faire un tri en gardant l'information de nom de colonne

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François Bonnot
Messages : 463
Enregistré le : 10 Nov 2004, 15:19
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Re: faire un tri en gardant l'information de nom de colonne

Messagepar François Bonnot » 26 Oct 2018, 06:52

Bonjour,
Error in 1:nrow(ADCP_longformat) : argument of length 0

Il es impossible que vous obteniez cette erreur avec le code que je vous ai envoyé, puisque l'instruction n'y figure pas (c'est 1:nrow(df1)).
Reprenez exactement les 2 fonctions sans les modifier.
Ensuite, si ça ne marche pas, extrayez un sous-ensemble de lignes (pas plus de 100 lignes) de vos 3 data frames de façon à reproduire l'erreur et postez sur le forum le contenu de ces sous-ensembles avec dput() en utilisant le lien suivant:
http://forums.cirad.fr/logiciel-R/viewtopic.php?f=1&t=3302
François

Guillaume Dramais
Messages : 22
Enregistré le : 25 Sep 2018, 00:04

Re: faire un tri en gardant l'information de nom de colonne

Messagepar Guillaume Dramais » 02 Nov 2018, 23:40

Bonjour François,
Merci pour ce message, et désolé de répondre avec tant de retard, en fait je ne l'avait pas vu, il n'apparait pas directement dans l'arborescence de la discussion, je viens de me rendre compte qu'il y avait plusieurs pages...c'est ballot...

J'ai réessayé tes codes et effectivement ça marche...

En fait en testant les différentes possibilités la semaine dernière je me suis arrêté sur celle ci :

Code : Tout sélectionner

ADCP_longformat1$conc=NA

for (i in 1:nrow(ADCP_longformat1)){
  ddistance = samplesand$distance - ADCP_longformat1$distance[i] # distance entre chaque position et la position de mon sample
  ddepth    = samplesand$depth - ADCP_longformat1$depth[i] # depth entre chaque position et la position de mon sample
    d = sqrt(ddistance^2+ddepth^2) # distance en metre entre chaque sample et chaque valeur de data1
 
  ADCP_longformat1$conc[i]=as.numeric(samplesand$sand[which.min(d)])
}


Elle n'est pas optimale, très longue en temps de calcul, mais par contre elle fait le job...

En fait en faisant mes essais j'ai changé de stratégie pour traiter ce jeux de données. Pour pouvoir non pas garder le nom de colonne qui me permettait ensuite d'aller chercher une autre donnée correspondante à ce n° ou cette position. Mais en affectant directement la donnée finale désirée à chaque cellule de mon dataframe.

Dans le code

Code : Tout sélectionner

dist2 <- function(df1,df2) {
  d2 <- function(a,b) (a-b)^2
  x2 <- outer(df1[[1]],df2[[1]],d2)
  y2 <- outer(df1[[2]],df2[[2]],d2)
  dist <- sqrt(x2+y2)
  colnames(dist) <- rownames(df2)
  dist
}

d <- dist2(ADCP_longformat1,samplesand)
dmin <- apply(d,1,min)
positions <- apply(d,1,which.min)

res=data.frame(min=dmin,sample=colnames(d)[positions])
res$sample=as.numeric(res$sample)


Qui est beaucoup plus rapide que ma boucle...J'ai essayé de modifier cette ligne qui affecte le nom de colonne dans le df "res"

Code : Tout sélectionner

res=data.frame(min=dmin,sample=colnames(d)[positions])

par une commande qui appellerait directement la valeur du df2 par exemple les valeurs de la colonne "sand" du df2 ci dessous, plutôt que le nom de colonne.

Code : Tout sélectionner

> samplesand
   distance depth sand
1        -8     0   46
2        17     0   46
3        17     3   49
4        17     4  106
5        17     6  128
6        62     0   59
7        62     2  173
8        62     3  131
9        62     4  160
10      122     0   48
11      122     2   70
12      122     5   32
13      122     6  228
14      162     0   48


Je n'ai pas réussi à régler ça du coup, je continue avec ma boucle lente mais je serais très intéressé par la bonne ligne de code. Merci d'avance

Et merci pour ce forum qui est vraiment une aide précieuse pour moi et pour beaucoup d'autres je pense.
Cordialement
Guillaume

François Bonnot
Messages : 463
Enregistré le : 10 Nov 2004, 15:19
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Re: faire un tri en gardant l'information de nom de colonne

Messagepar François Bonnot » 05 Nov 2018, 07:20

Bonjour,
Le code n'est pas reproductible :

Code : Tout sélectionner

> d <- dist2(ADCP_longformat1,samplesand)
Error in outer(df1[[1]], df2[[1]], d2) :
  object 'ADCP_longformat1' not found

Voir :
viewtopic.php?f=1&t=7638
François

Guillaume Dramais
Messages : 22
Enregistré le : 25 Sep 2018, 00:04

Re: faire un tri en gardant l'information de nom de colonne

Messagepar Guillaume Dramais » 05 Nov 2018, 13:21

Bonjour,

Voilà la partie manquante

Code : Tout sélectionner

ADCP_longformat1
         distance depth         value
1       0.0000000  1.08  0.0000000000
2       0.1060068  1.08  0.0000000000
3       0.1912294  1.08  0.0000000000
4       0.2846596  1.08  0.0000000000
5       0.3803486  1.08  0.0000000000
6       0.4808231  1.08  0.0000000000
7       0.6095348  1.08  0.0000000000
8       0.7040308  1.08 -0.0202964700
9       0.7561350  1.08 -0.0142817400
10      0.8272756  1.08 -0.0002730300
11      0.9557846  1.08 -0.0040251300
12      1.0531275  1.08 -0.0002454600
13      1.1287192  1.08 -0.0006689200
14      1.1999160  1.08  0.0276251700
15      1.2775185  1.08 -0.0049981400
16      1.3619830  1.08  0.0152091300
17      1.4515981  1.08  0.0105527900
18      1.5283761  1.08  0.0128743200
19      1.5982381  1.08  0.0097106300
20      1.6819898  1.08  0.0186148900
21      1.7838634  1.08  0.0149464500
22      1.8738047  1.08  0.0010123100
23      1.9639120  1.08  0.0119514800
24      2.0420091  1.08 -0.0117951600
25      2.1299796  1.08 -0.0077695300
26      2.2145304  1.08  0.0061955700
27      2.3021601  1.08  0.0218680600
28      2.3980683  1.08  0.0299263700
29      2.4917993  1.08 -0.0111009900
30      2.5886522  1.08 -0.0019216700
31      2.7032839  1.08  0.0115691200
32      2.8486075  1.08  0.0127649300
33      3.0111455  1.08  0.0072114800
34      3.1504175  1.08  0.0361685000
35      3.2880275  1.08  0.0811530500
36      3.4106399  1.08 -0.0009499800
37      3.6430576  1.08  0.0499153200
38      3.8260922  1.08  0.0596510100
39      4.0283387  1.08  0.0564972800
40      4.2660494  1.08  0.0727215000
41      4.5349951  1.08  0.0567576300
42      4.7428332  1.08  0.0949366900
43      5.0160503  1.08  0.0806705700
44      5.3028905  1.08  0.0719064600
45      5.5953920  1.08  0.0686280300
46      5.8601342  1.08  0.0857928200
47      6.0945338  1.08  0.0491024200
48      6.4054823  1.08  0.0615013800
49      6.7292941  1.08  0.1224473100
50      7.0390274  1.08  0.1028158700
51      7.3329957  1.08 -0.4148611500
52      7.6417603  1.08  0.4866138200
53      7.9371796  1.08  0.1879431600
54      8.2537888  1.08  0.1623397000
55      8.5981189  1.08  0.1510652100
56      8.9670857  1.08  0.2289173200
57      9.3223678  1.08  0.2177043100
58      9.6786181  1.08  0.2414772100
59     10.0541322  1.08  0.2710560000
60     10.4202932  1.08  0.1857409700
61     10.7705831  1.08  0.1931900100
62     11.1232062  1.08  0.2790350300
63     11.4911509  1.08  0.2086736000
64     11.8577373  1.08  0.2422003100
65     12.2301689  1.08  0.2315036800
66     12.6338491  1.08  0.2262027200
67     13.0210258  1.08  0.1581657700
68     13.4279304  1.08  0.2135074200
69     13.8429876  1.08  0.2347081800
70     14.2507912  1.08  0.2341553300
71     14.6305135  1.08  0.2450224700
72     15.0265244  1.08  0.2766496600
73     15.4185909  1.08  0.2143093400
74     15.7987384  1.08  0.4474373900
75     16.1714031  1.08  0.1569959800
76     16.5538830  1.08  0.2464452600
77     16.9344079  1.08  0.2502518000
78     17.2941682  1.08  0.2269311100
79     17.6452451  1.08  0.2823520600
80     18.0189914  1.08  0.3070245900
81     18.3100919  1.08  0.2560665700
82     18.7180915  1.08  0.3415769000
83     19.0865323  1.08  0.3487847800
84     19.4326795  1.08  0.4388906800
85     19.8474561  1.08  0.4369437900
86     20.2568071  1.08  0.4026029100
87     20.6404574  1.08  0.4879498600
88     21.0831526  1.08  0.5064062200
89     21.5994479  1.08  0.6168583800
90     22.1711953  1.08  0.5527371100
91     22.7545467  1.08  0.5217190600
92     23.4112545  1.08  0.5907812500
93     24.0881922  1.08  0.6016582100
94     24.7764316  1.08  0.5874396100
95     25.4191582  1.08  0.4435744800
96     26.0413195  1.08  0.5752815000
97     26.6440865  1.08  0.5386839100
98     27.2255539  1.08  0.5772614200
99     27.7430780  1.08  0.5679287200
100    27.7430780  1.08  0.0000000000
il y a en fait plusieurs milliers de lignes

merci
Guillaume

François Bonnot
Messages : 463
Enregistré le : 10 Nov 2004, 15:19
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Re: faire un tri en gardant l'information de nom de colonne

Messagepar François Bonnot » 05 Nov 2018, 16:56

Ce format ne permet pas de récupérer les données facilement.
Comme indiqué dans mon message du Ven Oct 26, 2018 6:52 am , il faut utiliser dput().
François

Guillaume Dramais
Messages : 22
Enregistré le : 25 Sep 2018, 00:04

Re: faire un tri en gardant l'information de nom de colonne

Messagepar Guillaume Dramais » 06 Nov 2018, 18:01

Bonjour,
Voilà les détails des data.frame que je veux utiliser (le premier est complet)

Code : Tout sélectionner

> dput(samplesand)
structure(list(distance = c(0L, 40L, 40L, 40L, 40L, 80L, 80L,
80L, 80L, 120L, 120L, 120L, 120L, 160L), depth = c(0, 0, 5, 10,
12.5, 0, 5, 10, 12.5, 0, 5, 10, 12.5, 0), sand = c(14L, 14L,
161L, 141L, 1024L, 24L, 84L, 160L, 356L, 17L, 33L, 53L, 167L,
17L)), class = "data.frame", row.names = c(NA, -14L))


Le second (qui est un assemblage) de 31320 lignes + 435 lignes de deux dataframes

Voilà le dataframe que je souhaite utiliser (ADCP_longformat)
il est structuré comme ceci

Code : Tout sélectionner

   distance      depth   value
1   0.00777069   1.08   0.01686950
2   0.05495153   1.08   0.02143795
3   0.07466094   1.08   0.02638049
4   0.11414045   1.08   0.02730889
5   0.14561783   1.08   0.02738411
6   0.16427647   1.08   0.02054586
7   0.19168068   1.08   0.03736404
8   0.25491445   1.08   0.02036974
9   0.30149560   1.08   0.03141198
10   0.35503996   1.08   0.0424875


si je fait dput() je rate les premières lignes mais j'ai la fin

Code : Tout sélectionner

> dput(ADCP_longformat)
......
    0.0162485299999844, 0.0198921900000073, 0.0284403200000156,
    0.0345834499999853, 0.0335096900000167, 0.0343464999999981,
    0.0418096899999796, 0.0428487500000188, -0.0681494899999961,
    0.0271059499999922, 0.0291717899999924, 0.00430575999999405
    )), class = "data.frame", row.names = c(NA, -31755L))

Voilà des infos supplémentaires

Code : Tout sélectionner

    > colnames(ADCP_longformat)
[1] "distance" "depth"    "value"   
> dim(ADCP_longformat)
[1] 31755     3
> is(ADCP_longformat)
[1] "data.frame" "list"       "oldClass"   "vector"   


Le premier dataframe de l'assemblage

Code : Tout sélectionner

> dput(ADCP_longformat1)
.....
0.156952835167499, 0.132014879424997, 0.150906972475004, 0.137842230542496,
0.181856851312501, 0.166907209859999, 0.183606683015002, 0.222718422352502,
0.196741088032499, 0.168455113012501, 0.103652736330001, 0.118056346087498,
0.112533110650002, 0.114287605049997, 0.1236405863875, 0.11162612461,
0.128755183077502, 0.1274193789, 0.110453246249997, 0.175641404355,
0.1626577293875, 0.167979286720001, 0.170418725599999, 0.169851815860001,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA)), row.names = c(NA, -31320L), class = "data.frame")


le second (plus petit)

Code : Tout sélectionner

> dput(Bot)
structure(list(distance = c(0, 0.00777069, 0.05495153, 0.07466094,
0.11414045, 0.14561783, 0.16427647, 0.19168068, 0.25491445, 0.3014956,
0.35503996, 0.39509682, 0.4796326, 0.51894043, 0.5600886, 0.59568112,
0.64222619, 0.6903943, 0.75670169, 0.83534086, 0.93712976, 1.0255487,
1.12066791, 1.22545977, 1.32665723, 1.44250813, 1.58586431, 1.71745616,
1.84511643, 1.9749109, 2.10859778, 2.22893517, 2.37833003, 2.52266385,
2.65236748, 2.77150684, 2.91479959, 3.07946338, 3.2323296, 3.36610105,
0.0275498100000107, 0.0193078699999774, 0.0172700500000076, 0.0142707999999914,
0.013895400000024, 0.014191889999978, 0.0133223600000179, 0.00866569999999456,
0.0195576899999992, 0.0162485299999844, 0.0198921900000073, 0.0284403200000156,
0.0345834499999853, 0.0335096900000167, 0.0343464999999981, 0.0418096899999796,
0.0428487500000188, -0.0681494899999961, 0.0271059499999922,
0.0291717899999924, 0.00430575999999405)), class = "data.frame", row.names = c(NA,
-435L))
>


Voilà, j'espère que ça va permettre d'adapter le code
merci

François Bonnot
Messages : 463
Enregistré le : 10 Nov 2004, 15:19
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Re: faire un tri en gardant l'information de nom de colonne

Messagepar François Bonnot » 07 Nov 2018, 07:49

Bonjour,
C'est mieux mais il manque des informations pour vous répondre.
Pour vous aider, je dois (sans y passer plus de quelques minutes) reproduire votre code d <- dist2(ADCP_longformat1,samplesand) qui (d'après ce que j'ai compris) fonctionne mais lentement.
L'extrait de samplesand avec dput est OK, mais pas ADCP_longformat1, parce que vous avez utilisé dput sur tout votre data frame. Il faut un PETIT extrait de données (c'est clairement indiqué dans le lien concernant dput), pas plus d'une centaine de lignes, et vérifier sur les données correspondantes sont suffisantes pour permettre une réponse à la question.
François

Guillaume Dramais
Messages : 22
Enregistré le : 25 Sep 2018, 00:04

Re: faire un tri en gardant l'information de nom de colonne

Messagepar Guillaume Dramais » 07 Nov 2018, 17:14

Bonjour,
Non votre code est beaucoup plus rapide que ma boucle, c'est pour cela que je préfèrerais arriver à l'adapter à mon utilisation...
Il ya deux problèmes:
1. j'essaie de faire fonctionner votre code sur mon fichier combiné (là ça coince, je ne n'arrive pas à comprendre pourquoi)
2. Je voudrais modifier le code pour obtenir comme résultat non pas la position de l'échantillon le plus proche mais directement une valeur du tableau correspondnate effectivement à l'échantillon le plus proche. En d'autres termes je voudrais que "res" me renvoie eventuellement la distance minimale comme actuellement et au lieu de la position de la ligne une valeur du tableau samplesand correspondant à cet indice de ligne.

La fonction que vous me proposiez :

Code : Tout sélectionner

dist2 <- function(df1,df2) {
  d2 <- function(a,b) (a-b)^2
  x2 <- outer(df1[[1]],df2[[1]],d2)
  y2 <- outer(df1[[2]],df2[[2]],d2)
  dist <- sqrt(x2+y2)
  colnames(dist) <- rownames(df2)
  dist
}

d <- dist2(ADCP_longformat,samplesand)
dmin <- apply(d,1,min)
positions <- apply(d,1,which.min)

res=data.frame(min=dmin,sample=colnames(d)[positions])
res$sample=as.numeric(res$sample)


Ce code marche très bien sur la première partie du fichier, renvoie l'indice de ligne que je cherchais au début, mais ne répond pas encore à mon problème n°2.

Voici les fichiers

Code : Tout sélectionner

> dput(samplesand)
structure(list(distance = c(0L, 40L, 40L, 40L, 40L, 80L, 80L,
80L, 80L, 120L, 120L, 120L, 120L, 160L), depth = c(0, 0, 5, 10,
12.5, 0, 5, 10, 12.5, 0, 5, 10, 12.5, 0), sand = c(14L, 14L,
161L, 141L, 1024L, 24L, 84L, 160L, 356L, 17L, 33L, 53L, 167L,
17L)), class = "data.frame", row.names = c(NA, -14L))


Voilà un extrait dput() de ADCP_longformat

Code : Tout sélectionner

       structure(list(distance = c(50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146
), depth = c(1.08, 1.33, 1.58, 1.83, 2.08, 2.33, 2.58, 2.83,
3.08, 3.33, 3.58, 3.83, 4.08, 4.33, 4.58, 4.83, 5.08, 5.33, 6.08,
6.33, 6.58, 6.83, 7.08, 7.33, 7.58, 7.83, 8.08, 8.33, 8.58, 8.83,
9.08, 9.33, 9.58, 9.83, 10.08, 10.33, 10.58, 10.83, 11.08, 11.33,
11.58, 11.83, 12.08, 12.33, 12.58, 12.83, 13.08, 13.33, 13.58,
13.83, 14.08, 14.33, 14.58, 14.83, 15.08, 15.33, 15.58, 15.83,
16.08, 16.33, 16.58, 16.83, 17.08, 17.33, 17.58, 17.83, 18.08,
18.33, 18.58, 18.83, 19.08, 19.33, 12.4894603), value = c(0.783433710000004,
0.172884149459999, 0, 0, 0.526975907105001, 0.16223667759, 0.167460776594999,
0, 0, 0.2950769495125, 0, 0.244022185117501, 0.191827690970001,
0.161530432537499, 0, 0, 0.559841891700001, 0, 0, 0.806963551679998,
0.231366713857502, 0.219194466547498, 0.223880471429999, 0.20128381371,
0.196237811267502, 0.19954142127, 0, 0.35891775465, 0.154718862934998,
0.185072871060002, 0.145497987809997, 0.130401111757503, 0.136347933049999,
0.0866487700649998, 0.1185256578375, 0.114278757925002, 0.138977725147499,
0.151146321097497, 0.116399512785, 0.0800894439675003, 0.0619966953975011,
0.0761066922825002, 0.119270501599998, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, 0.620063869999996)), class = "data.frame", row.names = c(NA,
-73L))


J'espère que c'est exploitable
merci

François Bonnot
Messages : 463
Enregistré le : 10 Nov 2004, 15:19
Contact :

Re: faire un tri en gardant l'information de nom de colonne

Messagepar François Bonnot » 08 Nov 2018, 09:57

Bonjour,
C'est beaucoup plus facile avec un extrait du jeu de données.
Dans votre exemple du Mer Nov 07, 2018 5:14 pm vous obtenez un vecteur positions qui vous permet d'obtenir le même résultat que votre boucle avec le code

Code : Tout sélectionner

ADCP_longformat$conc <- samplesand$sand[positions]
François

Guillaume Dramais
Messages : 22
Enregistré le : 25 Sep 2018, 00:04

Re: faire un tri en gardant l'information de nom de colonne

Messagepar Guillaume Dramais » 08 Nov 2018, 18:21

Bonjour,
Merci de votre patience, ça marche très bien sur ADCP_longformat, mais ça coince toujours sur le second, par contre je crois avoir une piste

si j'essaie le code

Code : Tout sélectionner

dist2 <- function(df1,df2) {
  d2 <- function(a,b) (a-b)^2
  x2 <- outer(df1[[1]],df2[[1]],d2)
  y2 <- outer(df1[[2]],df2[[2]],d2)
  dist <- sqrt(x2+y2)
  colnames(dist) <- rownames(df2)
  dist
}

d <- dist2(Bot,samplesand)
dmin <- apply(d,1,min)
positions <- apply(d,1,which.min)

res=data.frame(min=dmin,sample=colnames(d)[positions])
res$sample=as.numeric(res$sample)

Bot$conc <- samplesand$sand[positions]


La fonction dist2 s'exécute bien, on crée "positions"
Mais ça coince à la création du dataframe "res"
Error in colnames(d)[positions] : invalid subscript type 'list'


Le vecteur "position" n'a pas la même structure quand j'applique le code à "ADCP_longformat"
> is(positions)
[1] "integer" "numeric" "vector" "data.frameRowLabels"

et a Bot
> is(positions)
[1] "list" "vector"


Pourtant "ADCP_longformat" et "Bot" ont la même structure de départ...
> is(Bot)
[1] "data.frame" "list" "oldClass" "vector"
> is(ADCP_longformat1)
[1] "data.frame" "list" "oldClass" "vector"


ça explique pourquoi le code ne marchait pas sur la combinaison des fichiers "ADCP_longfromat" et "Bot"

Comment construire autrement "Bot" pour que le code fonctionne?

Bot est créé simplement par l'assemblage de 3 vecteurs, mais le problème doit venir de là

Code : Tout sélectionner

#Add the bottom discharge
Bot <- data.frame (distance, Botdepth, BotDisch2)
colnames(Bot) <- c('distance', 'depth', 'value')


Ces trois vecteurs sont de structure vector
[1] "matrix" "array" "structure" "vector"
> is(depth)
[1] "matrix" "array" "structure" "vector"
> is(Botdepth)
[1] "matrix" "array" "structure" "vector"
> is(BotDisch2)
[1] "numeric" "vector"



Revoilà les extraits de df celui là est Bot

Code : Tout sélectionner

 dput(Bot)
structure(list(distance = c(0, 0.00777069, 0.05495153, 0.07466094,
0.11414045, 0.14561783, 0.16427647, 0.19168068, 0.25491445, 0.3014956,
0.35503996, 0.39509682, 0.4796326, 0.51894043, 0.5600886, 0.59568112,
0.64222619, 0.6903943, 0.75670169, 0.83534086, 0.93712976, 1.0255487,
1.12066791, 1.22545977, 1.32665723, 1.44250813, 1.58586431, 1.71745616,
1.84511643, 1.9749109, 2.10859778, 2.22893517, 2.37833003, 2.52266385,
2.65236748, 2.77150684, 2.91479959, 3.07946338, 3.2323296, 3.36610105,
3.52860756, 3.70293673, 3.88871174, 4.1153479, 4.3462683, 4.57721393,
4.80679395, 5.0667142, 5.32353686, 5.58459851, 5.83657338, 6.09579399,
6.3581206, 6.63773354, 6.88965494, 7.14640927, 7.39825909, 7.66255211,
7.93839273, 8.20625076, 8.47881698, 8.76348811, 9.07283076, 9.39672844,
9.7070809, 10.02303497, 10.34749054, 10.65584852, 10.994718,
11.32052767, 11.62478651, 11.92615145, 12.25500259, 12.55142603,
12.83669657, 13.16011548, 13.43656897, 13.43656897, 14.00918158,
14.30757688, 14.59375824, 14.88317388, 15.20069185, 15.20069185,
15.78028829, 16.05940808, 16.35157415, 16.64097127, 16.88286052,
17.14727333, 17.40879499, 17.61104385, 17.81531982, 18.05345426,
18.3602787, 18.69643568, 19.02086501, 19.35689024, 19.69342137,
20.00740936), depth = c(3.35152351, 3.31418865, 3.33633333, 3.32612218,
3.30906367, 3.3194591, 3.31805222, 3.32364217, 3.3058855, 3.41494574,
3.39555897, 3.62133672, 3.38610711, 3.46624371, 3.50955268, 3.48222668,
3.91713147, 4.23859394, 4.29509498, 4.32926234, 4.35238771, 4.41169294,
4.33545166, 4.34553048, 4.40547996, 4.35832938, 4.20798305, 3.97897817,
3.97115789, 4.24211789, 4.0803125, 4.69859438, 4.10619484, 4.51312667,
4.59217725, 4.73495032, 4.83366312, 4.89860994, 4.50957219, 4.54678544,
5.19008226, 5.38566193, 5.44288534, 5.62533182, 5.87336791, 6.05352217,
6.06610808, 6.32542069, 6.48104926, 6.691269, 6.90352023, 7.02918899,
6.90284817, 7.30516672, 7.53393827, 7.53920581, 7.65860852, 7.84809338,
8.07762928, 8.21116294, 8.25273891, 8.50228102, 8.58819589, 8.51430572,
8.95869441, 9.10004866, 9.30748994, 9.36050582, 9.38172796, 9.49004304,
9.55214726, 9.59989075, 9.5734046, 9.98140373, 9.96519857, 9.59493068,
9.99883531, NA, 10.10626851, 10.45272298, 10.48532556, 10.54980492,
10.6702884, NA, 10.69172869, 10.62455011, 10.74860274, 10.67805865,
10.88044872, 10.76756244, 10.88822813, 11.04925185, 11.0399168,
11.0399168, 11.35574207, 11.40641953, 11.50892749, 11.45751297,
11.64584628, 11.60961223), value = c(0, 0.01416743, 0.01840211,
0.02241883, 0.02281748, 0.02311879, 0.01732144, 0.03167525, 0.01696539,
0.02904014, 0.02930869, 0.04434403, 0.01709864, 0.02113226, 0.02534766,
0.02400586, 0.01479869, 0.03511881, 0.01989324, 0.01476095, 0.030652,
0.00801474999999996, 0.04002372, -0.00772527999999995, 0.02972804,
0.00725947999999998, -0.00551517999999995, -0.00547403999999996,
-0.00510890000000008, 0.00691571000000002, -0.00457819999999998,
0.00685462000000003, 0.02050836, 0.03077758, 0.04695564, 0.0303501,
0.10027534, 0.0668014100000001, 0.03466876, 0.07245313, 0.07505076,
0.07370901, 0.10794792, 0.1047011, 0.11703724, 0.18680078, 0.2367611,
0.28907416, 0.31522422, 0.31489968, 0.27168073, 0.33237669, 0.2947128,
0.29036957, 0.3100101, 0.379245180000001, 0.4758263, 0.39840622,
0.41876426, 0.5186063, 0.51606542, 0.49666069, 0.48251716, 0.35764661,
0.425182530000001, 0.411718049999999, 0.35174029, 0.514642369999999,
0.389445530000001, 0.344183209999999, 0.356269860000001, 0.394838089999999,
0.35660693, 0.31639015, 0.38676933, 0.256098580000002, 0.39301929,
0, 0.697705579999999, 0.327558939999999, 0.36292946, 0.380207520000001,
0.480858769999999, 0, 1.03057745, 0.43814609, 0.454436170000001,
0.349263430000001, 0.39411904, 0.383897579999999, 0.277793540000001,
0.275131639999998, 0.291093100000001, 0.308066180000001, 0.396132980000001,
0.43501569, 0.363055069999998, 0.35895743, 0.338373350000001,
0.42223997)), class = "data.frame", row.names = c(NA, -100L))


Samplesand

Code : Tout sélectionner

> dput(samplesand)
structure(list(distance = c(0L, 40L, 40L, 40L, 40L, 80L, 80L,
80L, 80L, 120L, 120L, 120L, 120L, 160L), depth = c(0, 0, 5, 10,
12.5, 0, 5, 10, 12.5, 0, 5, 10, 12.5, 0), sand = c(14L, 14L,
161L, 141L, 1024L, 24L, 84L, 160L, 356L, 17L, 33L, 53L, 167L,
17L)), class = "data.frame", row.names = c(NA, -14L))


ADCP_longformat si besoin

Code : Tout sélectionner

     structure(list(distance = c(50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146,
50.09320146, 50.09320146, 50.09320146, 50.09320146, 50.09320146
), depth = c(1.08, 1.33, 1.58, 1.83, 2.08, 2.33, 2.58, 2.83,
3.08, 3.33, 3.58, 3.83, 4.08, 4.33, 4.58, 4.83, 5.08, 5.33, 6.08,
6.33, 6.58, 6.83, 7.08, 7.33, 7.58, 7.83, 8.08, 8.33, 8.58, 8.83,
9.08, 9.33, 9.58, 9.83, 10.08, 10.33, 10.58, 10.83, 11.08, 11.33,
11.58, 11.83, 12.08, 12.33, 12.58, 12.83, 13.08, 13.33, 13.58,
13.83, 14.08, 14.33, 14.58, 14.83, 15.08, 15.33, 15.58, 15.83,
16.08, 16.33, 16.58, 16.83, 17.08, 17.33, 17.58, 17.83, 18.08,
18.33, 18.58, 18.83, 19.08, 19.33, 12.4894603), value = c(0.783433710000004,
0.172884149459999, 0, 0, 0.526975907105001, 0.16223667759, 0.167460776594999,
0, 0, 0.2950769495125, 0, 0.244022185117501, 0.191827690970001,
0.161530432537499, 0, 0, 0.559841891700001, 0, 0, 0.806963551679998,
0.231366713857502, 0.219194466547498, 0.223880471429999, 0.20128381371,
0.196237811267502, 0.19954142127, 0, 0.35891775465, 0.154718862934998,
0.185072871060002, 0.145497987809997, 0.130401111757503, 0.136347933049999,
0.0866487700649998, 0.1185256578375, 0.114278757925002, 0.138977725147499,
0.151146321097497, 0.116399512785, 0.0800894439675003, 0.0619966953975011,
0.0761066922825002, 0.119270501599998, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, 0.620063869999996)), class = "data.frame", row.names = c(NA,
-73L))



Et des extraits des trois vecteurs constitutifs de Bot : Distance

Code : Tout sélectionner

 > dput(distance)
structure(c(0, 0.00777069, 0.05495153, 0.07466094, 0.11414045,
0.14561783, 0.16427647, 0.19168068, 0.25491445, 0.3014956, 0.35503996,
0.39509682, 0.4796326, 0.51894043, 0.5600886, 0.59568112, 0.64222619,
0.6903943, 0.75670169, 0.83534086, 0.93712976, 1.0255487, 1.12066791,
1.22545977, 1.32665723, 1.44250813, 1.58586431, 1.71745616, 1.84511643,
1.9749109, 2.10859778, 2.22893517, 2.37833003, 2.52266385, 2.65236748,
2.77150684, 2.91479959, 3.07946338, 3.2323296, 3.36610105, 3.52860756,
3.70293673, 3.88871174, 4.1153479, 4.3462683, 4.57721393, 4.80679395,
5.0667142, 5.32353686, 5.58459851, 5.83657338, 6.09579399, 6.3581206,
6.63773354, 6.88965494, 7.14640927, 7.39825909, 7.66255211, 7.93839273,
8.20625076, 8.47881698, 8.76348811, 9.07283076, 9.39672844, 9.7070809,
10.02303497, 10.34749054, 10.65584852, 10.994718, 11.32052767,
11.62478651, 11.92615145, 12.25500259, 12.55142603, 12.83669657,
13.16011548, 13.43656897, 13.43656897, 14.00918158, 14.30757688,
14.59375824, 14.88317388, 15.20069185, 15.20069185, 15.78028829,
16.05940808, 16.35157415, 16.64097127, 16.88286052, 17.14727333,
17.40879499, 17.61104385, 17.81531982, 18.05345426, 18.3602787,
18.69643568, 19.02086501, 19.35689024, 19.69342137, 20.00740936,
20.32382423, 20.63579765, 20.94055493, 21.26794158, 21.52536238,
21.78228777, 22.03740104, 22.32085607, 22.59845193, 22.85131342,
23.13391896, 23.43074616, 23.71803531, 24.01976597, 24.35272285,
24.6957525, 25.05556822, 25.43484452, 25.82558788, 26.23747727,
26.64712787, 27.06550188, 27.44370697, 27.83607621, 28.26176843,
28.67307611, 29.11875077, 29.57240666, 30.05427555, 30.541581,
31.05595991, 31.57539214, 32.12941819, 32.70816123, 33.26120449,
33.81928882, 34.35353391, 34.88294659, 35.45701911, 35.45701911,
36.56310326, 37.12157726, 37.63873173, 38.16710785, 38.72903894,
39.31147807, 39.8590885, 40.38517292, 40.90370585, 41.44372658,
42.00732707, 42.56718654, 43.14393596, 43.73670887, 44.35211168,
44.98936378, 45.60967467, 46.21566562, 46.7616909, 47.29522161,
47.82897069, 48.39216629, 48.951682, 49.53462584, 50.09320146,
50.61948502, 50.61948502, 50.61948502, 52.07021016, 52.51993068,
52.95097515, 52.95097515, 52.95097515, 53.84854762, 53.84854762,
54.46671655, 54.87356213, 55.24172266, 55.24172266, 55.24172266,
56.61472546, 56.61472546, 56.61472546, 58.2889237, 58.87429173,
59.4198909, 59.94853428, 60.49401887, 61.0176688, 61.54871716,
61.54871716, 62.6004908, 63.08626431, 63.57587508, 64.04560224,
64.44963357, 64.90794595, 65.33796466, 65.78313145, 66.25438406,
66.66708703, 67.1159254, 67.50620038, 67.86574895, 68.22671952,
68.55441249, 68.86181069, 69.18479188, 69.49171313, 69.82564871,
70.15429037, 70.49481656, 70.86055906, 71.23388233, 71.56193098,
71.92701227, 72.2629159, 72.60752065, 72.94653397, 73.28429459,
73.6622073, 74.05996365, 74.44357218, 74.84206463, 75.25089174,
75.61787862, 76.00218445, 76.41680509, 76.82177378, 77.25540645,
77.68713254, 78.14156306, 78.58490248, 79.04891017, 79.48364148,
79.94631618, 80.38818617, 80.80781267, 81.20512391, 81.58470344,
81.9554756, 82.31519268, 82.68708613, 83.06940717, 83.44170404,
83.80692297, 84.17619536, 84.55607446, 84.93870383, 85.35319238,
85.78447716, 86.22610478, 86.67809549, 87.10649198, 87.50402617,
87.91372078, 88.32470893, 88.75259148, 89.20746752, 89.66328535,
90.11521298, 90.58383967, 91.07156935, 91.53663565, 92.04244243,
92.56087344, 93.11894416, 93.67769408, 94.25055012, 94.84031263,
95.42996873, 96.02247692, 96.59529079, 97.16001573, 97.72917135,
98.26277578, 98.80888414, 99.37127989, 99.93416286, 100.52885039,
101.1116291, 101.72168145, 102.33660479, 102.95508888, 103.57756618,
104.18292798, 104.81920632, 105.4598302, 106.09386941, 106.7603258,
107.43918238, 108.14082775, 108.83562623, 109.49940239, 110.22534156,
110.95981841, 111.69915885, 112.41234082, 113.13606839, 113.84537913,
114.54102435, 115.19132811, 115.82335743, 116.47631006, 117.14025665,
117.81386287, 118.50995334, 119.1790642, 119.81354309, 120.41725926,
121.0259537, 121.60639374, 122.20258588, 122.82270048, 123.50562306,
124.19115213, 124.89742431, 125.56508207, 126.23847694, 126.84095785,
127.38381916, 127.87104852, 128.36745054, 128.86929545, 129.37638737,
129.87803557, 130.37825433, 130.87776139, 131.351596, 131.81616179,
132.2978845, 132.75798095, 133.24158291, 133.72461137, 134.22835139,
134.77565124, 135.31210506, 135.85228267, 136.38000404, 136.88813964,
137.40060151, 137.89391839, 138.37109838, 138.85673079, 139.32165484,
139.77772676, 140.2069285, 140.65015987, 141.09970781, 141.54339601,
141.95271403, 142.34986875, 142.74300264, 143.15621239, 143.5814287,
144.0073305, 144.42803071, 144.84983292, 145.29943515, 145.74552919,
146.18725294, 146.64578685, 147.15074347, 147.65704863, 148.18318224,
148.71553905, 149.28349181, 149.8496405, 150.42629235, 150.9906969,
151.52166449, 152.03898927, 152.53499894, 152.99993722, 153.47203118,
153.9070386, 154.33068872, 154.76056356, 155.18376423, 155.58379582,
155.99129133, 156.42163861, 156.80918925, 157.19284911, 157.5728436,
157.93024623, 158.27513612, 158.60446909, 158.91695337, 159.18803196,
159.44305886, 159.65985646, 159.85088084, 160.02865622, 160.21565663,
160.35119165, 160.4687179, 160.58496786, 160.72332375, 160.84182043,
160.93432674, 161.00382785, 161.09878849, 161.19701648, 161.30731928,
161.40586097, 161.46720074, 161.53472786, 161.6437622, 161.72863833,
161.81036027, 161.88891273, 161.95574495, 162.05100135, 162.14029882,
162.21461479, 162.25436099, 162.35513005, 162.44690336, 162.4997396,
162.57033187, 162.63731476, 162.70183159, 162.76515002, 162.86632327,
162.96758717, 163.07529484, 163.20944032, 163.32541219, 163.47115412,
163.5942067, 163.72799856, 163.79801642, 163.89331803, 164.00818654
), .Dim = c(435L, 1L))


BotDepth

Code : Tout sélectionner

> dput(Botdepth)
structure(c(3.35152351, 3.31418865, 3.33633333, 3.32612218, 3.30906367,
3.3194591, 3.31805222, 3.32364217, 3.3058855, 3.41494574, 3.39555897,
3.62133672, 3.38610711, 3.46624371, 3.50955268, 3.48222668, 3.91713147,
4.23859394, 4.29509498, 4.32926234, 4.35238771, 4.41169294, 4.33545166,
4.34553048, 4.40547996, 4.35832938, 4.20798305, 3.97897817, 3.97115789,
4.24211789, 4.0803125, 4.69859438, 4.10619484, 4.51312667, 4.59217725,
4.73495032, 4.83366312, 4.89860994, 4.50957219, 4.54678544, 5.19008226,
5.38566193, 5.44288534, 5.62533182, 5.87336791, 6.05352217, 6.06610808,
6.32542069, 6.48104926, 6.691269, 6.90352023, 7.02918899, 6.90284817,
7.30516672, 7.53393827, 7.53920581, 7.65860852, 7.84809338, 8.07762928,
8.21116294, 8.25273891, 8.50228102, 8.58819589, 8.51430572, 8.95869441,
9.10004866, 9.30748994, 9.36050582, 9.38172796, 9.49004304, 9.55214726,
9.59989075, 9.5734046, 9.98140373, 9.96519857, 9.59493068, 9.99883531,
NA, 10.10626851, 10.45272298, 10.48532556, 10.54980492, 10.6702884,
NA, 10.69172869, 10.62455011, 10.74860274, 10.67805865, 10.88044872,
10.76756244, 10.88822813, 11.04925185, 11.0399168, 11.0399168,
11.35574207, 11.40641953, 11.50892749, 11.45751297, 11.64584628,
11.60961223, 11.70598694, 11.70743166, 11.85225469, 11.87323609,
11.90463557, 11.94477723, 11.91636461, 11.91636461, 12.09266246,
12.13028408, 12.14888377, 12.23894945, 12.23991681, 12.27156017,
12.27275519, 12.33279108, 12.34386139, 12.57010528, 12.50696587,
12.52575474, 12.67801312, 12.62885373, 12.70643029, 12.72452824,
12.67748996, 12.78751194, 12.9199547, 12.97498268, 12.92825591,
12.91364078, 13.01160245, 12.97407088, 12.99407233, 13.08884526,
13.08180185, 13.08116125, 13.04948388, 13.00444879, 13.05722276,
13.10219913, 13.08180185, 13.14616799, 13.06175921, 13.0172219,
13.00488976, 13.03, 13.06978063, 12.98729571, 12.96466824, 12.96197199,
12.89642195, 12.93394202, 12.9163711, 12.9140678, 12.85436436,
12.83784695, 12.90114224, 12.88216252, 12.87071584, 12.869048,
12.83949907, 12.77719134, 12.75471191, 12.72229137, 12.4894603,
12.60961228, 12.54221117, 12.59198989, 12.53992689, 12.55973236,
12.59198989, 12.63448341, 12.5868157, 12.54430099, 12.59198989,
12.57397867, 12.57228884, 12.66411473, 12.65181928, 12.64849302,
12.80307356, 12.82821825, 12.82782143, 12.79361117, 12.85662972,
12.83911265, 12.83719403, 12.77592947, 12.7210573, 12.52095655,
12.65064668, 12.65017576, 12.70979438, 12.69263805, 12.87742556,
12.93295028, 12.94825865, 13.05155815, 13.00378735, 13.08884526,
13.14594994, 13.0619787, 13.11180442, 13.14594994, 13.15847512,
13.12545261, 13.1578216, 13.12392389, 13.09182537, 13.14465841,
13.12457905, 13.15716808, 13.15716808, 13.15716808, 13.15847512,
13.15760376, 13.28762762, 13.22315762, 13.2330232, 13.18380419,
13.23408945, 13.31446185, 13.28956866, 13.32155878, 13.41935936,
13.35677585, 13.40403795, 13.34699003, 13.2744602, 13.28220328,
13.25677029, 13.28220328, 13.28935299, 13.22467487, 13.23220214,
13.2172018, 13.19978283, 13.16844024, 13.20188154, 13.16951185,
13.19978283, 13.19978283, 13.16741836, 13.12719972, 13.06219819,
13.04655289, 13.00610905, 12.99093111, 12.99093111, 12.96030303,
12.92825591, 12.91654319, 12.88428684, 12.90471532, 12.85458746,
12.84219293, 12.81186237, 12.79599032, 12.76916932, 12.75118453,
12.75344777, 12.72102395, 12.58342641, 12.66577353, 12.67866533,
12.66185468, 12.68199358, 12.66145251, 12.65181928, 12.74189211,
12.78218881, 12.75201637, 12.65866318, 12.61915927, 12.62188622,
12.65201248, 12.62188622, 12.58973301, 12.63488647, 12.6198063,
12.58700991, 12.53992689, 12.58970874, 12.50970684, 12.52980488,
12.59198989, 12.54221117, 12.49973105, 12.57681514, 12.54430099,
12.59198989, 12.54221117, 12.6216159, 12.68075554, 12.66145251,
12.58700991, 12.6932023, 12.66145251, 12.71431051, 12.75431271,
12.81431598, 12.85867511, 12.77927224, 12.81471328, 12.79949748,
12.86221848, 12.81, 12.86221848, 12.8097761, 12.77, 12.75241565,
12.78488783, 12.72229137, 12.58470795, 12.63718517, 12.61688597,
12.57438369, 12.50905402, 12.46784178, 12.39328949, 12.33285144,
12.25713217, 12.27614108, 12.18618729, 12.13875551, 12.12304896,
12.01933588, 11.8343052, 11.80618678, 11.7142535, 11.65632124,
11.52926155, 11.46585001, 11.36993272, 11.35969779, 11.22325002,
11.00762534, 10.94032494, 10.8690939, 10.79589635, 10.64419963,
10.43686399, 10.32863535, 10.19110109, 10.0747025, 9.98754754,
9.90024092, 9.69607083, 9.58896356, 9.43162915, 9.32041266, 9.1912899,
9.00466174, 8.87296681, 8.72293784, 8.63206194, 8.48451158, 8.25512996,
8.09897054, 7.97284917, 7.83862449, 7.59591289, 7.47663226, 7.27967917,
7.15157654, 6.93168032, 6.7907785, 6.64312054, 6.52639704, 6.42710869,
6.2508769, 6.18214106, 6.13303133, 6.04541899, 5.98881655, 5.98657838,
5.94593062, 5.85816755, 5.81267681, 5.78235824, 5.66832797, 5.51089562,
5.4930723, 5.41247711, 5.30613051, 5.25378396, 5.17183931, 5.12441837,
4.99571978, 4.9955311, 4.92562057, 4.89117542, 4.80212022, 4.80174499,
4.76697871, 4.7458052, 4.71301747, 4.67786142, 4.69068721, 4.71685608,
4.69213259, 4.64655159, 4.65688876, 4.67967416, 4.66963589, 4.6923268,
4.70220421, 4.64732503, 4.68227026, 4.68953288, 4.70220421, 4.7240267,
4.7017943, 4.69172176, 4.72547156, 4.77012108, 4.70162661, 4.7137867,
4.78015559, 4.73559068, 4.72342603, 4.75818617, 4.7262053, 4.73657053,
4.72606448, 4.73523202, 4.73335553, 4.72329255, 4.72329255, 4.70355307,
4.72323322, 4.69172176, 4.70146637, 4.64952866, 4.68966741), .Dim = c(435L,
1L))


et Botdischarge2

Code : Tout sélectionner

> dput(BotDisch2)
c(0, 0.01416743, 0.01840211, 0.02241883, 0.02281748, 0.02311879,
0.01732144, 0.03167525, 0.01696539, 0.02904014, 0.02930869, 0.04434403,
0.01709864, 0.02113226, 0.02534766, 0.02400586, 0.01479869, 0.03511881,
0.01989324, 0.01476095, 0.030652, 0.00801474999999996, 0.04002372,
-0.00772527999999995, 0.02972804, 0.00725947999999998, -0.00551517999999995,
-0.00547403999999996, -0.00510890000000008, 0.00691571000000002,
-0.00457819999999998, 0.00685462000000003, 0.02050836, 0.03077758,
0.04695564, 0.0303501, 0.10027534, 0.0668014100000001, 0.03466876,
0.07245313, 0.07505076, 0.07370901, 0.10794792, 0.1047011, 0.11703724,
0.18680078, 0.2367611, 0.28907416, 0.31522422, 0.31489968, 0.27168073,
0.33237669, 0.2947128, 0.29036957, 0.3100101, 0.379245180000001,
0.4758263, 0.39840622, 0.41876426, 0.5186063, 0.51606542, 0.49666069,
0.48251716, 0.35764661, 0.425182530000001, 0.411718049999999,
0.35174029, 0.514642369999999, 0.389445530000001, 0.344183209999999,
0.356269860000001, 0.394838089999999, 0.35660693, 0.31639015,
0.38676933, 0.256098580000002, 0.39301929, 0, 0.697705579999999,
0.327558939999999, 0.36292946, 0.380207520000001, 0.480858769999999,
0, 1.03057745, 0.43814609, 0.454436170000001, 0.349263430000001,
0.39411904, 0.383897579999999, 0.277793540000001, 0.275131639999998,
0.291093100000001, 0.308066180000001, 0.396132980000001, 0.43501569,
0.363055069999998, 0.35895743, 0.338373350000001, 0.42223997,
0.37232921, 0.45973609, 0.4669834, 0.441870359999999, 0.343018950000001,
0.385240829999997, 0.38737794, 0.416992010000001, 0.48235227,
0.462261909999999, 0.517585830000002, 0.464685880000001, 0.467495159999999,
0.498563570000002, 0.482974609999999, 0.583940769999998, 0.560260830000001,
0.711962870000001, 0.626561129999999, 0.42666345, 0.536448719999999,
0.511468910000005, 0.582002129999999, 0.544123710000001, 0.477305609999995,
0.641136809999999, 0.680828990000002, 0.597664370000004, 0.637270869999995,
0.647325479999999, 0.594151330000003, 0.558346100000001, 0.627788410000001,
0.763898990000001, 0.747515459999995, 0.773076760000002, 0.74886644,
0.716753769999997, 0.751149030000001, 0.900174920000005, 0.836169659999996,
0.841591530000002, 0.772080599999995, 0.6930531, 0.727656930000002,
0.606789920000004, 0.709819319999994, 0.631966410000004, 0.654845590000001,
0.671583040000002, 0.803956009999993, 0.718842500000001, 0.76175113,
0.72972541, 0.754614270000005, 0.78222306, 0.605258689999999,
0.72461457, 0.636076539999998, 0.464322039999999, 0.453936679999998,
0.431106270000001, 0.642090639999999, 0.650543230000004, 0.620063869999996,
0.632778390000006, 0.517831979999997, 0.521109799999998, 0.446312690000006,
0.408990160000002, 0.38572185999999, 0.385764470000012, 0.50297703999999,
0.354636350000007, 0.279146699999998, 0.405943499999992, 0.28915868,
0.473321920000004, 0.611838410000004, 0.819650499999995, 0.914503679999996,
0.927520980000011, 0.92947925, 1.0105583, 0.864621339999999,
0.893991499999998, 0.80546957, 0.699628079999997, 0.787631489999995,
0.648499300000012, 0.69326568999999, 0.637199600000002, 0.684149320000003,
0.678809950000002, 0.685499239999999, 0.808583189999993, 0.633156450000001,
0.859030840000003, 0.717572610000005, 0.66494376, 0.752744809999996,
0.667670889999997, 0.60821412, 0.68426937000001, 0.599122949999995,
0.526183970000005, 0.484353679999998, 0.573892959999995, 0.586616160000005,
0.468568640000001, 0.524945160000001, 0.593804710000001, 0.579465189999993,
0.613381029999999, 0.525261810000003, 0.509734479999992, 0.499916760000005,
0.452270370000008, 0.484722019999992, 0.444454730000004, 0.389127540000004,
0.416896229999992, 0.468753169999999, 0.494447140000005, 0.465336949999994,
0.508196220000002, 0.508663749999997, 0.474428189999998, 0.495607800000002,
0.501296809999999, 0.522512200000008, 0.569293169999995, 0.548098940000003,
0.495267229999996, 0.549616589999999, 0.50924886, 0.497889850000007,
0.522608959999999, 0.346847740000001, 0.332980739999996, 0.377742710000007,
0.389296019999989, 0.409081720000003, 0.356518980000004, 0.437577099999999,
0.392784859999992, 0.388830530000007, 0.483353989999998, 0.483400920000008,
0.476108939999989, 0.578384330000006, 0.500293639999995, 0.471659299999999,
0.400334810000004, 0.431158179999997, 0.402490870000008, 0.582227500000002,
0.520586399999999, 0.578230499999989, 0.543358060000003, 0.565377730000009,
0.495379709999995, 0.535594669999995, 0.506619610000001, 0.70266092,
0.636560770000003, 0.686429410000002, 0.680400980000002, 0.648521680000002,
0.76107786, 0.65525808999999, 0.712458519999998, 0.879347270000011,
0.889241409999997, 0.690819939999997, 0.657271179999995, 0.617595570000006,
0.697132490000001, 0.684628829999994, 0.703827010000012, 0.904382469999987,
0.713025079999994, 0.730583780000018, 1.01506638000001, 0.772495089999978,
0.775247390000004, 0.744901410000011, 0.644528049999991, 0.782681260000004,
0.962640410000006, 0.848824469999983, 0.862363740000006, 0.980142900000004,
1.36650416000001, 1.15738812000001, 1.33109948999999, 1.38512209999999,
1.07988722000002, 1.02922056, 0.96693934999999, 1.02835073, 1.06945333000002,
1.17483343999999, 1.01644379999999, 1.20463173000002, 0.99792217000001,
0.928412439999988, 0.913252989999989, 0.903960150000017, 0.957359849999989,
0.741917489999992, 0.783241220000008, 0.962800930000014, 0.843628769999981,
0.985671910000008, 1.22737043000001, 1.22739227, 1.19125137999998,
1.20338412000001, 0.943829340000008, 0.818064440000001, 0.80703183,
0.842162129999991, 0.860623090000018, 0.924660799999998, 0.924513059999981,
1.09749315000002, 0.933643910000001, 0.895296619999982, 0.937704209999993,
0.783229290000008, 0.892262479999999, 0.891166319999996, 0.812834510000016,
0.931692879999986, 0.958957600000019, 1.02655130999997, 1.06277286000002,
1.15143319999999, 0.923887790000009, 0.986522589999993, 0.745905969999995,
0.769035410000015, 0.84084039999999, 0.854123420000008, 0.747486069999979,
0.678888730000011, 0.809119159999995, 0.905038810000008, 0.80515822000001,
0.750871509999996, 0.696602689999992, 0.695129089999995, 0.722989030000008,
0.844726350000002, 0.801606469999996, 0.780852979999992, 0.754080390000013,
0.664239280000004, 0.600094780000006, 0.762242889999982, 0.737768979999998,
0.71259163000002, 0.676029519999986, 0.689090670000013, 0.720211059999997,
0.607597150000004, 0.507481709999979, 0.493742710000021, 0.371735089999987,
0.425050169999992, 0.314955600000019, 0.280138889999989, 0.249320890000007,
0.245511300000004, 0.222276069999992, 0.287098810000003, 0.31649471999998,
0.383321370000004, 0.32320642000002, 0.284330920000002, 0.253714949999988,
0.252353169999992, 0.216143369999998, 0.235184800000013, 0.174737190000002,
0.152573869999998, 0.192207160000009, 0.18242656999999, 0.116960890000001,
0.145042929999988, 0.0815519399999971, 0.0688195700000165, 0.0670563099999981,
0.0512423600000034, 0.0398953099999915, 0.0322520800000063, 0.040736939999988,
0.0367371700000092, 0.0400694500000043, 0.0292775899999924, 0.0300541299999963,
0.026211399999994, 0.0334384399999976, 0.0295196900000008, 0.0226773300000218,
0.0257848800000033, 0.0307718999999906, 0.0224783299999842, 0.0323548500000186,
0.0282327200000054, 0.0232346899999811, 0.0231430500000158, 0.0250010599999939,
0.0275498100000107, 0.0193078699999774, 0.0172700500000076, 0.0142707999999914,
0.013895400000024, 0.014191889999978, 0.0133223600000179, 0.00866569999999456,
0.0195576899999992, 0.0162485299999844, 0.0198921900000073, 0.0284403200000156,
0.0345834499999853, 0.0335096900000167, 0.0343464999999981, 0.0418096899999796,
0.0428487500000188, -0.0681494899999961, 0.0271059499999922,
0.0291717899999924, 0.00430575999999405)


désolé pour ce message à rallonge...
merci


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