Bump to version 0.1.1, edit docs (#50)

* Bump to version 0.1.1, edit docs

* Update frontend

- New KPI display formats
- Display version number in navbar
- Navbar: "Developer" links open in new tab

dighosp-des/dighosp_des/api.py

@@ -17,9 +17,9 @@
 from pymongo import MongoClient
 from rq import Queue
 
-from .conf import MONGO_CLIENT_ARGS, APP_VERSION
+from .conf import APP_VERSION, MONGO_CLIENT_ARGS
 from .config import Config
-from .kpis import lab_tats_fig, utilisation_fig, wips_fig
+from .kpis import lab_tats_fig, lab_tats_table, utilisation_fig, utilisation_table, wips_fig
 from .model import Model
 from .redis_worker import RedisSingleton
 
@@ -209,10 +209,12 @@ def save_dash_objs(job_id: ObjectIdStr):
     data = [get_result(job_id, idx) for idx in range(n)]
     kpi_objs = {
         'utilisation': utilisation_fig(data),
+        'utilisation_table': utilisation_table(data),
         'wip': wips_fig(data, wip='Total WIP'),
-        'tat': lab_tats_fig(data)
+        'tat': lab_tats_fig(data),
+        'tat_table': lab_tats_table(data)
     }
-    
+
     with MongoClient(**MONGO_CLIENT_ARGS) as client:
         coll = client['sim']['sim_jobs']
         obj = coll.find_one({'_id': ObjectId(job_id)})
@@ -221,18 +223,19 @@ def save_dash_objs(job_id: ObjectIdStr):
                 status_code=status.HTTP_404_NOT_FOUND,
                 detail=f"No simulation job with ObjectId {job_id}."
             )
-        
+
         output_bytes = orjson.dumps(kpi_objs)
 
         fs = GridFS(client['sim'])
         obj_id = fs.put(output_bytes)
-        
+
         coll.find_one_and_update(
             filter={'_id': ObjectId(job_id)},
             update={'$set': {'results_kpi_obj_id': str(obj_id)}}
         )
     return obj_id
 
+
 @app.get(
     '/jobs/{job_id}/results/dash_objs',
     summary='Get Plotly Dash objects'
@@ -251,11 +254,12 @@ def get_dash_objs(job_id: ObjectIdStr):
                 status_code=status.HTTP_404_NOT_FOUND,
                 detail=f"No simulation job with ObjectId {job_id}."
             )
-        
+
         fs = GridFS(client['sim'])
         obj_id = ObjectId(obj['results_kpi_obj_id'])
         return json.load(fs.get(obj_id))
 
+
 @app.get(
     '/jobs',
     summary='List jobs'

dighosp-des/dighosp_des/kpis.py

@@ -60,6 +60,18 @@ def utilisation_fig(data):
     fig.update_layout(title='Resource utilisation')
     return json.loads(fig.to_json())
 
+def utilisation_table(data):
+    """Create a table of mean resource utilisation by resource."""
+    res_names = list(data[0]['resources']['n_claimed'].keys())
+    res_means = [
+        np.mean([mean_claimed(dd, res)/mean_available(dd, res) for dd in data])
+        for res in res_names
+    ]
+    return {
+        'Resource': res_names,
+        'Utilisation': [f'{x:.3%}' for x in res_means]
+    }
+
 
 def wip_df(data, wip):
     """Get the hourly means for a given WIP counter, for a single simulation replication."""
@@ -143,3 +155,19 @@ def lab_tats_fig(data):
     fig.update_xaxes(title='Days')
     fig.update_yaxes(title='Probability')
     return json.loads(fig.to_json())
+
+
+def lab_tats_table(data):
+    """Create a table of lab turnaround times, showing the percentage of specimens completed within
+    7, 10, 14, or 21 days."""
+    lab_tats = [[
+        (x['qc_end']-x['reception_start'])/24.0
+        for x in data[n]['specimen_data'].values()
+        if 'reporting_end' in x
+    ] for n in range(len(data))]
+    lab_tats = np.array(list(chain(*lab_tats)))
+    days = [7, 10, 14, 21]
+    return {
+        'Days': days,
+        'Specimens completed': [f'{np.mean(lab_tats < x):.3%}' for x in days]
+    }

dighosp-des/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "dighosp-des"
-version = "0.1.1a0"
+version = "0.1.1"
 description = ""
 authors = ["Yin-Chi Chan <ycc39@cam.ac.uk>"]
 readme = "README.md"

dighosp-docs/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "dighosp-docs"
-version = "0.1.1a0"
+version = "0.1.1"
 description = "# Internal (developer) documentation"
 authors = ["Yin-Chi Chan <ycc39@cam.ac.uk>"]
 readme = "README.md"

dighosp-docs/source/changelog.md

@@ -2,6 +2,10 @@
 
 ## 0.1
 
+### 0.1.1
+- Modify DES service to precompute KPI figure/table data for improved page loading speed
+- Add version numbers to saved KPI data
+
 ### 0.1.0
 
 - Functioning frontend (based on existing [digital-hosp-frontend](https://github.com/cam-digital-hospitals/digital-hosp-frontend))

dighosp-docs/source/roadmap.md

@@ -2,15 +2,6 @@
 
 ## 0.1
 
-### 0.1.1
-- Modify DES service to precompute KPIs for improved page loading speed
-    - Actually, a entire Plotly Figure object is saved in `dict` form
-    - [x] Run automatically when all simulation replications finished, save results in database
-    - [x] New API endpoint for fetching precomputed KPI values from database; modify frontend accordingly
-    - Keep or remove full simulation results???
-        - If kept, can recompute KPIs if changes are made (e.g. to add more KPIs to the output)
-        - [x] Add version numbers to saved KPI values
-
 ### 0.1.2
 - [ ] Containerise the DES workers
     - See: https://github.com/yinchi/container-queue

dighosp-frontend/dighosp_frontend/app.py

@@ -28,7 +28,7 @@ def app_main():
         style={'max-width': '1600px'}
     ) as ret:
         with dbc.NavbarSimple(
-            brand='Digital Hospitals Demo',
+            brand=f'Digital Hospitals Demo v{conf.APP_VERSION.base_version}',
             brand_href=dash.get_relative_path('/#'),
             color='primary',
             dark=True,
@@ -47,8 +47,10 @@ def app_main():
                         href=dash.get_relative_path(service_data['href'])
                     )
             with dbc.DropdownMenu(nav=True, in_navbar=True, label='Developer'):
-                yield dbc.DropdownMenuItem("Docs", href='/docs', external_link=True)
-                yield dbc.DropdownMenuItem("MongoDB admin", href='/mongoadmin', external_link=True)
+                yield dbc.DropdownMenuItem(
+                    "Docs", href='/docs', external_link=True, target='_blank')
+                yield dbc.DropdownMenuItem(
+                    "MongoDB admin", href='/mongoadmin', external_link=True, target='_blank')
         yield dash.page_container
     return ret
 

dighosp-frontend/dighosp_frontend/conf.py

@@ -2,7 +2,9 @@
 import os
 from pathlib import Path
 
+import toml
 from dotenv import find_dotenv, load_dotenv
+from packaging.version import Version
 
 env_get = os.environ.get
 
@@ -23,3 +25,15 @@
 if __name__ == "__main__":
     print(ASSETS_DIRNAME)
     print(ASSETS_DIRNAME.is_dir())
+
+
+# APP VERSION
+APP_VERSION = None
+try:
+    data = toml.load('/app/pyproject.toml')
+    if 'project' in data and 'version' in data['project']:
+        APP_VERSION = Version(data['project']['version'])
+    elif 'tool' in data and 'poetry' in data['tool'] and 'version' in data['tool']['poetry']:
+        APP_VERSION = Version(data['tool']['poetry']['version'])
+except Exception:
+    pass  # Keep default of None

dighosp-frontend/dighosp_frontend/pages/des_result_single.py

@@ -46,23 +46,34 @@ def layout(job_id: str):
 @composition
 def populate_card(job_id: str):
     """Generate the Card layout showing KPIs for the simulation job."""
-    fig_data = get_kpi_figs(job_id)
+    kpi_objs = get_kpi_objs(job_id)
 
     with dbc.Card(class_name='mb-3') as ret1:
         with dbc.CardBody():
-            yield dcc.Graph(figure=fig_data['tat'])
+            yield html.H3('Lab Turnaround Times')
+            yield dbc.Table.from_dataframe(
+                pd.DataFrame(kpi_objs['tat_table']),
+                striped=True, bordered=True, hover=True
+            )
+            yield dcc.Graph(figure=kpi_objs['tat'])
 
     with dbc.Card(class_name='mb-3') as ret2:
         with dbc.CardBody():
-            yield dcc.Graph(figure=fig_data['wip'])
+            yield html.H3('Work in Progress')
+            yield dcc.Graph(figure=kpi_objs['wip'])
             n = get_num_reps(job_id)
             yield html.P(f"""\
 Bands denote the lower and upper deciles (light blue) and quantiles (dark blue); the black line \
 denotes the median ({n} simulation runs).""")
 
     with dbc.Card(class_name='mb-3') as ret3:
         with dbc.CardBody():
-            yield dcc.Graph(figure=fig_data['utilisation'])
+            yield html.H3('Resource Utilisation')
+            yield dbc.Table.from_dataframe(
+                pd.DataFrame(kpi_objs['utilisation_table']),
+                striped=True, bordered=True, hover=True
+            )
+            yield dcc.Graph(figure=kpi_objs['utilisation'])
 
     return [ret1, ret2, ret3]
 
@@ -78,7 +89,7 @@ def get_num_reps(job_id: str) -> dict:
 
 
 
-def get_kpi_figs(job_id: str) -> dict:
+def get_kpi_objs(job_id: str) -> dict:
     """Get the KPI-related figure objects for a given job."""
     url = f'{DES_FASTAPI_URL}/jobs/{job_id}/results/dash_objs'
     response = requests.get(url, timeout=100)

dighosp-frontend/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "dighosp-frontend"
-version = "0.1.1a0"
+version = "0.1.1"
 description = ""
 authors = ["Yin-Chi Chan <ycc39@cam.ac.uk>"]
 readme = "README.md"
@@ -24,6 +24,7 @@ gunicorn = "^22.0.0"
 
 [tool.poetry.group.dev.dependencies]
 pylint = "^3.2.5"
+ipykernel = "^6.29.5"
 
 [build-system]
 requires = ["poetry-core"]