bug fix and layout fix

src/api/templates/dashboard/graphs/chart.html

@@ -32,17 +32,19 @@
         <div class="board">
     {% endif %}
             {% for config in info %}
-                {% if info|length > 1%}
+                {% if info|length > 1 %}
-                    <div class="border border-round">
+                    <div class="border-round">
                 {% else %}
                         <div>
                 {% endif %}
                     <div class="title bold" align="center">{{config.title}}</div>
                     <!-- <canvas id="{{chart_id_|safe}}"></canvas> -->
                     <div id="chart_{{loop.index|int}}"></div>
+                    {% if config.info %}
                         <div id="descr_{{loop.index|int}}" class="border-top" align="center">
                             <br>{{config.info}}
                         </div>
+                    {% endif %}
                     <script>
                         render_chart({{loop.index|int}},{{config|tojson}})
                     </script>

src/models/basic.py

@@ -0,0 +1,63 @@
+""""
+    This class defines the basic structure for a model, models can be either statistical or machine learning
+    and will be tightly coupled with the rendering engines (matplotlib or chartjs)
+""""
+
+class model :
+    def __init__(**args):
+        self.data = args['data']
+        self.node = args['node']
+        self.months = {1:"Jan",2:"Feb",3:"Mar",4:"Apr",5:"May",6:"Jun",7:"Jul",8:"Aug",9:"Sep",10:"Oct",11:"Nov",12:"Dec"}
+        self.cache = {}
+    def can_do(self):
+        return False
+    def format_date(self,row):
+        m = {1:"Jan",2:"Feb",3:"Mar",4:"Apr",5:"May",6:"Jun",7:"Jul",8:"Aug",9:"Sep",10:"Oct",11:"Nov",12:"Dec"}
+        return "-".join([m[row['month']],str(row['day']),str(row['year'])]) +" "+ " ".join([str(row['hour']),'h :',str(row['minute']),'min' ])
+    
+    def set(self,key,value):
+        self.cache[key] = value
+    def get(self,key):
+        return self.cache[key]
+class simple:
+    class app_status(model):
+        """
+        This model will perform a simple count of application status
+        The intent is to quickly inform the user if there's a crash     
+        """
+        def __init(self,**args):
+            model.__init__(self,**args)
+        def compute(self):
+            """
+                This function performs the actual counts associated with the status of an application 
+            """
+            df      = self.data[df.name.str.contains('other',na=False)==False]
+            x_crash = df.status.str.contains('X').sum()
+            x_idle  = df.status.str.contains('S').sum()
+            x_run   = df.shape[0] - x_crash - x_idle
+            odf = pd.DataFrame({"labels":['crash','idle','running'],"counts":[x_crash,x_idle,x_run]})
+            self.set("type","doughnut")
+            # self.set("labels",["crash","idle","running"])
+            # self.set("data",{"data":[x_crash,x_idle,x_run]})
+            self.set('data',odf)
+            if x_crash > 0 :
+                self.set("analysis"," ".join([x_crash,"applications found out of ",str(df.shape[0]),"monitored" ]))
+    class app_ranking(model):
+        """
+            This model will group the applications that are monitored and the rest of the system to guage resource consumption (CPU,RAM)
+        """      
+        def __init__(self,**args):
+            model.__init__(self,**args)    
+        def compute(self):
+            N = self.data.shape[0] - 1
+            
+            df = pd.DataFrame(self.data[self.data.name == 'other'].sum()[['cpu','mem']] ) .T
+            df = df.append(pd.DataFrame( self.data[self.data.name != 'other'].sum()[['cpu','mem']] ).T)
+            df['labels'] = ['other','monitored']
+            # other_df = pd.DataFrame(self.data[self.data.name.str.contains('other',na=False)])
+            # watch_df = pd.DataFrame(self.data[self.data.name.str.contains('other',na=False)==False])
+            # datasets = [[other_df.cpu.sum(),watch_df.cpu.sum()],[other_df.mem.sum(),watch_df.mem.sum()]]
+            self.set("data",odf)
+            self.set("type","bar")
+
+