From 4ab6cfb8bf491edfcc634932d8d6c38458e16b83 Mon Sep 17 00:00:00 2001 From: Phil Elson Date: Thu, 26 Aug 2021 11:13:36 +0200 Subject: [PATCH] Refactor the weather data production, restoring as much of the old test behaviour as possible to minimise the changes --- README.md | 25 +-- cara/apps/calculator/model_generator.py | 35 ++- cara/apps/calculator/static/js/form.js | 13 +- .../templates/base/calculator.report.html.j2 | 6 +- .../templates/calculator.form.html.j2 | 8 +- cara/apps/expert.py | 4 +- cara/data.py | 93 -------- cara/data/__init__.py | 51 +++++ cara/data/weather.py | 114 ++++++++++ .../apps/calculator/test_model_generator.py | 210 ++++++++---------- cara/tests/data/__init__.py | 0 cara/tests/data/test_weather.py | 11 + cara/tests/models/test_piecewiseconstant.py | 2 +- cara/tests/test_known_quantities.py | 131 ++++++----- cara/tests/test_monte_carlo_full_models.py | 48 ++-- 15 files changed, 410 insertions(+), 341 deletions(-) delete mode 100644 cara/data.py create mode 100644 cara/data/__init__.py create mode 100644 cara/data/weather.py create mode 100644 cara/tests/data/__init__.py create mode 100644 cara/tests/data/test_weather.py diff --git a/README.md b/README.md index 1194fec3..7b3949b9 100644 --- a/README.md +++ b/README.md @@ -85,26 +85,20 @@ This will start a local version of CARA, which can be visited at http://localhos ## Development guide -### Running the COVID calculator app in development mode +The CARA repository makes use of Git's Large File Storage (LFS) feature. +You will need a working installation of git-lfs in order to run CARA in development mode. +See https://git-lfs.github.com/ for installation instructions. -Download Git Large File Storage (LFS) - **macOS**: +### Installing CARA in editable mode ``` -brew install git-LFS -``` - -Download Git Large File Storage (LFS) - **Linux**: - -``` -apt-get install git-lfs -``` - -Install dependencies: - -``` -git lfs install git lfs pull # Fetch the data from LFS pip install -e . # At the root of the repository +``` + +### Running the COVID calculator app in development mode + +``` python -m cara.apps.calculator ``` @@ -123,7 +117,6 @@ python -m cara.apps.calculator --prefix=/mycalc ### Running the CARA Expert-App app in development mode ``` -pip install -e . # At the root of the repository voila cara/apps/expert/cara.ipynb --port=8080 ``` diff --git a/cara/apps/calculator/model_generator.py b/cara/apps/calculator/model_generator.py index 013756a6..69701a30 100644 --- a/cara/apps/calculator/model_generator.py +++ b/cara/apps/calculator/model_generator.py @@ -9,6 +9,7 @@ import numpy as np from cara import models from cara import data +import cara.data.weather import cara.monte_carlo as mc from .. import calculator from cara.monte_carlo.data import activity_distributions, virus_distributions @@ -20,8 +21,6 @@ LOG = logging.getLogger(__name__) minutes_since_midnight = typing.NewType('minutes_since_midnight', int) - - # Used to declare when an attribute of a class must have a value provided, and # there should be no default value used. _NO_DEFAULT = object() @@ -53,10 +52,9 @@ class FormData: infected_lunch_start: minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed infected_people: int infected_start: minutes_since_midnight - location: str - location_coordinates: str - weather_station_location: str - weather_station_ref: str + location_name: str + location_latitude: float + location_longitude: float mask_type: str mask_wearing_option: str mechanical_ventilation_type: str @@ -107,10 +105,9 @@ class FormData: 'infected_lunch_start': '12:30', 'infected_people': _NO_DEFAULT, 'infected_start': '08:30', - 'location': _NO_DEFAULT, - 'location_coordinates': _NO_DEFAULT, - 'weather_station_location':'GENEVA COINTRIN', - 'weather_station_ref': '067000-99999', + 'location_latitude': 46.20833, + 'location_longitude': 6.14275, + 'location_name': 'Geneva', 'mask_type': 'Type I', 'mask_wearing_option': 'mask_off', 'mechanical_ventilation_type': 'not-applicable', @@ -269,14 +266,12 @@ class FormData: month = datetime_object.month # set location - self.weather_station_location = data.location_to_weather_stn(self.location_coordinates)[1] - data.local_tempatures = data.location_celcius_per_hour(self.location_coordinates) - print(data.local_tempatures) + wx_station = self.nearest_weather_station() + temp_profile = cara.data.weather.mean_hourly_temperatures(wx_station[0], month) inside_temp = models.PiecewiseConstant((0, 24), (293,)) - outside_temp = data.Temperatures[str(month)] - - + # Interpolate the temperature to every 6 minutes (60/10). + outside_temp = cara.data.weather.hourly_to_piecewise(temp_profile).refine(10) ventilation: models.Ventilation if self.window_type == 'window_sliding': @@ -318,6 +313,12 @@ class FormData: else: return models.MultipleVentilation((ventilation, infiltration_ventilation)) + def nearest_weather_station(self) -> cara.data.weather.WxStationRecordType: + wx_station = cara.data.weather.nearest_wx_station( + longitude=self.location_longitude, latitude=self.location_latitude + ) + return wx_station + def mask(self) -> models.Mask: # Initializes the mask type if mask wearing is "continuous", otherwise instantiates the mask attribute as # the "No mask"-mask @@ -621,8 +622,6 @@ def baseline_raw_form_data(): 'infected_lunch_start': '12:30', 'infected_people': '1', 'infected_start': '09:00', - 'location': 'Geneva', - 'location_coordinates': '46.2044, 6.1432', 'mask_type': 'Type I', 'mask_wearing_option': 'mask_off', 'mechanical_ventilation_type': '', diff --git a/cara/apps/calculator/static/js/form.js b/cara/apps/calculator/static/js/form.js index 40334e5b..70755549 100644 --- a/cara/apps/calculator/static/js/form.js +++ b/cara/apps/calculator/static/js/form.js @@ -566,8 +566,8 @@ $(document).ready(function() { id: candidate.address, text: candidate.address, country: candidate.attributes.country, - latitude: String(candidate.location.y), - longitude: String(candidate.location.x), + latitude: candidate.location.y, + longitude: candidate.location.x, } }), pagination: { @@ -602,8 +602,13 @@ function formatlocation(location) { } function formatLocationSelection(location) { - if (location.latitude != null && location.latitude != null) - $(document.getElementById("coordinates_input").value = (location.latitude + ',' + location.longitude)); + console.log(location); + if (location.latitude != null && location.latitude != null) { + console.log('setting!'); + console.log($('input[name="location_latitude"]')); + $('input[name="location_latitude"]').val(location.latitude); + $('input[name="location_longitude"]').val(location.longitude); + } return location.text; } diff --git a/cara/apps/calculator/templates/base/calculator.report.html.j2 b/cara/apps/calculator/templates/base/calculator.report.html.j2 index 46e397a0..781a241c 100644 --- a/cara/apps/calculator/templates/base/calculator.report.html.j2 +++ b/cara/apps/calculator/templates/base/calculator.report.html.j2 @@ -53,9 +53,9 @@

  • Room Volume: {{ model.concentration_model.room.volume }} m³

  • Room Central Heating: {{ "On" if form.room_heating_option else "Off" }}

    • -

  • Geographic Location: {{ form.location }}

    • - {% if form.ventilation_type == "natural_ventilation"%} -

  • Nearest weather station: {{ form.weather_station_location }}

    • +

  • Geographic Location: {{ form.location_name }}

    • + {% if form.ventilation_type == "natural_ventilation" %} +

  • Nearest weather station: {{ form.nearest_weather_station()[1].strip().title() }}

    • {% endif %} diff --git a/cara/apps/calculator/templates/calculator.form.html.j2 b/cara/apps/calculator/templates/calculator.form.html.j2 index b39a54d4..d5cb4bc1 100644 --- a/cara/apps/calculator/templates/calculator.form.html.j2 +++ b/cara/apps/calculator/templates/calculator.form.html.j2 @@ -107,11 +107,11 @@ v{{ calculator_version }} Please sen
    - -
    - + + +
    diff --git a/cara/apps/expert.py b/cara/apps/expert.py index 5a9273ef..664f97b3 100644 --- a/cara/apps/expert.py +++ b/cara/apps/expert.py @@ -360,10 +360,10 @@ class ModelWidgets(View): def _build_month(self, node) -> WidgetGroup: - month_choice = widgets.Select(options=list(data.Temperatures.keys()), value='1') + month_choice = widgets.Select(options=list(data.GenevaTemperatures.keys()), value='Jan') def on_month_change(change): - node.outside_temp = data.Temperatures[change['new']] + node.outside_temp = data.GenevaTemperatures[change['new']] month_choice.observe(on_month_change, names=['value']) return WidgetGroup( diff --git a/cara/data.py b/cara/data.py deleted file mode 100644 index 956a906a..00000000 --- a/cara/data.py +++ /dev/null @@ -1,93 +0,0 @@ -import numpy as np -from cara import models -import json -import urllib.request -from pathlib import Path -from scipy.spatial import cKDTree -import os -import typing - -weather_debug = False - - -def location_to_weather_stn(location_loc): - # expects a tuple (lat, long) - # returns: weather station ID, weather station name, weather station lat, long - search_coords = location_loc.split(',') - lat = [] - long = [] - station_array = [] - fixed_delimits = [0, 12, 13, 44, 51, 60, 69, 90, 91] - station_file = Path(__file__).parent / 'data' / 'cara_weather_stations.txt' - - for line in station_file.open('rt'): - start_end_positions = zip(fixed_delimits[:-1], fixed_delimits[1:]) - split_vals = [line[start:end] for start, end in start_end_positions] - station_location = [split_vals[0], - split_vals[2], split_vals[3], split_vals[4]] - station_array.append(station_location) - lat.append(split_vals[3]) - long.append(split_vals[4]) - - tree = cKDTree(np.c_[lat, long]) - dd, ii = tree.query(search_coords, k=[1]) - - return (station_array[ii[0]][0], station_array[ii[0]][1], station_array[ii[0]][2], station_array[ii[0]][3]) - - -def location_celcius_per_hour(location: object) -> typing.Dict[str, typing.List[float]]: - # expects a tuple (lat, long) - # returns a json format set of weather data - w_station = location_to_weather_stn(location) - with open(Path(__file__).parent / 'data' / 'global_weather_set.json', "r") as json_file: - weather_dict = json.load(json_file) - Location_hourly_temperatures_celsius_per_hour = weather_dict[w_station[0]] - if weather_debug: - print(location) - print("weather station name: ", w_station[1]) - print("weather station ref: ", w_station[0]) - print("weather station location: ", w_station[2], " ", w_station[3]) - print(Location_hourly_temperatures_celsius_per_hour) - return Location_hourly_temperatures_celsius_per_hour - - -# initialise with Geneva, change if location is different. -local_tempatures = { - '1': [0.2, -0.3, -0.5, -0.9, -1.1, -1.4, -1.5, -1.5, -1.1, 0.1, 1.5, - 2.8, 3.8, 4.4, 4.5, 4.4, 4.4, 3.9, 3.1, 2.7, 2.2, 1.7, 1.5, 1.1], - '2': [0.9, 0.3, 0.0, -0.5, -0.7, -1.1, -1.2, -1.1, -0.7, 0.8, 2.5, - 4.2, 5.4, 6.2, 6.3, 6.2, 6.1, 5.5, 4.5, 4.1, 3.5, 2.8, 2.5, 2.0], - '3': [4.2, 3.5, 3.1, 2.5, 2.1, 1.6, 1.5, 1.6, 2.2, 4.0, 6.3, 8.4, - 10.0, 11.1, 11.2, 11.1, 11.0, 10.2, 8.9, 8.3, 7.5, 6.7, 6.3, 5.6], - '4': [7.4, 6.7, 6.2, 5.5, 5.2, 4.7, 4.5, 4.6, 5.3, 7.2, 9.6, 11.9, - 13.7, 14.8, 14.9, 14.8, 14.7, 13.8, 12.4, 11.8, 10.9, 10.1, 9.6, 8.9], - '5': [11.8, 11.1, 10.6, 9.9, 9.5, 8.9, 8.8, 8.9, 9.6, 11.6, 14.2, 16.6, - 18.4, 19.6, 19.7, 19.6, 19.4, 18.6, 17.1, 16.5, 15.6, 14.6, 14.2, 13.4], - '6': [15.2, 14.4, 13.9, 13.2, 12.7, 12.2, 12.0, 12.1, 12.8, 15.0, 17.7, - 20.2, 22.1, 23.3, 23.5, 23.4, 23.2, 22.3, 20.8, 20.1, 19.1, 18.2, 17.7, 16.9], - '7': [17.6, 16.7, 16.1, 15.3, 14.9, 14.3, 14.1, 14.2, 15.0, 17.3, 20.2, - 23.0, 25.0, 26.3, 26.5, 26.4, 26.2, 25.2, 23.6, 22.8, 21.8, 20.8, 20.2, 19.4], - '8': [17.1, 16.2, 15.7, 14.9, 14.5, 13.9, 13.7, 13.8, 14.6, 16.9, 19.7, - 22.4, 24.4, 25.6, 25.8, 25.7, 25.5, 24.5, 22.9, 22.2, 21.2, 20.2, 19.7, 18.9], - '9': [13.4, 12.7, 12.2, 11.5, 11.2, 10.7, 10.5, 10.6, 11.3, 13.2, 15.6, - 17.9, 19.6, 20.8, 20.9, 20.8, 20.7, 19.8, 18.4, 17.8, 16.9, 16.1, 15.6, 14.9], - '10': [9.4, 8.8, 8.5, 7.9, 7.6, 7.2, 7.1, 7.2, 7.7, 9.3, 11.2, 13.0, - 14.4, 15.3, 15.4, 15.3, 15.2, 14.5, 13.4, 12.9, 12.2, 11.6, 11.2, 10.6], - '11': [4.0, 3.6, 3.3, 2.9, 2.6, 2.3, 2.2, 2.2, 2.7, 3.9, 5.5, 6.9, 8.0, - 8.7, 8.8, 8.7, 8.7, 8.1, 7.2, 6.8, 6.3, 5.7, 5.5, 5.0], - '12': [1.4, 1.0, 0.8, 0.4, 0.2, -0.0, -0.1, -0.1, 0.3, 1.3, 2.6, 3.8, - 4.7, 5.2, 5.3, 5.2, 5.2, 4.7, 4.0, 3.7, 3.2, 2.8, 2.6, 2.2] -} - - -# Geneva hourly temperatures as piecewise constant function (in Kelvin) -Temperatures_hourly = { - month: models.PiecewiseConstant(tuple(np.arange(25.)), - tuple(273.15+np.array(temperatures))) - for month, temperatures in local_tempatures.items() -} -# same temperatures on a finer temperature mesh -Temperatures = { - month: Temperatures_hourly[month].refine(refine_factor=10) - for month, temperatures in local_tempatures.items() -} diff --git a/cara/data/__init__.py b/cara/data/__init__.py new file mode 100644 index 00000000..353992e6 --- /dev/null +++ b/cara/data/__init__.py @@ -0,0 +1,51 @@ +import numpy as np +from cara import models + +# TODO: The values in this module to be removed and instead use the cara.data.weather functionality. + +# average temperature of each month, hour per hour (from midnight to 11 pm) +Geneva_hourly_temperatures_celsius_per_hour = { + 'Jan': [0.2, -0.3, -0.5, -0.9, -1.1, -1.4, -1.5, -1.5, -1.1, 0.1, 1.5, + 2.8, 3.8, 4.4, 4.5, 4.4, 4.4, 3.9, 3.1, 2.7, 2.2, 1.7, 1.5, 1.1], + 'Feb': [0.9, 0.3, 0.0, -0.5, -0.7, -1.1, -1.2, -1.1, -0.7, 0.8, 2.5, + 4.2, 5.4, 6.2, 6.3, 6.2, 6.1, 5.5, 4.5, 4.1, 3.5, 2.8, 2.5, 2.0], + 'Mar': [4.2, 3.5, 3.1, 2.5, 2.1, 1.6, 1.5, 1.6, 2.2, 4.0, 6.3, 8.4, + 10.0, 11.1, 11.2, 11.1, 11.0, 10.2, 8.9, 8.3, 7.5, 6.7, 6.3, 5.6], + 'Apr': [7.4, 6.7, 6.2, 5.5, 5.2, 4.7, 4.5, 4.6, 5.3, 7.2, 9.6, 11.9, + 13.7, 14.8, 14.9, 14.8, 14.7, 13.8, 12.4, 11.8, 10.9, 10.1, 9.6, 8.9], + 'May': [11.8, 11.1, 10.6, 9.9, 9.5, 8.9, 8.8, 8.9, 9.6, 11.6, 14.2, 16.6, + 18.4, 19.6, 19.7, 19.6, 19.4, 18.6, 17.1, 16.5, 15.6, 14.6, 14.2, 13.4], + 'Jun': [15.2, 14.4, 13.9, 13.2, 12.7, 12.2, 12.0, 12.1, 12.8, 15.0, 17.7, + 20.2, 22.1, 23.3, 23.5, 23.4, 23.2, 22.3, 20.8, 20.1, 19.1, 18.2, 17.7, 16.9], + 'Jul': [17.6, 16.7, 16.1, 15.3, 14.9, 14.3, 14.1, 14.2, 15.0, 17.3, 20.2, + 23.0, 25.0, 26.3, 26.5, 26.4, 26.2, 25.2, 23.6, 22.8, 21.8, 20.8, 20.2, 19.4], + 'Aug': [17.1, 16.2, 15.7, 14.9, 14.5, 13.9, 13.7, 13.8, 14.6, 16.9, 19.7, + 22.4, 24.4, 25.6, 25.8, 25.7, 25.5, 24.5, 22.9, 22.2, 21.2, 20.2, 19.7, 18.9], + 'Sep': [13.4, 12.7, 12.2, 11.5, 11.2, 10.7, 10.5, 10.6, 11.3, 13.2, 15.6, + 17.9, 19.6, 20.8, 20.9, 20.8, 20.7, 19.8, 18.4, 17.8, 16.9, 16.1, 15.6, 14.9], + 'Oct': [9.4, 8.8, 8.5, 7.9, 7.6, 7.2, 7.1, 7.2, 7.7, 9.3, 11.2, 13.0, + 14.4, 15.3, 15.4, 15.3, 15.2, 14.5, 13.4, 12.9, 12.2, 11.6, 11.2, 10.6], + 'Nov': [4.0, 3.6, 3.3, 2.9, 2.6, 2.3, 2.2, 2.2, 2.7, 3.9, 5.5, 6.9, 8.0, + 8.7, 8.8, 8.7, 8.7, 8.1, 7.2, 6.8, 6.3, 5.7, 5.5, 5.0], + 'Dec': [1.4, 1.0, 0.8, 0.4, 0.2, -0.0, -0.1, -0.1, 0.3, 1.3, 2.6, 3.8, + 4.7, 5.2, 5.3, 5.2, 5.2, 4.7, 4.0, 3.7, 3.2, 2.8, 2.6, 2.2] + } + + +# Geneva hourly temperatures as piecewise constant function (in Kelvin). +GenevaTemperatures_hourly = { + month: models.PiecewiseConstant( + # NOTE: It is important that the time type is float, not np.float, in + # order to allow hashability (for caching). + tuple(float(time) for time in range(25)), + tuple(273.15 + np.array(temperatures)), + ) + for month, temperatures in Geneva_hourly_temperatures_celsius_per_hour.items() +} + + +# Same temperatures on a finer temperature mesh (every 6 minutes). +GenevaTemperatures = { + month: GenevaTemperatures_hourly[month].refine(refine_factor=10) + for month, temperatures in Geneva_hourly_temperatures_celsius_per_hour.items() +} diff --git a/cara/data/weather.py b/cara/data/weather.py new file mode 100644 index 00000000..37ecde76 --- /dev/null +++ b/cara/data/weather.py @@ -0,0 +1,114 @@ +import functools +import json +from pathlib import Path +import typing + +import numpy as np +from scipy.spatial import cKDTree + +from cara import models + + +weather_debug = False + +DATA_LOCATION = Path(__file__).absolute().parent + + +WxStationIdType = str +MonthType = str +# HourlyTempType - 24 temperatures, one for each hour of the day (the average for the given month). +HourlyTempType = typing.List[float] + + +@functools.lru_cache() +def wx_data() -> typing.Dict[WxStationIdType, typing.Dict[MonthType, HourlyTempType]]: + """ + Load the weather data (temperature in kelvin). + + The data is structured by station location, and for each station location, by month. + + """ + with (DATA_LOCATION / 'global_weather_set.json').open("r") as json_file: + data = json.load(json_file) + + for station in list(data.keys()): + for month in list(data[station].keys()): + data[station][month] = tuple(273.15 + np.array(data[station][month])) + return data + + +WxStationRecordType = typing.Tuple[WxStationIdType, str, float, float] + + +@functools.lru_cache() +def wx_station_data() -> typing.Dict[WxStationIdType, WxStationRecordType]: + """ + Return a dictionary of ``station-id: station records``, where station records + are of the form ``(station-id, station-name, station-latitude, station-longitude)``. + + The stations returned are guaranteed to have valid weather data. + + """ + weather_data = wx_data() + station_data = {} + fixed_delimits = [0, 12, 13, 44, 51, 60, 69, 90, 91] + station_file = DATA_LOCATION / 'hadisd_station_fullinfo_v311_202001p.txt' + + for line in station_file.open('rt'): + start_end_positions = zip(fixed_delimits[:-1], fixed_delimits[1:]) + split_vals = [line[start:end] for start, end in start_end_positions] + station_location = ( + split_vals[0], split_vals[2], float(split_vals[3]), float(split_vals[4]), + ) + # We only consider stations with weather data, don't include the rest. + if split_vals[0] in weather_data: + station_data[split_vals[0]] = station_location + return station_data + + +@functools.lru_cache() +def _wx_station_kdtree() -> cKDTree: + """Build a kd-tree of wx station longitude & latitudes (note the coordinate order)""" + station_data = wx_station_data().values() + coords = np.array([(stn_record[3], stn_record[2]) for stn_record in station_data]) + return cKDTree(coords) + + +def mean_hourly_temperatures(wx_station: str, month: int) -> HourlyTempType: + """ + Return the mean monthly temperature for the given weather station and month. + + Returns + ------- + + temperatures: List[24 floats] + A list containing 24 temperature values, one for each hour, in kelvin. + Index 0 of the result corresponds to hour 00:00-01:00, and index 23 (the last) to 23:00-00:00. + + """ + return wx_data()[wx_station][str(month)] + + +def hourly_to_piecewise(hourly_data: HourlyTempType) -> models.PiecewiseConstant: + """ + Transform a list of 24 floats into a :class:`cara.models.PiecewiseConstant`. + + """ + pc = models.PiecewiseConstant( + # NOTE: It is important that the time type is float, not np.float, in + # order to allow hashability (for caching). + tuple(float(time) for time in range(25)), + tuple(hourly_data), + ) + return pc + + +def nearest_wx_station(*, longitude: float, latitude: float) -> WxStationRecordType: + """ + Given a latitude & longitude, return the nearest station with valid weather data. + + """ + ktree = _wx_station_kdtree() + station_data = list(wx_station_data().values()) + dd, ii = ktree.query((longitude, latitude), k=[1]) + return station_data[ii[0]] diff --git a/cara/tests/apps/calculator/test_model_generator.py b/cara/tests/apps/calculator/test_model_generator.py index 98a12438..82ab2279 100644 --- a/cara/tests/apps/calculator/test_model_generator.py +++ b/cara/tests/apps/calculator/test_model_generator.py @@ -1,16 +1,14 @@ import dataclasses +import typing -import pytest import numpy as np import numpy.testing as npt -from pathlib import Path -import json +import pytest from cara.apps.calculator import model_generator from cara.apps.calculator.model_generator import _hours2timestring from cara.apps.calculator.model_generator import minutes_since_midnight from cara import models -from cara import data def test_model_from_dict(baseline_form_data): @@ -35,13 +33,6 @@ def test_blend_expiration(): def test_ventilation_slidingwindow(baseline_form: model_generator.FormData): - room = models.Room(75) - window = models.SlidingWindow( - active=models.PeriodicInterval(period=120, duration=10), - inside_temp=models.PiecewiseConstant((0, 24), (293,)), - outside_temp=data.Temperatures['12'], - window_height=1.6, opening_length=0.6, - ) baseline_form.ventilation_type = 'natural_ventilation' baseline_form.windows_duration = 10 baseline_form.windows_frequency = 120 @@ -51,19 +42,28 @@ def test_ventilation_slidingwindow(baseline_form: model_generator.FormData): baseline_form.window_height = 1.6 baseline_form.opening_distance = 0.6 - ts = np.linspace(8, 16, 100) - np.testing.assert_allclose([window.air_exchange(room, t)+0.25 for t in ts], - [baseline_form.ventilation().air_exchange(room, t) for t in ts]) + baseline_vent = baseline_form.ventilation() + assert isinstance(baseline_vent, models.MultipleVentilation) + baseline_window = baseline_vent.ventilations[0] + assert isinstance(baseline_window, models.SlidingWindow) + + window = models.SlidingWindow( + active=models.PeriodicInterval(period=120, duration=10), + inside_temp=models.PiecewiseConstant((0, 24), (293,)), + outside_temp=baseline_window.outside_temp, + window_height=1.6, opening_length=0.6, + ) + + ach = models.AirChange( + active=models.PeriodicInterval(period=120, duration=120), + air_exch=0.25, + ) + ventilation = models.MultipleVentilation((window, ach)) + + assert ventilation == baseline_vent def test_ventilation_hingedwindow(baseline_form: model_generator.FormData): - room = models.Room(75) - window = models.HingedWindow( - active=models.PeriodicInterval(period=120, duration=10), - inside_temp=models.PiecewiseConstant((0, 24), (293,)), - outside_temp=data.Temperatures['12'], - window_height=1.6, window_width=1., opening_length=0.6, - ) baseline_form.ventilation_type = 'natural_ventilation' baseline_form.windows_duration = 10 baseline_form.windows_frequency = 120 @@ -74,9 +74,24 @@ def test_ventilation_hingedwindow(baseline_form: model_generator.FormData): baseline_form.window_width = 1. baseline_form.opening_distance = 0.6 - ts = np.linspace(8, 16, 100) - np.testing.assert_allclose([window.air_exchange(room, t)+0.25 for t in ts], - [baseline_form.ventilation().air_exchange(room, t) for t in ts]) + baseline_vent = baseline_form.ventilation() + assert isinstance(baseline_vent, models.MultipleVentilation) + baseline_window = baseline_vent.ventilations[0] + assert isinstance(baseline_window, models.HingedWindow) + + window = models.HingedWindow( + active=models.PeriodicInterval(period=120, duration=10), + inside_temp=models.PiecewiseConstant((0, 24), (293,)), + outside_temp=baseline_window.outside_temp, + window_height=1.6, window_width=1., opening_length=0.6, + ) + ach = models.AirChange( + active=models.PeriodicInterval(period=120, duration=120), + air_exch=0.25, + ) + ventilation = models.MultipleVentilation((window, ach)) + + assert ventilation == baseline_vent def test_ventilation_mechanical(baseline_form: model_generator.FormData): @@ -110,19 +125,6 @@ def test_ventilation_airchanges(baseline_form: model_generator.FormData): def test_ventilation_window_hepa(baseline_form: model_generator.FormData): - room = models.Room(75) - window = models.SlidingWindow( - active=models.PeriodicInterval(period=120, duration=10), - inside_temp=models.PiecewiseConstant((0, 24), (293,)), - outside_temp=data.Temperatures['12'], - window_height=1.6, opening_length=0.6, - ) - hepa = models.HEPAFilter( - active=models.PeriodicInterval(period=120, duration=120), - q_air_mech=250., - ) - ventilation = models.MultipleVentilation((window, hepa)) - baseline_form.ventilation_type = 'natural_ventilation' baseline_form.windows_duration = 10 baseline_form.windows_frequency = 120 @@ -132,9 +134,29 @@ def test_ventilation_window_hepa(baseline_form: model_generator.FormData): baseline_form.opening_distance = 0.6 baseline_form.hepa_option = True - ts = np.linspace(9, 17, 100) - np.testing.assert_allclose([ventilation.air_exchange(room, t)+0.25 for t in ts], - [baseline_form.ventilation().air_exchange(room, t) for t in ts]) + baseline_vent = baseline_form.ventilation() + assert isinstance(baseline_vent, models.MultipleVentilation) + baseline_window = baseline_vent.ventilations[0] + assert isinstance(baseline_window, models.SlidingWindow) + + # Now build the equivalent ventilation instance directly, and compare. + window = models.SlidingWindow( + active=models.PeriodicInterval(period=120, duration=10), + inside_temp=models.PiecewiseConstant((0, 24), (293,)), + outside_temp=baseline_window.outside_temp, + window_height=1.6, opening_length=0.6, + ) + hepa = models.HEPAFilter( + active=models.PeriodicInterval(period=120, duration=120), + q_air_mech=250., + ) + ach = models.AirChange( + active=models.PeriodicInterval(period=120, duration=120), + air_exch=0.25, + ) + ventilation = models.MultipleVentilation((window, hepa, ach)) + + assert ventilation == baseline_vent def present_times(interval: models.Interval) -> models.BoundarySequence_t: @@ -163,8 +185,7 @@ def test_exposed_present_intervals(baseline_form: model_generator.FormData): baseline_form.exposed_finish = minutes_since_midnight(17 * 60) baseline_form.exposed_lunch_start = minutes_since_midnight(12 * 60 + 30) baseline_form.exposed_lunch_finish = minutes_since_midnight(13 * 60 + 30) - correct = ((9, 10+37/60), (10+52/60, 12.5), - (13.5, 15+7/60), (15+22/60, 17.0)) + correct = ((9, 10+37/60), (10+52/60, 12.5), (13.5, 15+7/60), (15+22/60, 17.0)) assert present_times(baseline_form.exposed_present_interval()) == correct @@ -172,50 +193,37 @@ def test_present_intervals_common_breaks(baseline_form: model_generator.FormData baseline_form.infected_dont_have_breaks_with_exposed = False baseline_form.infected_coffee_duration = baseline_form.exposed_coffee_duration = 15 baseline_form.infected_coffee_break_option = baseline_form.exposed_coffee_break_option = 'coffee_break_2' - baseline_form.exposed_lunch_start = baseline_form.infected_lunch_start = minutes_since_midnight( - 12 * 60 + 30) - baseline_form.exposed_lunch_finish = baseline_form.infected_lunch_finish = minutes_since_midnight( - 13 * 60 + 30) + baseline_form.exposed_lunch_start = baseline_form.infected_lunch_start = minutes_since_midnight(12 * 60 + 30) + baseline_form.exposed_lunch_finish = baseline_form.infected_lunch_finish = minutes_since_midnight(13 * 60 + 30) baseline_form.exposed_start = minutes_since_midnight(9 * 60) baseline_form.exposed_finish = minutes_since_midnight(17 * 60) baseline_form.infected_start = minutes_since_midnight(9 * 60) baseline_form.infected_finish = minutes_since_midnight(16 * 60) - correct_exposed = ((9, 10+37/60), (10+52/60, 12.5), - (13.5, 15+7/60), (15+22/60, 17.0)) - correct_infected = ((9, 10+37/60), (10+52/60, 12.5), - (13.5, 15+7/60), (15+22/60, 16.0)) - assert present_times( - baseline_form.exposed_present_interval()) == correct_exposed - assert present_times( - baseline_form.infected_present_interval()) == correct_infected + correct_exposed = ((9, 10+37/60), (10+52/60, 12.5), (13.5, 15+7/60), (15+22/60, 17.0)) + correct_infected = ((9, 10+37/60), (10+52/60, 12.5), (13.5, 15+7/60), (15+22/60, 16.0)) + assert present_times(baseline_form.exposed_present_interval()) == correct_exposed + assert present_times(baseline_form.infected_present_interval()) == correct_infected def test_present_intervals_split_breaks(baseline_form: model_generator.FormData): baseline_form.infected_dont_have_breaks_with_exposed = True baseline_form.infected_coffee_duration = baseline_form.exposed_coffee_duration = 15 baseline_form.infected_coffee_break_option = baseline_form.exposed_coffee_break_option = 'coffee_break_2' - baseline_form.infected_lunch_start = baseline_form.exposed_lunch_start = minutes_since_midnight( - 12 * 60 + 30) - baseline_form.infected_lunch_finish = baseline_form.exposed_lunch_finish = minutes_since_midnight( - 13 * 60 + 30) + baseline_form.infected_lunch_start = baseline_form.exposed_lunch_start = minutes_since_midnight(12 * 60 + 30) + baseline_form.infected_lunch_finish = baseline_form.exposed_lunch_finish = minutes_since_midnight(13 * 60 + 30) baseline_form.exposed_start = minutes_since_midnight(9 * 60) baseline_form.exposed_finish = minutes_since_midnight(17 * 60) baseline_form.infected_start = minutes_since_midnight(9 * 60) baseline_form.infected_finish = minutes_since_midnight(16 * 60) - correct_exposed = ((9, 10+37/60), (10+52/60, 12.5), - (13.5, 15+7/60), (15+22/60, 17.0)) - correct_infected = ((9, 10+37/60), (10+52/60, 12.5), - (13.5, 14+37/60), (14+52/60, 16.0)) - assert present_times( - baseline_form.exposed_present_interval()) == correct_exposed - assert present_times( - baseline_form.infected_present_interval()) == correct_infected + correct_exposed = ((9, 10+37/60), (10+52/60, 12.5), (13.5, 15+7/60), (15+22/60, 17.0)) + correct_infected = ((9, 10+37/60), (10+52/60, 12.5), (13.5, 14+37/60), (14+52/60, 16.0)) + assert present_times(baseline_form.exposed_present_interval()) == correct_exposed + assert present_times(baseline_form.infected_present_interval()) == correct_infected def test_exposed_present_intervals_starting_with_lunch(baseline_form: model_generator.FormData): baseline_form.exposed_coffee_break_option = 'coffee_break_0' - baseline_form.exposed_start = baseline_form.exposed_lunch_start = minutes_since_midnight( - 13 * 60) + baseline_form.exposed_start = baseline_form.exposed_lunch_start = minutes_since_midnight(13 * 60) baseline_form.exposed_finish = minutes_since_midnight(18 * 60) baseline_form.exposed_lunch_finish = minutes_since_midnight(14 * 60) correct = ((14.0, 18.0), ) @@ -225,8 +233,7 @@ def test_exposed_present_intervals_starting_with_lunch(baseline_form: model_gene def test_exposed_present_intervals_ending_with_lunch(baseline_form: model_generator.FormData): baseline_form.exposed_coffee_break_option = 'coffee_break_0' baseline_form.exposed_start = minutes_since_midnight(11 * 60) - baseline_form.exposed_finish = baseline_form.exposed_lunch_start = minutes_since_midnight( - 13 * 60) + baseline_form.exposed_finish = baseline_form.exposed_lunch_start = minutes_since_midnight(13 * 60) baseline_form.exposed_lunch_finish = minutes_since_midnight(14 * 60) correct = ((11.0, 13.0),) assert present_times(baseline_form.exposed_present_interval()) == correct @@ -308,8 +315,7 @@ def breaks_every_25_mins_for_20_mins(baseline_form: model_generator.FormData): baseline_form.exposed_lunch_finish = time2mins("12:15") baseline_form.exposed_lunch_option = True - breaks = baseline_form.exposed_coffee_break_times( - ) + baseline_form.exposed_lunch_break_times() + breaks = baseline_form.exposed_coffee_break_times() + baseline_form.exposed_lunch_break_times() interval = baseline_form.present_interval( baseline_form.exposed_start, baseline_form.exposed_finish, breaks=breaks, ) @@ -326,8 +332,7 @@ def breaks_every_25_mins_for_20_mins(baseline_form: model_generator.FormData): def test_present_after_two_breaks_for_small_interval(breaks_every_25_mins_for_20_mins): - breaks = breaks_every_25_mins_for_20_mins.exposed_coffee_break_times( - ) + breaks_every_25_mins_for_20_mins.exposed_lunch_break_times() + breaks = breaks_every_25_mins_for_20_mins.exposed_coffee_break_times() + breaks_every_25_mins_for_20_mins.exposed_lunch_break_times() # The first two breaks start at 10:25 and 11:10. interval = breaks_every_25_mins_for_20_mins.present_interval( time2mins("11:35"), time2mins("11:40"), breaks=breaks, @@ -337,8 +342,7 @@ def test_present_after_two_breaks_for_small_interval(breaks_every_25_mins_for_20 def test_present_only_during_second_break(breaks_every_25_mins_for_20_mins): - breaks = breaks_every_25_mins_for_20_mins.exposed_coffee_break_times( - ) + breaks_every_25_mins_for_20_mins.exposed_lunch_break_times() + breaks = breaks_every_25_mins_for_20_mins.exposed_coffee_break_times() + breaks_every_25_mins_for_20_mins.exposed_lunch_break_times() # The first two breaks start at 10:25 and 11:10. interval = breaks_every_25_mins_for_20_mins.present_interval( time2mins("11:15"), time2mins("11:20"), breaks=breaks @@ -366,10 +370,8 @@ def test_no_breaks(baseline_form: model_generator.FormData): baseline_form.infected_finish = minutes_since_midnight(15 * 60) exposed_correct = ((9, 17),) infected_correct = ((10, 15),) - assert present_times( - baseline_form.exposed_present_interval()) == exposed_correct - assert present_times( - baseline_form.infected_present_interval()) == infected_correct + assert present_times(baseline_form.exposed_present_interval()) == exposed_correct + assert present_times(baseline_form.infected_present_interval()) == infected_correct def test_coffee_lunch_breaks(baseline_form: model_generator.FormData): @@ -381,8 +383,7 @@ def test_coffee_lunch_breaks(baseline_form: model_generator.FormData): baseline_form.exposed_lunch_finish = minutes_since_midnight(13 * 60 + 30) correct = ((9, 9+50/60), (10+20/60, 11+10/60), (11+40/60, 12+30/60), (13+30/60, 14+40/60), (15+10/60, 16+20/60), (16+50/60, 18)) - np.testing.assert_allclose(present_times( - baseline_form.exposed_present_interval()), correct, rtol=1e-14) + np.testing.assert_allclose(present_times(baseline_form.exposed_present_interval()), correct, rtol=1e-14) def test_coffee_lunch_breaks_unbalance(baseline_form: model_generator.FormData): @@ -393,8 +394,7 @@ def test_coffee_lunch_breaks_unbalance(baseline_form: model_generator.FormData): baseline_form.exposed_lunch_start = minutes_since_midnight(12 * 60 + 30) baseline_form.exposed_lunch_finish = minutes_since_midnight(13 * 60 + 30) correct = ((9, 9+50/60), (10+20/60, 11+10/60), (11+40/60, 12+30/60)) - np.testing.assert_allclose(present_times( - baseline_form.exposed_present_interval()), correct, rtol=1e-14) + np.testing.assert_allclose(present_times(baseline_form.exposed_present_interval()), correct, rtol=1e-14) def test_coffee_breaks(baseline_form: model_generator.FormData): @@ -403,10 +403,8 @@ def test_coffee_breaks(baseline_form: model_generator.FormData): baseline_form.exposed_start = minutes_since_midnight(9 * 60) baseline_form.exposed_finish = minutes_since_midnight(10 * 60) baseline_form.exposed_lunch_option = False - correct = ((9, 9+4/60), (9+14/60, 9+18/60), (9+28/60, 9+32/60), - (9+42/60, 9+46/60), (9+56/60, 10)) - np.testing.assert_allclose(present_times( - baseline_form.exposed_present_interval()), correct, rtol=1e-14) + correct = ((9, 9+4/60), (9+14/60, 9+18/60), (9+28/60, 9+32/60), (9+42/60, 9+46/60), (9+56/60, 10)) + np.testing.assert_allclose(present_times(baseline_form.exposed_present_interval()), correct, rtol=1e-14) def test_key_validation(baseline_form_data): @@ -439,8 +437,7 @@ def test_key_validation_mech_ventilation_type_na(baseline_form_data): def test_default_types(): # Validate that FormData._DEFAULTS are complete and of the correct type. # Validate that we have the right types and matching attributes to the DEFAULTS. - fields = {field.name: field for field in dataclasses.fields( - model_generator.FormData)} + fields = {field.name: field for field in dataclasses.fields(model_generator.FormData)} for field, value in model_generator.FormData._DEFAULTS.items(): if field not in fields: raise ValueError(f"Unmatched default {field}") @@ -454,12 +451,10 @@ def test_default_types(): continue if field in model_generator._CAST_RULES_FORM_ARG_TO_NATIVE: - value = model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[field]( - value) + value = model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[field](value) if not isinstance(value, field_type): - raise TypeError( - f'{field} has type {field_type}, got {type(value)}') + raise TypeError(f'{field} has type {field_type}, got {type(value)}') for field in fields.values(): assert field.name in model_generator.FormData._DEFAULTS, f"No default set for field name {field.name}" @@ -471,28 +466,5 @@ def test_form_to_dict(baseline_form): assert 1 < len(stripped) < len(full) assert 'exposed_coffee_break_option' in stripped # If we set the value to the default one, it should no longer turn up in the dictionary. - baseline_form.exposed_coffee_break_option = model_generator.FormData._DEFAULTS[ - 'exposed_coffee_break_option'] - assert 'exposed_coffee_break_option' not in baseline_form.to_dict( - baseline_form, strip_defaults=True) - - -def test_weather_stations(): - fixed_delimits = [0, 12, 13, 44, 51, 60, 69, 90, 91] - - station_file = Path(__file__).parent.parent.parent.parent / 'data' / \ - 'hadisd_station_fullinfo_v311_202001p.txt' - - with open(Path(__file__).parent.parent.parent.parent / 'data' / 'global_weather_set.json', "r") as json_file: - weather_dict = json.load(json_file) - - for line in station_file.open('rt'): - start_end_positions = zip(fixed_delimits[:-1], fixed_delimits[1:]) - split_vals = [line[start:end] for start, end in start_end_positions] - - station_id = split_vals[0] - # Check if weather station exists - temp_dict = weather_dict[station_id] - - for month in range(1, 13): - assert not np.any(np.isnan(temp_dict[str(month)])) + baseline_form.exposed_coffee_break_option = model_generator.FormData._DEFAULTS['exposed_coffee_break_option'] + assert 'exposed_coffee_break_option' not in baseline_form.to_dict(baseline_form, strip_defaults=True) diff --git a/cara/tests/data/__init__.py b/cara/tests/data/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/cara/tests/data/test_weather.py b/cara/tests/data/test_weather.py new file mode 100644 index 00000000..b0f75611 --- /dev/null +++ b/cara/tests/data/test_weather.py @@ -0,0 +1,11 @@ +import cara.data.weather as wx + + +def test_nearest_wx_station(): + melbourne_lat, melbourne_lon = -37.81739, 144.96751 + station_rec = wx.nearest_wx_station(longitude=melbourne_lon, latitude=melbourne_lat) + + station_name = station_rec[1].strip() + # Note: For Melbourne, the nearest station is 'MELBOURNE REGIONAL OFFICE', + # but the nearest location with suitable wx data is 'MELBOURNE ESSENDON' + assert station_name == 'MELBOURNE ESSENDON' diff --git a/cara/tests/models/test_piecewiseconstant.py b/cara/tests/models/test_piecewiseconstant.py index 1f90a5a9..a0ba14f0 100644 --- a/cara/tests/models/test_piecewiseconstant.py +++ b/cara/tests/models/test_piecewiseconstant.py @@ -81,5 +81,5 @@ def test_piecewiseconstant_vs_interval(time): def test_piecewiseconstant_transition_times(): - outside_temp = data.Temperatures['1'] + outside_temp = data.GenevaTemperatures['Jan'] assert set(outside_temp.transition_times) == outside_temp.interval().transition_times() diff --git a/cara/tests/test_known_quantities.py b/cara/tests/test_known_quantities.py index 6f67b834..89c0268d 100644 --- a/cara/tests/test_known_quantities.py +++ b/cara/tests/test_known_quantities.py @@ -9,7 +9,7 @@ import cara.data as data def test_no_mask_superspeading_emission_rate(baseline_model): expected_rate = 48500. npt.assert_allclose( - [baseline_model.infected.emission_rate(t) for t in [0, 1, 4, 4.5, 5, 8, 9]], + [baseline_model.infected.emission_rate(float(t)) for t in [0, 1, 4, 4.5, 5, 8, 9]], [0, expected_rate, expected_rate, 0, 0, expected_rate, 0], rtol=1e-12 ) @@ -19,8 +19,8 @@ def test_no_mask_superspeading_emission_rate(baseline_model): def baseline_periodic_window(): return models.SlidingWindow( active=models.PeriodicInterval(period=120, duration=15), - inside_temp=models.PiecewiseConstant((0,24),(293,)), - outside_temp=models.PiecewiseConstant((0,24),(283,)), + inside_temp=models.PiecewiseConstant((0., 24.), (293,)), + outside_temp=models.PiecewiseConstant((0., 24.), (283,)), window_height=1.6, opening_length=0.6, ) @@ -41,7 +41,7 @@ def baseline_periodic_hepa(): def test_concentrations(baseline_model): # expected concentrations were computed analytically ts = [0, 4, 5, 7, 10] - concentrations = [baseline_model.concentration(t) for t in ts] + concentrations = [baseline_model.concentration(float(t)) for t in ts] npt.assert_allclose( concentrations, [0.000000e+00, 20.805628, 6.602814e-13, 20.805628, 2.09545e-26], @@ -55,7 +55,7 @@ def test_smooth_concentrations(baseline_model): dx = 0.002 dy_limit = 0.2 # Anything more than this (in relative) is a bit steep. ts = np.arange(0, 10, dx) - concentrations = [baseline_model.concentration(t) for t in ts] + concentrations = [baseline_model.concentration(float(t)) for t in ts] assert np.abs(np.diff(concentrations)).max()/np.mean(concentrations) < dy_limit @@ -69,7 +69,7 @@ def build_model(interval_duration): infected=models.InfectedPopulation( number=1, virus=models.Virus.types['SARS_CoV_2'], - presence=models.SpecificInterval(((0, 4), (5, 8))), + presence=models.SpecificInterval(((0., 4.), (5., 8.))), mask=models.Mask.types['No mask'], activity=models.Activity.types['Light activity'], expiration=models.Expiration.types['Superspreading event'], @@ -78,7 +78,7 @@ def build_model(interval_duration): return model -def test_concentrations_startup(baseline_model): +def test_concentrations_startup(): # The concentrations should be the same until the beginning of the # first time that the ventilation is disabled. m1 = build_model(interval_duration=120) @@ -183,28 +183,38 @@ def test_multiple_ventilation_HEPA_HVAC_AirChange(volume, expected_value): ], ) def test_windowopening(time, expected_value): - tempOutside = models.PiecewiseConstant((0,10,24),(273.15,283.15)) - tempInside = models.PiecewiseConstant((0,24),(293.15,)) - w = models.SlidingWindow(active=models.SpecificInterval([(0,24)]), - inside_temp=tempInside,outside_temp=tempOutside, - window_height=1.,opening_length=0.6) - npt.assert_allclose(w.air_exchange(models.Room(volume=68),time), - expected_value,rtol=1e-5) + tempOutside = models.PiecewiseConstant((0., 10., 24.),(273.15, 283.15)) + tempInside = models.PiecewiseConstant((0., 24.), (293.15,)) + w = models.SlidingWindow( + active=models.SpecificInterval([(0., 24.)]), + inside_temp=tempInside,outside_temp=tempOutside, + window_height=1., opening_length=0.6, + ) + npt.assert_allclose( + w.air_exchange(models.Room(volume=68), time), expected_value, rtol=1e-5 + ) -def build_hourly_dependent_model(month, intervals_open=((7.5, 8.5),), - intervals_presence_infected=((0, 4), (5, 7.5)), - artificial_refinement=False, - temperatures=data.Temperatures_hourly): +def build_hourly_dependent_model( + month, + intervals_open=((7.5, 8.5),), + intervals_presence_infected=((0., 4.), (5., 7.5)), + artificial_refinement=False, + temperatures=data.GenevaTemperatures_hourly +): if artificial_refinement: # 5-fold increase of number of times, WITHOUT interpolation # (hence transparent for the results) refine_factor = 2 - times_refined = tuple(np.linspace(0.,24, - refine_factor*len(temperatures[month].values)+1)) - temperatures_refined = tuple(np.hstack([[v]*refine_factor - for v in temperatures[month].values])) - outside_temp = models.PiecewiseConstant(times_refined,temperatures_refined) + times_refined = tuple( + float(t) for t in np.linspace( + 0., 24, refine_factor * len(temperatures[month].values) + 1 + ) + ) + temperatures_refined = tuple(np.hstack( + [[v] * refine_factor for v in temperatures[month].values] + )) + outside_temp = models.PiecewiseConstant(times_refined, temperatures_refined) else: outside_temp = temperatures[month] @@ -212,7 +222,7 @@ def build_hourly_dependent_model(month, intervals_open=((7.5, 8.5),), room=models.Room(volume=75), ventilation=models.SlidingWindow( active=models.SpecificInterval(intervals_open), - inside_temp=models.PiecewiseConstant((0,24),(293,)), + inside_temp=models.PiecewiseConstant((0., 24.), (293, )), outside_temp=outside_temp, window_height=1.6, opening_length=0.6, ), @@ -233,14 +243,14 @@ def build_constant_temp_model(outside_temp, intervals_open=((7.5, 8.5),)): room=models.Room(volume=75), ventilation=models.SlidingWindow( active=models.SpecificInterval(intervals_open), - inside_temp=models.PiecewiseConstant((0,24),(293,)), - outside_temp=models.PiecewiseConstant((0,24),(outside_temp,)), + inside_temp=models.PiecewiseConstant((0., 24.), (293,)), + outside_temp=models.PiecewiseConstant((0., 24.), (outside_temp,)), window_height=1.6, opening_length=0.6, ), infected=models.InfectedPopulation( number=1, virus=models.Virus.types['SARS_CoV_2'], - presence=models.SpecificInterval(((0, 4), (5, 7.5))), + presence=models.SpecificInterval(((0., 4.), (5., 7.5))), mask=models.Mask.types['No mask'], activity=models.Activity.types['Light activity'], expiration=models.Expiration.types['Superspreading event'], @@ -253,21 +263,22 @@ def build_hourly_dependent_model_multipleventilation(month, intervals_open=((7.5 vent = models.MultipleVentilation(( models.SlidingWindow( active=models.SpecificInterval(intervals_open), - inside_temp=models.PiecewiseConstant((0,24),(293,)), - outside_temp=data.Temperatures[month], + inside_temp=models.PiecewiseConstant((0., 24.), (293,)), + outside_temp=data.GenevaTemperatures[month], window_height=1.6, opening_length=0.6, ), models.HEPAFilter( - active=models.SpecificInterval(((0,24),)), - q_air_mech=500., - ))) + active=models.SpecificInterval(((0., 24.),)), + q_air_mech=500., + ), + )) model = models.ConcentrationModel( room=models.Room(volume=75), ventilation=vent, infected=models.InfectedPopulation( number=1, virus=models.Virus.types['SARS_CoV_2'], - presence=models.SpecificInterval(((0, 4), (5, 7.5))), + presence=models.SpecificInterval(((0., 4.), (5., 7.5))), mask=models.Mask.types['No mask'], activity=models.Activity.types['Light activity'], expiration=models.Expiration.types['Superspreading event'], @@ -278,7 +289,7 @@ def build_hourly_dependent_model_multipleventilation(month, intervals_open=((7.5 @pytest.mark.parametrize( "month, temperatures", - data.local_tempatures.items(), + data.Geneva_hourly_temperatures_celsius_per_hour.items(), ) @pytest.mark.parametrize( "time", @@ -288,12 +299,12 @@ def test_concentrations_hourly_dep_temp_vs_constant(month, temperatures, time): # The concentrations should be the same up to 8 AM (time when the # temperature changes DURING the window opening). m1 = build_hourly_dependent_model(month) - m2 = build_constant_temp_model(temperatures[7]+273.15) + m2 = build_constant_temp_model(temperatures[7] + 273.15) npt.assert_allclose(m1.concentration(time), m2.concentration(time), rtol=1e-5) @pytest.mark.parametrize( "month, temperatures", - data.local_tempatures.items(), + data.Geneva_hourly_temperatures_celsius_per_hour.items(), ) @pytest.mark.parametrize( "time", @@ -301,20 +312,23 @@ def test_concentrations_hourly_dep_temp_vs_constant(month, temperatures, time): ) def test_concentrations_hourly_dep_temp_startup(month, temperatures, time): # The concentrations should be the zero up to the first presence time - # of an infecter person. - m = build_hourly_dependent_model(month,((0.,0.5),(1,1.5),(4,4.5),(7.5,8)), - ((8,12.),)) + # of an infected person. + m = build_hourly_dependent_model( + month, + ((0., 0.5), (1., 1.5), (4., 4.5), (7.5, 8), ), + ((8., 12.), ), + ) assert m.concentration(time) == 0. def test_concentrations_hourly_dep_multipleventilation(): - m = build_hourly_dependent_model_multipleventilation('1') + m = build_hourly_dependent_model_multipleventilation('Jan') m.concentration(12.) @pytest.mark.parametrize( "month_temp_item", - data.local_tempatures.items(), + data.Geneva_hourly_temperatures_celsius_per_hour.items(), ) @pytest.mark.parametrize( "time", @@ -323,19 +337,22 @@ def test_concentrations_hourly_dep_multipleventilation(): def test_concentrations_hourly_dep_adding_artificial_transitions(month_temp_item, time): month, temperatures = month_temp_item # Adding a second opening inside the first one should not change anything - m1 = build_hourly_dependent_model(month,intervals_open=((7.5, 8.5),)) - m2 = build_hourly_dependent_model(month,intervals_open=((7.5, 8.5),(8.,8.1))) + m1 = build_hourly_dependent_model(month, intervals_open=((7.5, 8.5), )) + m2 = build_hourly_dependent_model(month, intervals_open=((7.5, 8.5), (8., 8.1), )) npt.assert_allclose(m1.concentration(time), m2.concentration(time), rtol=1e-5) @pytest.mark.parametrize( "time", - list(np.random.random_sample(10)*24.)+list(np.arange(0,24.5,0.5)), + ( + [float(t) for t in np.random.random_sample(10) * 24.] # type: ignore + + [float(t) for t in np.arange(0, 24.5, 0.5)] + ), ) def test_concentrations_refine_times(time): - month = '1' - m1 = build_hourly_dependent_model(month,intervals_open=((0, 24),)) - m2 = build_hourly_dependent_model(month,intervals_open=((0, 24),), + month = 'Jan' + m1 = build_hourly_dependent_model(month, intervals_open=((0., 24.),)) + m2 = build_hourly_dependent_model(month, intervals_open=((0., 24.),), artificial_refinement=True) npt.assert_allclose(m1.concentration(time), m2.concentration(time), rtol=1e-8) @@ -350,7 +367,7 @@ def build_exposure_model(concentration_model): activity=infected.activity, mask=infected.mask, ), - fraction_deposited = 1., + fraction_deposited=1., ) @@ -359,16 +376,16 @@ def build_exposure_model(concentration_model): @pytest.mark.parametrize( "month, expected_exposure", [ - ['1', 496.5427], - ['6', 1898.1354], + ['Jan', 496.5427], + ['Jun', 1898.1354], ], ) def test_exposure_hourly_dep(month,expected_exposure): m = build_exposure_model( build_hourly_dependent_model( month, - intervals_open=((0,24),), - intervals_presence_infected=((8, 12), (13, 17)) + intervals_open=((0., 24.), ), + intervals_presence_infected=((8., 12.), (13., 17.)) ) ) exposure = m.exposure() @@ -380,17 +397,17 @@ def test_exposure_hourly_dep(month,expected_exposure): @pytest.mark.parametrize( "month, expected_exposure", [ - ['1', 499.6921], - ['6', 2007.59925], + ['Jan', 499.6921], + ['Jun', 2007.59925], ], ) def test_exposure_hourly_dep_refined(month,expected_exposure): m = build_exposure_model( build_hourly_dependent_model( month, - intervals_open=((0, 24),), - intervals_presence_infected=((8, 12), (13, 17)), - temperatures=data.Temperatures, + intervals_open=((0., 24.),), + intervals_presence_infected=((8., 12.), (13., 17.)), + temperatures=data.GenevaTemperatures, ) ) exposure = m.exposure() diff --git a/cara/tests/test_monte_carlo_full_models.py b/cara/tests/test_monte_carlo_full_models.py index 8776cb13..5cf88198 100644 --- a/cara/tests/test_monte_carlo_full_models.py +++ b/cara/tests/test_monte_carlo_full_models.py @@ -26,12 +26,12 @@ def shared_office_mc(): ( models.SlidingWindow( active=models.PeriodicInterval(period=120, duration=10), - inside_temp=models.PiecewiseConstant((0, 24), (293,)), - outside_temp=models.PiecewiseConstant((0, 24), (283,)), + inside_temp=models.PiecewiseConstant((0., 24.), (293,)), + outside_temp=models.PiecewiseConstant((0., 24.), (283,)), window_height=1.6, opening_length=0.6, ), models.AirChange( - active=models.SpecificInterval(((0,24),)), + active=models.SpecificInterval(((0., 24.), )), air_exch=0.25, ), ), @@ -39,7 +39,7 @@ def shared_office_mc(): infected=mc.InfectedPopulation( number=1, virus=virus_distributions['SARS_CoV_2_B117'], - presence=mc.SpecificInterval(((0, 2), (2.1, 4), (5, 7), (7.1, 9))), + presence=mc.SpecificInterval(((0., 2.), (2.1, 4.), (5., 7.), (7.1, 9.))), mask=models.Mask(η_inhale=0.3), activity=activity_distributions['Seated'], expiration=models.MultipleExpiration( @@ -70,12 +70,12 @@ def classroom_mc(): ( models.SlidingWindow( active=models.PeriodicInterval(period=120, duration=10), - inside_temp=models.PiecewiseConstant((0, 24), (293,)), - outside_temp=models.PiecewiseConstant((0, 24), (283,)), + inside_temp=models.PiecewiseConstant((0., 24.), (293,)), + outside_temp=models.PiecewiseConstant((0., 24.), (283,)), window_height=1.6, opening_length=0.6, ), models.AirChange( - active=models.SpecificInterval(((0,24),)), + active=models.SpecificInterval(((0., 24.),)), air_exch=0.25, ), ), @@ -83,7 +83,7 @@ def classroom_mc(): infected=mc.InfectedPopulation( number=1, virus=virus_distributions['SARS_CoV_2_B117'], - presence=mc.SpecificInterval(((0, 2), (2.5, 4), (5, 7), (7.5, 9))), + presence=mc.SpecificInterval(((0., 2.), (2.5, 4.), (5., 7.), (7.5, 9.))), mask=models.Mask.types['No mask'], activity=activity_distributions['Light activity'], expiration=models.Expiration.types['Talking'], @@ -108,13 +108,13 @@ def ski_cabin_mc(): concentration_mc = mc.ConcentrationModel( room=models.Room(volume=10, humidity=0.5), ventilation=models.AirChange( - active=models.SpecificInterval(((0,24),)), + active=models.SpecificInterval(((0., 24.),)), air_exch=0, ), infected=mc.InfectedPopulation( number=1, virus=virus_distributions['SARS_CoV_2_B117'], - presence=mc.SpecificInterval(((0, 1/3),)), + presence=mc.SpecificInterval(((0., 1/3),)), mask=models.Mask(η_inhale=0.3), activity=activity_distributions['Moderate activity'], expiration=models.Expiration.types['Talking'], @@ -141,13 +141,13 @@ def gym_mc(): concentration_mc = mc.ConcentrationModel( room=models.Room(volume=300, humidity=0.5), ventilation=models.AirChange( - active=models.SpecificInterval(((0,24),)), + active=models.SpecificInterval(((0., 24.),)), air_exch=6, ), infected=mc.InfectedPopulation( number=2, virus=virus_distributions['SARS_CoV_2_B117'], - presence=mc.SpecificInterval(((0, 1),)), + presence=mc.SpecificInterval(((0., 1.),)), mask=models.Mask.types["No mask"], activity=activity_distributions['Heavy exercise'], expiration=models.Expiration.types['Breathing'], @@ -173,13 +173,13 @@ def waiting_room_mc(): concentration_mc = mc.ConcentrationModel( room=models.Room(volume=100, humidity=0.5), ventilation=models.AirChange( - active=models.SpecificInterval(((0,24),)), + active=models.SpecificInterval(((0., 24.),)), air_exch=0.25, ), infected=mc.InfectedPopulation( number=1, virus=virus_distributions['SARS_CoV_2_B117'], - presence=mc.SpecificInterval(((0, 2),)), + presence=mc.SpecificInterval(((0., 2.),)), mask=models.Mask.types["No mask"], activity=activity_distributions['Seated'], expiration=models.MultipleExpiration( @@ -215,7 +215,7 @@ def skagit_chorale_mc(): infected=mc.InfectedPopulation( number=1, virus=virus_distributions['SARS_CoV_2'], - presence=mc.SpecificInterval(((0, 2.5),)), + presence=mc.SpecificInterval(((0., 2.5),)), mask=models.Mask.types["No mask"], activity=activity_distributions['Light activity'], expiration=models.Expiration((5., 5., 5.)), @@ -261,10 +261,10 @@ def test_report_models(mc_model, expected_pi, expected_new_cases, @pytest.mark.parametrize( "mask_type, month, expected_pi, expected_dose, expected_ER", [ - ["No mask", "7", 30.0, 405.84, 3894], - ["Type I", "7", 10.2, 73.38, 702], - ["FFP2", "7", 4.0, 73.38, 702], - ["Type I", "2", 4.25, 21.42, 702], + ["No mask", "Jul", 30.0, 405.84, 3894], + ["Type I", "Jul", 10.2, 73.38, 702], + ["FFP2", "Jul", 4.0, 73.38, 702], + ["Type I", "Feb", 4.25, 21.42, 702], ], ) def test_small_shared_office_Geneva(mask_type, month, expected_pi, @@ -274,13 +274,13 @@ def test_small_shared_office_Geneva(mask_type, month, expected_pi, ventilation=models.MultipleVentilation( ( models.SlidingWindow( - active=models.SpecificInterval(((0,24),)), - inside_temp=models.PiecewiseConstant((0, 24), (293,)), - outside_temp=data.Temperatures[month], + active=models.SpecificInterval(((0., 24.),)), + inside_temp=models.PiecewiseConstant((0., 24.), (293,)), + outside_temp=data.GenevaTemperatures[month], window_height=1.5, opening_length=0.2, ), models.AirChange( - active=models.SpecificInterval(((0,24),)), + active=models.SpecificInterval(((0., 24.),)), air_exch=0.25, ), ), @@ -288,7 +288,7 @@ def test_small_shared_office_Geneva(mask_type, month, expected_pi, infected=mc.InfectedPopulation( number=1, virus=virus_distributions['SARS_CoV_2_B117'], - presence=mc.SpecificInterval(((9, 10+2/3), (10+5/6, 12.5), (13.5, 15+2/3), (15+5/6, 18))), + presence=mc.SpecificInterval(((9., 10+2/3), (10+5/6, 12.5), (13.5, 15+2/3), (15+5/6, 18.))), mask=models.Mask.types[mask_type], activity=activity_distributions['Seated'], expiration=models.MultipleExpiration(