def hist_matrix(dataset_id):
d = dataset_getter(dataset_id, 'matrix')
r = asrange(flask.request.args.get('range',None))
data = d.asnumpy(r)
import numpy as np
hist, bin_edges = np.histogram(data, bins=int(flask.request.args.get('bins',np.sqrt(len(data)))), range=d.range)
return jsonify(hist)
def col_table(dataset_id, column):
d = dataset_getter(dataset_id, 'table')
r = asrange(flask.request.args.get('range',None))
for col in d.columns:
if col.name == column:
return jsonify(col.aslist(r), allow_nan=False)
flask.abort(404)
def list_items(datasetid):
d = dataset_getter(datasetid, 'graph')
if flask.request.method == 'GET':
r = asrange(flask.request.args.get('range',None))
return jsonify([n.asjson() for n in getattr(d,name+'s')(r[0] if r is not None else None)])
if flask.request.method == 'DELETE':
if d.clear():
return jsonify(d.to_description(),indent=1)
flask.abort(400)
#post
n = _to_desc()
if getattr(d,'add_'+name)(n):
return jsonify(d.to_description(),indent=1)
#invalid upload
flask.abort(400)
def handle_item(datasetid, itemid):
d = dataset_getter(datasetid, 'graph')
if flask.request.method == 'GET':
n = getattr(d,'get_'+name)(itemid)
return jsonify(n.asjson())
if flask.request.method == 'DELETE':
if getattr(d,'remove_'+name)(itemid):
return jsonify(d.to_description(),indent=1)
flask.abort(400)
#put
n = _to_desc()
n['id'] = itemid
if getattr(d,'update_'+name)(n):
return jsonify(d.to_description(),indent=1)
#invalid upload
flask.abort(400)
def create(dataset, range, args):
"""
a special method to 'format' a dataset into an mds format
:param dataset: the dataset to convert
:param range: a subrange of the data
:param args: additional request arguments
:return:
"""
#get the data as numpy
data = np.array(dataset.asnumpy(range))
#get the row ids aka samples
samples = dataset.rows(range[0] if range is not None else None)
#TODO compute MDS and prepare the result set
r = {}
#convert to json
return jsonify(r)
def list_graphs(datasetid): d = dataset_getter(datasetid, 'graph') return jsonify(d.to_description())
def view_raw_table(dataset_id, view_name): view, args = find_view(dataset_id, view_name) return jsonify(view.aslist(args), allow_nan=False)
def desc_gen(dataset_id): d = dataset_getter(dataset_id, type) return jsonify(d.to_description())
def rowids_gen(dataset_id):
d = dataset_getter(dataset_id, type)
r = asrange(flask.request.args.get('range',None))
ids = d.rowids(r[0] if r is not None else None)
return jsonify(str(ranges.from_list(list(ids))))
def _list_types_api(): return jsonify(list_types())
def _map_ids_api(source, target):
return jsonify(map_ids(source, target, flask.request.args.getlist('ids[]')))
def _map_id_api(source, target, sid): return jsonify(map_id(source, target, sid))
def _list_ids_api(source): return jsonify(list_ids(source))
def view_rowids_table(dataset_id, view_name): view, args = find_view(dataset_id, view_name) ids = view.rowids(args) return jsonify(str(ranges.from_list(list(ids))))
def view_rows_table(dataset_id, view_name): view, args = find_view(dataset_id, view_name) return jsonify(view.rows(args))
def format_json(dataset, range, args):
d = dataset.asjson(range)
if bool(args.get('f_pretty_print', False)):
return jsonify(d, indent=' ')
return jsonify(d)
def colids_matrix(dataset_id):
d = dataset_getter(dataset_id, 'matrix')
r = asrange(flask.request.args.get('range',None))
return jsonify(d.colids(r[0] if r is not None else None))
def raw_gen(dataset_id):
d = dataset_getter(dataset_id, type)
r = asrange(flask.request.args.get('range',None))
return jsonify(d.asnumpy(r), allow_nan=False)
def rowids_gen(dataset_id):
d = dataset_getter(dataset_id, type)
r = asrange(flask.request.args.get('range',None))
return jsonify(d.rowids(r[0] if r is not None else None))
def colids_matrix(dataset_id):
d = dataset_getter(dataset_id, 'matrix')
r = asrange(flask.request.args.get('range',None))
ids = d.colids(r[0] if r is not None else None)
return jsonify(str(ranges.from_list(list(ids))))
