源碼
https://github.com/carlosqsilva/pyspc
https://github.com/carlosqsilva/ccharts-online
使用
demo地址:
https://carlosqsilva.github.io/ccharts-online/
from pyspc import *
a = spc(pistonrings) + ewma()
print(a)
添加高亮規則
a + rules()
添加更多控制圖
a + cusum() + xbar_sbar() + sbar()
包含有18個示例數據庫,支持的自定義數據結構有nested lists (嵌套列表), numpy array (numpy數組 )或 pandas DataFrame(pandas 數據幀).
import numpy
from pyspc import *
fake_data = numpy.random.randn(30, 5) + 100
a = spc(fake_data) + xbar_rbar() + rbar() + rules()
print(a)
也可使用GUID,而非編碼。(作爲獨立SPC分析工具可使用GUI,如果集成到應用程序等可使用代碼)
$ python3 pyspc_gui.py
功能特點
變量
- Mean and Amplitude
- Mean and Standard Deviation
- Individual Values and Moving Range 移動均值
- Individual values with subgroups 子組
- Exponentially Weighted Moving Average (EWMA)
- Cumulative Sum (CUSUM)
特性
- P Chart
- NP Chart
- C Chart
- U Chart
多變量
- T Square Hotelling
- T Square Hotelling with SubGroup
- Multivariate Exponentially Weighted Moving Average (MEWMA)
安裝
$ pip install pyspc