tests/testthat/_snaps/get_jacobians.md
In franzikoch/Feedbackloops: Feedback loop analysis for competition networks
Read in data functions
Code
read_contact_matrix(competition_path)
Output
B B.1 Ar Ar.1 M M.1 I I.1 E E.1 C C.1 Ai Ai.1 H H.1
B 1 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA
B.1 0 1 3 3 3 3 12 12 5 5 2 2 NA NA NA NA
Ar NA NA 1 0 0 0 0 0 0 0 0 0 0 0 0 0
Ar.1 NA NA 0 1 2 2 3 3 4 4 2 2 3 3 1 1
M NA NA NA NA 2 0 1 0 0 0 0 1 0 0 0 0
M.1 NA NA NA NA 0 2 3 4 2 2 3 4 3 3 3 3
I NA NA NA NA NA NA 91 0 2 12 1 3 1 5 1 2
I.1 NA NA NA NA NA NA 0 91 10 24 33 37 21 27 8 11
E NA NA NA NA NA NA NA NA 3 0 1 0 0 1 NA NA
E.1 NA NA NA NA NA NA NA NA 0 3 4 5 7 8 NA NA
C NA NA NA NA NA NA NA NA NA NA 19 0 1 4 0 1
C.1 NA NA NA NA NA NA NA NA NA NA 0 19 3 8 5 6
Ai NA NA NA NA NA NA NA NA NA NA NA NA 4 0 0 4
Ai.1 NA NA NA NA NA NA NA NA NA NA NA NA 0 4 1 5
H NA NA NA NA NA NA NA NA NA NA NA NA NA NA 2 0
H.1 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 0 2
Code
read_abundance(abundance_path, contact_matrix)
Output
species abundance
1 B 27
2 Ar 30
3 M 23
4 I 358
5 E 62
6 C 209
7 Ai 95
8 H 63
Calculation interaction strength table
Code
interaction_strengths(contact_matrix, abundance, c(-0.1, -0.9, -0.2))
Output
Species_i Species_j Interactions Wins_i Wins_j Draws F_ii a_ii F_ij
1 B B 1 0 0 1 -0.4 -0.01481481 0.0
2 B Ar 3 3 0 0 0.0 0.00000000 -0.3
3 B M 3 3 0 0 0.0 0.00000000 -0.3
4 B I 12 12 0 0 0.0 0.00000000 -1.2
5 B E 5 5 0 0 0.0 0.00000000 -0.5
6 B C 2 2 0 0 0.0 0.00000000 -0.2
7 Ar Ar 1 0 0 1 -0.4 -0.01333333 0.0
8 Ar M 2 2 0 0 0.0 0.00000000 -0.2
9 Ar I 3 3 0 0 0.0 0.00000000 -0.3
10 Ar E 4 4 0 0 0.0 0.00000000 -0.4
11 Ar C 2 2 0 0 0.0 0.00000000 -0.2
12 Ar Ai 3 3 0 0 0.0 0.00000000 -0.3
13 Ar H 1 1 0 0 0.0 0.00000000 -0.1
14 M M 2 0 0 2 -0.8 -0.03478261 0.0
15 M I 4 3 0 1 0.0 0.00000000 -0.5
16 M E 2 2 0 0 0.0 0.00000000 -0.2
17 M C 4 3 1 0 0.0 0.00000000 -1.2
18 M Ai 3 3 0 0 0.0 0.00000000 -0.3
19 M H 3 3 0 0 0.0 0.00000000 -0.3
20 I I 91 0 0 91 -36.4 -0.10167598 0.0
21 I E 24 10 12 2 0.0 0.00000000 -12.2
22 I C 37 33 3 1 0.0 0.00000000 -6.2
23 I Ai 27 21 5 1 0.0 0.00000000 -6.8
24 I H 11 8 2 1 0.0 0.00000000 -2.8
25 E E 3 0 0 3 -1.2 -0.01935484 0.0
26 E C 5 4 0 1 0.0 0.00000000 -0.6
27 E Ai 8 7 1 0 0.0 0.00000000 -1.6
28 C C 19 0 0 19 -7.6 -0.03636364 0.0
29 C Ai 8 3 4 1 0.0 0.00000000 -4.1
30 C H 6 5 1 0 0.0 0.00000000 -1.4
31 Ai Ai 4 0 0 4 -1.6 -0.01684211 0.0
32 Ai H 5 1 4 0 0.0 0.00000000 -3.7
33 H H 2 0 0 2 -0.8 -0.01269841 0.0
a_ij F_ji a_ji
1 0.0000000000 0.0 0.00000000
2 -0.0100000000 -2.7 -0.10000000
3 -0.0130434783 -2.7 -0.10000000
4 -0.0033519553 -10.8 -0.40000000
5 -0.0080645161 -4.5 -0.16666667
6 -0.0009569378 -1.8 -0.06666667
7 0.0000000000 0.0 0.00000000
8 -0.0086956522 -1.8 -0.06000000
9 -0.0008379888 -2.7 -0.09000000
10 -0.0064516129 -3.6 -0.12000000
11 -0.0009569378 -1.8 -0.06000000
12 -0.0031578947 -2.7 -0.09000000
13 -0.0015873016 -0.9 -0.03000000
14 0.0000000000 0.0 0.00000000
15 -0.0013966480 -2.9 -0.12608696
16 -0.0032258065 -1.8 -0.07826087
17 -0.0057416268 -2.8 -0.12173913
18 -0.0031578947 -2.7 -0.11739130
19 -0.0047619048 -2.7 -0.11739130
20 0.0000000000 0.0 0.00000000
21 -0.1967741935 -10.6 -0.02960894
22 -0.0296650718 -30.2 -0.08435754
23 -0.0715789474 -19.6 -0.05474860
24 -0.0444444444 -7.6 -0.02122905
25 0.0000000000 0.0 0.00000000
26 -0.0028708134 -3.8 -0.06129032
27 -0.0168421053 -6.4 -0.10322581
28 0.0000000000 0.0 0.00000000
29 -0.0431578947 -3.3 -0.01578947
30 -0.0222222222 -4.6 -0.02200957
31 0.0000000000 0.0 0.00000000
32 -0.0587301587 -1.3 -0.01368421
33 0.0000000000 0.0 0.00000000
Assemble a Jacobian matrix
Code
assemble_jacobian(interaction_table, abundance[, 1], "a_ij", "a_ji")
Output
[,1] [,2] [,3] [,4] [,5]
[1,] -0.01481481 -0.01000000 -0.013043478 -0.0033519553 -0.008064516
[2,] -0.10000000 -0.01333333 -0.008695652 -0.0008379888 -0.006451613
[3,] -0.10000000 -0.06000000 -0.034782609 -0.0013966480 -0.003225806
[4,] -0.40000000 -0.09000000 -0.126086957 -0.1016759777 -0.196774194
[5,] -0.16666667 -0.12000000 -0.078260870 -0.0296089385 -0.019354839
[6,] -0.06666667 -0.06000000 -0.121739130 -0.0843575419 -0.061290323
[7,] 0.00000000 -0.09000000 -0.117391304 -0.0547486034 -0.103225806
[8,] 0.00000000 -0.03000000 -0.117391304 -0.0212290503 0.000000000
[,6] [,7] [,8]
[1,] -0.0009569378 0.000000000 0.000000000
[2,] -0.0009569378 -0.003157895 -0.001587302
[3,] -0.0057416268 -0.003157895 -0.004761905
[4,] -0.0296650718 -0.071578947 -0.044444444
[5,] -0.0028708134 -0.016842105 0.000000000
[6,] -0.0363636364 -0.043157895 -0.022222222
[7,] -0.0157894737 -0.016842105 -0.058730159
[8,] -0.0220095694 -0.013684211 -0.012698413
franzikoch/Feedbackloops documentation built on July 1, 2023, 12:42 p.m.
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Read in data functions
Code
read_contact_matrix(competition_path)
Output
B B.1 Ar Ar.1 M M.1 I I.1 E E.1 C C.1 Ai Ai.1 H H.1
B 1 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA
B.1 0 1 3 3 3 3 12 12 5 5 2 2 NA NA NA NA
Ar NA NA 1 0 0 0 0 0 0 0 0 0 0 0 0 0
Ar.1 NA NA 0 1 2 2 3 3 4 4 2 2 3 3 1 1
M NA NA NA NA 2 0 1 0 0 0 0 1 0 0 0 0
M.1 NA NA NA NA 0 2 3 4 2 2 3 4 3 3 3 3
I NA NA NA NA NA NA 91 0 2 12 1 3 1 5 1 2
I.1 NA NA NA NA NA NA 0 91 10 24 33 37 21 27 8 11
E NA NA NA NA NA NA NA NA 3 0 1 0 0 1 NA NA
E.1 NA NA NA NA NA NA NA NA 0 3 4 5 7 8 NA NA
C NA NA NA NA NA NA NA NA NA NA 19 0 1 4 0 1
C.1 NA NA NA NA NA NA NA NA NA NA 0 19 3 8 5 6
Ai NA NA NA NA NA NA NA NA NA NA NA NA 4 0 0 4
Ai.1 NA NA NA NA NA NA NA NA NA NA NA NA 0 4 1 5
H NA NA NA NA NA NA NA NA NA NA NA NA NA NA 2 0
H.1 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 0 2
Code
read_abundance(abundance_path, contact_matrix)
Output
species abundance
1 B 27
2 Ar 30
3 M 23
4 I 358
5 E 62
6 C 209
7 Ai 95
8 H 63
Calculation interaction strength table
Code
interaction_strengths(contact_matrix, abundance, c(-0.1, -0.9, -0.2))
Output
Species_i Species_j Interactions Wins_i Wins_j Draws F_ii a_ii F_ij
1 B B 1 0 0 1 -0.4 -0.01481481 0.0
2 B Ar 3 3 0 0 0.0 0.00000000 -0.3
3 B M 3 3 0 0 0.0 0.00000000 -0.3
4 B I 12 12 0 0 0.0 0.00000000 -1.2
5 B E 5 5 0 0 0.0 0.00000000 -0.5
6 B C 2 2 0 0 0.0 0.00000000 -0.2
7 Ar Ar 1 0 0 1 -0.4 -0.01333333 0.0
8 Ar M 2 2 0 0 0.0 0.00000000 -0.2
9 Ar I 3 3 0 0 0.0 0.00000000 -0.3
10 Ar E 4 4 0 0 0.0 0.00000000 -0.4
11 Ar C 2 2 0 0 0.0 0.00000000 -0.2
12 Ar Ai 3 3 0 0 0.0 0.00000000 -0.3
13 Ar H 1 1 0 0 0.0 0.00000000 -0.1
14 M M 2 0 0 2 -0.8 -0.03478261 0.0
15 M I 4 3 0 1 0.0 0.00000000 -0.5
16 M E 2 2 0 0 0.0 0.00000000 -0.2
17 M C 4 3 1 0 0.0 0.00000000 -1.2
18 M Ai 3 3 0 0 0.0 0.00000000 -0.3
19 M H 3 3 0 0 0.0 0.00000000 -0.3
20 I I 91 0 0 91 -36.4 -0.10167598 0.0
21 I E 24 10 12 2 0.0 0.00000000 -12.2
22 I C 37 33 3 1 0.0 0.00000000 -6.2
23 I Ai 27 21 5 1 0.0 0.00000000 -6.8
24 I H 11 8 2 1 0.0 0.00000000 -2.8
25 E E 3 0 0 3 -1.2 -0.01935484 0.0
26 E C 5 4 0 1 0.0 0.00000000 -0.6
27 E Ai 8 7 1 0 0.0 0.00000000 -1.6
28 C C 19 0 0 19 -7.6 -0.03636364 0.0
29 C Ai 8 3 4 1 0.0 0.00000000 -4.1
30 C H 6 5 1 0 0.0 0.00000000 -1.4
31 Ai Ai 4 0 0 4 -1.6 -0.01684211 0.0
32 Ai H 5 1 4 0 0.0 0.00000000 -3.7
33 H H 2 0 0 2 -0.8 -0.01269841 0.0
a_ij F_ji a_ji
1 0.0000000000 0.0 0.00000000
2 -0.0100000000 -2.7 -0.10000000
3 -0.0130434783 -2.7 -0.10000000
4 -0.0033519553 -10.8 -0.40000000
5 -0.0080645161 -4.5 -0.16666667
6 -0.0009569378 -1.8 -0.06666667
7 0.0000000000 0.0 0.00000000
8 -0.0086956522 -1.8 -0.06000000
9 -0.0008379888 -2.7 -0.09000000
10 -0.0064516129 -3.6 -0.12000000
11 -0.0009569378 -1.8 -0.06000000
12 -0.0031578947 -2.7 -0.09000000
13 -0.0015873016 -0.9 -0.03000000
14 0.0000000000 0.0 0.00000000
15 -0.0013966480 -2.9 -0.12608696
16 -0.0032258065 -1.8 -0.07826087
17 -0.0057416268 -2.8 -0.12173913
18 -0.0031578947 -2.7 -0.11739130
19 -0.0047619048 -2.7 -0.11739130
20 0.0000000000 0.0 0.00000000
21 -0.1967741935 -10.6 -0.02960894
22 -0.0296650718 -30.2 -0.08435754
23 -0.0715789474 -19.6 -0.05474860
24 -0.0444444444 -7.6 -0.02122905
25 0.0000000000 0.0 0.00000000
26 -0.0028708134 -3.8 -0.06129032
27 -0.0168421053 -6.4 -0.10322581
28 0.0000000000 0.0 0.00000000
29 -0.0431578947 -3.3 -0.01578947
30 -0.0222222222 -4.6 -0.02200957
31 0.0000000000 0.0 0.00000000
32 -0.0587301587 -1.3 -0.01368421
33 0.0000000000 0.0 0.00000000
Assemble a Jacobian matrix
Code
assemble_jacobian(interaction_table, abundance[, 1], "a_ij", "a_ji")
Output
[,1] [,2] [,3] [,4] [,5]
[1,] -0.01481481 -0.01000000 -0.013043478 -0.0033519553 -0.008064516
[2,] -0.10000000 -0.01333333 -0.008695652 -0.0008379888 -0.006451613
[3,] -0.10000000 -0.06000000 -0.034782609 -0.0013966480 -0.003225806
[4,] -0.40000000 -0.09000000 -0.126086957 -0.1016759777 -0.196774194
[5,] -0.16666667 -0.12000000 -0.078260870 -0.0296089385 -0.019354839
[6,] -0.06666667 -0.06000000 -0.121739130 -0.0843575419 -0.061290323
[7,] 0.00000000 -0.09000000 -0.117391304 -0.0547486034 -0.103225806
[8,] 0.00000000 -0.03000000 -0.117391304 -0.0212290503 0.000000000
[,6] [,7] [,8]
[1,] -0.0009569378 0.000000000 0.000000000
[2,] -0.0009569378 -0.003157895 -0.001587302
[3,] -0.0057416268 -0.003157895 -0.004761905
[4,] -0.0296650718 -0.071578947 -0.044444444
[5,] -0.0028708134 -0.016842105 0.000000000
[6,] -0.0363636364 -0.043157895 -0.022222222
[7,] -0.0157894737 -0.016842105 -0.058730159
[8,] -0.0220095694 -0.013684211 -0.012698413
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