Analysis

Module for repeatedly calculating ACM and PACM and corresponding eigenvalues

TEP = GetTEP(); TEP.head()

Name	A Feed	D Feed	E Feed	A and C feed	Recycle flow	Reactor feed rate	Reactor pressure	Reactor level	Reactor temperature	Purge rate	...	A feed flow	A and C feed flow	Compressor recycle valve	Purge valve	Separator pot liquid flow	Stripper liquid product flow	Stripper steam valve	Reactor cooling water flow	Condenser cooling water flow	Agitator speed
0	0.24889	3702.3	4502.7	9.4170	26.996	42.183	2705.2	75.173	120.40	0.33611	...	54.059	24.804	63.269	21.950	40.188	39.461	47.000	47.594	41.384	18.905
1	0.24904	3666.2	4526.0	9.2682	26.710	42.332	2705.5	74.411	120.41	0.33676	...	53.781	24.790	62.171	22.239	40.108	43.710	46.128	47.508	41.658	18.976
2	0.25034	3673.3	4501.3	9.4212	26.842	42.360	2705.3	75.125	120.41	0.33739	...	54.075	24.669	61.585	22.191	40.030	39.480	44.121	47.612	41.721	16.562
3	0.25109	3657.8	4497.8	9.3792	26.528	41.982	2707.3	73.992	120.38	0.33664	...	54.117	24.595	61.561	21.959	40.121	32.848	45.858	47.459	40.836	20.094
4	0.24563	3698.0	4537.4	9.3746	26.736	42.354	2705.3	75.283	120.42	0.32521	...	53.906	24.451	61.388	22.271	39.538	36.682	45.753	47.458	41.727	18.330

5 rows × 52 columns

source

ACM_analysis

 ACM_analysis (X:pandas.core.frame.DataFrame, lag:int)

	Type	Details
X	DataFrame	Raw data to perform analysis on
lag	int	Number of lags to investigate
Returns	dict	Dict with eigenvalues

source

PACM_analysis

 PACM_analysis (X:pandas.core.frame.DataFrame, lag:int)

	Type	Details
X	DataFrame	Raw data to perform analysis on
lag	int	Number of lags to investigate
Returns	dict	Dict with eigenvalues

source

Analysis

 Analysis (X, lag)

Initialize self. See help(type(self)) for accurate signature.

test = Analysis(TEP,15)

test.show_plots()

To check the eigenvalues for a given pair we can simply access the matrix and display the first eigenvector which has been sorted to correspond to the largest eigenvalue:

test.PACM['EigenVectors',15][0]

array([-3.53665965e-02,  9.91247845e-02,  1.48473068e-01,  1.48473068e-01,
       -7.78141954e-02, -7.78141954e-02, -1.18819213e-01, -1.18819213e-01,
        1.46763021e-01,  1.46763021e-01, -2.72832315e-02, -2.72832315e-02,
        1.71289600e-02,  1.71289600e-02,  1.24926467e-01,  1.24926467e-01,
       -1.61051399e-01, -1.61051399e-01, -2.85690998e-01, -2.85690998e-01,
       -4.29317663e-01,  9.09143716e-02,  1.75729524e-01,  1.75729524e-01,
        3.34182238e-01,  3.34182238e-01, -1.36434720e-01, -1.36434720e-01,
        4.48605229e-01,  4.48605229e-01,  2.58924861e-02,  2.58924861e-02,
        9.55567158e-03,  4.99279556e-02,  4.99279556e-02, -4.30792202e-01,
        4.43065546e-01,  4.43065546e-01,  5.03627719e-01,  5.03627719e-01,
        1.60398868e-01,  1.60398868e-01,  3.08507125e-01,  3.08507125e-01,
        8.13763194e-02,  8.13763194e-02,  4.71123697e-02,  4.71123697e-02,
        4.08169775e-02, -4.87651437e-02,  3.38536505e-04, -2.44402708e-03])