{"action":"created","issue":{"url":"https://api.github.com/repos/Model-R/Back-end/issues/3","repository_url":"https://api.github.com/repos/Model-R/Back-end","labels_url":"https://api.github.com/repos/Model-R/Back-end/issues/3/labels{/name}","comments_url":"https://api.github.com/repos/Model-R/Back-end/issues/3/comments","events_url":"https://api.github.com/repos/Model-R/Back-end/issues/3/events","html_url":"https://github.com/Model-R/Back-end/issues/3","id":219633888,"number":3,"title":"Fazer funções de modelagem funcionarem isoladamente","user":{"login":"gmgall","id":973834,"avatar_url":"https://avatars1.githubusercontent.com/u/973834?v=3","gravatar_id":"","url":"https://api.github.com/users/gmgall","html_url":"https://github.com/gmgall","followers_url":"https://api.github.com/users/gmgall/followers","following_url":"https://api.github.com/users/gmgall/following{/other_user}","gists_url":"https://api.github.com/users/gmgall/gists{/gist_id}","starred_url":"https://api.github.com/users/gmgall/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gmgall/subscriptions","organizations_url":"https://api.github.com/users/gmgall/orgs","repos_url":"https://api.github.com/users/gmgall/repos","events_url":"https://api.github.com/users/gmgall/events{/privacy}","received_events_url":"https://api.github.com/users/gmgall/received_events","type":"User","site_admin":false},"labels":[{"id":571472814,"url":"https://api.github.com/repos/Model-R/Back-end/labels/enhancement","name":"enhancement","color":"84b6eb","default":true}],"state":"closed","locked":false,"assignee":{"login":"gmgall","id":973834,"avatar_url":"https://avatars1.githubusercontent.com/u/973834?v=3","gravatar_id":"","url":"https://api.github.com/users/gmgall","html_url":"https://github.com/gmgall","followers_url":"https://api.github.com/users/gmgall/followers","following_url":"https://api.github.com/users/gmgall/following{/other_user}","gists_url":"https://api.github.com/users/gmgall/gists{/gist_id}","starred_url":"https://api.github.com/users/gmgall/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gmgall/subscriptions","organizations_url":"https://api.github.com/users/gmgall/orgs","repos_url":"https://api.github.com/users/gmgall/repos","events_url":"https://api.github.com/users/gmgall/events{/privacy}","received_events_url":"https://api.github.com/users/gmgall/received_events","type":"User","site_admin":false},"assignees":[{"login":"gmgall","id":973834,"avatar_url":"https://avatars1.githubusercontent.com/u/973834?v=3","gravatar_id":"","url":"https://api.github.com/users/gmgall","html_url":"https://github.com/gmgall","followers_url":"https://api.github.com/users/gmgall/followers","following_url":"https://api.github.com/users/gmgall/following{/other_user}","gists_url":"https://api.github.com/users/gmgall/gists{/gist_id}","starred_url":"https://api.github.com/users/gmgall/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gmgall/subscriptions","organizations_url":"https://api.github.com/users/gmgall/orgs","repos_url":"https://api.github.com/users/gmgall/repos","events_url":"https://api.github.com/users/gmgall/events{/privacy}","received_events_url":"https://api.github.com/users/gmgall/received_events","type":"User","site_admin":false}],"milestone":null,"comments":2,"created_at":"2017-04-05T16:00:37Z","updated_at":"2017-05-08T20:05:47Z","closed_at":"2017-05-08T20:05:47Z","body":"Hoje para gerarmos os modelos de `especieX` com os algoritmos Bioclim, Domain, GLM e RF temos que fazer:\r\n\r\n```R\r\ndismo.mod('especieX',\r\n  predictors = predictors,\r\n  mask = mask,\r\n  n.back = 500,\r\n  Bioclim = T,\r\n  Domain = T,\r\n  GLM = T,\r\n  RF = T)\r\n```\r\n\r\nMinha intenção é ser possível fazer algo como:\r\n\r\n```R\r\nbioclim('especieX', ...)\r\ndomain('especieX', ...)\r\nGLM('especieX', ...)\r\nrandomForest('especieX', ...)\r\n```\r\n\r\nIsso vai ser positivo porque:\r\n\r\n* ganharemos mais uma camada de paralelismo (por algoritmo, antes tínhamos apenas por espécie)\r\n* reduziremos o trabalho que cada um dos _jobs_ submetidos aos clusters terão que fazer"},"comment":{"url":"https://api.github.com/repos/Model-R/Back-end/issues/comments/299975402","html_url":"https://github.com/Model-R/Back-end/issues/3#issuecomment-299975402","issue_url":"https://api.github.com/repos/Model-R/Back-end/issues/3","id":299975402,"user":{"login":"gmgall","id":973834,"avatar_url":"https://avatars1.githubusercontent.com/u/973834?v=3","gravatar_id":"","url":"https://api.github.com/users/gmgall","html_url":"https://github.com/gmgall","followers_url":"https://api.github.com/users/gmgall/followers","following_url":"https://api.github.com/users/gmgall/following{/other_user}","gists_url":"https://api.github.com/users/gmgall/gists{/gist_id}","starred_url":"https://api.github.com/users/gmgall/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gmgall/subscriptions","organizations_url":"https://api.github.com/users/gmgall/orgs","repos_url":"https://api.github.com/users/gmgall/repos","events_url":"https://api.github.com/users/gmgall/events{/privacy}","received_events_url":"https://api.github.com/users/gmgall/received_events","type":"User","site_admin":false},"created_at":"2017-05-08T20:05:47Z","updated_at":"2017-05-08T20:05:47Z","body":"Os commits\r\n\r\n```\r\nf677774 Isola SVM\r\n5d32478 Isola Mahalanobis\r\n53023f8 Isola SVM2\r\nf9f1fe0 Isola GLM\r\nd4b554f Isola Random Forest\r\ncd202a0 Isola maxent\r\n5aa7a72 Isola bioclim\r\n858ae18 Isola domain\r\n```\r\n\r\nimplementam as funções de modelagem separadamente. São o resultado do rebase do branch `algortimos_separados`, que será excluído.\r\n\r\nObservações:\r\n\r\n* O diretório `ENM/fct/algoritmos` contém os arquivos com as novas funções de modelagem. Como ainda temos que corrigir `createBuffer()`, `modelos.R` foi mantido em `ENM/fct/` para termos uma referência para testes.\r\n* Todas as funções agora possuem uma mesma assinatura:\r\n```R\r\ndo_ALG(especie = \"especie\",\r\n       coordinates = ocorrencias,\r\n       partitions = 3,\r\n       buffer = FALSE,\r\n       seed = 512,\r\n       predictors = variaveis_preditoras,\r\n       models.dir = \"/tmp/novo\",\r\n       project.model = F,\r\n       projections = NULL,\r\n       mask = mascara,\r\n       n.back = 500)\r\n```\r\n* O parâmetro `coordinates` recebe só as ocorrências da espécie em questão, `dismo.mod()` recebe todas as ocorrências de todas as espécies de interesse.\r\n* O parâmetro `buffer` fará buffer se definido para `mean` ou `max`. **Qualquer** outro valor fará a execução sem buffer. Isso elimina a redundância de ter um parâmetro `buffer.type` e outro `buffer` que a `dismo.mod()` possui.\r\n* Não mexi em nenhum código relacionado à projeções.\r\n* Exemplo de como usar as novas funções :arrow_forward:  [aqui](https://gist.github.com/gmgall/21d46ab4b084150a2cda512795993bfa) :arrow_backward: ."}}
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