Initial project version
This commit is contained in:
sebastiankloth
204
store/webview/view.py
Executable file
204
store/webview/view.py
Executable file
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from flask import Flask, render_template, request, url_for
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from numbers import Number
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# from datetime import datetime
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import pandas as pd
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import json
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try:
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import altair
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_ALTAIR = True
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except ImportError:
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_ALTAIR = False
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from .. import store
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from . import settings
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def numlike(x):
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return isinstance(x, Number)
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session = store.Session()
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app = Flask(__name__)
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app.config.from_object(settings)
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app.config.from_envvar('STOREVIEW_SETTINGS', silent=True)
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if 'DB_FILE' in app.config:
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print('Setting DB_FILE:', app.config['DB_FILE'])
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store.DB_FILE = app.config['DB_FILE']
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def db_total_stats():
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session = store.Session()
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df = pd.DataFrame(
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session.execute("""
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SELECT relname AS "relation",
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pg_size_pretty(pg_total_relation_size(C.oid)) AS "total_size"
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FROM pg_class C
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LEFT JOIN pg_namespace N ON (N.oid = C.relnamespace)
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WHERE nspname NOT IN ('pg_catalog', 'information_schema')
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AND C.relkind <> 'i'
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AND nspname !~ '^pg_toast'
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AND relname !~ 'id_seq'
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ORDER BY pg_total_relation_size(C.oid) DESC
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LIMIT 20;
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""").fetchall(), columns=['tabel name', 'total size']
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)
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session.close()
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return df
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def db_user_stats():
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session = store.Session()
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df = pd.DataFrame(
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session.execute("""
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SELECT simulations.user, COUNT(DISTINCT simulations),
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pg_size_pretty(SUM(pg_column_size(data))) as "data-size",
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pg_size_pretty(SUM(pg_column_size(data)) / COUNT(DISTINCT simulations)) as "size / sim"
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FROM evaluations
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JOIN simulations
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ON (simulations.id = evaluations.simulation_id)
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GROUP BY simulations.user
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ORDER BY count DESC;
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""").fetchall(), columns=['user', '# of simulations', 'total data', 'data per simulation']
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)
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session.close()
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return df
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def db_eval_stats():
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session = store.Session()
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df = pd.DataFrame(
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session.execute("""
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SELECT observable,
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pg_size_pretty(ROUND(AVG(pg_column_size(data)), 0)) as "size-avg",
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pg_size_pretty(ROUND(SUM(pg_column_size(data)), 0)) as "size-total",
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COUNT(*), AVG(pg_column_size(data)) as "size_bytes"
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FROM evaluations
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GROUP BY observable
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ORDER BY size_bytes DESC;
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""").fetchall(), columns=['observable', 'Avg. size', 'Total size', '# of evaluations', 'size_bytes']
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).drop('size_bytes', axis=1)
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session.close()
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return df[~df['Total size'].isnull()]
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@app.route('/')
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def view_simulations():
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session = store.Session()
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simulations = store.query_simulation(
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directory='%' + request.args.get('directory', '') + '%',
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user=request.args.get('user', '') + '%',
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session=session
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).all()
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r = render_template('simulations.html', simulations=simulations)
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session.close()
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return r
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@app.route('/statistics')
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def view_statistics():
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return render_template('statistics.html', user_stats=db_user_stats(),
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total_stats=db_total_stats(), eval_stats=db_eval_stats())
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@app.route('/simulation/<int:sim_id>')
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def view_simulation(sim_id):
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session = store.Session()
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simulation = store.query_simulation(session=session).filter(store.Simulation.id == sim_id).first()
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params = simulation.string_params + simulation.float_params
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evaluations = list(session.query(store.Evaluation).filter(
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store.Evaluation.simulation_id == simulation.id).order_by('observable').values(
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'id', 'observable', 'selection'
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)
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)
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r = render_template('simulation-details.html', simulation=simulation,
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sim_params=params, evaluations=evaluations)
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session.close()
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return r
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@app.route('/evaluation/<int:id>')
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def view_evaluation(id):
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session = store.Session()
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evaluation = session.query(store.Evaluation).filter(store.Evaluation.id == id).first()
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df = evaluation.data
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if numlike(df):
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data = df
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elif df is not None:
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data_columns = list(df.columns)
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for col in ['directory', 'T', 'user', 'selection', 'system', 'ensemble']:
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if col in data_columns:
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data_columns.remove(col)
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data = df[data_columns]
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else:
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data = None
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simulation = evaluation.simulation
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sim_params = simulation.string_params + simulation.float_params
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r = render_template('evaluation-details.html', simulation=simulation, evaluation=evaluation,
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sim_params=sim_params, evaluation_params=evaluation.parameters, data=data)
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session.close()
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return r
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@app.route('/evaluation/<int:id>/data.csv')
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def get_evaluation_data(id):
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session = store.Session()
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evaluation = session.query(store.Evaluation).filter(store.Evaluation.id == id).first()
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df = evaluation.data
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if numlike(df):
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data = df
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else:
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data_columns = list(df.columns)
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for col in ['directory', 'T', 'user', 'selection', 'system', 'ensemble']:
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if col in data_columns:
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data_columns.remove(col)
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data = df[data_columns]
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session.close()
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return data.to_csv()
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@app.route('/evaluation/<int:id>/spec.json')
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def get_evaluation_plot_spec(id):
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session = store.Session()
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evaluation = session.query(store.Evaluation).filter(store.Evaluation.id == id).first()
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df = evaluation.data
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if numlike(df) or not _ALTAIR:
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return '{}'
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else:
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data_columns = list(df.columns)
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for col in ['directory', 'T', 'user', 'selection', 'system', 'ensemble']:
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if col in data_columns:
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data_columns.remove(col)
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plot_spec = {}
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x = y = None
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for col in ['time', 'radius', 'r']:
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if col in data_columns:
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ycol = data_columns[(data_columns.index(col) + 1) % 2]
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if col == 'time':
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x = altair.X(col + ':Q', scale=altair.Scale(type='log'))
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else:
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x = altair.X(col + ':Q')
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if ycol == 'msd':
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y = altair.Y(ycol + ':Q', scale=altair.Scale(type='log'))
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else:
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y = altair.Y(ycol + ':Q')
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if x is None:
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xcol, ycol = data_columns[:2]
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x = altair.X(xcol + ':Q')
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y = altair.Y(ycol + ':Q')
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ch = altair.Chart(
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url_for('get_evaluation_data', id=id),
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# data,
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width=300, height=200).mark_point().encode(
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x=x, y=y)
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plot_spec = ch.to_dict()
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plot_spec["$schema"] = "https://vega.github.io/schema/vega-lite/v1.json"
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json.codecs
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session.close()
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return json.dumps(plot_spec)
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