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authorgebele <gebele@in-silico.ch>2018-07-16 14:54:59 +0000
committergebele <gebele@in-silico.ch>2018-07-16 14:54:59 +0000
commitc93afb84a46af1500679cc5b314b0aeffcd7e6e9 (patch)
tree0fbd3a27a6ccc6c0b8b2157ae799d6579995209c
parent44d9ceb30f6f8649f2d6fc179a925302f14d8a05 (diff)
refined mazza rules
-rw-r--r--application.rb2
-rw-r--r--views/batch.haml8
2 files changed, 5 insertions, 5 deletions
diff --git a/application.rb b/application.rb
index fdb7086..fbebc66 100644
--- a/application.rb
+++ b/application.rb
@@ -478,7 +478,7 @@ post '/predict/?' do
end
predictions = {}
predictions["mazzatorta"] = output["mazzatorta"]
- #predictions["compounds"] = @compounds
+ predictions["compounds"] = @compounds
# write csv
t[:csv] = csv
# write predictions
diff --git a/views/batch.haml b/views/batch.haml
index 165b64b..76338bc 100644
--- a/views/batch.haml
+++ b/views/batch.haml
@@ -29,7 +29,7 @@
var aClient = new HttpClient();
aClient.get(uri, function(res) {
var response = JSON.parse(res);
- if (model_id == "Cramer"){
+ if (model_id =~ /Cramer|Mazzatorta/){
$("img.circle").show();
}else{
progress(response['percent'],id);
@@ -100,7 +100,7 @@
- @models.each_with_index do |model,idx|
- - m = Model::Validation.find model unless model == "Cramer"
+ - m = Model::Validation.find model unless model =~ /Cramer|Mazzatorta/
- task = @tasks[idx].id
#result.panel{:id=>idx}
%div.row
@@ -118,9 +118,9 @@
%a.btn.btn-default.btn-xs.disabled{:id => "downbutton_#{idx}", :href=>"#{to("/predict/csv/#{task}/#{model}/#{@filename}")}", :title=>"download", :style=>"font-size:small;"}
%span.glyphicon.glyphicon-download-alt
CSV
- - if model == "Cramer"
+ - if model =~ /Cramer|Mazzatorta/
%img.h2{:src=>"/images/wait30trans.gif", :id=>"circle", :class=>"circle", :alt=>"wait", :style=>"display:none;"}
- - if model != "Cramer"
+ - else
%div{:id=>"progress_#{idx}", :style=>"width:100%;height:3px;position:relative;background-color:#ccc;"}
%div{:id=>"bar_#{idx}", :style=>"background-color: #4CAF50;width:10px;height:3px;position:absolute;"}
- # increase interval timer for large datasets