一套用于绘制非确定性实验(例如机器学习、优化、遗传算法)结果的实用工具。
项目描述
Pen'n'paper
Pen'n'paper是一个易于收集(有噪声)过程数据并将其进行比较的软件包。此软件包的目标不是功能完整性。相反,它应该让您在项目阶段轻松开始,当时您只想专注于实验想法。
安装:pip install pennpaper
示例
# We have a mysterious function that we would like to better understand on the interval [0.1, 5.].
# Unfortunately the function is noisy.
import numpy as np
X = np.arange(0.1, 5, step=0.01)
import random
def noisy_mapping(mapping):
def _(x):
y = mapping(x)
y += random.gauss(0, 1)
return y
return _
pow2 = noisy_mapping(lambda x: x ** 2)
# lets record the pairs (x, f(x)) in a metric and make a plot:
from pennpaper import Metric, plot_group, plot
m1 = Metric("pow2")
for x in X:
m1.add_record(x, pow2(x))
plot(m1)
# try again - see in how far it repeats itself.
m2 = Metric("pow2_second_try")
for x in X:
m2.add_record(x, pow2(x))
# lets plot two metrics side-by-side
plot_group([m1, m2])
# Actually, m1 and m2 are metrics of the same process.
# What if we create a new metric tracking the mean and stddev of this process?
m3 = m1 + m2
plot(m3)
# the plot is too noisy to understand. We can smoothen it!
plot(m3, smoothen=True)
项目详情
下载文件
下载适用于您平台的应用程序。如果您不确定要选择哪个,请了解更多关于安装包的信息。
源代码分布
pennpaper-0.15.tar.gz (6.2 kB 查看哈希值)
构建分布
pennpaper-0.15-py3-none-any.whl (9.1 kB 查看哈希值)
关闭
pennpaper-0.15.tar.gz的哈希值
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MD5 | 0cbdb5955b12520acf798f69b23833ca |
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BLAKE2b-256 | f2df3e9a72d59d1d9c13a38d2138c524acf1303ae59e0c6ba0b5fa471136333f |