From 92a8e2c725f963a7e71e34f388cd2e2a38d056d1 Mon Sep 17 00:00:00 2001 From: Richard Leyshon <49126943+r-leyshon@users.noreply.github.com> Date: Thu, 15 Feb 2024 13:03:13 +0000 Subject: [PATCH 1/4] 5 update readme intro (#247) * docs: Update contributing include pre-commit blurb from readme * docs: Update README intro * docs: Add Example usage & understanding TP stat section * chore: Add README images to version control * docs: Try img tag with centred style * refactor: Git readme won't recognise img tag * docs: Remove example mermaid process chart * docs: Minor typos --- .gitignore | 5 + CONTRIBUTING.md | 24 ++-- README.md | 154 ++++++++++++++++++++------ www/cardiff-street-map.png | Bin 0 -> 475605 bytes www/tp-explained.png | Bin 0 -> 463455 bytes www/transport-performance-newport.png | Bin 0 -> 461720 bytes 6 files changed, 144 insertions(+), 39 deletions(-) create mode 100644 www/cardiff-street-map.png create mode 100644 www/tp-explained.png create mode 100644 www/transport-performance-newport.png diff --git a/.gitignore b/.gitignore index 12704198..90fae26f 100644 --- a/.gitignore +++ b/.gitignore @@ -73,6 +73,11 @@ outputs/* *.jpeg *.svg +# specific rules for README images +!/www/cardiff-street-map.png +!/www/tp-explained.png +!/www/transport-performance-newport.png + # The following was created by https://www.toptal.com/developers/gitignore/api/macos,windows,r,python # Edit at https://www.toptal.com/developers/gitignore?templates=macos,windows,r,python diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 91d0e109..26eeda18 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -76,9 +76,21 @@ following dependencies installed on macos: * `brew install boost` * `brew install cmake` -### Pre-commit +### Pre-commit actions +This repository contains a configuration of pre-commit hooks. These are language agnostic and focussed on repository security (such as detection of passwords and API keys). If approaching this project as a developer, you are encouraged to install and enable `pre-commits` by running the following in your shell: + 1. Install `pre-commit`: -*Placeholder section* + ``` + pip install pre-commit + ``` + 2. Enable `pre-commit`: + + ``` + pre-commit install + ``` +Once pre-commits are activated, whenever you commit to this repository a series of checks will be executed. The pre-commits include checking for security keys, large files and unresolved merge conflict headers. The use of active pre-commits are highly encouraged and the given hooks can be expanded with Python or R specific hooks that can automate the code style and linting. For example, the `flake8` and `black` hooks are useful for maintaining consistent Python code formatting. + +**NOTE:** Pre-commit hooks execute Python, so it expects a working Python build. ### Note on Issues, Feature Requests, and Pull Requests @@ -100,12 +112,8 @@ We mainly follow the [Quality Assurance of Code for Analysis and Research](https ## Testing -*Placeholder section* +Testing with [`pytest`](https://pytest.org/en/latest/getting-started.html). ## Code coverage -*Placeholder section* - -## Documentation - -*Placeholder section* +Coverage with [Coverage.py](https://coverage.readthedocs.io/en/7.4.1/) diff --git a/README.md b/README.md index 2c91e15c..6745b6d9 100644 --- a/README.md +++ b/README.md @@ -7,58 +7,150 @@ # transport-network-performance -> :warning: This repository is still in the development phase. Caution should be taken before using or referencing this work in any way - use it at your own risk. +> :warning: This repository is still in the development phase. Caution should +be taken before using or referencing this work in any way - use it at your own +risk. -# Introduction -## About -*Describe what this repo contains and what the project is.* +## Introduction + + +`transport_performance` provides a method for analysing the efficiency of +moving people into and around urban centres. The method employed here builds +upon that established by [Poelman *et al*, European Commission 2020](https://ec.europa.eu/regional_policy/sources/work/012020_low_carbon_urban.pdf). Specifically, this python package provides +features useful for: + +- Defining an urban centre boundary based upon contiguous population density. +- Inspecting, cleaning and filtering public transit data in [GTFS format](https://gtfs.org/). +- Inspecting and filtering Open Street Map data in [PBF format](https://wiki.openstreetmap.org/wiki/PBF_Format). +- Multimodal routing with r5 [using r5py](https://r5py.readthedocs.io/en/stable/) +to create travel time matrices. +- Calculation of transport performance statistics. ## Developers -We welcome contributions from others. Please check out our [code of conduct](CODE_OF_CONDUCT.md) and [contributing guidance](CONTRIBUTING.md###Set-up). +We welcome contributions from others. Please check out our +[code of conduct](CODE_OF_CONDUCT.md) and +[contributing guidance](CONTRIBUTING.md###Set-up). ## Installation *Describe technical set-up. Such as the required dependencies.* -### Pre-commit actions -This repository contains a configuration of pre-commit hooks. These are language agnostic and focussed on repository security (such as detection of passwords and API keys). If approaching this project as a developer, you are encouraged to install and enable `pre-commits` by running the following in your shell: - 1. Install `pre-commit`: +This package is designed to work with python 3.9.13. Full functionality is +tested on macos only. Other operating systems may be incompatible with +`transport_performance.osm` specifically. - ``` - pip install pre-commit - ``` - 2. Enable `pre-commit`: +The transport modelling features in `transport_performance.analyse_network` +depends upon a compatible Java Development Kit (JDK). Please consult the +[r5py installation docs](https://r5py.readthedocs.io/en/stable/user-guide/installation/installation.html#dependencies) +and our [Contributing Guidance](/./CONTRIBUTING.md) for more on configuring a +JDK. - ``` - pre-commit install - ``` -Once pre-commits are activated, whenever you commit to this repository a series of checks will be executed. The pre-commits include checking for security keys, large files and unresolved merge conflict headers. The use of active pre-commits are highly encouraged and the given hooks can be expanded with Python or R specific hooks that can automate the code style and linting. For example, the `flake8` and `black` hooks are useful for maintaining consistent Python code formatting. +## Usage + -**NOTE:** Pre-commit hooks execute Python, so it expects a working Python build. +### Installation -## Usage -*Explain how to use the things in the repo.* +Currently, `transport_performance` is not published to PyPI or Conda Forge. To +use the code, we suggest forking the repository and cloning the fork to your +development environment. + +``` +git clone /transport-network-performance.git +``` -### Workflow -*You may wish to consider generating a graph to show your project workflow. GitHub markdown provides native support for [mermaid](https://mermaid.js.org/syntax/flowchart.html), an example of which is provided below:* +We recommend running the package with a virtual environment such as +[conda](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) +or [venv](https://docs.python.org/3/library/venv.html). -```mermaid -flowchart TD - id1[(Some data)] --> id2(Some processing) - id3[(More data)] --> id2 - id2 --> id4[Some output] +With conda: ``` +conda create -n transport-performance python=3.9.13 -y +``` +Once completed, activate the environment: +``` +conda activate transport-performance +``` +Install the python requirements: +``` +pip install -r requirements.txt +``` +Additional Java dependencies are required for full functionality. See the +[contributing guidance](./CONTRIBUTING.md) for assistance. + +### Required Data + +You will need the following data, appropriate to the territory that you wish to +analyse: + +* [Open Street Map data](https://download.geofabrik.de/) in PBF format. +* [Public Transport Schedule data](https://data.bus-data.dft.gov.uk/downloads/) +in GTFS format. +* [Global Human Settlement Layer](https://ghsl.jrc.ec.europa.eu/download.php) +population estimates. + +### Usage + +For guidance on how to use the `transport_performance` package, consult the +[end to end notebooks](/./notebooks/e2e/). These notebooks demonstrate the +workflow required to calculate transport performance in a number of urban +centres. + +![Transport performance folium map of Newport, South Wales.](/./www/transport-performance-newport.png) + +## Understanding Transport Performance + +Transport performance is a statistic developed by The European Commission that +allows measurement and comparison of how efficiently people move through +transport networks. + +In the example below, transport performance is visualised for a single location +in Cardiff. + + display: block; + margin-left: auto; + margin-right: auto; + width: 50%; + +![Google (2021) A4161 Cardiff. Available at: http://maps.google.co.uk (Accessed: 11 December 2023).](/./www/cardiff-street-map.png) + +Using this location as the journey origin, travel times to the surrounding +neighbourhood within 45 minutes can be calculated. The proximal population that +can be reached is summed. This population would be reachable from the journey +origin if travel at 15 km/h in a straight line were possible. This assumption +is coherent with the European Commission’s assumption of average travel speed +by public transport. + +The accessible population for the same journey duration is also calculated. +This is the number of people reachable from the journey origin by public +transport and walking modes. + +To calculate the transport performance statistic, the ratio of accessible to +proximal population is taken. +![Breakdown of Transport Performance statistic.](/./www/tp-explained.png) -# Data Science Campus -At the [Data Science Campus](https://datasciencecampus.ons.gov.uk/about-us/) we apply data science, and build skills, for public good across the UK and internationally. Get in touch with the Campus at [datasciencecampus@ons.gov.uk](datasciencecampus@ons.gov.uk). +The transport performance statistic is calculated for every 200 m2 +cell in the urban centre. As the journey departure time is known to affect the +available public transport services, varying the departure time results in +differing transport performance. In order to produce a less volatile statistic, +the transport performance for every cell is calculated at 1 minute interval +departure times between 08:00 and 09:00 on a single day. The chosen date in +this example is Wednesday 22nd November 2023, a day that is +representative of average public transport service in the public transport +schedules. -# License +## Data Science Campus +At the [Data Science Campus](https://datasciencecampus.ons.gov.uk/about-us/) we +apply data science, and build skills, for public good across the UK and +internationally. Get in touch with the Campus at +[datasciencecampus@ons.gov.uk](datasciencecampus@ons.gov.uk). - +## License + The code, unless otherwise stated, is released under [the MIT Licence][mit]. -The documentation for this work is subject to [© Crown copyright][copyright] and is available under the terms of the [Open Government 3.0][ogl] licence. +The documentation for this work is subject to [© Crown copyright][copyright] +and is available under the terms of the [Open Government 3.0][ogl] licence. 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z``KMntXat%lG6F|GZ(U34`#Dp{qA1&&RZ|oUNv;6PSFc}>FULa?7dHKWw*5|d0rEI zfB1tJt!ykD+cq}VM2}8QJo$s*7|;D327IMBd%W;|GfEFyUWBphPRM2P4!@@fWzA>D zsVVVrj|cy4>Qj>%+}4b@9;}BL_@_TP2COyJrY5wip;6k#H5T^Cl#wwKUP+T1u5*MV z+~GLZe_jFyw1Bx}zXo#pD2|i;7Bzsc~-;{4S7f%_|g#WoS;|7wZx)mT>B|0(A z=mmwbYGP}2mh%l@G;>;2&K6IU#OP6Us3@XIpFp7E?Cqi+Pe1*Pc#_5qrRAF^^^HXy z{80X`-#H7+r|E3(l#A;K8ze&alGjGbo5eH?3Is$_&4CISQ#37t8=$d!; z)8027(t$bWOV8?{Lzx(Y0N}I!CEAZOAt)QUlEk!8+CFyX0x$}9uf z81T#UAby(8;8(fGkuixuv6#36Gcb@3FnBv)XJ%kqI6tKG{d+xjM#z8qvp>uJ?tlMX a_WuF2HI~2GRp~1L0000 Date: Mon, 19 Feb 2024 09:50:08 +0000 Subject: [PATCH 2/4] 220 df index sort mgtfs (#249) * feat: sorting params for mgtfs summaries * feat: additional tests for new sorting features * fix: restructured param to remove unnecessary sort options * fix: add reset index after sorting by route type * fix: update docstring to address sorting conditions * fix: moved reset_index to return statement --------- Co-authored-by: Sergio Recio --- .../gtfs/multi_validation.py | 48 +++++++++++++++---- tests/gtfs/test_multi_validation.py | 36 ++++++++++++-- 2 files changed, 70 insertions(+), 14 deletions(-) diff --git a/src/transport_performance/gtfs/multi_validation.py b/src/transport_performance/gtfs/multi_validation.py index e48582fa..84319b2b 100644 --- a/src/transport_performance/gtfs/multi_validation.py +++ b/src/transport_performance/gtfs/multi_validation.py @@ -379,12 +379,21 @@ def filter_to_bbox( self._raise_empty_feed_error(bbox) return None + def _summary_col_sorter(self, df: pd.DataFrame) -> pd.DataFrame: + """Sort columns for summary dfs.""" + presets = ["day", "route_type"] + for col in sorted(df.columns.values): + if col not in presets: + presets.append(col) + return df.reindex(presets, axis=1).copy() + def _summarise_core( self, which: str = "trips", summ_ops: list = [np.min, np.max, np.mean, np.median], return_summary: bool = True, to_days: bool = False, + sort_by_route_type: bool = False, ) -> pd.DataFrame: """Summarise the MultiGtfsInstance by either trip_id or route_id. @@ -399,12 +408,16 @@ def _summarise_core( by default [np.min, np.max, np.mean, np.median] return_summary : bool, optional When set to False, full data for each trip on each date will be - returned. Defaults to True. + returned, by default True. to_days : bool, optional Whether or not to aggregate to days, or to just return counts for trips/routes for each date. When False, summ_ops becomes useless, and should therefore nothing should be passed when calling this - function (so it remains as the default). Defaults to False. + function (so it remains as the default), by default False. + sort_by_route_type : bool, optional + Whether or not to sort the resulting dataframe by route_type. + This only impacts the resulting df when to_days=True, + by default False. Returns ------- @@ -422,12 +435,12 @@ def _summarise_core( _type_defence(which, "which", str) _type_defence(return_summary, "return_summary", bool) _type_defence(to_days, "to_days", bool) + _type_defence(sort_by_route_type, "sort_by_route_type", bool) which = which.lower().strip() if which not in ["trips", "routes"]: raise ValueError( f"'which' must be one of ['trips', 'routes']. Got {which}" ) - # choose summary if which == "trips": group_col = "trip_id" @@ -476,14 +489,20 @@ def _summarise_core( column.replace("amin", "min").replace("amax", "max") for column in trip_counts.columns.values ] + # Always sort by day so that route_type sorts are more organised trip_counts = self.instances[0]._order_dataframe_by_day(trip_counts) - return trip_counts + if sort_by_route_type: + trip_counts = trip_counts.sort_values("route_type") + if to_days: + trip_counts = self._summary_col_sorter(trip_counts) + return trip_counts.reset_index(drop=True) def summarise_trips( self, summ_ops: list = [np.min, np.max, np.mean, np.median], return_summary: bool = True, to_days: bool = False, + sort_by_route_type: bool = False, ) -> pd.DataFrame: """Summarise the combined GTFS data by trip_id. @@ -496,12 +515,16 @@ def summarise_trips( ,by default [np.min, np.max, np.mean, np.median] return_summary: bool, optional When set to False, full data for each trip on each date will be - returned. Defaults to True. + returned, by default True. to_days : bool, optional Whether or not to aggregate to days, or to just return counts for trips/routes for each date. When False, summ_ops becomes useless, and should therefore nothing should be passed when calling this - function (so it remains as the default). Defaults to False. + function (so it remains as the default), by default False. + sort_by_route_type : bool, optional + Whether or not to sort the resulting dataframe by route_type. + This only impacts the resulting df when to_days=True, + by default False. Returns ------- @@ -514,6 +537,7 @@ def summarise_trips( summ_ops=summ_ops, return_summary=return_summary, to_days=to_days, + sort_by_route_type=sort_by_route_type, ) return self.daily_trip_summary.copy() @@ -522,6 +546,7 @@ def summarise_routes( summ_ops: list = [np.min, np.max, np.mean, np.median], return_summary: bool = True, to_days: bool = False, + sort_by_route_type: bool = False, ) -> pd.DataFrame: """Summarise the combined GTFS data by route_id. @@ -534,12 +559,16 @@ def summarise_routes( by default [np.min, np.max, np.mean, np.median]. return_summary: bool, optional When set to False, full data for each trip on each date will be - returned. Defaults to True. + returned, by default True. to_days : bool, optional Whether or not to aggregate to days, or to just return counts for trips/routes for each date. When False, summ_ops becomes useless, and should therefore nothing should be passed when calling this - function (so it remains as the default). Defaults to False. + function (so it remains as the default), by default False. + sort_by_route_type : bool, optional + Whether or not to sort the resulting dataframe by route_type. + This only impacts the resulting df when to_days=True, + by default False. Returns ------- @@ -552,6 +581,7 @@ def summarise_routes( summ_ops=summ_ops, return_summary=return_summary, to_days=to_days, + sort_by_route_type=sort_by_route_type, ) return self.daily_route_summary.copy() @@ -571,7 +601,7 @@ def viz_stops( Whether or not to return the folium map object, by default True. filtered_only : bool, optional Whether to filter the stops that are plotted to only stop_id's that - are present in the stop_times table. + are present in the stop_times table, by default True. Returns ------- diff --git a/tests/gtfs/test_multi_validation.py b/tests/gtfs/test_multi_validation.py index ba3b8939..35ed7334 100644 --- a/tests/gtfs/test_multi_validation.py +++ b/tests/gtfs/test_multi_validation.py @@ -453,24 +453,42 @@ def test_filter_to_bbox(self, multi_gtfs_fixture): ), "Gtfs inst[1] not as expected after filter" @pytest.mark.parametrize( - "which, summ_ops, raises, match", + "which, summ_ops, sort_by_route_type, raises, match", ( - ["route", True, TypeError, ".*summ_ops.*list.*bool"], - [True, [np.max], TypeError, ".*which.*str.*bool"], + ["route", True, True, TypeError, ".*summ_ops.*list.*bool"], + [True, [np.max], True, TypeError, ".*which.*str.*bool"], [ "not_which", [np.max], + True, ValueError, ".*which.*trips.*routes.*not_which.*", ], + [ + "trips", + [np.max], + "not_sort", + TypeError, + ".*sort_by_route_type.*bool.*str", + ], ), ) def test__summarise_core_defence( - self, multi_gtfs_fixture, which, summ_ops, raises, match + self, + multi_gtfs_fixture, + which, + summ_ops, + sort_by_route_type, + raises, + match, ): """Defensive tests for _summarise_core().""" with pytest.raises(raises, match=match): - multi_gtfs_fixture._summarise_core(which=which, summ_ops=summ_ops) + multi_gtfs_fixture._summarise_core( + which=which, + summ_ops=summ_ops, + sort_by_route_type=sort_by_route_type, + ) def test__summarise_core(self, multi_gtfs_fixture): """General tests for _summarise_core().""" @@ -532,6 +550,14 @@ def test__summarise_core(self, multi_gtfs_fixture): assert ( dated_sum[dated_sum.date == "2024-04-06"].route_count.iloc[0] == 9 ), "Unexpecteed number of routes on 2024-04-06" + # test sorting to route_type + route_sort = multi_gtfs_fixture._summarise_core( + which="routes", to_days=True, sort_by_route_type=True + ) + first_three_types = route_sort.route_type[:3] + assert np.array_equal( + first_three_types, [3, 3, 3] + ), "Summary not sorted by route_type" def test_summarise_trips(self, multi_gtfs_fixture): """General tests for summarise_trips().""" From 2b0444ec8814cd7b782ea059e404451647deb2c6 Mon Sep 17 00:00:00 2001 From: SergioRec <117715997+SergioRec@users.noreply.github.com> Date: Mon, 19 Feb 2024 10:14:32 +0000 Subject: [PATCH 3/4] fix: removed markdown formatting text appearing in README.md (#253) --- README.md | 5 ----- 1 file changed, 5 deletions(-) diff --git a/README.md b/README.md index 6745b6d9..709a8a86 100644 --- a/README.md +++ b/README.md @@ -105,11 +105,6 @@ transport networks. In the example below, transport performance is visualised for a single location in Cardiff. - display: block; - margin-left: auto; - margin-right: auto; - width: 50%; - ![Google (2021) A4161 Cardiff. Available at: http://maps.google.co.uk (Accessed: 11 December 2023).](/./www/cardiff-street-map.png) Using this location as the journey origin, travel times to the surrounding From 7bb4863ae31251b947f45773f4bbb71f05472297 Mon Sep 17 00:00:00 2001 From: Charlie Browning <121952297+CBROWN-ONS@users.noreply.github.com> Date: Tue, 20 Feb 2024 05:32:40 +0000 Subject: [PATCH 4/4] 239 plot trips and routes real (#251) * feat: add code from other branch * feat: add improvements from mirror branch * fix: CSS left in readme from merge to main * 239 hotfix refactor (#252) * refactor: Reduce tests to common func * refactor: Adjust plot_trips & plot_routes -> plot_service * fix: Failing test in plot core updated params * fix: re-organise plotting functions --------- Co-authored-by: Browning --------- Co-authored-by: r-leyshon Co-authored-by: Richard Leyshon <49126943+r-leyshon@users.noreply.github.com> --- .../gtfs/multi_validation.py | 165 ++++++++++++++++++ tests/gtfs/test_multi_validation.py | 73 ++++++++ 2 files changed, 238 insertions(+) diff --git a/src/transport_performance/gtfs/multi_validation.py b/src/transport_performance/gtfs/multi_validation.py index 84319b2b..9f53579f 100644 --- a/src/transport_performance/gtfs/multi_validation.py +++ b/src/transport_performance/gtfs/multi_validation.py @@ -12,6 +12,8 @@ import pandas as pd import folium from folium.plugins import FastMarkerCluster +import plotly.express as px +import plotly.graph_objs as go from transport_performance.gtfs.validation import GtfsInstance from transport_performance.utils.defence import ( @@ -73,6 +75,8 @@ class MultiGtfsInstance: creates a calendar table from calendar_times. get_dates() Get the range of dates that the gtfs(s) span. + plot_service() + Plot a timeseries of route or trip counts. Raises ------ @@ -747,3 +751,164 @@ def get_dates(self, return_range: bool = True) -> list: if return_range: return [min(sorted_dates), max(sorted_dates)] return sorted_dates + + def _reformat_col_names(self, col_name: str, cap_all: bool = True): + """Convert a column name to a more readable format.""" + parts = col_name.split("_") + for i, part in enumerate(parts): + part = list(part) + part[0] = part[0].upper() + parts[i] = "".join(part) + if not cap_all: + break + return " ".join(parts) + + def _plot_core( + self, + df: pd.DataFrame, + count_col: str = "routes", + width: int = 1000, + height: int = 550, + title: str = None, + kwargs: dict = {}, + rolling_average: Union[int, None] = None, + line_date: Union[str, None] = None, + ): + """Plot a timeseries for trip/route count.""" + # defences + _type_defence(df, "df", pd.DataFrame) + _type_defence(count_col, "count_col", str) + _type_defence(width, "width", int) + _type_defence(height, "height", int) + _type_defence(title, "title", (str, type(None))) + _type_defence(kwargs, "kwargs", dict) + _type_defence(rolling_average, "rolling_average", (int, type(None))) + _type_defence(line_date, "line_date", (str, type(None))) + # preparation + LABEL_FORMAT = { + count_col: self._reformat_col_names(count_col), + "date": "Date", + } + PLOT_TITLE = { + "text": f"{self._reformat_col_names(count_col, False)} over time", + "x": 0.5, + "xanchor": "center", + } + if "route_type" in df.columns: + kwargs["color"] = "route_type" + LABEL_FORMAT["route_type"] = self._reformat_col_names("route_type") + PLOT_TITLE["text"] = PLOT_TITLE["text"] + " by route type" + kwargs["width"] = width + kwargs["height"] = height + if title: + PLOT_TITLE["text"] = title + + if rolling_average: + new_count_col = f"{rolling_average} Day Rolling Average" + temp_dfs = [] + # impute route type if there is none + if "route_type" not in df.columns: + df["route_type"] = 15000 + for rt in df.route_type.unique(): + temp = df[df.route_type == rt].copy() + # resample to account for missing dates + temp = temp.set_index("date").resample("1D").sum() + # add correct route type + temp["route_type"] = rt + # calculate rolling average over [x] days + temp[new_count_col] = ( + temp[count_col] + .rolling(window=rolling_average, center=True) + .mean() + ) + temp_dfs.append(temp) + df = pd.concat(temp_dfs).sort_values("date").reset_index() + count_col = new_count_col + # plotting + fig = px.line(df, x="date", y=count_col, labels=LABEL_FORMAT, **kwargs) + fig.update_layout(title=PLOT_TITLE) + if line_date: + fig.add_vline(x=line_date, line_dash="dash") + + return fig + + def plot_service( + self, + service_type: str = "routes", + route_type: bool = True, + width: int = 1000, + height: int = 550, + title: str = None, + plotly_kwargs: dict = None, + rolling_average: Union[int, None] = None, + line_date: Union[str, None] = None, + ) -> go.Figure: + """Create a line plot of route or trip counts over time. + + Parameters + ---------- + service_type: str, optional + Whether to plot 'routes' or 'trips'. By default 'routes'. + route_type : bool, optional + Whether or not to draw a line for each modality, by default True + width : int, optional + Plot width, by default 1000 + height : int, optional + Plot height, by default 550 + title : str, optional + Plot title, by default None + plotly_kwargs : dict, optional + Kwargs to pass to plotly.express.line, by default None + rolling_average : Union[int, None], optional + How many days to calculate the rolling average over. When left as + None, rolling average is not used. + The rolling average is calculated from the center, meaning if ra=3, + the average will be calculated from the current date, previous date + and following date. Missing dates are imputed and treated as having + values of 0. + line_date : Union[str, None], optional + A data to draw a dashed vertical line on. Date should be in format: + YYYY-MM-DD, by default None + + Returns + ------- + go.Figure + The timerseries plot + + """ + # defences + _type_defence(service_type, "service_type", str) + _type_defence(route_type, "route_type", bool) + _type_defence(plotly_kwargs, "plotly_kwargs", (dict, type(None))) + if not plotly_kwargs: + plotly_kwargs = {} + SERVICE_TYPES = ["routes", "trips"] + if service_type not in SERVICE_TYPES: + raise ValueError( + "`service_type` expects 'routes' or 'trips'," + f" found: {service_type}" + ) + if service_type == "routes": + data = self.summarise_routes().copy() + count_col = "route_count" + else: + data = self.summarise_trips().copy() + count_col = "trip_count" + if not route_type: + data = ( + data.drop("route_type", axis=1) + .groupby("date") + .sum() + .reset_index() + ) + figure = self._plot_core( + data, + count_col=count_col, + width=width, + height=height, + title=title, + kwargs=plotly_kwargs, + rolling_average=rolling_average, + line_date=line_date, + ) + return figure diff --git a/tests/gtfs/test_multi_validation.py b/tests/gtfs/test_multi_validation.py index 35ed7334..cabaa175 100644 --- a/tests/gtfs/test_multi_validation.py +++ b/tests/gtfs/test_multi_validation.py @@ -13,6 +13,7 @@ import pandas as pd import folium from pyprojroot import here +import plotly.graph_objs as go from transport_performance.gtfs.multi_validation import ( MultiGtfsInstance, @@ -691,3 +692,75 @@ def test_get_dates(self, multi_gtfs_fixture, multi_gtfs_altered_fixture): len(multi_gtfs_altered_fixture.get_dates(return_range=False)) == 6 ), "Unexpected number of dates" pass + + def test__plot_core(self, multi_gtfs_fixture): + """General tests for _plot_core().""" + # route summary + data = multi_gtfs_fixture.summarise_routes() + route_fig = multi_gtfs_fixture._plot_core(data, "route_count") + assert isinstance(route_fig, go.Figure), "Route counts not plotted" + # trip summary + data = multi_gtfs_fixture.summarise_trips() + trip_fig = multi_gtfs_fixture._plot_core(data, "trip_count") + assert isinstance(trip_fig, go.Figure), "Trip counts not plotted" + # trip summary with custom title + trip_fig = multi_gtfs_fixture._plot_core( + data, "trip_count", title="test" + ) + found_title = trip_fig.layout["title"]["text"] + assert found_title == "test", "Title not as expected" + # trip summary with custom dimensions + trip_fig = multi_gtfs_fixture._plot_core( + data, "trip_count", height=100, width=150 + ) + found_height = trip_fig.layout["height"] + found_width = trip_fig.layout["width"] + assert found_height == 100, "Height not as expected" + assert found_width == 150, "Width not as expected" + # custom kwargs + trip_fig = multi_gtfs_fixture._plot_core( + data, "trip_count", kwargs={"markers": True} + ) + assert trip_fig.data[0]["mode"] in [ + "markers+lines", + "lines+markers", + ], "Markers not plotted" + # rolling average + avg_fig = multi_gtfs_fixture._plot_core( + data, "trip_count", rolling_average=7 + ) + found_ylabel = avg_fig.layout["yaxis"]["title"]["text"] + assert ( + found_ylabel == "7 Day Rolling Average" + ), "Rolling average not plotted" + # draw a line on a date + avg_fig = multi_gtfs_fixture._plot_core( + data, "trip_count", rolling_average=7, line_date="2023-12-01" + ) + found_line = avg_fig.layout["shapes"][0]["line"]["dash"] + assert found_line == "dash", "Date line not plotted" + + def test_plot_service(self, multi_gtfs_fixture): + """General tests for .plot_service().""" + # plot route_type + fig = multi_gtfs_fixture.plot_service(service_type="routes") + assert len(fig.data) == 2, "Not plotted by modality" + # plot without route type + fig = multi_gtfs_fixture.plot_service( + service_type="routes", route_type=False + ) + assert len(fig.data) == 1, "Plot not as expected" + # rolling average + no route type + avg_fig = multi_gtfs_fixture.plot_service( + service_type="routes", rolling_average=7, route_type=False + ) + leg_status = avg_fig.data[0]["showlegend"] + assert not leg_status, "Multiple route types found" + # plot trips + fig = multi_gtfs_fixture.plot_service(service_type="trips") + assert len(fig.data) == 2, "Not plotted by modality" + # plot without route type + fig = multi_gtfs_fixture.plot_service( + service_type="trips", route_type=False + ) + assert len(fig.data) == 1, "Plot not as expected"

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