Função get_dataframe
Com as informações dos arquivos de namelist do SCANTEC carregados, o próximo passo é ler as tabelas geradas na avaliação com o SCANTEC e transformá-las em dataframes do Pandas. Para isso, o usuário deverá utilizar a função get_dataframe do módulo scanplot. Esta função está implementada no script data_structures.py
Da mesma forma como foi feito com a função read_namelists, pode-se digitar o comando print(funcao.__doc__) ou simplesmente, help(funcao) para descobrir como a função deve ser utilizada:
Informação
Um dataframe é uma estrutura de dados tabulados.
Comando Resultado
help ( scanplot . get_dataframe )
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42 Help on function get_dataframe in module data_structures :
get_dataframe ( dataInicial , dataFinal , Stats , Exps , outDir , ** kwargs )
get_dataframe
=============
Esta função transforma a ( s ) tabela ( s ) do SCANTEC em dataframe ( s ) .
Parâmetros de entrada
---------------------
dataInicial : objeto datetime com a data inicial do experimento ;
dataFinal : objeto datetime com a data final do experimento ;
Stats : lista com os nomes das estatísticas a serem processadas ;
Exps : lista com os nomes dos experimentos ;
outDir : string com o diretório com as tabelas do SCANTEC .
Parâmetros de entrada opcionais
-------------------------------
series : valor Booleano para ler uma série temporal das tabelas do SCANTEC :
* series = False ( valor padrão ), lê as tabelas do SCANTEC geradas para a avaliação de um período ;
* series = True , lê as tabelas do SCANTEC geradas para a avaliação dos dias dentro de um período ;
tExt : string com o extensão dos nomes das tabelas do SCANTEC :
* tExt = 'scan' ( valor padrão ), considera as tabelas do SCANTEC ;
* tExt = 'scam' , considera os nomes das tabelas das versões antigas do SCANTEC .
Resultado
---------
Dicionário com o ( s ) dataframe ( s ) com a ( s ) tabela ( s ) do SCANTEC .
Uso
---
import scanplot
data_vars , data_conf = scanplot . read_namelists ( "~/SCANTEC" )
dataInicial = data_conf [ "Starting Time" ]
dataFinal = data_conf [ "Ending Time" ]
Stats = [ "ACOR" , "RMSE" , "VIES" ]
Exps = list ( data_conf [ "Experiments" ] . keys ())
outDir = data_conf [ "Output directory" ]
dTable = scanplot . get_dataframe ( dataInicial , dataFinal , Stats , Exps , outDir )
A função get_dataframe recebe uma série de parâmetros de entrada e retorna um dicionário com uma ou mais tabelas que já estarão na estrutura de dataframe do Pandas. Na célula a seguir, serão definidos os valores de entrada da função get_dataframe a partir dos dicionários data_conf e data_vars, criados anteriormente.
Observe que os parâmetros Vars e Stats são atribuídos de formas diferentes dos demais. O parâmetro Stats é uma lista que deve possuir pelo menos um elemento e ele sempre deve possuir a forma Stat = [...]. Na versão atual do SCANPLOT, o usuário pode escolher as estatísticas ACOR (correlação de anomalias), RMSE (raiz do erro quadrático médio) e VIES (viés), em qualquer ordem ou combinação entre elas.
O parâmetro Vars também é uma lista, mas é definido de forma diferente. O usuário deve observar que no dicionário data_vars, para cada índice está associada uma tupla do tipo ('VAR:LEV', 'Nome da Variável @ Nível hPa [unidade]'). Isto foi feito para facilitar ao usuário a escolha da variável, pois ao invés de se digitar o nome da variável, basta escolher pelo menos um dos índices do dicionário data_vars que deseja, da seguinte forma Vars = list(map(data_vars.get,[1,2,3,...].
Informação
Uma tupla é uma estrutura de dados imutável que pode armazenar vários elementos.
Nota
No exemplo acima, o parâmetro outDir considera o valor que consta no arquivo scantec.conf. Para uso com os arquivos de teste (veja o diretório test na raiz da instalação do SCANPLOT), considere alterar o valor deste parâmetro para que o SCANPLOT possa encontrar os arquivos de teste que estão dentro da sua cópia local do SCANPLOT:
outDir = '/algum/local/SCANPLOT/test/SCANTEC.TESTS/dataout'
Dica
Os comandos:
Vars = list ( map ( data_vars . get ,[ 11 , 12 , 13 ]))
Exps = list ( data_conf [ 'Experiments' ] . keys ())
podem ser substituídos, respectivamente, por:
Vars = [ * map ( data_vars . get ,[ 12 , 14 ])]
Exps = [ * data_conf [ "Experiments" ] . keys ()]
Com a definição dos parâmetros de entrada da função get_dataframe, a sua utilização é feita da seguinte forma:
Na chamada da função get_dataframe, o objeto dTable é um dicionário que deverá conter as tabelas escolhidas pelo usuário a partir do ajuste dos parâmetros de entrada da função. Para inspecionar o conteúdo do dicionário dTable, basta digitar no prompt:
Comando Resultado
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636 { 'ACORX126_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 0.999 0.997 1.000 0.999 0.250 0.154
1 24 0.981 0.986 0.997 0.992 0.228 0.137
2 48 0.964 0.978 0.994 0.985 0.216 0.123
3 72 0.937 0.968 0.989 0.977 0.203 0.108
4 96 0.906 0.959 0.983 0.968 0.196 0.098
5 120 0.868 0.949 0.976 0.958 0.190 0.090
6 144 0.829 0.942 0.970 0.950 0.187 0.085
7 168 0.791 0.934 0.964 0.942 0.184 0.081
8 192 0.753 0.929 0.958 0.936 0.182 0.077
9 216 0.718 0.924 0.953 0.930 0.182 0.076
10 240 0.691 0.921 0.949 0.926 0.179 0.075
11 264 0.672 0.918 0.946 0.923 0.177 0.074
12 288 0.660 0.916 0.944 0.919 0.176 0.072
13 312 0.648 0.915 0.941 0.917 0.177 0.071
14 336 0.632 0.912 0.939 0.915 0.177 0.071
15 360 0.624 0.911 0.937 0.914 0.177 0.071
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 0.071 0.997 1.000 1.000 1.000 0.991 0.997
1 0.069 0.984 0.996 0.999 1.000 0.923 0.970
2 0.064 0.964 0.990 0.997 0.998 0.888 0.943
3 0.059 0.941 0.979 0.994 0.996 0.840 0.906
4 0.053 0.917 0.965 0.988 0.993 0.787 0.860
5 0.047 0.896 0.947 0.982 0.988 0.734 0.809
6 0.042 0.878 0.928 0.974 0.984 0.683 0.758
7 0.037 0.862 0.909 0.967 0.979 0.637 0.710
8 0.033 0.849 0.890 0.960 0.974 0.595 0.668
9 0.029 0.838 0.871 0.953 0.970 0.560 0.630
10 0.027 0.827 0.857 0.947 0.966 0.534 0.597
11 0.024 0.819 0.846 0.943 0.964 0.518 0.575
12 0.022 0.812 0.840 0.940 0.962 0.502 0.554
13 0.021 0.806 0.833 0.938 0.960 0.488 0.537
14 0.019 0.800 0.825 0.934 0.958 0.476 0.525
15 0.019 0.794 0.820 0.932 0.956 0.469 0.514
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 0.998 0.984 0.995 0.997
1 0.979 0.871 0.948 0.958
2 0.955 0.806 0.897 0.908
3 0.922 0.726 0.826 0.837
4 0.882 0.629 0.733 0.743
5 0.838 0.532 0.626 0.638
6 0.795 0.444 0.520 0.534
7 0.752 0.372 0.419 0.425
8 0.717 0.302 0.322 0.324
9 0.684 0.243 0.235 0.234
10 0.654 0.200 0.168 0.163
11 0.633 0.173 0.130 0.123
12 0.613 0.158 0.104 0.100
13 0.598 0.146 0.091 0.088
14 0.588 0.129 0.067 0.073
15 0.578 0.118 0.054 0.060 ,
'ACORXENM_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 0.999 0.996 1.000 0.999 0.246 0.150
1 24 0.983 0.988 0.997 0.990 0.226 0.134
2 48 0.965 0.980 0.994 0.982 0.215 0.121
3 72 0.938 0.970 0.989 0.973 0.203 0.107
4 96 0.907 0.961 0.984 0.964 0.195 0.097
5 120 0.872 0.953 0.978 0.956 0.190 0.090
6 144 0.838 0.946 0.973 0.949 0.188 0.085
7 168 0.805 0.941 0.968 0.943 0.185 0.081
8 192 0.773 0.936 0.964 0.938 0.184 0.077
9 216 0.745 0.933 0.960 0.934 0.184 0.076
10 240 0.726 0.931 0.958 0.931 0.181 0.076
11 264 0.713 0.930 0.957 0.929 0.179 0.075
12 288 0.705 0.929 0.955 0.927 0.178 0.074
13 312 0.697 0.929 0.954 0.926 0.180 0.073
14 336 0.690 0.929 0.954 0.926 0.181 0.074
15 360 0.688 0.929 0.954 0.926 0.181 0.075
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 0.053 0.995 1.000 1.000 1.000 0.991 0.997
1 0.051 0.982 0.996 0.999 1.000 0.931 0.969
2 0.050 0.964 0.990 0.997 0.998 0.897 0.942
3 0.047 0.944 0.979 0.994 0.996 0.852 0.906
4 0.044 0.924 0.965 0.989 0.993 0.802 0.863
5 0.040 0.906 0.950 0.982 0.989 0.754 0.818
6 0.037 0.890 0.934 0.976 0.985 0.711 0.776
7 0.034 0.878 0.917 0.970 0.980 0.673 0.735
8 0.031 0.868 0.901 0.964 0.976 0.638 0.701
9 0.029 0.859 0.888 0.959 0.973 0.612 0.672
10 0.027 0.852 0.878 0.955 0.970 0.594 0.649
11 0.025 0.845 0.872 0.953 0.969 0.582 0.633
12 0.023 0.839 0.869 0.951 0.967 0.571 0.621
13 0.023 0.834 0.865 0.949 0.966 0.563 0.611
14 0.021 0.830 0.861 0.948 0.966 0.557 0.607
15 0.020 0.826 0.860 0.948 0.965 0.555 0.607
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 0.998 0.984 0.995 0.997
1 0.977 0.881 0.946 0.956
2 0.953 0.819 0.894 0.905
3 0.921 0.743 0.825 0.835
4 0.884 0.648 0.733 0.744
5 0.846 0.559 0.634 0.645
6 0.810 0.475 0.537 0.548
7 0.774 0.405 0.444 0.448
8 0.744 0.344 0.354 0.352
9 0.719 0.291 0.277 0.270
10 0.698 0.253 0.215 0.206
11 0.682 0.226 0.175 0.167
12 0.669 0.213 0.144 0.139
13 0.661 0.204 0.119 0.112
14 0.656 0.198 0.102 0.094
15 0.655 0.191 0.094 0.086 ,
'ACORT126_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 0.999 0.997 1.000 0.999 0.249 0.154
1 24 0.984 0.989 0.997 0.992 0.235 0.138
2 48 0.972 0.984 0.994 0.986 0.228 0.125
3 72 0.951 0.978 0.990 0.978 0.218 0.113
4 96 0.922 0.972 0.984 0.970 0.212 0.105
5 120 0.888 0.965 0.978 0.962 0.207 0.099
6 144 0.852 0.959 0.972 0.955 0.205 0.095
7 168 0.818 0.953 0.966 0.949 0.205 0.092
8 192 0.784 0.947 0.960 0.943 0.204 0.089
9 216 0.754 0.943 0.956 0.939 0.204 0.088
10 240 0.729 0.940 0.952 0.935 0.202 0.086
11 264 0.711 0.937 0.949 0.932 0.200 0.085
12 288 0.697 0.935 0.946 0.930 0.199 0.084
13 312 0.687 0.934 0.945 0.928 0.199 0.082
14 336 0.675 0.932 0.943 0.928 0.200 0.083
15 360 0.666 0.930 0.942 0.927 0.199 0.083
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 0.071 0.996 1.000 1.000 1.000 0.992 0.997
1 0.069 0.985 0.996 0.999 1.000 0.928 0.970
2 0.065 0.970 0.991 0.998 0.999 0.895 0.944
3 0.060 0.955 0.981 0.994 0.997 0.855 0.910
4 0.056 0.940 0.967 0.989 0.994 0.810 0.867
5 0.052 0.927 0.951 0.983 0.990 0.764 0.821
6 0.048 0.915 0.934 0.976 0.985 0.719 0.774
7 0.045 0.906 0.917 0.969 0.981 0.680 0.729
8 0.043 0.898 0.900 0.963 0.976 0.644 0.690
9 0.040 0.891 0.885 0.957 0.973 0.613 0.656
10 0.039 0.887 0.872 0.952 0.970 0.589 0.628
11 0.038 0.883 0.864 0.948 0.967 0.571 0.605
12 0.037 0.879 0.858 0.946 0.965 0.556 0.584
13 0.036 0.876 0.854 0.944 0.964 0.546 0.572
14 0.035 0.873 0.848 0.942 0.962 0.537 0.560
15 0.034 0.870 0.843 0.939 0.961 0.527 0.545
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 0.998 0.986 0.995 0.997
1 0.979 0.881 0.948 0.959
2 0.957 0.819 0.900 0.912
3 0.928 0.747 0.832 0.845
4 0.893 0.659 0.741 0.756
5 0.856 0.568 0.636 0.656
6 0.820 0.482 0.533 0.556
7 0.782 0.413 0.433 0.450
8 0.751 0.352 0.343 0.351
9 0.723 0.298 0.270 0.272
10 0.699 0.255 0.213 0.211
11 0.680 0.219 0.166 0.168
12 0.660 0.196 0.132 0.130
13 0.648 0.189 0.114 0.108
14 0.638 0.175 0.093 0.085
15 0.627 0.164 0.072 0.062 ,
'ACORTENM_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 0.999 0.996 1.000 0.999 0.246 0.150
1 24 0.986 0.990 0.997 0.990 0.232 0.135
2 48 0.972 0.985 0.994 0.983 0.226 0.124
3 72 0.950 0.980 0.990 0.975 0.216 0.111
4 96 0.922 0.974 0.984 0.967 0.211 0.103
5 120 0.891 0.967 0.979 0.960 0.206 0.098
6 144 0.860 0.963 0.974 0.954 0.204 0.094
7 168 0.831 0.958 0.970 0.950 0.204 0.092
8 192 0.804 0.955 0.966 0.946 0.204 0.089
9 216 0.780 0.952 0.963 0.943 0.205 0.087
10 240 0.762 0.950 0.962 0.941 0.203 0.086
11 264 0.750 0.949 0.960 0.939 0.202 0.085
12 288 0.743 0.948 0.959 0.938 0.201 0.085
13 312 0.735 0.948 0.958 0.938 0.201 0.085
14 336 0.728 0.948 0.958 0.938 0.204 0.086
15 360 0.727 0.947 0.958 0.938 0.204 0.087
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 0.053 0.994 1.000 1.000 1.000 0.992 0.997
1 0.051 0.984 0.996 0.999 1.000 0.935 0.969
2 0.050 0.971 0.990 0.997 0.999 0.904 0.943
3 0.049 0.958 0.980 0.994 0.996 0.865 0.909
4 0.047 0.945 0.967 0.989 0.993 0.822 0.869
5 0.045 0.935 0.953 0.983 0.990 0.781 0.827
6 0.043 0.927 0.938 0.978 0.986 0.745 0.789
7 0.042 0.920 0.924 0.972 0.982 0.714 0.752
8 0.041 0.916 0.910 0.966 0.979 0.687 0.722
9 0.040 0.913 0.899 0.962 0.976 0.666 0.697
10 0.040 0.911 0.891 0.959 0.974 0.651 0.677
11 0.040 0.909 0.886 0.957 0.972 0.639 0.660
12 0.039 0.907 0.883 0.955 0.971 0.632 0.650
13 0.039 0.906 0.879 0.954 0.970 0.625 0.642
14 0.038 0.905 0.877 0.953 0.970 0.621 0.638
15 0.038 0.904 0.876 0.953 0.970 0.623 0.639
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 0.998 0.986 0.995 0.997
1 0.978 0.891 0.947 0.957
2 0.955 0.832 0.897 0.908
3 0.926 0.761 0.830 0.841
4 0.893 0.675 0.740 0.753
5 0.861 0.589 0.641 0.659
6 0.831 0.511 0.545 0.567
7 0.800 0.449 0.457 0.472
8 0.775 0.393 0.374 0.379
9 0.755 0.348 0.308 0.305
10 0.738 0.311 0.254 0.249
11 0.725 0.281 0.209 0.207
12 0.716 0.264 0.173 0.174
13 0.709 0.258 0.151 0.148
14 0.706 0.251 0.137 0.132
15 0.706 0.253 0.129 0.119 ,
'RMSEX126_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 0.702 1.132 0.251 0.490 1.654 1.652
1 24 2.547 2.607 0.901 1.191 1.653 1.652
2 48 3.554 3.297 1.378 1.631 1.653 1.652
3 72 4.683 3.932 1.847 2.002 1.653 1.652
4 96 5.756 4.475 2.318 2.351 1.653 1.652
5 120 6.815 4.935 2.763 2.655 1.653 1.652
6 144 7.773 5.294 3.141 2.901 1.653 1.652
7 168 8.591 5.619 3.496 3.113 1.653 1.652
8 192 9.281 5.887 3.804 3.290 1.653 1.652
9 216 9.879 6.107 4.081 3.442 1.653 1.652
10 240 10.331 6.290 4.293 3.549 1.653 1.652
11 264 10.649 6.436 4.462 3.630 1.653 1.652
12 288 10.862 6.564 4.612 3.714 1.653 1.652
13 312 11.102 6.671 4.744 3.775 1.653 1.652
14 336 11.437 6.788 4.846 3.831 1.653 1.652
15 360 11.645 6.883 4.924 3.860 1.653 1.652
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 1.65 1.376 2.837 2.466 4.236 1.144 0.929
1 1.65 2.991 13.869 15.497 18.265 3.342 2.888
2 1.65 4.400 21.591 29.092 36.514 4.069 3.974
3 1.65 5.604 30.360 42.508 55.440 4.875 5.076
4 1.65 6.614 39.356 56.192 74.851 5.638 6.175
5 1.65 7.415 48.222 69.503 93.510 6.318 7.200
6 1.65 8.033 56.414 81.561 110.184 6.900 8.078
7 1.65 8.518 63.433 92.237 125.439 7.406 8.839
8 1.65 8.904 69.568 101.652 138.942 7.831 9.444
9 1.65 9.249 74.934 109.955 150.873 8.169 9.948
10 1.65 9.543 79.032 116.618 160.514 8.409 10.366
11 1.65 9.771 81.881 121.264 167.531 8.547 10.639
12 1.65 9.965 83.762 124.726 173.217 8.701 10.896
13 1.65 10.146 85.793 127.973 178.334 8.831 11.108
14 1.65 10.306 88.636 131.740 183.081 8.958 11.272
15 1.65 10.450 90.426 134.401 186.695 9.052 11.430
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 1.052 1.107 0.905 1.008
1 3.894 3.213 2.852 3.810
2 5.649 3.946 3.955 5.539
3 7.346 4.657 5.072 7.233
4 8.949 5.401 6.221 8.950
5 10.423 6.029 7.267 10.476
6 11.716 6.543 8.143 11.753
7 12.863 6.898 8.854 12.890
8 13.718 7.239 9.451 13.774
9 14.472 7.515 9.938 14.478
10 15.106 7.714 10.302 15.029
11 15.546 7.852 10.528 15.376
12 15.978 7.945 10.690 15.585
13 16.275 8.036 10.815 15.750
14 16.494 8.137 10.989 15.938
15 16.732 8.237 11.093 16.108 ,
'RMSEXENM_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 0.689 1.213 0.273 0.491 1.653 1.652
1 24 2.380 2.407 0.932 1.814 1.653 1.652
2 48 3.509 3.142 1.359 2.168 1.653 1.652
3 72 4.646 3.784 1.774 2.436 1.653 1.652
4 96 5.698 4.318 2.195 2.677 1.653 1.652
5 120 6.639 4.754 2.572 2.888 1.653 1.652
6 144 7.442 5.083 2.886 3.045 1.653 1.652
7 168 8.116 5.359 3.184 3.182 1.653 1.652
8 192 8.673 5.579 3.449 3.292 1.653 1.652
9 216 9.115 5.754 3.657 3.383 1.653 1.652
10 240 9.404 5.897 3.828 3.449 1.653 1.652
11 264 9.570 6.006 3.952 3.493 1.653 1.652
12 288 9.660 6.091 4.061 3.532 1.653 1.652
13 312 9.792 6.166 4.143 3.559 1.653 1.652
14 336 9.911 6.230 4.203 3.580 1.653 1.652
15 360 9.941 6.279 4.237 3.592 1.653 1.652
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 1.65 2.035 3.977 7.082 9.750 1.147 0.929
1 1.65 3.198 13.663 14.806 16.896 3.173 2.945
2 1.65 4.413 21.729 27.988 32.024 3.834 3.993
3 1.65 5.465 30.547 41.312 50.287 4.592 5.049
4 1.65 6.359 39.119 54.490 69.033 5.293 6.060
5 1.65 7.055 47.035 66.939 86.600 5.890 6.959
6 1.65 7.584 54.070 77.871 101.949 6.344 7.677
7 1.65 7.993 60.047 87.424 115.871 6.729 8.295
8 1.65 8.301 65.109 95.664 128.125 7.035 8.773
9 1.65 8.567 69.188 102.462 138.148 7.256 9.129
10 1.65 8.797 71.953 107.613 146.145 7.389 9.403
11 1.65 8.981 73.622 110.942 151.688 7.466 9.578
12 1.65 9.149 74.667 113.501 156.183 7.526 9.700
13 1.65 9.293 75.973 116.073 160.284 7.560 9.785
14 1.65 9.417 77.089 118.129 163.480 7.584 9.822
15 1.65 9.526 77.437 119.138 165.376 7.573 9.807
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 1.052 1.110 0.905 1.008
1 4.045 3.061 2.899 3.939
2 5.798 3.754 3.993 5.654
3 7.405 4.410 5.062 7.270
4 8.879 5.079 6.139 8.859
5 10.139 5.596 7.045 10.195
6 11.193 5.996 7.754 11.252
7 12.124 6.257 8.301 12.145
8 12.842 6.457 8.729 12.832
9 13.402 6.608 9.030 13.300
10 13.841 6.691 9.211 13.582
11 14.159 6.729 9.284 13.687
12 14.411 6.728 9.321 13.750
13 14.566 6.721 9.353 13.811
14 14.657 6.710 9.350 13.829
15 14.672 6.713 9.331 13.825 ,
'RMSET126_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 0.709 1.099 0.251 0.489 1.654 1.652
1 24 2.297 2.317 0.886 1.195 1.653 1.652
2 48 3.095 2.728 1.318 1.619 1.653 1.652
3 72 4.107 3.144 1.759 1.963 1.653 1.652
4 96 5.160 3.565 2.201 2.281 1.653 1.652
5 120 6.190 3.960 2.613 2.548 1.653 1.652
6 144 7.128 4.286 2.963 2.766 1.653 1.652
7 168 7.899 4.597 3.289 2.947 1.653 1.652
8 192 8.571 4.857 3.564 3.098 1.653 1.652
9 216 9.127 5.070 3.791 3.220 1.653 1.652
10 240 9.582 5.239 3.985 3.305 1.653 1.652
11 264 9.888 5.386 4.141 3.383 1.653 1.652
12 288 10.133 5.507 4.276 3.449 1.653 1.652
13 312 10.364 5.582 4.362 3.492 1.653 1.652
14 336 10.682 5.663 4.415 3.514 1.653 1.652
15 360 10.956 5.762 4.462 3.542 1.653 1.652
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 1.65 1.400 2.916 2.439 4.240 1.070 0.929
1 1.65 2.846 12.999 12.947 15.005 3.245 2.876
2 1.65 3.990 20.082 24.505 29.841 3.947 3.927
3 1.65 4.903 28.319 36.811 46.664 4.628 4.976
4 1.65 5.638 37.064 49.981 64.532 5.281 6.020
5 1.65 6.230 45.518 62.718 81.852 5.886 6.982
6 1.65 6.712 53.379 74.292 97.503 6.409 7.831
7 1.65 7.073 59.912 84.565 111.948 6.850 8.575
8 1.65 7.357 65.680 93.551 124.813 7.229 9.172
9 1.65 7.593 70.564 101.017 135.175 7.518 9.653
10 1.65 7.756 74.406 106.842 143.371 7.749 10.025
11 1.65 7.881 77.102 111.415 150.087 7.910 10.319
12 1.65 8.019 79.028 114.640 155.234 8.037 10.573
13 1.65 8.118 80.936 117.197 159.027 8.148 10.732
14 1.65 8.195 83.679 120.371 162.481 8.262 10.912
15 1.65 8.293 85.905 123.195 165.450 8.396 11.128
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 1.051 1.049 0.905 1.007
1 3.845 3.088 2.831 3.756
2 5.477 3.806 3.905 5.431
3 7.063 4.467 4.996 7.073
4 8.549 5.160 6.137 8.750
5 9.887 5.770 7.185 10.244
6 11.090 6.277 8.062 11.508
7 12.184 6.646 8.792 12.657
8 13.028 6.947 9.375 13.593
9 13.716 7.216 9.794 14.243
10 14.301 7.427 10.115 14.732
11 14.732 7.605 10.400 15.127
12 15.165 7.736 10.616 15.451
13 15.406 7.778 10.742 15.626
14 15.634 7.857 10.864 15.805
15 15.881 7.929 10.987 16.006 ,
'RMSETENM_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 0.695 1.184 0.274 0.491 1.653 1.652
1 24 2.124 2.122 0.921 1.848 1.653 1.652
2 48 3.078 2.585 1.317 2.221 1.653 1.652
3 72 4.106 3.008 1.711 2.476 1.653 1.652
4 96 5.125 3.415 2.105 2.689 1.653 1.652
5 120 6.051 3.779 2.452 2.864 1.653 1.652
6 144 6.826 4.058 2.731 2.992 1.653 1.652
7 168 7.430 4.301 2.997 3.092 1.653 1.652
8 192 7.931 4.496 3.222 3.171 1.653 1.652
9 216 8.339 4.651 3.386 3.234 1.653 1.652
10 240 8.621 4.770 3.515 3.274 1.653 1.652
11 264 8.794 4.855 3.610 3.300 1.653 1.652
12 288 8.890 4.908 3.684 3.314 1.653 1.652
13 312 9.031 4.954 3.730 3.324 1.653 1.652
14 336 9.168 4.994 3.744 3.327 1.653 1.652
15 360 9.210 5.024 3.750 3.322 1.653 1.652
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 1.65 2.056 4.049 7.086 9.773 1.074 0.929
1 1.65 3.060 12.920 12.760 17.639 3.058 2.937
2 1.65 4.022 20.344 24.080 29.467 3.720 3.957
3 1.65 4.810 28.691 36.333 45.110 4.379 4.974
4 1.65 5.437 37.075 49.078 61.990 4.989 5.938
5 1.65 5.913 44.770 61.116 77.984 5.510 6.787
6 1.65 6.271 51.464 71.507 91.820 5.897 7.469
7 1.65 6.517 56.781 80.400 104.543 6.213 8.066
8 1.65 6.682 61.257 87.847 115.442 6.457 8.507
9 1.65 6.786 64.878 93.729 123.759 6.639 8.840
10 1.65 6.864 67.403 98.075 130.035 6.748 9.090
11 1.65 6.932 69.072 101.179 134.588 6.827 9.281
12 1.65 6.996 70.069 103.339 138.112 6.859 9.382
13 1.65 7.017 71.393 105.361 141.083 6.893 9.456
14 1.65 7.041 72.598 106.875 142.908 6.911 9.495
15 1.65 7.068 73.002 107.607 143.768 6.883 9.466
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 1.051 1.051 0.905 1.007
1 3.998 2.935 2.880 3.879
2 5.646 3.621 3.949 5.562
3 7.161 4.254 5.000 7.158
4 8.530 4.886 6.074 8.721
5 9.667 5.399 6.994 10.026
6 10.627 5.785 7.706 11.062
7 11.495 6.029 8.237 11.942
8 12.155 6.215 8.641 12.639
9 12.648 6.348 8.899 13.083
10 13.039 6.438 9.055 13.328
11 13.319 6.497 9.162 13.472
12 13.508 6.509 9.223 13.553
13 13.636 6.491 9.233 13.595
14 13.692 6.488 9.221 13.594
15 13.690 6.462 9.202 13.595 ,
'VIESX126_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 - 0.195 - 0.091 0.037 0.237 1.653 1.652
1 24 0.055 - 1.141 - 0.236 0.315 1.653 1.652
2 48 - 0.065 - 1.530 - 0.467 0.300 1.653 1.652
3 72 - 0.110 - 1.801 - 0.654 0.250 1.653 1.652
4 96 - 0.127 - 2.009 - 0.833 0.164 1.653 1.652
5 120 - 0.135 - 2.180 - 1.008 0.080 1.653 1.652
6 144 - 0.136 - 2.321 - 1.180 0.010 1.653 1.652
7 168 - 0.118 - 2.442 - 1.343 - 0.055 1.653 1.652
8 192 - 0.085 - 2.556 - 1.497 - 0.133 1.653 1.652
9 216 - 0.030 - 2.666 - 1.629 - 0.201 1.653 1.652
10 240 0.026 - 2.771 - 1.748 - 0.254 1.653 1.652
11 264 0.089 - 2.868 - 1.842 - 0.300 1.653 1.652
12 288 0.128 - 2.951 - 1.913 - 0.337 1.653 1.652
13 312 0.146 - 3.023 - 1.965 - 0.362 1.653 1.652
14 336 0.152 - 3.078 - 2.012 - 0.364 1.653 1.652
15 360 0.184 - 3.139 - 2.051 - 0.362 1.653 1.652
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 1.65 - 0.039 0.002 1.480 3.245 0.002 - 0.006
1 1.65 - 0.157 - 2.687 - 9.471 - 10.008 - 0.000 - 0.034
2 1.65 - 0.256 - 5.216 - 17.497 - 20.679 - 0.085 - 0.125
3 1.65 - 0.368 - 6.637 - 23.107 - 28.947 - 0.172 - 0.133
4 1.65 - 0.465 - 7.565 - 27.485 - 36.440 - 0.252 - 0.157
5 1.65 - 0.564 - 8.276 - 31.297 - 43.281 - 0.292 - 0.081
6 1.65 - 0.651 - 8.814 - 34.679 - 49.465 - 0.320 - 0.013
7 1.65 - 0.741 - 9.155 - 37.503 - 55.084 - 0.346 0.071
8 1.65 - 0.831 - 9.326 - 39.852 - 60.236 - 0.368 0.173
9 1.65 - 0.920 - 9.327 - 41.767 - 64.698 - 0.377 0.255
10 1.65 - 1.002 - 9.327 - 43.522 - 68.554 - 0.362 0.349
11 1.65 - 1.077 - 9.269 - 44.974 - 71.604 - 0.368 0.448
12 1.65 - 1.152 - 9.340 - 46.239 - 74.142 - 0.364 0.511
13 1.65 - 1.223 - 9.507 - 47.371 - 76.162 - 0.353 0.594
14 1.65 - 1.294 - 9.706 - 48.408 - 77.750 - 0.327 0.640
15 1.65 - 1.361 - 9.733 - 49.137 - 78.807 - 0.304 0.683
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 - 0.071 0.006 0.002 0.010
1 - 0.464 - 0.068 - 0.001 0.276
2 - 0.673 0.027 0.075 0.233
3 - 0.738 - 0.018 0.028 0.187
4 - 0.769 0.056 0.076 0.183
5 - 0.722 0.051 0.040 0.166
6 - 0.643 0.056 0.042 0.159
7 - 0.525 0.007 0.028 0.203
8 - 0.401 0.054 0.056 0.194
9 - 0.278 0.022 0.056 0.202
10 - 0.121 0.015 0.047 0.179
11 0.038 0.019 0.066 0.179
12 0.174 0.008 0.066 0.201
13 0.305 0.002 0.060 0.204
14 0.401 - 0.015 0.046 0.235
15 0.492 0.006 0.058 0.221 ,
'VIESXENM_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 - 0.179 0.049 0.061 0.240 1.653 1.652
1 24 0.027 - 0.988 - 0.093 1.260 1.653 1.652
2 48 - 0.051 - 1.423 - 0.265 1.268 1.653 1.652
3 72 - 0.138 - 1.714 - 0.406 1.173 1.653 1.652
4 96 - 0.172 - 1.919 - 0.559 1.038 1.653 1.652
5 120 - 0.196 - 2.089 - 0.721 0.906 1.653 1.652
6 144 - 0.206 - 2.233 - 0.894 0.784 1.653 1.652
7 168 - 0.186 - 2.358 - 1.066 0.677 1.653 1.652
8 192 - 0.144 - 2.477 - 1.231 0.576 1.653 1.652
9 216 - 0.086 - 2.588 - 1.378 0.482 1.653 1.652
10 240 - 0.024 - 2.693 - 1.510 0.400 1.653 1.652
11 264 0.028 - 2.792 - 1.616 0.330 1.653 1.652
12 288 0.061 - 2.883 - 1.697 0.276 1.653 1.652
13 312 0.083 - 2.962 - 1.760 0.227 1.653 1.652
14 336 0.101 - 3.029 - 1.813 0.193 1.653 1.652
15 360 0.120 - 3.086 - 1.855 0.160 1.653 1.652
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 1.65 1.074 0.849 3.638 6.290 0.002 - 0.006
1 1.65 0.600 - 2.136 - 7.545 4.022 - 0.138 0.121
2 1.65 0.513 - 4.637 - 14.992 - 5.526 - 0.060 - 0.034
3 1.65 0.391 - 6.447 - 20.536 - 13.806 - 0.154 - 0.069
4 1.65 0.260 - 7.477 - 24.640 - 21.317 - 0.200 - 0.109
5 1.65 0.122 - 8.278 - 28.294 - 28.482 - 0.248 - 0.022
6 1.65 - 0.007 - 8.903 - 31.687 - 35.291 - 0.259 0.041
7 1.65 - 0.142 - 9.253 - 34.560 - 41.432 - 0.296 0.116
8 1.65 - 0.280 - 9.389 - 37.023 - 46.980 - 0.318 0.208
9 1.65 - 0.415 - 9.372 - 39.076 - 51.807 - 0.332 0.318
10 1.65 - 0.542 - 9.326 - 40.900 - 56.087 - 0.310 0.417
11 1.65 - 0.659 - 9.366 - 42.557 - 59.651 - 0.310 0.528
12 1.65 - 0.771 - 9.507 - 44.043 - 62.602 - 0.307 0.597
13 1.65 - 0.876 - 9.691 - 45.333 - 65.027 - 0.298 0.679
14 1.65 - 0.974 - 9.859 - 46.461 - 67.032 - 0.266 0.751
15 1.65 - 1.062 - 9.981 - 47.366 - 68.636 - 0.237 0.816
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 - 0.071 0.005 0.002 0.010
1 - 0.434 - 0.031 0.016 0.252
2 - 0.754 - 0.036 0.103 0.199
3 - 0.866 - 0.048 0.037 0.110
4 - 0.916 0.055 0.093 0.192
5 - 0.884 0.055 0.086 0.168
6 - 0.828 0.043 0.056 0.124
7 - 0.720 - 0.010 0.028 0.168
8 - 0.565 0.067 0.082 0.159
9 - 0.424 0.030 0.070 0.185
10 - 0.259 0.012 0.037 0.152
11 - 0.086 0.010 0.057 0.153
12 0.068 0.016 0.083 0.198
13 0.222 0.009 0.069 0.196
14 0.356 - 0.013 0.050 0.208
15 0.483 - 0.003 0.065 0.209 ,
'VIEST126_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 - 0.219 - 0.073 0.037 0.236 1.653 1.652
1 24 0.012 - 0.848 - 0.161 0.404 1.653 1.652
2 48 - 0.076 - 1.032 - 0.326 0.488 1.653 1.652
3 72 - 0.110 - 1.151 - 0.472 0.515 1.653 1.652
4 96 - 0.137 - 1.248 - 0.607 0.498 1.653 1.652
5 120 - 0.160 - 1.338 - 0.739 0.461 1.653 1.652
6 144 - 0.171 - 1.420 - 0.865 0.421 1.653 1.652
7 168 - 0.173 - 1.491 - 0.980 0.377 1.653 1.652
8 192 - 0.175 - 1.559 - 1.089 0.322 1.653 1.652
9 216 - 0.162 - 1.632 - 1.193 0.273 1.653 1.652
10 240 - 0.135 - 1.713 - 1.291 0.243 1.653 1.652
11 264 - 0.111 - 1.783 - 1.370 0.219 1.653 1.652
12 288 - 0.113 - 1.838 - 1.426 0.181 1.653 1.652
13 312 - 0.115 - 1.898 - 1.466 0.152 1.653 1.652
14 336 - 0.145 - 1.950 - 1.486 0.129 1.653 1.652
15 360 - 0.159 - 1.996 - 1.493 0.110 1.653 1.652
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 1.65 - 0.036 - 0.056 1.511 3.276 - 0.014 - 0.006
1 1.65 - 0.074 - 0.065 - 5.504 - 4.459 0.047 0.032
2 1.65 - 0.058 - 0.998 - 10.493 - 10.433 - 0.020 0.009
3 1.65 - 0.019 - 1.493 - 14.068 - 15.362 - 0.074 0.048
4 1.65 0.015 - 1.906 - 16.984 - 20.035 - 0.101 0.058
5 1.65 0.032 - 2.313 - 19.653 - 24.613 - 0.092 0.140
6 1.65 0.035 - 2.649 - 22.087 - 28.868 - 0.070 0.216
7 1.65 0.015 - 2.908 - 24.142 - 32.688 - 0.070 0.297
8 1.65 - 0.012 - 3.137 - 25.943 - 36.393 - 0.063 0.396
9 1.65 - 0.039 - 3.240 - 27.500 - 39.787 - 0.070 0.473
10 1.65 - 0.068 - 3.326 - 29.060 - 42.804 - 0.057 0.541
11 1.65 - 0.099 - 3.426 - 30.450 - 45.271 - 0.048 0.617
12 1.65 - 0.136 - 3.636 - 31.567 - 47.391 - 0.028 0.681
13 1.65 - 0.178 - 3.904 - 32.560 - 49.143 - 0.008 0.764
14 1.65 - 0.221 - 4.383 - 33.580 - 50.619 0.035 0.819
15 1.65 - 0.258 - 4.685 - 34.259 - 51.622 0.039 0.870
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 - 0.071 0.010 0.002 0.010
1 - 0.336 - 0.011 0.010 0.220
2 - 0.465 - 0.009 0.055 0.222
3 - 0.495 - 0.011 0.062 0.189
4 - 0.515 0.030 0.053 0.160
5 - 0.489 0.033 0.061 0.158
6 - 0.462 0.012 0.032 0.122
7 - 0.408 0.002 0.028 0.125
8 - 0.327 - 0.010 0.027 0.160
9 - 0.229 0.001 0.040 0.157
10 - 0.144 - 0.022 0.026 0.146
11 - 0.031 - 0.021 0.039 0.165
12 0.069 - 0.016 0.043 0.177
13 0.192 - 0.027 0.052 0.181
14 0.301 - 0.051 0.040 0.210
15 0.386 - 0.021 0.049 0.205 ,
'VIESTENM_20200601002020081500T.scan' : % Previsao psnm : 000 temp : 850 temp : 500 temp : 250 umes : 925 umes : 850 \
0 0 - 0.203 0.067 0.061 0.241 1.653 1.652
1 24 - 0.015 - 0.731 - 0.029 1.327 1.653 1.652
2 48 - 0.065 - 0.939 - 0.133 1.423 1.653 1.652
3 72 - 0.140 - 1.064 - 0.229 1.402 1.653 1.652
4 96 - 0.178 - 1.153 - 0.333 1.331 1.653 1.652
5 120 - 0.213 - 1.238 - 0.452 1.246 1.653 1.652
6 144 - 0.240 - 1.318 - 0.584 1.160 1.653 1.652
7 168 - 0.236 - 1.391 - 0.715 1.081 1.653 1.652
8 192 - 0.220 - 1.467 - 0.845 1.006 1.653 1.652
9 216 - 0.189 - 1.546 - 0.969 0.936 1.653 1.652
10 240 - 0.160 - 1.620 - 1.080 0.874 1.653 1.652
11 264 - 0.138 - 1.691 - 1.166 0.819 1.653 1.652
12 288 - 0.135 - 1.756 - 1.232 0.767 1.653 1.652
13 312 - 0.136 - 1.817 - 1.275 0.723 1.653 1.652
14 336 - 0.147 - 1.869 - 1.300 0.683 1.653 1.652
15 360 - 0.159 - 1.913 - 1.315 0.649 1.653 1.652
umes : 500 agpl : 925 zgeo : 850 zgeo : 500 zgeo : 250 uvel : 850 uvel : 500 \
0 1.65 1.081 0.785 3.665 6.329 - 0.013 - 0.006
1 1.65 0.714 0.359 - 3.857 9.071 - 0.066 0.175
2 1.65 0.730 - 0.497 - 8.195 4.194 0.009 0.093
3 1.65 0.746 - 1.317 - 11.556 - 0.623 - 0.071 0.096
4 1.65 0.741 - 1.771 - 14.058 - 5.228 - 0.054 0.092
5 1.65 0.717 - 2.222 - 16.472 - 10.071 - 0.052 0.189
6 1.65 0.686 - 2.663 - 18.947 - 14.970 - 0.005 0.259
7 1.65 0.631 - 2.894 - 21.040 - 19.390 - 0.013 0.336
8 1.65 0.560 - 3.015 - 22.958 - 23.591 - 0.032 0.404
9 1.65 0.493 - 3.038 - 24.688 - 27.458 - 0.054 0.504
10 1.65 0.424 - 3.098 - 26.309 - 30.939 - 0.030 0.581
11 1.65 0.355 - 3.221 - 27.766 - 33.828 - 0.022 0.681
12 1.65 0.289 - 3.452 - 29.051 - 36.285 - 0.006 0.750
13 1.65 0.218 - 3.727 - 30.119 - 38.202 0.009 0.819
14 1.65 0.146 - 4.043 - 31.009 - 39.696 0.047 0.884
15 1.65 0.080 - 4.331 - 31.753 - 40.899 0.075 0.942
uvel : 250 vvel : 850 vvel : 500 vvel : 250
0 - 0.071 0.010 0.002 0.010
1 - 0.338 0.017 0.021 0.196
2 - 0.575 - 0.053 0.079 0.186
3 - 0.645 - 0.044 0.072 0.135
4 - 0.680 0.034 0.077 0.168
5 - 0.650 0.041 0.113 0.157
6 - 0.629 - 0.004 0.057 0.091
7 - 0.569 - 0.008 0.036 0.102
8 - 0.455 0.003 0.047 0.157
9 - 0.341 0.006 0.056 0.151
10 - 0.227 - 0.029 0.032 0.121
11 - 0.091 - 0.029 0.044 0.148
12 0.028 - 0.013 0.067 0.178
13 0.147 - 0.026 0.061 0.184
14 0.252 - 0.051 0.042 0.191
15 0.352 - 0.036 0.055 0.208 }
No dicionário dTable, observe que foram carregadas as tabelas referente às estatísticas escolhidas (VIES, RMSE e ACOR). Para visualizar o dataframe da tabela, basta passar o nome da tabela como argumento do dicionário dTable, como em dTable['NOME_TABELA']. Veja o exemplo a seguir: