alu/tra-analysis
1
0
Fork 0
mirror of https://github.com/titanscouting/tra-analysis.git synced 2024-11-13 22:56:18 +00:00
Code Issues Packages Projects Releases Wiki Activity

analysis.py - v 1.0.8.003

Browse Source 
changelog:
- added p_value function
This commit is contained in:
ltcptgeneral 2018-12-29 16:28:41 -06:00
parent 444bfb5945
commit 1a8da3fdd5
2 changed files with 7 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

BIN
data analysis/__pycache__/analysis.cpython-37.pyc
View File

Binary file not shown.

8
data analysis/analysis.py
View File

@ -7,10 +7,12 @@
#number of easter eggs: 2 #number of easter eggs: 2
#setup: #setup:
__version__ = "1.0.8.002" __version__ = "1.0.8.003"
#changelog should be viewed using print(analysis.__changelog__) #changelog should be viewed using print(analysis.__changelog__)
__changelog__ = """changelog: __changelog__ = """changelog:
1.0.8.003:
- added p_value function
1.0.8.002: 1.0.8.002:
- updated __all__ correctly to contain changes made in v 1.0.8.000 and v 1.0.8.001 - updated __all__ correctly to contain changes made in v 1.0.8.000 and v 1.0.8.001
1.0.8.001: 1.0.8.001:
@ -142,6 +144,7 @@ import pandas
import random import random
import scipy import scipy
from scipy.optimize import curve_fit from scipy.optimize import curve_fit
from scipy import stats
from sklearn import * from sklearn import *
#import statistics <-- statistics.py functions have been integrated into analysis.py as of v 1.0.3.002 #import statistics <-- statistics.py functions have been integrated into analysis.py as of v 1.0.3.002
import time import time
@ -872,6 +875,9 @@ def select_best_regression(eqs, rmss, r2s, overfit, selector):
return b_eq, b_rms, b_r2, b_overfit return b_eq, b_rms, b_r2, b_overfit
def p_value(x, y): #takes 2 1d arrays
return stats.ttest_ind(x, y)[1]
def basic_analysis(data): #assumes that rows are the independent variable and columns are the dependant. also assumes that time flows from lowest column to highest column. def basic_analysis(data): #assumes that rows are the independent variable and columns are the dependant. also assumes that time flows from lowest column to highest column.