fix: workaround for Docker EACCESS issue

INSTALL.md

@@ -90,6 +90,12 @@ python manage.py fake_data -n <num samples>
 ## Development
 
 1. Run the images in containers:
+
+If you are running containers for the first time:
+```sh
+docker-compose up -d && docker-compose exec nodeserver sh -c "mkdir -p node_modules/.cache/ && touch node_modules/.cache/.eslintcache && chown -R node:node node_modules/.cache && chmod -R 777 node_modules/.cache/"
+``` 
+Otherwise just run:
 ```sh
 docker-compose up
 ``` 

backend/clin_overview/api/views.py

@@ -20,10 +20,9 @@ class ClinicalViewSet(viewsets.ModelViewSet):
     queryset = ClinicalData.objects.all()
 
     def retrieve(self, request, pk=None):
-
         serializer_class = ClinicalDataSerializer
         queryset = ClinicalData.objects.all()
-        patient = get_object_or_404(queryset, pk=pk)
+        patient = get_object_or_404(queryset, patient_id=pk)
         timelinerecords = TimelineRecord.objects.filter(patient=patient, event="laboratory")
         date_relative_max = timelinerecords.aggregate(Max("date_relative"))['date_relative__max']
         date_relative_min = timelinerecords.aggregate(Min("date_relative"))['date_relative__min']
@@ -69,16 +68,35 @@ def retrieve(self, request, pk=None):
                                         ],
                 }
 
+        # def add_data(data, range_min, range_max, thresholds, colors):
+        #     date_relative = []
+        #     result        = []
+        #     for item in data.iterator():
+        #         date_relative.append(item.date_relative)
+        #         result.append(item.result)
+        #     newdict = {'y': result,
+        #                'x': date_relative,
+        #                'colors': colors,
+        #                'thresholds': thresholds,
+        #               }
+        #     return newdict
+
         def add_data(data, range_min, range_max, thresholds, colors):
             date_relative = np.arange(range_min, range_max + 1)
             result        = np.empty_like(date_relative, dtype=np.float32)
             result[:]     = np.nan
+            sparse_date = []
+            sparse_result = []
             for item in data.iterator():
                 result[item.date_relative-range_min] = item.result
+                sparse_date.append(item.date_relative)
+                sparse_result.append(item.result)
             newdict = {'y': result.tolist(),
                        'x': date_relative.tolist(),
                        'colors': colors,
                        'thresholds': thresholds,
+                       'sparse_y': sparse_result,
+                       'sparse_x': sparse_date,
                       }
             return newdict
 
@@ -87,13 +105,15 @@ def add_data(data, range_min, range_max, thresholds, colors):
         leuk_dict      = add_data(leuk,        date_relative_min, date_relative_max, thresholds["leuk"], colors["leuk"])
         platelets_dict = add_data(platelets,   date_relative_min, date_relative_max, thresholds["platelets"], colors["platelets"])
         neut_dict      = add_data(neut,        date_relative_min, date_relative_max, thresholds["neut"], colors["neut"])
+        # navigator      = {'x': np.arange(date_relative_min, date_relative_max + 1).tolist()}
 
         time_series = {
             'ca125': ca125_dict,
             'hb': hb_dict,
             'leuk': leuk_dict,
             'platelets': platelets_dict,
             'neut' : neut_dict,
+            # 'navigator': navigator,
         }
 
         fresh_sample = TimelineRecord.objects.filter(patient=patient, event="fresh_sample").order_by("date_relative").values_list("date_relative", "name").distinct()
@@ -170,6 +190,7 @@ class TimelineViewSet(viewsets.ModelViewSet): # id paziente
     serializer_class = TimelineRecordSerializer
 
     def retrieve(self, request, patient_id=None):
+        print(patient_id)
         queryset = TimelineRecord.objects.filter(patient_id=patient_id, event="laboratory")
         ca125 = queryset.filter(name="ca125").order_by("date_relative")
         hb = queryset.filter(name="hb").order_by("date_relative")

oncodash-app/Dockerfile

@@ -8,22 +8,22 @@ ENTRYPOINT ["/sbin/tini", "--"]
 # Get latest npm
 RUN npm i npm@latest -g
 
-# install dependencies first, in a different location for easier app 
-# bind mounting for local development due to default /opt permissions 
+# install dependencies first, in a different location for easier app
+# bind mounting for local development due to default /opt permissions
 # we have to create the dir with root and change perms
 RUN mkdir /opt/node_app && chown node:node /opt/node_app
 WORKDIR /opt/node_app
 
 # the official node image provides an unprivileged user as a security
-# best practice but we have to manually enable it. We put it here so 
+# best practice but we have to manually enable it. We put it here so
 # npm installs dependencies as the same user who runs the app.
 # https://github.com/nodejs/docker-node/blob/master/docs/BestPractices.md#non-root-user
 USER node
 
 # copy package.json, install deps and set $PATH-var for node_modules
 COPY --chown=node:node package.json package-lock.json* ./
-RUN chmod 777 ./
-RUN npm install --no-optional --legacy-peer-deps --unsafe-perm=true --allow-root && npm cache clean --force
+
+RUN npm install --no-optional --legacy-peer-deps && npm cache clean --force
 ENV PATH /opt/node_app/node_modules/.bin:$PATH
 
 # copy in our source code last, as it changes the most
@@ -36,4 +36,4 @@ COPY --chown=node:node . .
 EXPOSE 8000
 
 # start the dev server
-CMD ["npm", "start", "--prefix", "/opt/node_app/app"]
+CMD ["npm", "start", "--prefix", "/opt/node_app/app"]

oncodash-app/src/API.js

@@ -40,21 +40,44 @@ import {Patient} from './Clinical/Patient.js';
         },
       })
     ).then(patients => {
-      return patients.map((s)=> new Patient(  s.id, 
-                                              s.age, 
-                                              s.cud_survival, 
-                                              s.cud_histology, 
-                                              s.cud_stage, 
-                                              s.cud_treatment_strategy,
-                                              s.cud_primary_therapy_outcome,
-                                              s.cud_current_treatment_phase,
-                                              s.maintenance_therapy,
-                                              s.extra_patient_info,
-                                              s.other_diagnosis,
-                                              s.cancer_in_family,
-                                              s.chronic_illness,
-                                              s.other_medication,  
-                                              s.time_series,                                       
+      // console.log(patients);
+      return patients.map((s)=> new Patient(  
+                      s.patient_id,
+                      s.cohort_code,
+                      s.chronic_illnesses_at_dg,
+                      s.chronic_illnesses_type,
+                      s.time_series,
+                      s.event_series,
+                      s.histology,
+                      s.stage,
+                      s.primary_therapy_outcome,
+                      s.survival,
+                      s.treatment_strategy,
+                      s.followup_time,
+                      s.platinum_free_interval_at_update,
+                      s.platinum_free_interval,
+                      s.days_to_progression,
+                      s.days_from_beva_maintenance_end_to_progression,
+                      s.days_to_death,
+                      s.age_at_diagnosis,
+                      s.height_at_diagnosis,
+                      s.weight_at_diagnosis,
+                      s.bmi_at_diagnosis,
+                      s.previous_cancer,
+                      s.previous_cancer_diagnosis,
+                      s.progression,
+                      s.operation1_cancelled,
+                      s.residual_tumor_pds,
+                      s.wgs_available,
+                      s.operation2_cancelled,
+                      s.residual_tumor_ids,
+                      s.debulking_surgery_ids,
+                      s.brca_mutation_status,
+                      s.hr_signature_pretreatment_wgs,
+                      s.hr_signature_per_patient,
+                      s.hrd_myriad_status,
+                      s.sequencing_available,
+                      s.paired_fresh_samples_available,
                                             ));
     });
 
@@ -70,26 +93,44 @@ import {Patient} from './Clinical/Patient.js';
         },
       })
     ).then(patient => {
+      // console.log(patient.time_series);
       return new Patient(                     
-                          patient.id, 
-                          patient.age, 
-                          patient.cud_survival, 
-                          patient.cud_histology, 
-                          patient.cud_stage, 
-                          patient.cud_treatment_strategy,
-                          patient.cud_primary_therapy_outcome,
-                          patient.cud_current_treatment_phase,
-                          patient.maintenance_therapy,
-                          patient.extra_patient_info,
-                          patient.other_diagnosis,
-                          patient.cancer_in_family,
-                          patient.chronic_illness,
-                          patient.other_medication,   
-                          JSON.parse(patient.time_series),                             
-                          JSON.parse(patient.event_series),     
-                          patient.height,
-                          patient.weight,
-                          patient.has_brca_mutation,                
+              patient.patient_id,
+              patient.cohort_code,
+              patient.chronic_illnesses_at_dg,
+              patient.chronic_illnesses_type,
+              JSON.parse(patient.time_series),
+              JSON.parse(patient.event_series),
+              patient.histology,
+              patient.stage,
+              patient.primary_therapy_outcome,
+              patient.survival,
+              patient.treatment_strategy,
+              patient.followup_time,
+              patient.platinum_free_interval_at_update,
+              patient.platinum_free_interval,
+              patient.days_to_progression,
+              patient.days_from_beva_maintenance_end_to_progression,
+              patient.days_to_death,
+              patient.age_at_diagnosis,
+              patient.height_at_diagnosis,
+              patient.weight_at_diagnosis,
+              patient.bmi_at_diagnosis,
+              patient.previous_cancer,
+              patient.previous_cancer_diagnosis,
+              patient.progression,
+              patient.operation1_cancelled,
+              patient.residual_tumor_pds,
+              patient.wgs_available,
+              patient.operation2_cancelled,
+              patient.residual_tumor_ids,
+              patient.debulking_surgery_ids,
+              patient.brca_mutation_status,
+              patient.hr_signature_pretreatment_wgs,
+              patient.hr_signature_per_patient,
+              patient.hrd_myriad_status,
+              patient.sequencing_available,
+              patient.paired_fresh_samples_available,               
                         );
     });
 

oncodash-app/src/App.js

@@ -61,7 +61,7 @@ function App() {
             try{
                 // setToken(cookie["token"]);
                 // setLogged(true);
-                console.log(cookie);
+                // console.log(cookie);
                 setWaiting(true);
                 const patients = await API.getPatients(token);
                 setPatients([...patients]);
@@ -80,7 +80,7 @@ function App() {
   const getFilteredPatients = () =>{
     let filteredPatients = [...patients];
     if(filter!=="")
-      filteredPatients = filteredPatients.filter(p=>String(p.id).includes(String(filter)) || String(p.stage).toLowerCase().includes(String(filter).toLowerCase()));
+      filteredPatients = filteredPatients.filter(p=>String(p.patient_id).includes(String(filter)) || String(p.stage).toLowerCase().includes(String(filter).toLowerCase()));
     if(statusFilter!=="")
       filteredPatients = filteredPatients.filter(p=>String(p.survival).toLowerCase()===String(statusFilter).toLowerCase()); 
     return filteredPatients;

oncodash-app/src/Clinical/Clinical.js

@@ -4,9 +4,9 @@ import alive from '../assets/alive.svg';
 import dead from '../assets/not-alive.svg';
 
 function Clinical(props) {
-    const displayOrder1 = ["id", "age", "survival", "histology", "stage", "bmi"];
-    const displayOrder2 = ["cancer_in_family", "BRCA"];
-    const displayOrder3 = ["strategy", "primary_outcome", "current_phase", "maintenance"];
+    const displayOrder1 = ["patient_id", "age_at_diagnosis", "survival", "histology", "stage", "bmi_at_diagnosis"];
+    const displayOrder2 = ["brca_mutation_status"]; // cancer_in_family deprecated
+    const displayOrder3 = ["treatment_strategy", "primary_therapy_outcome", ]; // "current_phase", "maintenance" deprecated
 
     // const location = useLocation();
 
@@ -69,7 +69,7 @@ function Clinical(props) {
                                     {displayOrder2.map(d=>
                                                         <Row key={d} className="text-center text-primary font-weight-bold">
                                                             <Col className="text-end text-dark">{d.replace('', '')}: </Col> 
-                                                            <Col className="text-start">{props.patient[d]}{props.patient[d]===true?"True": ""}{props.patient[d]===false?"False": ""}{props.patient[d]===NaN?"NaN": ""}</Col> 
+                                                            <Col className="text-start">{props.patient[d]}{props.patient[d]===true?"True": ""}{props.patient[d]===false?"False": ""}{props.patient[d]===NaN?"NaN": ""}{props.patient[d]===null?"Not Available": ""}</Col> 
                                                         </Row>)}    
                                 </div> 
                             </Col>