo import pre_radar, pos_radar
labels = ("brightness", "defocus_blur", "fog", "gaussian_blur", "glass_blur",
"jpeg_compression", "motion_blur", "saturate, snow", "speckle_noise",
"contrast", "elastic_transform", "frost", "gaussian_noise",
"impulse_noise", "pixelate", "shot_noise", "spatter", "zoom_blur",
"transform", "flowSong")
theta = pre_radar(len(labels), frame="polygon")
# shape: 1, 1; figsize: 4, 4;
fp = FreePlot((1, 1), (4, 4), dpi=100, titles=["RADAR"], projection="radar")
data = {
"A": np.random.rand(len(labels)),
'B': np.random.rand(len(labels)),
'C': np.random.rand(len(labels))
}
pos_radar(data, labels, fp)
fp[0, 0].legend()
# fp.savefig("radar_demo.pdf", format="pdf", tight_layout=True)
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()
from mpl_toolkits import axisartist
import json
import os
import sys
import seaborn as sns
from freeplot.base import FreePlot
A = [1., 2., 3.]
B = [2., 3., 4.]
T = ['One', 'Two', 'Three'] * 2
Hue = ['A'] * len(A) + ['B'] * len(B)
data = pd.DataFrame(
{
"T": T,
"val": A + B,
"category": Hue
}
)
# shape: 1, 1; figsize: 2.2, 2
fp = FreePlot((1, 1), (2.2, 2), titles=("Bar Demo",), dpi=200)
fp.barplot(x='T', y='val', hue='category', data=data, index=(0, 0), auto_fmt=True)
fp.set(xlabel='X')
fp.set_label('Y', index=(0, 0), axis='y')
fp[0, 0].legend(ncol=2)
# fp.savefig("heatmap_demo.pdf", format="pdf", tight_layout=False)
plt.show()