python.workflows._linReg Namespace Reference

Script for computing and plotting linear regressions. More...

Classes
class	biomassPlot
class	linearRegression

Functions
def	main (b, forcezero, *a)

Variables
	b
	a1
	a2
	a3
	a4
bool	forcezero = True

Detailed Description

Script for computing and plotting linear regressions.

See also

Script documentation

Variable Documentation

a1

a1

Initial value:

=  np.array([
        33.9852597125,
        12.6768900871,
        48.9714299486,
        94.4210810821,
        7.0802089703,
        50.5995948798,
        239.004924478,
        9.19608072677,
        182.822591547,
        177.307158459,
        500.737789016,
        1210.86185367,
        657.905132314,
        1011.80502227,
        237.277515801
    ])

a2

a2

Initial value:

=  np.array([
        265.952524396,
        272.672478715,
        20.2346754675,
        37.6388870506,
        82.815263199,
        4.3771723595,
        495.312805361,
        1.85764508452,
        23.2555117612,
        92.4958431765,
        638.634921389,
        41.9119593508,
        816.328050994,
        479.296872273,
        88.9742277261
    ])

a3

a3

Initial value:

=  np.array([
        348.94070629,
        290.434434553,
        840.084835795,
        200.649459402,
        827.441640848,
        208.046894404,
        218.175095975,
        452.510967194,
        285.306985889,
        840.592284886,
        278.188880645,
        0.0,
        50.0640387695,
        6.76864164487,
        524.953965557
    ])

a4

a4

Initial value:

=  np.array([
        0.0,
        0.0,
        295.751401885,
        713.651303726,
        119.422507744,
        246.078165213,
        0.0,
        655.807661822,
        548.002338263,
        12.402032032,
        0.0,
        0.0,
        0.0,
        0.0,
        178.79020764
    ])

b

b

Initial value:

=  np.array([
        0.033,
        0.025,
        0.0746,
        0.1073,
        0.0658,
        0.0542,
        0.035,
        0.0508,
        0.0845,
        0.0591,
        0.0281,
        0.0027,
        0.0293,
        0.0158,
        0.0472])