gtfspy is a Python package for analyzing public transport timetable data provided in the General Transit Feed Specification, GTFS, -format. Core features: Import one or multiple GTFS feeds into one SQLite database for efficient querying of the data. Augment the sqlite with real walking distances...
main(args.netex, args.database, args.clean_database, args.referencing, args.log_file) File "/mnt/storage/home/skinkie/Sources/references/gtfs-netex-test/netex_to_db.py", line 32, in main insert_database(db, classes, sub_file) File "/mnt/storage/home/skinkie/Sources/references/gtfs-...
an open-source data service sponsored byMapzenthat aggregates transit network data from around the world. Transitland enables us to merge transit schedules from different operators without having to worry about the granular details of each operator’s GTFS data. ...
Although transfer locations can be inferred from GPS data processed in the General Transit Feed Specification (GTFS) format, such data are less useful in studying network-wide integration, as tracking occurs at the vehicle and route level, and contains limited information on the actual locations ...
We’ll start our program by importing the Python packages: fromgoogle.transitimportgtfs_realtime_pb2importrequestsimporttime Next, we’ll issue our HTTP request to the NYC MTA GTFS feed: api_key="YOUR_API_KEY"# Requests subway status data feed from the NYC MTA APIheaders={'x-api-key':...
Among commonly used approaches for obtaining aSBP are generalized transfer functions (GTFs)14–16, moving average m odels17,18 and pulse wave analysis-based methods8,19,20. Nevertheless, the totality of them relies on the acquisition of the entire peripheral pressure wave- form which ...
Here we introduce a mostly natural sequencing-by-synthesis (mnSBS) method for single-cell RNA sequencing (scRNA-seq), adapted to the Ultima genomics platform, and systematically benchmark it against current scRNA-seq technology. mnSBS uses mostly natural
Our pipeline is based on a Topic-Supervised Non-Negative Matrix Factorization model, using a Weak-Labeling strategy on user trajectories with data obtained from open datasets, such as GTFS and OpenStreetMap. As a case study, we show results for the city of Santiago, Chile, which has a ...
Among commonly used approaches for obtaining aSBP are generalized transfer functions (GTFs)14–16, moving average m odels17,18 and pulse wave analysis-based methods8,19,20. Nevertheless, the totality of them relies on the acquisition of the entire peripheral pressure wave- form which ...
In this study, we describe a new approach combining reservoir modeling and machine learning to produce models that enable such a strategy. Our computational approach allows us, first, to translate sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy, ...