diff --git a/cesium_app/app_server.py b/cesium_app/app_server.py
index 6af65d9..8b4b5c4 100644
--- a/cesium_app/app_server.py
+++ b/cesium_app/app_server.py
@@ -56,8 +56,10 @@ def make_app(cfg, baselayer_handlers, baselayer_settings):
handlers = baselayer_handlers + [
(r'/project(/.*)?', ProjectHandler),
(r'/dataset(/.*)?', DatasetHandler),
- (r'/features(/.*)?', FeatureHandler),
- (r'/models(/.*)?', ModelHandler),
+ (r'/features(/[0-9]+)?', FeatureHandler),
+ (r'/features/([0-9]+)/(download)', FeatureHandler),
+ (r'/models(/[0-9]+)?', ModelHandler),
+ (r'/models/([0-9]+)/(download)', ModelHandler),
(r'/predictions(/[0-9]+)?', PredictionHandler),
(r'/predictions/([0-9]+)/(download)', PredictionHandler),
(r'/predict_raw_data', PredictRawDataHandler),
diff --git a/cesium_app/handlers/feature.py b/cesium_app/handlers/feature.py
index e2000e2..8d84511 100644
--- a/cesium_app/handlers/feature.py
+++ b/cesium_app/handlers/feature.py
@@ -13,20 +13,35 @@
from os.path import join as pjoin
import uuid
import datetime
+import pandas as pd
class FeatureHandler(BaseHandler):
@auth_or_token
- def get(self, featureset_id=None):
- if featureset_id is not None:
- featureset_info = Featureset.get_if_owned_by(featureset_id,
- self.current_user)
+ def get(self, featureset_id=None, action=None):
+ if action == 'download':
+ featureset = Featureset.get_if_owned_by(featureset_id,
+ self.current_user)
+ fset_path = featureset.file_uri
+ fset, data = featurize.load_featureset(fset_path)
+ if 'labels' in data:
+ fset['labels'] = data['labels']
+ self.set_header("Content-Type", 'text/csv; charset="utf-8"')
+ self.set_header(
+ "Content-Disposition", "attachment; "
+ f"filename=cesium_featureset_{featureset.project.name}"
+ f"_{featureset.name}_{featureset.finished}.csv")
+ self.write(fset.to_csv(index=True))
else:
- featureset_info = [f for p in self.current_user.projects
- for f in p.featuresets]
- featureset_info.sort(key=lambda f: f.created_at, reverse=True)
-
- self.success(featureset_info)
+ if featureset_id is not None:
+ featureset_info = Featureset.get_if_owned_by(featureset_id,
+ self.current_user)
+ else:
+ featureset_info = [f for p in self.current_user.projects
+ for f in p.featuresets]
+ featureset_info.sort(key=lambda f: f.created_at, reverse=True)
+
+ self.success(featureset_info)
@auth_or_token
async def _await_featurization(self, future, fset):
diff --git a/cesium_app/handlers/model.py b/cesium_app/handlers/model.py
index 5aa4fe1..c8fbfd7 100644
--- a/cesium_app/handlers/model.py
+++ b/cesium_app/handlers/model.py
@@ -13,6 +13,7 @@
import uuid
import datetime
+import sklearn
from sklearn.model_selection import GridSearchCV
import joblib
@@ -72,14 +73,28 @@ def _build_model_compute_statistics(fset_path, model_type, model_params,
class ModelHandler(BaseHandler):
@auth_or_token
- def get(self, model_id=None):
- if model_id is not None:
- model_info = Model.get_if_owned_by(model_id, self.current_user)
+ def get(self, model_id=None, action=None):
+ if action == 'download':
+ model = Model.get_if_owned_by(model_id, self.current_user)
+ model_path = model.file_uri
+ with open(model_path, 'rb') as f:
+ model_data = f.read()
+ self.set_header("Content-Type", "application/octet-stream")
+ self.set_header(
+ "Content-Disposition", "attachment; "
+ f"filename=cesium_model_{model.project.name}"
+ f"_{model.name}_{str(model.finished).replace(' ', 'T')}"
+ f"_joblib_v{joblib.__version__}"
+ f"_sklearn_v{sklearn.__version__}.pkl")
+ self.write(model_data)
else:
- model_info = [model for p in self.current_user.projects
- for model in p.models]
+ if model_id is not None:
+ model_info = Model.get_if_owned_by(model_id, self.current_user)
+ else:
+ model_info = [model for p in self.current_user.projects
+ for model in p.models]
- return self.success(model_info)
+ return self.success(model_info)
@auth_or_token
async def _await_model_statistics(self, model_stats_future, model):
diff --git a/cesium_app/handlers/prediction.py b/cesium_app/handlers/prediction.py
index 406f102..f249470 100644
--- a/cesium_app/handlers/prediction.py
+++ b/cesium_app/handlers/prediction.py
@@ -121,8 +121,8 @@ async def post(self):
@auth_or_token
def get(self, prediction_id=None, action=None):
if action == 'download':
- pred_path = Prediction.get_if_owned_by(prediction_id,
- self.current_user).file_uri
+ prediction = Prediction.get_if_owned_by(prediction_id, self.current_user)
+ pred_path = prediction.file_uri
fset, data = featurize.load_featureset(pred_path)
result = pd.DataFrame(({'label': data['labels']}
if len(data['labels']) > 0 else None),
@@ -133,8 +133,11 @@ def get(self, prediction_id=None, action=None):
result['prediction'] = data['preds']
result.index.name = 'ts_name'
self.set_header("Content-Type", 'text/csv; charset="utf-8"')
- self.set_header("Content-Disposition", "attachment; "
- "filename=cesium_prediction_results.csv")
+ self.set_header(
+ "Content-Disposition", "attachment; "
+ f"filename=cesium_prediction_results_{prediction.project.name}"
+ f"_{prediction.dataset.name}"
+ f"_{prediction.model.name}_{prediction.finished}.csv")
self.write(result.to_csv(index=True))
else:
if prediction_id is None:
diff --git a/cesium_app/tests/frontend/test_predict.py b/cesium_app/tests/frontend/test_predict.py
index 2e9e2dd..287189f 100644
--- a/cesium_app/tests/frontend/test_predict.py
+++ b/cesium_app/tests/frontend/test_predict.py
@@ -10,7 +10,12 @@
import pandas as pd
import json
import subprocess
+import glob
from cesium_app.model_util import create_token_user
+from baselayer.app.config import load_config
+
+
+cfg = load_config()
def _add_prediction(proj_id, driver):
@@ -154,10 +159,12 @@ def test_download_prediction_csv_class(driver, project, dataset, featureset,
model, prediction):
driver.get('/')
_click_download(project.id, driver)
- assert os.path.exists('/tmp/cesium_prediction_results.csv')
+ matching_downloads_paths = glob.glob(f'{cfg["paths:downloads_folder"]}/'
+ 'cesium_prediction_results*.csv')
+ assert len(matching_downloads_paths) == 1
try:
npt.assert_equal(
- np.genfromtxt('/tmp/cesium_prediction_results.csv', dtype='str'),
+ np.genfromtxt(matching_downloads_paths[0], dtype='str'),
['ts_name,label,prediction',
'0,Mira,Mira',
'1,Classical_Cepheid,Classical_Cepheid',
@@ -165,30 +172,34 @@ def test_download_prediction_csv_class(driver, project, dataset, featureset,
'3,Classical_Cepheid,Classical_Cepheid',
'4,Mira,Mira'])
finally:
- os.remove('/tmp/cesium_prediction_results.csv')
+ os.remove(matching_downloads_paths[0])
@pytest.mark.parametrize('model__type', ['LinearSGDClassifier'])
def test_download_prediction_csv_class_unlabeled(driver, project, unlabeled_prediction):
driver.get('/')
_click_download(project.id, driver)
- assert os.path.exists('/tmp/cesium_prediction_results.csv')
+ matching_downloads_paths = glob.glob(f'{cfg["paths:downloads_folder"]}/'
+ 'cesium_prediction_results*.csv')
+ assert len(matching_downloads_paths) == 1
try:
- result = np.genfromtxt('/tmp/cesium_prediction_results.csv', dtype='str')
+ result = np.genfromtxt(matching_downloads_paths[0], dtype='str')
assert result[0] == 'ts_name,prediction'
assert all([el[0].isdigit() and el[1] == ',' and el[2:] in
['Mira', 'Classical_Cepheid'] for el in result[1:]])
finally:
- os.remove('/tmp/cesium_prediction_results.csv')
+ os.remove(matching_downloads_paths[0])
def test_download_prediction_csv_class_prob(driver, project, dataset,
featureset, model, prediction):
driver.get('/')
_click_download(project.id, driver)
- assert os.path.exists('/tmp/cesium_prediction_results.csv')
+ matching_downloads_paths = glob.glob(f'{cfg["paths:downloads_folder"]}/'
+ 'cesium_prediction_results*.csv')
+ assert len(matching_downloads_paths) == 1
try:
- result = pd.read_csv('/tmp/cesium_prediction_results.csv')
+ result = pd.read_csv(matching_downloads_paths[0])
npt.assert_array_equal(result.ts_name, np.arange(5))
npt.assert_array_equal(result.label, ['Mira', 'Classical_Cepheid',
'Mira', 'Classical_Cepheid',
@@ -198,16 +209,19 @@ def test_download_prediction_csv_class_prob(driver, project, dataset,
[1, 0, 1, 0, 1])
assert (pred_probs.values >= 0.0).all()
finally:
- os.remove('/tmp/cesium_prediction_results.csv')
+ os.remove(matching_downloads_paths[0])
@pytest.mark.parametrize('featureset__name, model__type', [('regr', 'LinearRegressor')])
-def test_download_prediction_csv_regr(driver, project, dataset, featureset, model, prediction):
+def test_download_prediction_csv_regr(driver, project, dataset, featureset,
+ model, prediction):
driver.get('/')
_click_download(project.id, driver)
- assert os.path.exists('/tmp/cesium_prediction_results.csv')
+ matching_downloads_paths = glob.glob(f'{cfg["paths:downloads_folder"]}/'
+ 'cesium_prediction_results*.csv')
+ assert len(matching_downloads_paths) == 1
try:
- results = np.genfromtxt('/tmp/cesium_prediction_results.csv',
+ results = np.genfromtxt(matching_downloads_paths[0],
dtype='str', delimiter=',')
npt.assert_equal(results[0],
['ts_name', 'label', 'prediction'])
@@ -219,7 +233,7 @@ def test_download_prediction_csv_regr(driver, project, dataset, featureset, mode
[3, 2.2, 2.2],
[4, 3.1, 3.1]])
finally:
- os.remove('/tmp/cesium_prediction_results.csv')
+ os.remove(matching_downloads_paths[0])
def test_predict_specific_ts_name(driver, project, dataset, featureset, model):
diff --git a/static/css/base.css b/static/css/base.css
index c85a77b..ec3f502 100644
--- a/static/css/base.css
+++ b/static/css/base.css
@@ -33,4 +33,7 @@ body {
.loginBox .logo {
float: left;
padding: 1em;
-}
\ No newline at end of file
+}
+a:hover {
+ cursor:pointer;
+}
diff --git a/static/js/components/Download.jsx b/static/js/components/Download.jsx
new file mode 100644
index 0000000..526f3ab
--- /dev/null
+++ b/static/js/components/Download.jsx
@@ -0,0 +1,27 @@
+import React from 'react';
+import PropTypes from 'prop-types';
+
+
+const Download = (props) => {
+ const style = {
+ display: 'inline-block'
+ };
+ return (
+ {
+ e.stopPropagation();
+ }
+ }
+ >
+ Download
+
+ );
+};
+Download.propTypes = {
+ url: PropTypes.string.isRequired
+};
+
+export default Download;
diff --git a/static/js/components/Features.jsx b/static/js/components/Features.jsx
index 4e61ce3..c574f8e 100644
--- a/static/js/components/Features.jsx
+++ b/static/js/components/Features.jsx
@@ -13,6 +13,7 @@ import Plot from './Plot';
import FoldableRow from './FoldableRow';
import { reformatDatetime, contains } from '../utils';
import Delete from './Delete';
+import Download from './Download';
const { Tab, Tabs, TabList, TabPanel } = { ...ReactTabs };
@@ -257,7 +258,14 @@ export let FeatureTable = props => (
| {featureset.name} |
{reformatDatetime(featureset.created_at)} |
{status}
- |
+
+ {
+ done &&
+
+ }
+
+
+ |
{foldedContent}
@@ -290,7 +298,6 @@ FeatureTable = connect(ftMapStateToProps)(FeatureTable);
const mapDispatchToProps = dispatch => (
{ delete: id => dispatch(Action.deleteFeatureset(id)) }
);
-
const DeleteFeatureset = connect(null, mapDispatchToProps)(Delete);
export default FeaturesTab;
diff --git a/static/js/components/Models.jsx b/static/js/components/Models.jsx
index e76e47e..8f3b6aa 100644
--- a/static/js/components/Models.jsx
+++ b/static/js/components/Models.jsx
@@ -10,6 +10,7 @@ import * as Validate from '../validate';
import * as Action from '../actions';
import Expand from './Expand';
import Delete from './Delete';
+import Download from './Download';
import { $try, reformatDatetime } from '../utils';
import FoldableRow from './FoldableRow';
@@ -237,7 +238,14 @@ export let ModelTable = props => (
{model.name} |
{reformatDatetime(model.created_at)} |
{status}
- |
+
+ {
+ done &&
+
+ }
+
+
+ |
{foldedContent}
@@ -265,11 +273,10 @@ const mtMapStateToProps = (state, ownProps) => (
ModelTable = connect(mtMapStateToProps)(ModelTable);
-const dmMapDispatchToProps = dispatch => (
+const deleteMapDispatchToProps = dispatch => (
{ delete: id => dispatch(Action.deleteModel(id)) }
);
-
-const DeleteModel = connect(null, dmMapDispatchToProps)(Delete);
+const DeleteModelButton = connect(null, deleteMapDispatchToProps)(Delete);
export default ModelsTab;
diff --git a/static/js/components/Predictions.jsx b/static/js/components/Predictions.jsx
index dd1245d..0071a83 100644
--- a/static/js/components/Predictions.jsx
+++ b/static/js/components/Predictions.jsx
@@ -135,7 +135,10 @@ let PredictionsTable = props => (
{reformatDatetime(prediction.created_at)} |
{status}
-
+ {
+ done &&
+
+ }
|