From 7a62a04839567390d146975caa1a2c0ba569aa83 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 17 May 2023 17:25:48 +0200 Subject: [PATCH 01/61] added CO2 data class --- caimira/models.py | 73 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 73 insertions(+) diff --git a/caimira/models.py b/caimira/models.py index 3d8d5a3f..a9e1c892 100644 --- a/caimira/models.py +++ b/caimira/models.py @@ -38,6 +38,7 @@ import numpy as np from scipy.interpolate import interp1d import scipy.stats as sct +from scipy.optimize import minimize if not typing.TYPE_CHECKING: from memoization import cached @@ -440,6 +441,18 @@ def air_exchange(self, room: Room, time: float) -> _VectorisedFloat: return self.air_exch +@dataclass(frozen=True) +class CustomVentilation(_VentilationBase): + # The ventilation value for a given time + ventilation_value: PiecewiseConstant + + def transition_times(self, room: Room) -> typing.Set[float]: + return self.ventilation_value.transition_times + + def air_exchange(self, room: Room, time: float) -> _VectorisedFloat: + return self.ventilation_value.value(time) + + @dataclass(frozen=True) class Virus: #: RNA copies / mL @@ -1472,6 +1485,63 @@ def _normed_interpolated_longrange_exposure_between_bounds( return normed_int_concentration_interpolated +@dataclass(frozen=True) +class CO2Data: + # TODO - docstring + room_volume: float + number: typing.Union[int, IntPiecewiseConstant] + presence: typing.Optional[Interval] + ventilation_transition_times: typing.Tuple[float, ...] + times: typing.Sequence[float] + CO2_concentrations: typing.Sequence[float] + + def CO2_concentrations_from_params(self, + exhalation_rate: float, + ventilation_values: typing.Tuple[float, ...]) -> typing.List[float]: + + CO2_concentrations = CO2ConcentrationModel( + room=Room(volume=self.room_volume), + ventilation=CustomVentilation(PiecewiseConstant( + self.ventilation_transition_times, ventilation_values)), + CO2_emitters=Population( + number=self.number, + presence=self.presence, + mask=Mask.types['No mask'], + activity=Activity( + exhalation_rate=exhalation_rate, inhalation_rate=exhalation_rate), + host_immunity=0. + ) + ) + + return [CO2_concentrations.concentration(time) for time in self.times] + + def CO2_fit_params(self): + if len(self.times) != len(self.CO2_concentrations): + raise ValueError('times and CO2_concentrations must have same length.') + + if len(self.times) < 2: + raise ValueError( + 'times and CO2_concentrations must contain at last two elements') + + def fun(x): + exhalation_rate = x[0] + ventilation_values = tuple(x[1:]) + the_concentrations = self.CO2_concentrations_from_params( + exhalation_rate=exhalation_rate, + ventilation_values=ventilation_values + ) + return np.sqrt(np.sum((np.array(self.CO2_concentrations) - np.array(the_concentrations))**2)) + + # The goal is to minimize the difference between the two different curves (known concentrations vs. predicted concentrations) + res_dict = minimize(fun=fun, x0=np.ones(len(self.ventilation_transition_times)), method='powell', bounds=[ + (0, None) for _ in range(len(self.ventilation_transition_times))], options={'xtol': 1e-3}) + + exhalation_rate = res_dict['x'][0] + ventilation_values = res_dict['x'][1:] + + return exhalation_rate, ventilation_values + + @dataclass(frozen=True) class ExposureModel: """ @@ -1489,6 +1559,9 @@ class ExposureModel: #: Geographical data geographical_data: Cases + #: CO2 data + CO2_profile: CO2Data = () + #: The number of times the exposure event is repeated (default 1). repeats: int = config.exposure_model['repeats'] # type: ignore From 641a572d9d2305a253f002df6d7ac497507db10f Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 17 May 2023 17:27:05 +0200 Subject: [PATCH 02/61] ui modifications --- caimira/apps/calculator/defaults.py | 2 + caimira/apps/calculator/model_generator.py | 2 + caimira/apps/calculator/static/js/form.js | 20 ++ .../templates/base/calculator.form.html.j2 | 212 ++++++++++-------- 4 files changed, 139 insertions(+), 97 deletions(-) diff --git a/caimira/apps/calculator/defaults.py b/caimira/apps/calculator/defaults.py index 8bae7e23..08318c7f 100644 --- a/caimira/apps/calculator/defaults.py +++ b/caimira/apps/calculator/defaults.py @@ -22,6 +22,8 @@ 'ceiling_height': 0., 'conditional_probability_plot': False, 'conditional_probability_viral_loads': False, + 'CO2_data': '{}', + 'CO2_data_option': '{}', 'exposed_coffee_break_option': 'coffee_break_0', 'exposed_coffee_duration': 5, 'exposed_finish': '17:30', diff --git a/caimira/apps/calculator/model_generator.py b/caimira/apps/calculator/model_generator.py index b844aa68..d52b569b 100644 --- a/caimira/apps/calculator/model_generator.py +++ b/caimira/apps/calculator/model_generator.py @@ -37,6 +37,8 @@ class FormData: ceiling_height: float conditional_probability_plot: bool conditional_probability_viral_loads: bool + CO2_data: dict + CO2_data_option: bool exposed_coffee_break_option: str exposed_coffee_duration: int exposed_finish: minutes_since_midnight diff --git a/caimira/apps/calculator/static/js/form.js b/caimira/apps/calculator/static/js/form.js index a88c5ccc..1d1e39f1 100644 --- a/caimira/apps/calculator/static/js/form.js +++ b/caimira/apps/calculator/static/js/form.js @@ -493,6 +493,20 @@ function on_coffee_break_option_change() { } } +function on_CO2_data_option_change() { + CO2_data_options = $('input[type=radio][name=CO2_data_option]'); + CO2_data_options.each(function (index){ + if (this.checked) { + getChildElement($(this)).show(); + require_fields(this); + } + else { + getChildElement($(this)).hide(); + require_fields(this); + } + }) +} + /* -------UI------- */ function show_disclaimer() { @@ -1039,6 +1053,12 @@ $(document).ready(function () { // Call the function now to handle forward/back button presses in the browser. on_coffee_break_option_change(); + // When the CO2_data_option changes we want to make its respective + // children show/hide. + $("input[type=radio][name=CO2_data_option]").change(on_CO2_data_option_change); + // Call the function now to handle forward/back button presses in the browser. + on_CO2_data_option_change(); + // Setup the maximum number of people at page load (to handle back/forward), // and update it when total people is changed. validateMaxInfectedPeople(); diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index 8277f829..83b30069 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -185,127 +185,145 @@
+ Ventilation data:
?
-
- -
Ventilation type:
- -
-
- - - - -
-
- -
+
+
Use CO₂ concentration values:
+
+ + + + +
+ + - - +
+
HEPA filtration:
From 7617ac3c05ae7cd829c132bea58c59d596156286 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Tue, 27 Jun 2023 15:11:17 +0200 Subject: [PATCH 19/61] fixed download template by adding file to CERNBox resources --- caimira/apps/calculator/static/js/co2_form.js | 20 ++++++++----------- 1 file changed, 8 insertions(+), 12 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index b48c5d90..c2a03447 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -92,18 +92,14 @@ function displayJsonToHtmlTable(jsonData) { } } -function downloadTemplate() { - let final_export = [["Times", "CO2"], [8.5, 440.44]]; - // Prepare the CSV file. - let csvContent = "data:text/csv;charset=utf8," - + final_export.map(e => e.join(",")).join("\n"); - var encodedUri = encodeURI(csvContent); - // Set a name for the file. - var link = document.createElement("a"); - link.setAttribute("href", encodedUri); - link.setAttribute("download", "CO2_template.XLSX"); - document.body.appendChild(link); - link.click(); +function downloadTemplate(uri = 'https://caimira-resources.web.cern.ch/CO2_template.xlsx', filename = 'CO2_template.xlsx') { + var link = document.createElement("a"); + link.download = filename; + link.href = uri; + document.body.appendChild(link); + link.click(); + document.body.removeChild(link); + delete link; } function insertErrorFor(referenceNode, text) { From fb887f7db6e1ea10f0fa47cb589e292acc079ad2 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Tue, 27 Jun 2023 17:03:27 +0200 Subject: [PATCH 20/61] added back compatibility (form report -> calculator) --- caimira/apps/calculator/__init__.py | 1 - caimira/apps/calculator/static/js/co2_form.js | 27 ++++++++++++------- caimira/apps/calculator/static/js/form.js | 18 +++++++++++++ .../templates/base/calculator.form.html.j2 | 2 +- 4 files changed, 36 insertions(+), 12 deletions(-) diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index 12b8d885..668a91bf 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -379,7 +379,6 @@ def generate_image(transition_times: tuple, ventilation_values: tuple): fig = plt.figure(figsize=(7, 4), dpi=110) plt.plot(form.CO2_data['times'], form.CO2_data['CO2']) for index, time in enumerate(transition_times[:-1]): - print(time) plt.axvline(x = time, color = 'grey', linewidth=0.5, linestyle='--') y_location = (form.CO2_data['CO2'][min(range(len(form.CO2_data['times'])), key=lambda i: abs(form.CO2_data['times'][i]-time))]) plt.text(x = time + 0.04, y = y_location, s=round(ventilation_values[index], 2)) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index c2a03447..5315379b 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -1,3 +1,4 @@ +// JS file to handle manipulation on CO2 Fitting Algorithm Dialog. const CO2_data = [ 'CO2_data', 'specific_breaks', @@ -92,6 +93,7 @@ function displayJsonToHtmlTable(jsonData) { } } +// Method to download Excel template available on CERNBox function downloadTemplate(uri = 'https://caimira-resources.web.cern.ch/CO2_template.xlsx', filename = 'CO2_template.xlsx') { var link = document.createElement("a"); link.download = filename; @@ -114,15 +116,26 @@ function validate() { $('span.' + "error_text").remove(); let submit = true; for (var i = 0; i < CO2_data.length; i++) { - let element = $(`[name=${CO2_data[i]}]`); - if (element[0].value === '') { - insertErrorFor($('#CO2_input_data_div'), `'${element[0].name}' must be defined.`); // raise error for total number and room volume. + let element = $(`[name=${CO2_data[i]}]`)[0]; + if (element.value === '') { + insertErrorFor($('#CO2_input_data_div'), `'${element.name}' must be defined.`); // raise error for total number and room volume. submit = false; }; } return submit; } +function display_fitting_data(json_response) { + $("#DIV_CO2_fitting_result").show(); + $("#CO2_data_plot").attr("src", json_response['CO2_plot']); + delete json_response['CO2_plot']; + $("#CO2_fitting_result").val(JSON.stringify(json_response)); + $("#exhalation_rate_fit").html('Exhalation rate: ' + String(json_response['exhalation_rate'].toFixed(2)) + ' m³/h'); + // $("#ventilation_rate_fit").html(json_response['ventilation_values']); + $("#generate_fitting_data").html('Fit data'); + $("#save_and_dismiss_dialog").show(); +} + function submit_fitting_algorithm(url) { if (validate()) { let CO2_mapping = {}; @@ -143,13 +156,7 @@ function submit_fitting_algorithm(url) { }) .then((response) => response.json()) .then((json_response) => { - $("#DIV_CO2_fitting_result").show(); - $("#CO2_fitting_result").val(JSON.stringify(json_response)); - $("#exhalation_rate_fit").html('Exhalation rate: ' + String(json_response['exhalation_rate'].toFixed(2)) + ' m³/h'); - // $("#ventilation_rate_fit").html(json_response['ventilation_values']); - $("#CO2_data_plot").attr("src", json_response['CO2_plot']); - $("#generate_fitting_data").html('Fit data'); - $("#save_and_dismiss_dialog").show(); + display_fitting_data(json_response); }); } } diff --git a/caimira/apps/calculator/static/js/form.js b/caimira/apps/calculator/static/js/form.js index 02c2408a..3b7ce7bf 100644 --- a/caimira/apps/calculator/static/js/form.js +++ b/caimira/apps/calculator/static/js/form.js @@ -946,6 +946,12 @@ $(document).ready(function () { // Validation after } + + // Read CO2 Fitting Algorithms result + else if (name == 'CO2_fitting_result' || name == 'CO2_data') { + // Validation after + } + //Ignore 0 (default) values from server side else if (!(elemObj.classList.contains("non_zero") || elemObj.classList.contains("remove_zero")) || (value != "0.0" && value != "0")) { elemObj.value = value; @@ -956,6 +962,18 @@ $(document).ready(function () { // Handle default URL values if they are not explicitly defined. + // Populate CO2 Fitting Algorithm Dialog + let CO2_data = url.searchParams.has('CO2_data') ? url.searchParams.get('CO2_data') : null; + if (CO2_data) { + let CO2_inputs = JSON.parse(CO2_data); + let input_for_table = []; + for (let i = 0; i < CO2_inputs['times'].length; i++) { + input_for_table.push({'Times': CO2_inputs['times'][i], 'CO2': CO2_inputs['CO2'][i]}); + }; + displayJsonToHtmlTable(input_for_table); + submit_fitting_algorithm(`${$('#url_prefix').data().calculator_prefix}/co2-fit`); + } + // Populate primary vaccine dropdown $("#vaccine_type option").remove(); let primary_vaccine = url.searchParams.has('vaccine_type') ? url.searchParams.get('vaccine_type') : null; diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index 7561d4a6..bb04819b 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -708,7 +708,7 @@
-
Upload an excel file to display in HTML Table
+
Upload an Excel file to preview in HTML Table

From c8fa2889ceffa1c5f4de0eac5c55c9670cfc5979 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Thu, 29 Jun 2023 12:48:24 +0100 Subject: [PATCH 21/61] added ventilation option validations on form --- caimira/apps/calculator/static/js/co2_form.js | 1 + caimira/apps/calculator/static/js/form.js | 19 ++++++++++++------- 2 files changed, 13 insertions(+), 7 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 5315379b..b9e7c50b 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -170,6 +170,7 @@ function clear_fitting_algorithm() { $('#DIV_CO2_fitting_result').hide(); $('#CO2_input_data_div').hide(); $('#CO2_data_no').click(); + ventilation_from_fitting(false); } function dismiss_co2_dialog() { diff --git a/caimira/apps/calculator/static/js/form.js b/caimira/apps/calculator/static/js/form.js index 3b7ce7bf..d2b0dbf1 100644 --- a/caimira/apps/calculator/static/js/form.js +++ b/caimira/apps/calculator/static/js/form.js @@ -244,9 +244,6 @@ function removeInvalid(id) { } function on_ventilation_type_change() { - if ($('input[type=radio][id=from_fitting').is(':checked')) $('#DIVfrom_fitting').after($('#window_opening_regime')); - else $('#DIVopening_distance').after($('#window_opening_regime')); - ventilation_types = $('input[type=radio][name=ventilation_type]'); ventilation_types.each(function (index) { if (this.checked) { @@ -496,15 +493,23 @@ function on_coffee_break_option_change() { } } -function ventilation_from_fitting(condition) { - if (condition) { - $('input[type=radio][id=from_fitting]').click(); +function ventilation_from_fitting(condition_from_fitting) { + $('input[type=radio][id=no_ventilation]').prop("disabled", condition_from_fitting); + $('input[type=radio][id=mechanical_ventilation]').prop("disabled", condition_from_fitting); + $('input[type=radio][id=natural_ventilation]').prop("disabled", condition_from_fitting); + $('input[type=radio][id=from_fitting]').prop("disabled", !condition_from_fitting); + if (condition_from_fitting) { + $('input[type=radio][id=from_fitting]').prop('checked',true); $('#DIVfrom_fitting').after($('#window_opening_regime')); } else { - $('input[type=radio][id=no_ventilation]').click(); + // Select the URL ventilation option, if any (from back-navigation) + var url = new URL(decodeURIComponent(window.location.href)); + let ventilation_from_url = url.searchParams.has('ventilation_type') ? url.searchParams.get('ventilation_type') : "no_ventilation"; + $(`input[type=radio][id=${ventilation_from_url}]`).prop('checked',true); $('#DIVopening_distance').after($('#window_opening_regime')); } + on_ventilation_type_change(); } function on_CO2_data_option_change() { From 587df676936facfa29f7cb89a39f622051c510fd Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Thu, 29 Jun 2023 16:24:00 +0100 Subject: [PATCH 22/61] form modifications - table format --- caimira/apps/calculator/__init__.py | 6 ++-- .../apps/calculator/co2_model_generator.py | 35 ++++++++++++++++--- caimira/apps/calculator/defaults.py | 1 - caimira/apps/calculator/model_generator.py | 1 - caimira/apps/calculator/static/js/co2_form.js | 35 ++++++++++--------- caimira/apps/calculator/static/js/form.js | 19 +++++----- .../templates/base/calculator.form.html.j2 | 8 +++-- 7 files changed, 66 insertions(+), 39 deletions(-) diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index 668a91bf..97b20fca 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -354,7 +354,6 @@ def check_xsrf_cookie(self): async def post(self) -> None: requested_model_config = tornado.escape.json_decode(self.request.body) - try: form = co2_model_generator.CO2FormData.from_dict(requested_model_config) except Exception as err: @@ -375,7 +374,7 @@ async def post(self) -> None: ) report = await asyncio.wrap_future(report_task) - def generate_image(transition_times: tuple, ventilation_values: tuple): + def generate_ventilation_plot(transition_times: tuple, ventilation_values: tuple): fig = plt.figure(figsize=(7, 4), dpi=110) plt.plot(form.CO2_data['times'], form.CO2_data['CO2']) for index, time in enumerate(transition_times[:-1]): @@ -387,7 +386,8 @@ def generate_image(transition_times: tuple, ventilation_values: tuple): return fig result = dict(report.CO2_fit_params()) - result['CO2_plot'] = img2base64(_figure2bytes(generate_image(report.ventilation_transition_times, result['ventilation_values']))) + result['transition_times'] = report.ventilation_transition_times + result['CO2_plot'] = img2base64(_figure2bytes(generate_ventilation_plot(report.ventilation_transition_times, result['ventilation_values']))) self.finish(result) diff --git a/caimira/apps/calculator/co2_model_generator.py b/caimira/apps/calculator/co2_model_generator.py index f0341338..39e61d29 100644 --- a/caimira/apps/calculator/co2_model_generator.py +++ b/caimira/apps/calculator/co2_model_generator.py @@ -46,7 +46,7 @@ class CO2FormData: #: and the defaults in the html form must not be contradictory. _DEFAULTS: typing.ClassVar[typing.Dict[str, typing.Any]] = { 'CO2_data': '{}', - 'specific_breaks': '{}', # CHECK INTEGRATION WITH WHO + 'specific_breaks': '{}', 'exposed_coffee_break_option': 'coffee_break_0', 'exposed_coffee_duration': 5, 'exposed_finish': '17:30', @@ -89,8 +89,8 @@ def from_dict(cls, form_data: typing.Dict) -> "CO2FormData": form_data[key] = default_value for key, value in form_data.items(): - if key in model_generator._CAST_RULES_FORM_ARG_TO_NATIVE: - form_data[key] = model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[key](value) + if key in _CAST_RULES_FORM_ARG_TO_NATIVE: + form_data[key] = _CAST_RULES_FORM_ARG_TO_NATIVE[key](value) if key not in cls._DEFAULTS: raise ValueError(f'Invalid argument "{html.escape(key)}" given') @@ -318,6 +318,33 @@ def ventilation_transition_times(self, last_present_time) -> typing.Tuple[float, if self.ventilation_type == 'from_fitting' and self.window_opening_regime == 'windows_open_periodically': transition_times = sorted(models.PeriodicInterval(self.windows_frequency, self.windows_duration, min(self.infected_start, self.exposed_start)/60).transition_times()) - return tuple(filter(lambda x: x < last_present_time, transition_times)) + return tuple(filter(lambda x: x <= last_present_time, transition_times)) else: return tuple((min(self.infected_start, self.exposed_start)/60, max(self.infected_finish, self.exposed_finish)/60), ) # all day long + +#: Mapping of field name to a callable which can convert values from form +#: input (URL encoded arguments / string) into the correct type. +_CAST_RULES_FORM_ARG_TO_NATIVE: typing.Dict[str, typing.Callable] = {} + +#: Mapping of field name to callable which can convert native type to values +#: that can be encoded to URL arguments. +_CAST_RULES_NATIVE_TO_FORM_ARG: typing.Dict[str, typing.Callable] = {} + + +for _field in dataclasses.fields(CO2FormData): + if _field.type is minutes_since_midnight: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.time_string_to_minutes + _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.time_minutes_to_string + elif _field.type is int: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator._safe_int_cast + elif _field.type is float: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = float + elif _field.type is bool: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = lambda v: v == '1' + _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = int + elif _field.type is list: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.string_to_list + _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.list_to_string + elif _field.type is dict: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.string_to_dict + _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.dict_to_string diff --git a/caimira/apps/calculator/defaults.py b/caimira/apps/calculator/defaults.py index c230e4a9..35ced634 100644 --- a/caimira/apps/calculator/defaults.py +++ b/caimira/apps/calculator/defaults.py @@ -22,7 +22,6 @@ 'ceiling_height': 0., 'conditional_probability_plot': False, 'conditional_probability_viral_loads': False, - 'CO2_data': '{}', 'CO2_data_option': False, 'CO2_fitting_result': '{}', 'exposed_coffee_break_option': 'coffee_break_0', diff --git a/caimira/apps/calculator/model_generator.py b/caimira/apps/calculator/model_generator.py index 58ddc8e8..97749fd2 100644 --- a/caimira/apps/calculator/model_generator.py +++ b/caimira/apps/calculator/model_generator.py @@ -37,7 +37,6 @@ class FormData: ceiling_height: float conditional_probability_plot: bool conditional_probability_viral_loads: bool - CO2_data: dict CO2_data_option: bool CO2_fitting_result: dict exposed_coffee_break_option: str diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index b9e7c50b..e5277f3f 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -1,5 +1,5 @@ // JS file to handle manipulation on CO2 Fitting Algorithm Dialog. -const CO2_data = [ +const CO2_data_form = [ 'CO2_data', 'specific_breaks', 'exposed_coffee_break_option', @@ -74,11 +74,11 @@ function displayJsonToHtmlTable(jsonData) { var row = jsonData[i]; if (i < 5) { htmlData += - "" + - row["Times"].toFixed(2) + - "" + - row["CO2"].toFixed(2) + - ""; + ` + ${row["Times"].toFixed(2)} + + ${row["CO2"].toFixed(2)} + `; } structure["times"].push(row["Times"]); structure["CO2"].push(row["CO2"]); @@ -115,8 +115,8 @@ function insertErrorFor(referenceNode, text) { function validate() { $('span.' + "error_text").remove(); let submit = true; - for (var i = 0; i < CO2_data.length; i++) { - let element = $(`[name=${CO2_data[i]}]`)[0]; + for (var i = 0; i < CO2_data_form.length; i++) { + let element = $(`[name=${CO2_data_form[i]}]`)[0]; if (element.value === '') { insertErrorFor($('#CO2_input_data_div'), `'${element.name}' must be defined.`); // raise error for total number and room volume. submit = false; @@ -128,10 +128,17 @@ function validate() { function display_fitting_data(json_response) { $("#DIV_CO2_fitting_result").show(); $("#CO2_data_plot").attr("src", json_response['CO2_plot']); - delete json_response['CO2_plot']; + // Not needed for the form submit + delete json_response['CO2_plot']; $("#CO2_fitting_result").val(JSON.stringify(json_response)); $("#exhalation_rate_fit").html('Exhalation rate: ' + String(json_response['exhalation_rate'].toFixed(2)) + ' m³/h'); - // $("#ventilation_rate_fit").html(json_response['ventilation_values']); + let ventilation_table = "TimeVentilation value (ACH)"; + json_response['ventilation_values'].map((val, index) => { + console.log(json_response['transition_times']) + let transition_times = `${(json_response['transition_times'][index]).toFixed(2)} - ${(json_response['transition_times'][index + 1]).toFixed(2)}` + ventilation_table += `${transition_times}${val}`; + }); + $("#ventilation_rate_fit").html(ventilation_table); $("#generate_fitting_data").html('Fit data'); $("#save_and_dismiss_dialog").show(); } @@ -139,7 +146,7 @@ function display_fitting_data(json_response) { function submit_fitting_algorithm(url) { if (validate()) { let CO2_mapping = {}; - CO2_data.map(el => { + CO2_data_form.map(el => { let element = $(`[name=${el}]`); // Validate radio buttons if (element.length != 1) CO2_mapping[element[0].name] = $(`[name=${element[0].name}]:checked`)[0].value @@ -147,7 +154,7 @@ function submit_fitting_algorithm(url) { }) $('#CO2_input_data_div').show(); $("#generate_fitting_data").html( - `Loading...` + `Loading...` ); $('#CO2_input_data').html(JSON.stringify(CO2_mapping, null, "\t")) fetch(url, { @@ -172,7 +179,3 @@ function clear_fitting_algorithm() { $('#CO2_data_no').click(); ventilation_from_fitting(false); } - -function dismiss_co2_dialog() { - $('#CO2_data_no').click(); -} \ No newline at end of file diff --git a/caimira/apps/calculator/static/js/form.js b/caimira/apps/calculator/static/js/form.js index d2b0dbf1..715808f0 100644 --- a/caimira/apps/calculator/static/js/form.js +++ b/caimira/apps/calculator/static/js/form.js @@ -505,7 +505,12 @@ function ventilation_from_fitting(condition_from_fitting) { else { // Select the URL ventilation option, if any (from back-navigation) var url = new URL(decodeURIComponent(window.location.href)); - let ventilation_from_url = url.searchParams.has('ventilation_type') ? url.searchParams.get('ventilation_type') : "no_ventilation"; + let ventilation_from_url; + if (url.searchParams.has('ventilation_type')) { + ventilation_from_url = url.searchParams.get('ventilation_type'); + if (ventilation_from_url == 'from_fitting') ventilation_from_url = 'no_ventilation'; + } + else ventilation_from_url = 'no_ventilation'; $(`input[type=radio][id=${ventilation_from_url}]`).prop('checked',true); $('#DIVopening_distance').after($('#window_opening_regime')); } @@ -968,16 +973,8 @@ $(document).ready(function () { // Handle default URL values if they are not explicitly defined. // Populate CO2 Fitting Algorithm Dialog - let CO2_data = url.searchParams.has('CO2_data') ? url.searchParams.get('CO2_data') : null; - if (CO2_data) { - let CO2_inputs = JSON.parse(CO2_data); - let input_for_table = []; - for (let i = 0; i < CO2_inputs['times'].length; i++) { - input_for_table.push({'Times': CO2_inputs['times'][i], 'CO2': CO2_inputs['CO2'][i]}); - }; - displayJsonToHtmlTable(input_for_table); - submit_fitting_algorithm(`${$('#url_prefix').data().calculator_prefix}/co2-fit`); - } + let CO2_data = url.searchParams.has('CO2_fitting_result') ? url.searchParams.get('CO2_fitting_result') : null; + if (CO2_data) display_fitting_data(JSON.parse(CO2_data)); // Populate primary vaccine dropdown $("#vaccine_type option").remove(); diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index bb04819b..7c6cb522 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -702,7 +702,7 @@
-
@@ -719,7 +719,7 @@
-
+
From faf0a35bc8cc4a2ffbc41c392829bdd985228626 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Thu, 29 Jun 2023 16:24:15 +0100 Subject: [PATCH 23/61] added report data --- .../templates/base/calculator.report.html.j2 | 16 ++++++++ caimira/models.py | 5 +-- .../tests/models/test_dynamic_population.py | 40 +++++++++++++++---- 3 files changed, 50 insertions(+), 11 deletions(-) diff --git a/caimira/apps/templates/base/calculator.report.html.j2 b/caimira/apps/templates/base/calculator.report.html.j2 index 08a4596f..cdbd26d0 100644 --- a/caimira/apps/templates/base/calculator.report.html.j2 +++ b/caimira/apps/templates/base/calculator.report.html.j2 @@ -528,6 +528,19 @@

  • HEPA amount: {{ form.hepa_amount }} m³ / hour

    • {% endif %} +

  • From Fitting: + {% if form.ventilation_type == "from_fitting" %} + Yes + + + {% for ventilation in form.CO2_fitting_result['ventilation_values'] %} + + {% endfor %} +
    Ventilation value (ACH)
    {{ventilation}}
    + {% else %} + No

    • + {% endif %} +

    @@ -578,6 +591,9 @@ {% elif form.activity_type == "gym" %} Gym - For comparison only, all persons doing heavy physical exercise, breathing and not speaking. {% endif %} + {% if form.CO2_data_option %} +

    Exhalation rate from fitting algorithm - {{form.CO2_fitting_result['exhalation_rate'] | round(2, 'floor')}} m³/h

    + {% endif %}

    {% if form.short_range_option == "short_range_yes" %}

  • diff --git a/caimira/models.py b/caimira/models.py index 1d068088..a9f2c0ec 100644 --- a/caimira/models.py +++ b/caimira/models.py @@ -1578,10 +1578,7 @@ def __post_init__(self): c_model.ventilation.air_exchange(c_model.room, time)) for time in c_model.state_change_times()))): raise ValueError("If the diameter is an array, none of the ventilation parameters " "or virus decay constant can be arrays at the same time.") - if not isinstance(self.exposed.number, int): - raise NotImplementedError("Cannot use dynamic occupancy for" - " the exposed population") - + @method_cache def population_state_change_times(self) -> typing.List[float]: """ diff --git a/caimira/tests/models/test_dynamic_population.py b/caimira/tests/models/test_dynamic_population.py index 4bca0f73..8fe6b891 100644 --- a/caimira/tests/models/test_dynamic_population.py +++ b/caimira/tests/models/test_dynamic_population.py @@ -27,7 +27,7 @@ def full_exposure_model(): short_range=(), exposed=models.Population( number=10, - presence=models.SpecificInterval(((8, 12), (13, 17), )), + presence=models.SpecificInterval(((8, 12), (13, 17), )), mask=models.Mask.types['No mask'], activity=models.Activity.types['Seated'], host_immunity=0. @@ -51,11 +51,37 @@ def baseline_infected_population_number(): @pytest.fixture -def dynamic_single_exposure_model(full_exposure_model, baseline_infected_population_number): +def baseline_exposed_population_number(): + return models.Population( + number=models.IntPiecewiseConstant( + (8, 12, 13, 17), (10, 0, 10)), + presence=None, + mask=models.Mask.types['No mask'], + activity=models.Activity.types['Seated'], + host_immunity=0., + ) + + +@pytest.fixture +def dynamic_infected_single_exposure_model(full_exposure_model, baseline_infected_population_number): return dc_utils.nested_replace(full_exposure_model, {'concentration_model.infected': baseline_infected_population_number, }) +@pytest.fixture +def dynamic_exposed_single_exposure_model(full_exposure_model, baseline_exposed_population_number): + return dc_utils.nested_replace(full_exposure_model, + {'exposed': baseline_exposed_population_number, }) + + +@pytest.fixture +def dynamic_population_exposure_model(full_exposure_model, baseline_infected_population_number ,baseline_exposed_population_number): + return dc_utils.nested_replace(full_exposure_model, { + 'concentration_model.infected': baseline_infected_population_number, + 'exposed': baseline_exposed_population_number, + }) + + @pytest.mark.parametrize( "time", [4., 8., 10., 12., 13., 14., 16., 20., 24.], @@ -91,16 +117,16 @@ def test_population_number(full_exposure_model: models.ExposureModel, [4., 8., 10., 12., 13., 14., 16., 20., 24.], ) def test_concentration_model_dynamic_population(full_exposure_model: models.ExposureModel, - dynamic_single_exposure_model: models.ExposureModel, + dynamic_infected_single_exposure_model: models.ExposureModel, time: float): - assert full_exposure_model.concentration(time) == dynamic_single_exposure_model.concentration(time) + assert full_exposure_model.concentration(time) == dynamic_infected_single_exposure_model.concentration(time) @pytest.mark.parametrize("number_of_infected",[1, 2, 3, 4, 5]) @pytest.mark.parametrize("time",[9., 12.5, 16.]) def test_linearity_with_number_of_infected(full_exposure_model: models.ExposureModel, - dynamic_single_exposure_model: models.ExposureModel, + dynamic_infected_single_exposure_model: models.ExposureModel, time: float, number_of_infected: int): @@ -112,8 +138,8 @@ def test_linearity_with_number_of_infected(full_exposure_model: models.ExposureM } ) - npt.assert_almost_equal(static_multiple_exposure_model.concentration(time), dynamic_single_exposure_model.concentration(time) * number_of_infected) - npt.assert_almost_equal(static_multiple_exposure_model.deposited_exposure(), dynamic_single_exposure_model.deposited_exposure() * number_of_infected) + npt.assert_almost_equal(static_multiple_exposure_model.concentration(time), dynamic_infected_single_exposure_model.concentration(time) * number_of_infected) + npt.assert_almost_equal(static_multiple_exposure_model.deposited_exposure(), dynamic_infected_single_exposure_model.deposited_exposure() * number_of_infected) @pytest.mark.parametrize( From 1cfd7b684fbfff7602cf0e03d266148c333ae4af Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Tue, 4 Jul 2023 11:31:33 +0100 Subject: [PATCH 24/61] simplified the way to select previous ventilations --- caimira/apps/calculator/static/js/form.js | 14 +++++--------- .../apps/templates/base/calculator.form.html.j2 | 2 +- 2 files changed, 6 insertions(+), 10 deletions(-) diff --git a/caimira/apps/calculator/static/js/form.js b/caimira/apps/calculator/static/js/form.js index 715808f0..f24c21cc 100644 --- a/caimira/apps/calculator/static/js/form.js +++ b/caimira/apps/calculator/static/js/form.js @@ -247,6 +247,8 @@ function on_ventilation_type_change() { ventilation_types = $('input[type=radio][name=ventilation_type]'); ventilation_types.each(function (index) { if (this.checked) { + + if ($(this).val() != 'from_fitting') $('#button_fit_data').attr('data-previous-vent', $(this).val()) getChildElement($(this)).show(); require_fields(this); } else { @@ -498,20 +500,14 @@ function ventilation_from_fitting(condition_from_fitting) { $('input[type=radio][id=mechanical_ventilation]').prop("disabled", condition_from_fitting); $('input[type=radio][id=natural_ventilation]').prop("disabled", condition_from_fitting); $('input[type=radio][id=from_fitting]').prop("disabled", !condition_from_fitting); + if (condition_from_fitting) { $('input[type=radio][id=from_fitting]').prop('checked',true); $('#DIVfrom_fitting').after($('#window_opening_regime')); } else { - // Select the URL ventilation option, if any (from back-navigation) - var url = new URL(decodeURIComponent(window.location.href)); - let ventilation_from_url; - if (url.searchParams.has('ventilation_type')) { - ventilation_from_url = url.searchParams.get('ventilation_type'); - if (ventilation_from_url == 'from_fitting') ventilation_from_url = 'no_ventilation'; - } - else ventilation_from_url = 'no_ventilation'; - $(`input[type=radio][id=${ventilation_from_url}]`).prop('checked',true); + let selected_ventilation = $("#button_fit_data").attr('data-previous-vent'); + $(`input[type=radio][id=${selected_ventilation}]`).prop('checked',true); $('#DIVopening_distance').after($('#window_opening_regime')); } on_ventilation_type_change(); diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index 7c6cb522..f6f68ffa 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -692,7 +692,7 @@

    • - +
    From 594051eddc1f9abfac189fbece874b1573ea868e Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Tue, 4 Jul 2023 15:17:46 +0100 Subject: [PATCH 25/61] added visualisation for ach table in form and report --- caimira/apps/calculator/report_generator.py | 7 +++++++ caimira/apps/calculator/static/js/co2_form.js | 13 +++++++++---- caimira/apps/calculator/static/js/form.js | 1 - .../apps/templates/base/calculator.report.html.j2 | 10 +++++++--- 4 files changed, 23 insertions(+), 8 deletions(-) diff --git a/caimira/apps/calculator/report_generator.py b/caimira/apps/calculator/report_generator.py index 76c363f5..b70610bf 100644 --- a/caimira/apps/calculator/report_generator.py +++ b/caimira/apps/calculator/report_generator.py @@ -319,6 +319,12 @@ def readable_minutes(minutes: int) -> str: return time_str + unit +def hour_format(hour: float) -> str: + hours = int(hour) + minutes = int(hour % 1 * 60) + + return f"{hours}:{minutes}" + def percentage(absolute: float) -> float: return absolute * 100 @@ -514,6 +520,7 @@ def _template_environment(self) -> jinja2.Environment: env.filters['non_zero_percentage'] = non_zero_percentage env.filters['readable_minutes'] = readable_minutes env.filters['minutes_to_time'] = minutes_to_time + env.filters['hour_format'] = hour_format env.filters['float_format'] = "{0:.2f}".format env.filters['int_format'] = "{:0.0f}".format env.filters['percentage'] = percentage diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index e5277f3f..d03186a5 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -125,6 +125,12 @@ function validate() { return submit; } +function display_transition_times_hour_format(start, stop) { + var minutes_start = start % 1 * 60; + var minutes_stop = stop % 1 * 60; + return Math.floor(start) + ':' + minutes_start.toPrecision(2) + ' - ' + Math.floor(stop) + ':' + minutes_stop.toPrecision(2); +} + function display_fitting_data(json_response) { $("#DIV_CO2_fitting_result").show(); $("#CO2_data_plot").attr("src", json_response['CO2_plot']); @@ -132,11 +138,10 @@ function display_fitting_data(json_response) { delete json_response['CO2_plot']; $("#CO2_fitting_result").val(JSON.stringify(json_response)); $("#exhalation_rate_fit").html('Exhalation rate: ' + String(json_response['exhalation_rate'].toFixed(2)) + ' m³/h'); - let ventilation_table = "TimeVentilation value (ACH)"; + let ventilation_table = "Time (HH:MM)ACH value (h⁻¹)"; json_response['ventilation_values'].map((val, index) => { - console.log(json_response['transition_times']) - let transition_times = `${(json_response['transition_times'][index]).toFixed(2)} - ${(json_response['transition_times'][index + 1]).toFixed(2)}` - ventilation_table += `${transition_times}${val}`; + let transition_times = display_transition_times_hour_format(json_response['transition_times'][index], json_response['transition_times'][index + 1]); + ventilation_table += `${transition_times}${val.toPrecision(2)}`; }); $("#ventilation_rate_fit").html(ventilation_table); $("#generate_fitting_data").html('Fit data'); diff --git a/caimira/apps/calculator/static/js/form.js b/caimira/apps/calculator/static/js/form.js index f24c21cc..72eff671 100644 --- a/caimira/apps/calculator/static/js/form.js +++ b/caimira/apps/calculator/static/js/form.js @@ -500,7 +500,6 @@ function ventilation_from_fitting(condition_from_fitting) { $('input[type=radio][id=mechanical_ventilation]').prop("disabled", condition_from_fitting); $('input[type=radio][id=natural_ventilation]').prop("disabled", condition_from_fitting); $('input[type=radio][id=from_fitting]').prop("disabled", !condition_from_fitting); - if (condition_from_fitting) { $('input[type=radio][id=from_fitting]').prop('checked',true); $('#DIVfrom_fitting').after($('#window_opening_regime')); diff --git a/caimira/apps/templates/base/calculator.report.html.j2 b/caimira/apps/templates/base/calculator.report.html.j2 index cdbd26d0..fed4c361 100644 --- a/caimira/apps/templates/base/calculator.report.html.j2 +++ b/caimira/apps/templates/base/calculator.report.html.j2 @@ -530,11 +530,15 @@ {% endif %}

  • From Fitting: {% if form.ventilation_type == "from_fitting" %} - Yes + Yes - + {% for ventilation in form.CO2_fitting_result['ventilation_values'] %} - + {% set transition_time = form.CO2_fitting_result['transition_times'] %} + + + + {% endfor %}
    Ventilation value (ACH)
    Time (HH:MM)ACH value (h⁻¹)
    {{ventilation}}
    {{ transition_time[loop.index - 1] | hour_format }} - {{ transition_time[loop.index] | hour_format }}{{ ventilation | float_format }}
    {% else %} From e3b6326d238c49c8f38bb369ca9a660027b0ff3f Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Mon, 10 Jul 2023 15:45:22 +0100 Subject: [PATCH 26/61] deal with modal button labels and pre-selected ventilation options --- caimira/apps/calculator/static/js/co2_form.js | 5 ++++- caimira/apps/templates/base/calculator.form.html.j2 | 7 ++----- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index d03186a5..549a6329 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -28,6 +28,9 @@ const CO2_data_form = [ // Method to upload a valid excel file function upload_file() { + clear_fitting_algorithm(); + $("#generate_fitting_data").show(); + $("#save_and_dismiss_dialog").hide(); var files = document.getElementById("file_upload").files; if (files.length == 0) { alert("Please choose any file..."); @@ -145,6 +148,7 @@ function display_fitting_data(json_response) { }); $("#ventilation_rate_fit").html(ventilation_table); $("#generate_fitting_data").html('Fit data'); + $("#generate_fitting_data").hide(); $("#save_and_dismiss_dialog").show(); } @@ -181,6 +185,5 @@ function clear_fitting_algorithm() { $('span.' + "error_text").remove(); $('#DIV_CO2_fitting_result').hide(); $('#CO2_input_data_div').hide(); - $('#CO2_data_no').click(); ventilation_from_fitting(false); } diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index f6f68ffa..2b7f34b3 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -702,9 +702,6 @@

    -
    @@ -735,9 +732,9 @@
    - + - +
    From f9d4dead8703bcbc2ed825fa6c6e2d3f93fb47e0 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Mon, 10 Jul 2023 15:50:15 +0100 Subject: [PATCH 27/61] updated one text entry and variable declaration on JS --- caimira/apps/calculator/static/js/co2_form.js | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 549a6329..6fde640a 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -36,8 +36,8 @@ function upload_file() { alert("Please choose any file..."); return; } - var filename = files[0].name; - var extension = filename.substring(filename.lastIndexOf(".")).toUpperCase(); + const filename = files[0].name; + const extension = filename.substring(filename.lastIndexOf(".")).toUpperCase(); if (extension == ".XLS" || extension == ".XLSX") { //Here calling another method to read excel file into json excelFileToJSON(files[0]); @@ -92,7 +92,7 @@ function displayJsonToHtmlTable(jsonData) { format.value = JSON.stringify(structure); $('#generate_fitting_data').prop("disabled", false); } else { - table.innerHTML = "There is no data in Excel"; + table.innerHTML = "There is no data in the spreadsheet file"; } } From 5997049378634620a26f1d0a659da061996efa01 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Tue, 11 Jul 2023 14:09:17 +0100 Subject: [PATCH 28/61] renamed clear fitting algorithm method --- caimira/apps/calculator/static/js/co2_form.js | 9 +++++++-- caimira/apps/templates/base/calculator.form.html.j2 | 2 +- 2 files changed, 8 insertions(+), 3 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 6fde640a..59189d37 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -28,7 +28,7 @@ const CO2_data_form = [ // Method to upload a valid excel file function upload_file() { - clear_fitting_algorithm(); + clear_fitting_result_component(); $("#generate_fitting_data").show(); $("#save_and_dismiss_dialog").hide(); var files = document.getElementById("file_upload").files; @@ -177,7 +177,7 @@ function submit_fitting_algorithm(url) { } } -function clear_fitting_algorithm() { +function clear_fitting_result_component() { $('#generate_fitting_data').prop("disabled", true); $("#display_excel_data tbody").remove(); $('#CO2_fitting_result').val(''); @@ -185,5 +185,10 @@ function clear_fitting_algorithm() { $('span.' + "error_text").remove(); $('#DIV_CO2_fitting_result').hide(); $('#CO2_input_data_div').hide(); +} + +function clear_fitting_algorithm() { + clear_fitting_result_component(); + $('#CO2_data_no').click(); ventilation_from_fitting(false); } diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index 2b7f34b3..8880de6d 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -732,7 +732,7 @@
    - +
    From 91f16932ba5bd42f29072d355026e9a1a6cb4fb9 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 19 Jul 2023 17:04:31 +0200 Subject: [PATCH 29/61] ui modifications on html components --- .../templates/base/calculator.form.html.j2 | 146 +++++++++--------- .../templates/base/calculator.report.html.j2 | 2 +- 2 files changed, 74 insertions(+), 74 deletions(-) diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index 8880de6d..f7a4bc91 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -211,7 +211,7 @@ - +
    • From 6831b1ed7bea5bc37bca8029995d2998a1acd3fc Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 19 Jul 2023 17:04:40 +0200 Subject: [PATCH 30/61] ui modifications on js logic --- caimira/apps/calculator/static/js/co2_form.js | 313 +++++++++++------- caimira/apps/calculator/static/js/form.js | 44 +-- 2 files changed, 204 insertions(+), 153 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 59189d37..bf9751bd 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -1,7 +1,5 @@ -// JS file to handle manipulation on CO2 Fitting Algorithm Dialog. const CO2_data_form = [ 'CO2_data', - 'specific_breaks', 'exposed_coffee_break_option', 'exposed_coffee_duration', 'exposed_finish', @@ -9,6 +7,8 @@ const CO2_data_form = [ 'exposed_lunch_option', 'exposed_lunch_start', 'exposed_start', + 'fitting_ventilation_states', + 'fitting_ventilation_type', 'infected_coffee_break_option', 'infected_coffee_duration', 'infected_dont_have_breaks_with_exposed', @@ -21,174 +21,239 @@ const CO2_data_form = [ 'room_volume', 'total_people', 'ventilation_type', - 'windows_duration', - 'windows_frequency', - 'window_opening_regime', -] - -// Method to upload a valid excel file -function upload_file() { - clear_fitting_result_component(); - $("#generate_fitting_data").show(); - $("#save_and_dismiss_dialog").hide(); - var files = document.getElementById("file_upload").files; - if (files.length == 0) { - alert("Please choose any file..."); - return; - } - const filename = files[0].name; - const extension = filename.substring(filename.lastIndexOf(".")).toUpperCase(); - if (extension == ".XLS" || extension == ".XLSX") { - //Here calling another method to read excel file into json - excelFileToJSON(files[0]); - } else { - alert("Please select a valid excel file."); + ]; + + // Method to upload a valid excel file + function uploadFile(endpoint) { + clearFittingResultComponent(); + const files = document.getElementById("file_upload").files; + if (files.length === 0) { + alert("Please choose any file..."); + return; } -} - -//Method to read excel file and convert it into JSON -function excelFileToJSON(file) { + const file = files[0]; + const extension = file.name.substring(file.name.lastIndexOf(".")).toUpperCase(); + extension === ".XLS" || extension === ".XLSX" + ? excelFileToJSON(endpoint, file) + : alert("Please select a valid excel file."); + } + + // Method to read excel file and convert it into JSON + function excelFileToJSON(endpoint, file) { try { - var reader = new FileReader(); - reader.readAsBinaryString(file); - reader.onload = function (e) { - var data = e.target.result; - var workbook = XLSX.read(data, { type: "binary" }); - var firstSheetName = workbook.SheetNames[0]; - //reading only first sheet data - var jsonData = XLSX.utils.sheet_to_json(workbook.Sheets[firstSheetName]); - //displaying the json result into HTML table - displayJsonToHtmlTable(jsonData); - }; + const reader = new FileReader(); + reader.readAsBinaryString(file); + reader.onload = function (e) { + const data = e.target.result; + const workbook = XLSX.read(data, { type: "binary" }); + const firstSheetName = workbook.SheetNames[0]; + const jsonData = XLSX.utils.sheet_to_json(workbook.Sheets[firstSheetName]); + displayJsonToHtmlTable(endpoint, jsonData); + }; } catch (e) { - console.error(e); + console.error(e); } -} - -//Method to display the data in HTML Table -function displayJsonToHtmlTable(jsonData) { - var table = document.getElementById("display_excel_data"); - var format = document.getElementById("formatted_data"); - let structure = { times: [], CO2: [] }; + } + + // Method to display the data in HTML Table + function displayJsonToHtmlTable(endpoint, jsonData) { + const table = document.getElementById("display_excel_data"); + const format = document.getElementById("CO2_data"); + const structure = { times: [], CO2: [] }; if (jsonData.length > 0) { - var htmlData = "TimeCO2 Value"; - let jsonLength = jsonData.length; - for (var i = 0; i < jsonLength; i++) { - var row = jsonData[i]; - if (i < 5) { - htmlData += - ` - ${row["Times"].toFixed(2)} - - ${row["CO2"].toFixed(2)} - `; - } - structure["times"].push(row["Times"]); - structure["CO2"].push(row["CO2"]); + let htmlData = "TimeCO2 Value"; + const jsonLength = jsonData.length; + for (let i = 0; i < jsonLength; i++) { + const row = jsonData[i]; + if (i < 5) { + htmlData += ` + + ${row["Times"].toFixed(2)} + ${row["CO2"].toFixed(2)} + `; } - - if (jsonLength >= 5) htmlData += " ... ... "; - table.innerHTML = htmlData; - format.value = JSON.stringify(structure); - $('#generate_fitting_data').prop("disabled", false); + structure.times.push(row["Times"]); + structure.CO2.push(row["CO2"]); + } + + if (jsonLength >= 5) { + htmlData += " ... ... "; + } + format.value = JSON.stringify(structure); + $('#generate_fitting_data').prop("disabled", false); + $('#fitting_ventilation_states').prop('disabled', false); + $('[name=fitting_ventilation_type]').prop('disabled', false); + plotCO2Data(endpoint); } else { - table.innerHTML = "There is no data in the spreadsheet file"; + table.innerHTML = "There is no data in the spreadsheet file"; } -} - -// Method to download Excel template available on CERNBox -function downloadTemplate(uri = 'https://caimira-resources.web.cern.ch/CO2_template.xlsx', filename = 'CO2_template.xlsx') { - var link = document.createElement("a"); + } + + // Method to download Excel template available on CERNBox + function downloadTemplate(uri = 'https://caimira-resources.web.cern.ch/CO2_template.xlsx', filename = 'CO2_template.xlsx') { + const link = document.createElement("a"); link.download = filename; link.href = uri; document.body.appendChild(link); link.click(); document.body.removeChild(link); delete link; -} - -function insertErrorFor(referenceNode, text) { - var element = document.createElement("span"); + } + + function insertErrorFor(referenceNode, text) { + const element = document.createElement("span"); element.setAttribute("class", "error_text"); element.classList.add("red_text"); element.innerHTML = "  " + text; $(referenceNode).before(element); -} - -function validate() { + } + + function validateFormInputs(obj) { $('span.' + "error_text").remove(); let submit = true; - for (var i = 0; i < CO2_data_form.length; i++) { - let element = $(`[name=${CO2_data_form[i]}]`)[0]; - if (element.value === '') { - insertErrorFor($('#CO2_input_data_div'), `'${element.name}' must be defined.`); // raise error for total number and room volume. + for (let i = 0; i < CO2_data_form.length; i++) { + const element = $(`[name=${CO2_data_form[i]}]`)[0]; + if (element.name !== 'fitting_ventilation_states' && element.value === '') { + insertErrorFor($('#DIVCO2_data_dialog'), `'${element.name}' must be defined.
    `); + submit = false; + } + } + if (submit) { + $($(obj).data('target')).modal('show'); + } + return submit; + } + +function validateCO2Form() { + let submit = true; + if (validateFormInputs($('#button_fit_data'))) submit = true; + + // Check if natural ventilation is selected + if ($('input[name="fitting_ventilation_type"]:checked')[0].value == 'fitting_natural_ventilation') { + // Validate ventilation scheme + const element = $('[name=fitting_ventilation_states')[0] + if (element.value !== '') { + // validate input format + try { + const parsedValue = JSON.parse(element.value); + if (!Array.isArray(parsedValue)) { + insertErrorFor($('#DIVCO2_fitting_result'), `'${element.name}' must be a list.
    `); + submit = false; + }; + } catch { + insertErrorFor($('#DIVCO2_fitting_result'), `'${element.name}' must be a list of numbers.
    `); + submit = false; + }; + } else { + insertErrorFor($('#DIVCO2_fitting_result'), `'${element.name}' must be defined.
    `); submit = false; }; - } + }; + return submit; } -function display_transition_times_hour_format(start, stop) { - var minutes_start = start % 1 * 60; - var minutes_stop = stop % 1 * 60; - return Math.floor(start) + ':' + minutes_start.toPrecision(2) + ' - ' + Math.floor(stop) + ':' + minutes_stop.toPrecision(2); +function displayTransitionTimesHourFormat(start, stop) { + var minutes_start = (start % 1 * 60).toPrecision(2); + var minutes_stop = (stop % 1 * 60).toPrecision(2); + return Math.floor(start) + ':' + ((minutes_start != '0.0') ? minutes_start : '00') + ' - ' + Math.floor(stop) + ':' + ((minutes_stop != '0.0') ? minutes_stop : '00'); } -function display_fitting_data(json_response) { - $("#DIV_CO2_fitting_result").show(); +function displayFittingData(json_response) { + $("#DIVCO2_fitting_result").show(); $("#CO2_data_plot").attr("src", json_response['CO2_plot']); // Not needed for the form submit delete json_response['CO2_plot']; $("#CO2_fitting_result").val(JSON.stringify(json_response)); $("#exhalation_rate_fit").html('Exhalation rate: ' + String(json_response['exhalation_rate'].toFixed(2)) + ' m³/h'); let ventilation_table = "Time (HH:MM)ACH value (h⁻¹)"; - json_response['ventilation_values'].map((val, index) => { - let transition_times = display_transition_times_hour_format(json_response['transition_times'][index], json_response['transition_times'][index + 1]); + json_response['ventilation_values'].forEach((val, index) => { + let transition_times = displayTransitionTimesHourFormat(json_response['transition_times'][index], json_response['transition_times'][index + 1]); ventilation_table += `${transition_times}${val.toPrecision(2)}`; }); + $('#disable_fitting_algorithm').prop('disabled', false); $("#ventilation_rate_fit").html(ventilation_table); $("#generate_fitting_data").html('Fit data'); $("#generate_fitting_data").hide(); $("#save_and_dismiss_dialog").show(); } -function submit_fitting_algorithm(url) { - if (validate()) { - let CO2_mapping = {}; - CO2_data_form.map(el => { - let element = $(`[name=${el}]`); - // Validate radio buttons - if (element.length != 1) CO2_mapping[element[0].name] = $(`[name=${element[0].name}]:checked`)[0].value - else CO2_mapping[element[0].name] = element[0].value; - }) - $('#CO2_input_data_div').show(); - $("#generate_fitting_data").html( - `Loading...` - ); - $('#CO2_input_data').html(JSON.stringify(CO2_mapping, null, "\t")) +function formatCO2DataForm(CO2_data_form) { + let CO2_mapping = {}; + CO2_data_form.map(el => { + let element = $(`[name=${el}]`); + // Validate checkboxes + if (element[0].type == 'checkbox') { + CO2_mapping[element[0].name] = String(+element[0].checked); + } + // Validate radio buttons + else if (element[0].type == 'radio') CO2_mapping[element[0].name] = $(`[name=${element[0].name}]:checked`)[0].value; + else CO2_mapping[element[0].name] = element[0].value; + }); + return CO2_mapping; +} + +function plotCO2Data(url) { + if (validateFormInputs()) { + let CO2_mapping = formatCO2DataForm(CO2_data_form); fetch(url, { method: "POST", body: JSON.stringify(CO2_mapping), }) - .then((response) => response.json()) - .then((json_response) => { - display_fitting_data(json_response); - }); + .then((response) => + response.json() + .then(json_response => $("#CO2_data_plot").attr("src", json_response['CO2_plot'])) + .then($('#DIVCO2_fitting_to_submit').show()) + .catch(error => console.log(error)) + ); } } -function clear_fitting_result_component() { - $('#generate_fitting_data').prop("disabled", true); - $("#display_excel_data tbody").remove(); +function submitFittingAlgorithm(url) { + if (validateCO2Form()) { + // Disable all the ventilation inputs + $('#fitting_ventilation_states, [name=fitting_ventilation_type]').prop('disabled', true); + + // Prepare data for submission + const CO2_mapping = formatCO2DataForm(CO2_data_form); + $('#CO2_input_data_div').show(); + $('#disable_fitting_algorithm').prop('disabled', true); + $('#generate_fitting_data') + .html('Loading...') + .prop('disabled', true); + $('#CO2_input_data').html(JSON.stringify(CO2_mapping, null, '\t')); + + fetch(url, { + method: 'POST', + body: JSON.stringify(CO2_mapping), + }) + .then((response) => response.json()) + .then((json_response) => { + displayFittingData(json_response); + }); + } + } + + function clearFittingResultComponent() { + // Remove all the previously generated fitting elements + $('#generate_fitting_data').prop('disabled', true); $('#CO2_fitting_result').val(''); - $('#formatted_data').val(''); - $('span.' + "error_text").remove(); - $('#DIV_CO2_fitting_result').hide(); - $('#CO2_input_data_div').hide(); -} - -function clear_fitting_algorithm() { - clear_fitting_result_component(); - $('#CO2_data_no').click(); - ventilation_from_fitting(false); -} + $('#CO2_data').val('{}'); + $('#fitting_ventilation_states').val(''); + $('span.error_text').remove(); + $('#DIVCO2_fitting_result, #CO2_input_data_div').hide(); + $('#CO2_data_plot').attr('src', ''); + + // Update the ventilation scheme components + $('#fitting_ventilation_states, [name=fitting_ventilation_type]').prop('disabled', false); + + // Update the bottom right buttons + $('#generate_fitting_data').show(); + $('#save_and_dismiss_dialog').hide(); + } + + function disableFittingAlgorithm() { + clearFittingResultComponent(); + $('#CO2_data_no').click(); + } + diff --git a/caimira/apps/calculator/static/js/form.js b/caimira/apps/calculator/static/js/form.js index 72eff671..f497a3c4 100644 --- a/caimira/apps/calculator/static/js/form.js +++ b/caimira/apps/calculator/static/js/form.js @@ -247,8 +247,6 @@ function on_ventilation_type_change() { ventilation_types = $('input[type=radio][name=ventilation_type]'); ventilation_types.each(function (index) { if (this.checked) { - - if ($(this).val() != 'from_fitting') $('#button_fit_data').attr('data-previous-vent', $(this).val()) getChildElement($(this)).show(); require_fields(this); } else { @@ -495,32 +493,13 @@ function on_coffee_break_option_change() { } } -function ventilation_from_fitting(condition_from_fitting) { - $('input[type=radio][id=no_ventilation]').prop("disabled", condition_from_fitting); - $('input[type=radio][id=mechanical_ventilation]').prop("disabled", condition_from_fitting); - $('input[type=radio][id=natural_ventilation]').prop("disabled", condition_from_fitting); - $('input[type=radio][id=from_fitting]').prop("disabled", !condition_from_fitting); - if (condition_from_fitting) { - $('input[type=radio][id=from_fitting]').prop('checked',true); - $('#DIVfrom_fitting').after($('#window_opening_regime')); - } - else { - let selected_ventilation = $("#button_fit_data").attr('data-previous-vent'); - $(`input[type=radio][id=${selected_ventilation}]`).prop('checked',true); - $('#DIVopening_distance').after($('#window_opening_regime')); - } - on_ventilation_type_change(); -} - -function on_CO2_data_option_change() { - CO2_data_options = $('input[type=radio][name=CO2_data_option]'); - CO2_data_options.each(function (index){ +function on_CO2_fitting_ventilation_change() { + ventilation_options = $('input[type=radio][name=fitting_ventilation_type]'); + ventilation_options.each(function (index) { if (this.checked) { - if (this.id == 'CO2_data_yes') ventilation_from_fitting(true); - else if (this.id == 'CO2_data_no') ventilation_from_fitting(false); getChildElement($(this)).show(); require_fields(this); - } + } else { getChildElement($(this)).hide(); require_fields(this); @@ -700,6 +679,13 @@ function validate_form(form) { on_short_range_option_change(); } + // Check if fitting is selected + if ($('input[type=radio][id=from_fitting]').prop('checked') ) { + if ($('#CO2_fitting_result').val() == '') + $("input[type=radio][id=no_ventilation]").prop("checked", true); + on_ventilation_type_change(); + } + if (submit) { $("#generate_report").prop("disabled", true); //Add spinner to button @@ -969,7 +955,7 @@ $(document).ready(function () { // Populate CO2 Fitting Algorithm Dialog let CO2_data = url.searchParams.has('CO2_fitting_result') ? url.searchParams.get('CO2_fitting_result') : null; - if (CO2_data) display_fitting_data(JSON.parse(CO2_data)); + if (CO2_data) displayFittingData(JSON.parse(CO2_data)); // Populate primary vaccine dropdown $("#vaccine_type option").remove(); @@ -1086,11 +1072,11 @@ $(document).ready(function () { // Call the function now to handle forward/back button presses in the browser. on_coffee_break_option_change(); - // When the CO2_data_option changes we want to make its respective + // When the ventilation on the fitting changes we want to make its respective // children show/hide. - $("input[type=radio][name=CO2_data_option]").change(on_CO2_data_option_change); + $("input[type=radio][name=fitting_ventilation_type]").change(on_CO2_fitting_ventilation_change); // Call the function now to handle forward/back button presses in the browser. - on_CO2_data_option_change(); + on_CO2_fitting_ventilation_change(); // Setup the maximum number of people at page load (to handle back/forward), // and update it when total people is changed. From d3298c32310a04b16b5043d80d72ba653d787415 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 19 Jul 2023 17:05:11 +0200 Subject: [PATCH 31/61] back-end updates for co2 logic --- caimira/apps/calculator/__init__.py | 57 +++++----- .../apps/calculator/co2_model_generator.py | 100 +++++++++++------- caimira/apps/calculator/defaults.py | 1 - caimira/apps/calculator/model_generator.py | 20 ++-- caimira/apps/calculator/report_generator.py | 2 +- caimira/models.py | 9 +- 6 files changed, 106 insertions(+), 83 deletions(-) diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index 97b20fca..401849d7 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -351,8 +351,20 @@ def check_xsrf_cookie(self): Thus, XSRF cookies are disabled by overriding base class implementation of this method with a pass statement. """ pass + + def generate_ventilation_plot(self, CO2Data, transition_times = None, ventilation_values = None): + fig = plt.figure(figsize=(7, 4), dpi=110) + plt.plot(CO2Data['times'], CO2Data['CO2']) + if (transition_times and ventilation_values): + for index, time in enumerate(transition_times[:-1]): + plt.axvline(x = time, color = 'grey', linewidth=0.5, linestyle='--') + y_location = (CO2Data['CO2'][min(range(len(CO2Data['times'])), key=lambda i: abs(CO2Data['times'][i]-time))]) + plt.text(x = time + 0.04, y = y_location, s=round(ventilation_values[index], 2)) + plt.xlabel('Time of day') + plt.ylabel('Concentration (ppm)') + return img2base64(_figure2bytes(fig)) - async def post(self) -> None: + async def post(self, endpoint: str) -> None: requested_model_config = tornado.escape.json_decode(self.request.body) try: form = co2_model_generator.CO2FormData.from_dict(requested_model_config) @@ -365,31 +377,24 @@ async def post(self) -> None: self.finish(json.dumps(response_json)) return - executor = loky.get_reusable_executor( - max_workers=self.settings['handler_worker_pool_size'], - timeout=300, - ) - report_task = executor.submit( - co2_model_generator.CO2FormData.build_model, form, - ) - report = await asyncio.wrap_future(report_task) - - def generate_ventilation_plot(transition_times: tuple, ventilation_values: tuple): - fig = plt.figure(figsize=(7, 4), dpi=110) - plt.plot(form.CO2_data['times'], form.CO2_data['CO2']) - for index, time in enumerate(transition_times[:-1]): - plt.axvline(x = time, color = 'grey', linewidth=0.5, linestyle='--') - y_location = (form.CO2_data['CO2'][min(range(len(form.CO2_data['times'])), key=lambda i: abs(form.CO2_data['times'][i]-time))]) - plt.text(x = time + 0.04, y = y_location, s=round(ventilation_values[index], 2)) - plt.xlabel('Time of day') - plt.ylabel('Concentration (ppm)') - return fig + if endpoint == 'plot': + self.finish({'CO2_plot': self.generate_ventilation_plot(form.CO2_data)}) + else: + executor = loky.get_reusable_executor( + max_workers=self.settings['handler_worker_pool_size'], + timeout=300, + ) + report_task = executor.submit( + co2_model_generator.CO2FormData.build_model, form, + ) + report = await asyncio.wrap_future(report_task) + + result = dict(report.CO2_fit_params()) + result['fitting_ventilation_type'] = 'fitting_natural_ventilation' + result['transition_times'] = report.ventilation_transition_times + result['CO2_plot'] = self.generate_ventilation_plot(form.CO2_data, report.ventilation_transition_times, result['ventilation_values']) + self.finish(result) - result = dict(report.CO2_fit_params()) - result['transition_times'] = report.ventilation_transition_times - result['CO2_plot'] = img2base64(_figure2bytes(generate_ventilation_plot(report.ventilation_transition_times, result['ventilation_values']))) - self.finish(result) - def get_url(app_root: str, relative_path: str = '/'): return app_root.rstrip('/') + relative_path.rstrip('/') @@ -412,7 +417,7 @@ def make_app( base_urls: typing.List = [ (get_root_url(r'/?'), LandingPage), (get_root_calculator_url(r'/?'), CalculatorForm), - (get_root_calculator_url(r'/co2-fit/'), CO2Data), + (get_root_calculator_url(r'/co2-fit/(.*)'), CO2Data), (get_root_calculator_url(r'/report'), ConcentrationModel), (get_root_url(r'/static/(.*)'), StaticFileHandler, {'path': static_dir}), (get_root_calculator_url(r'/static/(.*)'), StaticFileHandler, {'path': calculator_static_dir}), diff --git a/caimira/apps/calculator/co2_model_generator.py b/caimira/apps/calculator/co2_model_generator.py index 39e61d29..063fc6a2 100644 --- a/caimira/apps/calculator/co2_model_generator.py +++ b/caimira/apps/calculator/co2_model_generator.py @@ -4,7 +4,10 @@ import typing from caimira import models +from caimira import data from . import model_generator +import caimira.monte_carlo as mc +from caimira.monte_carlo.data import activity_distributions, virus_distributions, mask_distributions, short_range_distances minutes_since_midnight = typing.NewType('minutes_since_midnight', int) @@ -18,7 +21,6 @@ @dataclasses.dataclass class CO2FormData: CO2_data: dict - specific_breaks: dict exposed_coffee_break_option: str exposed_coffee_duration: int exposed_finish: minutes_since_midnight @@ -26,6 +28,8 @@ class CO2FormData: exposed_lunch_option: bool exposed_lunch_start: minutes_since_midnight exposed_start: minutes_since_midnight + fitting_ventilation_states: list + fitting_ventilation_type: str infected_coffee_break_option: str #Used if infected_dont_have_breaks_with_exposed infected_coffee_duration: int #Used if infected_dont_have_breaks_with_exposed infected_dont_have_breaks_with_exposed: bool @@ -38,15 +42,11 @@ class CO2FormData: room_volume: float total_people: int ventilation_type: str - windows_duration: float - windows_frequency: float - window_opening_regime: str #: The default values for undefined fields. Note that the defaults here #: and the defaults in the html form must not be contradictory. _DEFAULTS: typing.ClassVar[typing.Dict[str, typing.Any]] = { 'CO2_data': '{}', - 'specific_breaks': '{}', 'exposed_coffee_break_option': 'coffee_break_0', 'exposed_coffee_duration': 5, 'exposed_finish': '17:30', @@ -54,6 +54,8 @@ class CO2FormData: 'exposed_lunch_option': True, 'exposed_lunch_start': '12:30', 'exposed_start': '08:30', + 'fitting_ventilation_states': '[]', + 'fitting_ventilation_type': 'fitting_natural_ventilation', 'infected_coffee_break_option': 'coffee_break_0', 'infected_coffee_duration': 5, 'infected_dont_have_breaks_with_exposed': False, @@ -66,9 +68,6 @@ class CO2FormData: 'room_volume': _NO_DEFAULT, 'total_people': _NO_DEFAULT, 'ventilation_type': 'no_ventilation', - 'windows_duration': 10., - 'windows_frequency': 60., - 'window_opening_regime': 'windows_open_permanently', } @classmethod @@ -100,18 +99,47 @@ def from_dict(cls, form_data: typing.Dict) -> "CO2FormData": return instance def build_model(self) -> models.CO2Data: - population_presence=self.population_present_interval() - last_time_present = population_presence.boundaries()[-1][-1] - last_present_time_index = next((index for index, time in enumerate(self.CO2_data['times']) - if time > last_time_present), len(self.CO2_data['times'])) + infected_population: models.Population = self.infected_population() + exposed_population: models.Population = self.exposed_population() + all_state_changes=self.population_present_interval() + + total_people = [infected_population.people_present(stop) + exposed_population.people_present(stop) + for _, stop in zip(all_state_changes[:-1], all_state_changes[1:])] return models.CO2Data( room_volume=self.room_volume, - number=self.total_people, - presence=population_presence, - ventilation_transition_times=self.ventilation_transition_times(last_time_present), - times=self.CO2_data['times'][:last_present_time_index], - CO2_concentrations=self.CO2_data['CO2'][:last_present_time_index], + number=models.IntPiecewiseConstant(transition_times=tuple(all_state_changes), values=tuple(total_people)), + presence=None, + ventilation_transition_times=self.ventilation_transition_times(), + times=self.CO2_data['times'], + CO2_concentrations=self.CO2_data['CO2'], ) + + def exposed_population(self) -> models.Population: + infected_occupants = self.infected_people + # The number of exposed occupants is the total number of occupants + # minus the number of infected occupants. + exposed_occupants = self.total_people - infected_occupants + + exposed = models.Population( + number=exposed_occupants, + presence=self.exposed_present_interval(), + activity=models.Activity.types['Seated'], + mask=models.Mask.types['No mask'], + host_immunity=0., + ) + return exposed + + def infected_population(self) -> models.Population: + infected_occupants = self.infected_people + + infected = models.Population( + number=infected_occupants, + presence=self.infected_present_interval(), + activity=models.Activity.types['Seated'], + mask=models.Mask.types['No mask'], + host_immunity=0., + ) + return infected def _compute_breaks_in_interval(self, start, finish, n_breaks, duration) -> models.BoundarySequence_t: break_delay = ((finish - start) - (n_breaks * duration)) // (n_breaks+1) @@ -287,40 +315,32 @@ def present_interval( LOG.debug("trailing interval") present_intervals.append((current_time / 60, finish / 60)) return models.SpecificInterval(tuple(present_intervals)) - - def infected_present_interval(self) -> models.Interval: - if self.specific_breaks != {}: # It means the breaks are specific and not predefined - breaks = self.generate_specific_break_times(self.specific_breaks['infected_breaks']) - else: - breaks = self.infected_lunch_break_times() + self.infected_coffee_break_times() - return self.present_interval( - self.infected_start, self.infected_finish, - breaks=breaks, - ) - def population_present_interval(self) -> models.Interval: + def population_present_interval(self) -> typing.List[float]: state_change_times = set(self.infected_present_interval().transition_times()) state_change_times.update(self.exposed_present_interval().transition_times()) - all_state_changes = sorted(state_change_times) - return models.SpecificInterval(tuple(zip(all_state_changes[:-1], all_state_changes[1:]))) + return sorted(state_change_times) def exposed_present_interval(self) -> models.Interval: - if self.specific_breaks != {}: # It means the breaks are specific and not predefined - breaks = self.generate_specific_break_times(self.specific_breaks['exposed_breaks']) - else: - breaks = self.exposed_lunch_break_times() + self.exposed_coffee_break_times() + breaks = self.exposed_lunch_break_times() + self.exposed_coffee_break_times() return self.present_interval( self.exposed_start, self.exposed_finish, breaks=breaks, ) + + def infected_present_interval(self) -> models.Interval: + breaks = self.infected_lunch_break_times() + self.infected_coffee_break_times() + return self.present_interval( + self.infected_start, self.infected_finish, + breaks=breaks, + ) - def ventilation_transition_times(self, last_present_time) -> typing.Tuple[float, ...]: - if self.ventilation_type == 'from_fitting' and self.window_opening_regime == 'windows_open_periodically': - transition_times = sorted(models.PeriodicInterval(self.windows_frequency, - self.windows_duration, min(self.infected_start, self.exposed_start)/60).transition_times()) - return tuple(filter(lambda x: x <= last_present_time, transition_times)) + def ventilation_transition_times(self) -> typing.Tuple[float, ...]: + # Check what type of ventilation is considered for the fitting + if self.fitting_ventilation_type == 'fitting_natural_ventilation': + return tuple(self.fitting_ventilation_states) else: - return tuple((min(self.infected_start, self.exposed_start)/60, max(self.infected_finish, self.exposed_finish)/60), ) # all day long + return tuple((self.CO2_data['times'][0], self.CO2_data['times'][-1])) #: Mapping of field name to a callable which can convert values from form #: input (URL encoded arguments / string) into the correct type. diff --git a/caimira/apps/calculator/defaults.py b/caimira/apps/calculator/defaults.py index 35ced634..339a2bed 100644 --- a/caimira/apps/calculator/defaults.py +++ b/caimira/apps/calculator/defaults.py @@ -22,7 +22,6 @@ 'ceiling_height': 0., 'conditional_probability_plot': False, 'conditional_probability_viral_loads': False, - 'CO2_data_option': False, 'CO2_fitting_result': '{}', 'exposed_coffee_break_option': 'coffee_break_0', 'exposed_coffee_duration': 5, diff --git a/caimira/apps/calculator/model_generator.py b/caimira/apps/calculator/model_generator.py index 97749fd2..387b8e9d 100644 --- a/caimira/apps/calculator/model_generator.py +++ b/caimira/apps/calculator/model_generator.py @@ -37,7 +37,6 @@ class FormData: ceiling_height: float conditional_probability_plot: bool conditional_probability_viral_loads: bool - CO2_data_option: bool CO2_fitting_result: dict exposed_coffee_break_option: str exposed_coffee_duration: int @@ -438,16 +437,15 @@ def outside_temp(self) -> models.PiecewiseConstant: def ventilation(self) -> models._VentilationBase: always_on = models.PeriodicInterval(period=120, duration=120) - periodic_interval = models.PeriodicInterval(self.windows_frequency, self.windows_duration, min(self.infected_start, self.exposed_start)/60) - - if self.CO2_data_option: - ventilations = [] - if self.ventilation_type == 'from_fitting' and self.window_opening_regime == 'windows_open_periodically': - for index, time in enumerate(sorted(list(periodic_interval.transition_times()))[:-1]): - if index < len(self.CO2_fitting_result['ventilation_values']): - ventilations.append(models.AirChange(active=models.SpecificInterval(present_times=((time, time + self.windows_duration/60), )), - air_exch=self.CO2_fitting_result['ventilation_values'][index])) - else: break + periodic_interval = models.PeriodicInterval(self.windows_frequency, self.windows_duration, + min(self.infected_start, self.exposed_start)/60) + if self.ventilation_type == 'from_fitting': + ventilations = [] + if self.CO2_fitting_result['fitting_ventilation_type'] == 'fitting_natural_ventilation': + transition_times = self.CO2_fitting_result['transition_times'] + for index, (start, stop) in enumerate(zip(transition_times[:-1], transition_times[1:])): + ventilations.append(models.AirChange(active=models.SpecificInterval(present_times=((start, stop), )), + air_exch=self.CO2_fitting_result['ventilation_values'][index])) else: ventilations.append(models.AirChange(active=always_on, air_exch=self.CO2_fitting_result['ventilation_values'][0])) return models.MultipleVentilation(tuple(ventilations)) diff --git a/caimira/apps/calculator/report_generator.py b/caimira/apps/calculator/report_generator.py index b70610bf..eb33791d 100644 --- a/caimira/apps/calculator/report_generator.py +++ b/caimira/apps/calculator/report_generator.py @@ -323,7 +323,7 @@ def hour_format(hour: float) -> str: hours = int(hour) minutes = int(hour % 1 * 60) - return f"{hours}:{minutes}" + return f"{hours}:{minutes if minutes != 0 else '00'}" def percentage(absolute: float) -> float: return absolute * 100 diff --git a/caimira/models.py b/caimira/models.py index a9f2c0ec..c515144f 100644 --- a/caimira/models.py +++ b/caimira/models.py @@ -1527,11 +1527,12 @@ def fun(x): exhalation_rate=exhalation_rate, ventilation_values=ventilation_values ) - return np.sqrt(np.sum((np.array(self.CO2_concentrations) - np.array(the_concentrations))**2)) - + return np.sqrt(np.sum((np.array(self.CO2_concentrations) - + np.array(the_concentrations))**2)) # The goal is to minimize the difference between the two different curves (known concentrations vs. predicted concentrations) - res_dict = minimize(fun=fun, x0=np.ones(len(self.ventilation_transition_times)), method='powell', bounds=[ - (0, None) for _ in range(len(self.ventilation_transition_times))], options={'xtol': 1e-3}) + res_dict = minimize(fun=fun, x0=np.ones(len(self.ventilation_transition_times)), method='powell', + bounds=[(0, None) for _ in range(len(self.ventilation_transition_times))], + options={'xtol': 1e-3}) exhalation_rate = res_dict['x'][0] ventilation_values = res_dict['x'][1:] From 9abb4d64cf91932e8b6e43f86dd31b3edab4edaa Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 19 Jul 2023 17:29:02 +0200 Subject: [PATCH 32/61] version update and UI bugfix on form submission --- caimira/apps/calculator/__init__.py | 6 +++--- caimira/apps/templates/base/calculator.form.html.j2 | 6 +++--- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index 401849d7..3002f6f1 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -29,7 +29,7 @@ from . import markdown_tools from . import model_generator, co2_model_generator -from .report_generator import ReportGenerator, calculate_report_data +from .report_generator import ReportGenerator, calculate_report_data, img2base64, _figure2bytes from .user import AuthenticatedUser, AnonymousUser # The calculator version is based on a combination of the model version and the @@ -39,7 +39,7 @@ # calculator version. If the calculator needs to make breaking changes (e.g. change # form attributes) then it can also increase its MAJOR version without needing to # increase the overall CAiMIRA version (found at ``caimira.__version__``). -__version__ = "4.13.0" +__version__ = "4.14.0" LOG = logging.getLogger(__name__) @@ -390,7 +390,7 @@ async def post(self, endpoint: str) -> None: report = await asyncio.wrap_future(report_task) result = dict(report.CO2_fit_params()) - result['fitting_ventilation_type'] = 'fitting_natural_ventilation' + result['fitting_ventilation_type'] = form.fitting_ventilation_type result['transition_times'] = report.ventilation_transition_times result['CO2_plot'] = self.generate_ventilation_plot(form.CO2_data, report.ventilation_transition_times, result['ventilation_values']) self.finish(result) diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index f7a4bc91..c12cb6c0 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -344,15 +344,15 @@
    Ventilation scheme:
    - + - +
    From 580c63eb82ed4585640759378648957f5d7a8af4 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Thu, 20 Jul 2023 15:24:39 +0200 Subject: [PATCH 33/61] replaced alert message on file upload --- caimira/apps/calculator/static/js/co2_form.js | 8 ++++++-- caimira/apps/templates/base/calculator.form.html.j2 | 3 +-- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index bf9751bd..39596a61 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -28,9 +28,11 @@ const CO2_data_form = [ clearFittingResultComponent(); const files = document.getElementById("file_upload").files; if (files.length === 0) { - alert("Please choose any file..."); + $("#upload-error").show(); return; - } + } else { + $("#upload-error").hide(); + }; const file = files[0]; const extension = file.name.substring(file.name.lastIndexOf(".")).toUpperCase(); extension === ".XLS" || extension === ".XLSX" @@ -120,6 +122,7 @@ const CO2_data_form = [ } if (submit) { $($(obj).data('target')).modal('show'); + $("#upload-error").hide(); } return submit; } @@ -242,6 +245,7 @@ function submitFittingAlgorithm(url) { $('#fitting_ventilation_states').val(''); $('span.error_text').remove(); $('#DIVCO2_fitting_result, #CO2_input_data_div').hide(); + $('#DIVCO2_fitting_to_submit').hide(); $('#CO2_data_plot').attr('src', ''); // Update the ventilation scheme components diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index c12cb6c0..4516d187 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -297,7 +297,6 @@ -
    @@ -331,7 +330,7 @@ -
    +
    From 1fa2f8085bcdd463f7796f55de47f3d566a7d459 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Thu, 20 Jul 2023 16:10:22 +0200 Subject: [PATCH 34/61] added error handling on valid excel files and replaced plain javascript with jquery calls --- caimira/apps/calculator/static/js/co2_form.js | 40 +++++-------------- .../templates/base/calculator.form.html.j2 | 7 ++-- 2 files changed, 14 insertions(+), 33 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 39596a61..518127c7 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -26,7 +26,7 @@ const CO2_data_form = [ // Method to upload a valid excel file function uploadFile(endpoint) { clearFittingResultComponent(); - const files = document.getElementById("file_upload").files; + const files = $("#file_upload")[0].files; if (files.length === 0) { $("#upload-error").show(); return; @@ -37,7 +37,7 @@ const CO2_data_form = [ const extension = file.name.substring(file.name.lastIndexOf(".")).toUpperCase(); extension === ".XLS" || extension === ".XLSX" ? excelFileToJSON(endpoint, file) - : alert("Please select a valid excel file."); + : $('#upload-file-extention-error').show(); } // Method to read excel file and convert it into JSON @@ -59,36 +59,21 @@ const CO2_data_form = [ // Method to display the data in HTML Table function displayJsonToHtmlTable(endpoint, jsonData) { - const table = document.getElementById("display_excel_data"); - const format = document.getElementById("CO2_data"); + // const table = $("#display_excel_data"); + const format = $("#CO2_data"); const structure = { times: [], CO2: [] }; if (jsonData.length > 0) { - let htmlData = "TimeCO2 Value"; - const jsonLength = jsonData.length; - for (let i = 0; i < jsonLength; i++) { + for (let i = 0; i < jsonData.length; i++) { const row = jsonData[i]; - if (i < 5) { - htmlData += ` - - ${row["Times"].toFixed(2)} - ${row["CO2"].toFixed(2)} - `; - } structure.times.push(row["Times"]); structure.CO2.push(row["CO2"]); } - - if (jsonLength >= 5) { - htmlData += " ... ... "; - } - format.value = JSON.stringify(structure); + format.val(JSON.stringify(structure)); $('#generate_fitting_data').prop("disabled", false); $('#fitting_ventilation_states').prop('disabled', false); $('[name=fitting_ventilation_type]').prop('disabled', false); plotCO2Data(endpoint); - } else { - table.innerHTML = "There is no data in the spreadsheet file"; - } + }; } // Method to download Excel template available on CERNBox @@ -103,15 +88,12 @@ const CO2_data_form = [ } function insertErrorFor(referenceNode, text) { - const element = document.createElement("span"); - element.setAttribute("class", "error_text"); - element.classList.add("red_text"); - element.innerHTML = "  " + text; + const element = $('').addClass('error_text red_text').html('  ' + text); $(referenceNode).before(element); } function validateFormInputs(obj) { - $('span.' + "error_text").remove(); + $('span.error_text').remove(); let submit = true; for (let i = 0; i < CO2_data_form.length; i++) { const element = $(`[name=${CO2_data_form[i]}]`)[0]; @@ -123,6 +105,7 @@ const CO2_data_form = [ if (submit) { $($(obj).data('target')).modal('show'); $("#upload-error").hide(); + $('#upload-file-extention-error').hide(); } return submit; } @@ -165,7 +148,7 @@ function displayTransitionTimesHourFormat(start, stop) { function displayFittingData(json_response) { $("#DIVCO2_fitting_result").show(); $("#CO2_data_plot").attr("src", json_response['CO2_plot']); - // Not needed for the form submit + // Not needed for the form submission delete json_response['CO2_plot']; $("#CO2_fitting_result").val(JSON.stringify(json_response)); $("#exhalation_rate_fit").html('Exhalation rate: ' + String(json_response['exhalation_rate'].toFixed(2)) + ' m³/h'); @@ -260,4 +243,3 @@ function submitFittingAlgorithm(url) { clearFittingResultComponent(); $('#CO2_data_no').click(); } - diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index 4516d187..109e2c99 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -331,12 +331,11 @@ +
    - -
    +
    - +
    - +
    @@ -323,7 +323,7 @@
    -
    Upload an Excel file to preview in HTML Table
    +
    Upload an Excel file to preview in HTML Table

    @@ -355,11 +355,11 @@
    diff --git a/caimira/apps/templates/base/calculator.report.html.j2 b/caimira/apps/templates/base/calculator.report.html.j2 index 9b1776f6..58bf8f68 100644 --- a/caimira/apps/templates/base/calculator.report.html.j2 +++ b/caimira/apps/templates/base/calculator.report.html.j2 @@ -531,7 +531,7 @@

  • From Fitting: {% if form.ventilation_type == "from_fitting" %} Yes - +
    {% for ventilation in form.CO2_fitting_result['ventilation_values'] %} {% set transition_time = form.CO2_fitting_result['transition_times'] %} @@ -596,7 +596,7 @@ Gym - For comparison only, all persons doing heavy physical exercise, breathing and not speaking. {% endif %} {% if form.ventilation_type == "from_fitting" %} -

    Exhalation rate from fitting algorithm - {{form.CO2_fitting_result['exhalation_rate'] | round(2, 'floor')}} m³/h

    +

    Exhalation rate from fitting algorithm - {{form.CO2_fitting_result['exhalation_rate'] | round(2, 'floor')}} m³/h

    {% endif %}

    {% if form.short_range_option == "short_range_yes" %} From 2a855e9dd2ea4247949ee27bca4088683e33c7ab Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Mon, 24 Jul 2023 11:32:36 +0200 Subject: [PATCH 36/61] validation on the excel file given as input (using SheetJS) --- caimira/apps/calculator/static/js/co2_form.js | 554 +++++++++++------- .../templates/base/calculator.form.html.j2 | 3 +- caimira/apps/templates/base/layout.html.j2 | 5 +- 3 files changed, 338 insertions(+), 224 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 4618263c..c87739ef 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -1,245 +1,357 @@ const CO2_data_form = [ - 'CO2_data', - 'exposed_coffee_break_option', - 'exposed_coffee_duration', - 'exposed_finish', - 'exposed_lunch_finish', - 'exposed_lunch_option', - 'exposed_lunch_start', - 'exposed_start', - 'fitting_ventilation_states', - 'fitting_ventilation_type', - 'infected_coffee_break_option', - 'infected_coffee_duration', - 'infected_dont_have_breaks_with_exposed', - 'infected_finish', - 'infected_lunch_finish', - 'infected_lunch_option', - 'infected_lunch_start', - 'infected_people', - 'infected_start', - 'room_volume', - 'total_people', - 'ventilation_type', - ]; - - // Method to upload a valid excel file - function uploadFile(endpoint) { - clearFittingResultComponent(); - const files = $("#file_upload")[0].files; - if (files.length === 0) { - $("#upload-error").show(); - return; - } else { - $("#upload-error").hide(); - }; - const file = files[0]; - const extension = file.name.substring(file.name.lastIndexOf(".")).toUpperCase(); - extension === ".XLS" || extension === ".XLSX" - ? excelFileToJSON(endpoint, file) - : $('#upload-file-extention-error').show(); + "CO2_data", + "exposed_coffee_break_option", + "exposed_coffee_duration", + "exposed_finish", + "exposed_lunch_finish", + "exposed_lunch_option", + "exposed_lunch_start", + "exposed_start", + "fitting_ventilation_states", + "fitting_ventilation_type", + "infected_coffee_break_option", + "infected_coffee_duration", + "infected_dont_have_breaks_with_exposed", + "infected_finish", + "infected_lunch_finish", + "infected_lunch_option", + "infected_lunch_start", + "infected_people", + "infected_start", + "room_volume", + "total_people", + "ventilation_type", +]; + +// Method to upload a valid excel file +function uploadFile(endpoint) { + clearFittingResultComponent(); + const files = $("#file_upload")[0].files; + if (files.length === 0) { + $("#upload-error").show(); + return; } - - // Method to read excel file and convert it into JSON - function excelFileToJSON(endpoint, file) { - try { - const reader = new FileReader(); - reader.readAsBinaryString(file); - reader.onload = function (e) { - const data = e.target.result; - const workbook = XLSX.read(data, { type: "binary" }); - const firstSheetName = workbook.SheetNames[0]; - const jsonData = XLSX.utils.sheet_to_json(workbook.Sheets[firstSheetName]); - displayJsonToHtmlTable(endpoint, jsonData); - }; - } catch (e) { - console.error(e); - } + const file = files[0]; + const extension = file.name + .substring(file.name.lastIndexOf(".")) + .toUpperCase(); + if (extension !== ".XLS" && extension !== ".XLSX") { + $("#upload-error") + .text("Please select a valid excel file (.XLS or .XLSX).") + .show(); + return; } - - // Method to display the data in HTML Table - function displayJsonToHtmlTable(endpoint, jsonData) { - // const table = $("#display_excel_data"); - const format = $("#CO2_data"); - const structure = { times: [], CO2: [] }; - if (jsonData.length > 0) { - for (let i = 0; i < jsonData.length; i++) { - const row = jsonData[i]; - structure.times.push(row["Times"]); - structure.CO2.push(row["CO2"]); - } - format.val(JSON.stringify(structure)); - $('#generate_fitting_data').prop("disabled", false); - $('#fitting_ventilation_states').prop('disabled', false); - $('[name=fitting_ventilation_type]').prop('disabled', false); - plotCO2Data(endpoint); - }; + + // FileReader API to read the Excel file + const reader = new FileReader(); + reader.onload = function (event) { + const fileContent = event.target.result; + const workbook = XLSX.read(fileContent, { type: "binary" }); + + // Assuming the first sheet is the one we want to validate + const firstSheetName = workbook.SheetNames[0]; + const worksheet = workbook.Sheets[firstSheetName]; + + // Check if the headers match the expected format + const headerCoordinates = { + Times: "A1", + CO2: "B1", + }; + for (const header in headerCoordinates) { + const cellValue = worksheet[headerCoordinates[header]]?.v; + if ( + !cellValue || + cellValue.trim().toLowerCase() !== header.toLowerCase() + ) { + $("#upload-error") + .text(`The file does not have the expected header "${header}".`) + .show(); + return; + } + } + + // Check if there is any data below the header row + if (data.length <= 1) { + $("#upload-error") + .text( + "The Excel file is empty. Please make sure it contains data below the header row." + ) + .show(); + return; + } + + // Validate data in the columns + const data = XLSX.utils.sheet_to_json(worksheet, { header: 1, raw: false }); + const timesColumnIndex = 0; + const CO2ColumnIndex = 1; + for (let i = 1; i < data.length; i++) { + try { + const timesCellValue = parseFloat(data[i][timesColumnIndex]); + const CO2CellValue = parseFloat(data[i][CO2ColumnIndex]); + + if (isNaN(timesCellValue) || isNaN(CO2CellValue)) { + throw new Error("Invalid data in the Times or CO2 columns."); + } + } catch (error) { + $("#upload-error") + .text( + "Invalid data in the Times or CO2 columns. Please make sure they contain only float values." + ) + .show(); + return; + } + } + + // Call function to convert Excel file to JSON and further processing + try { + generateJSONStructure(endpoint, data); + // If all validations pass, process the file here or display a success message + $("#upload-file-extention-error").hide(); + } catch (error) { + console.log(error); + } + }; + reader.readAsBinaryString(file); // Read the file as a binary string +} + +// Method to generate the JSON structure +function generateJSONStructure(endpoint, jsonData) { + const inputToPopulate = $("#CO2_data"); + + // Initialize the final structure + const finalStructure = { times: [], CO2: [] }; + + if (jsonData.length > 0) { + // Loop through the input dataArray and extract the values starting from the second array (index 1) + for (let i = 1; i < jsonData.length; i++) { + const arr = jsonData[i]; + // Assuming arr contains two float values + finalStructure.times.push(parseFloat(arr[0])); + finalStructure.CO2.push(parseFloat(arr[1])); + } + inputToPopulate.val(JSON.stringify(finalStructure)); + $("#generate_fitting_data").prop("disabled", false); + $("#fitting_ventilation_states").prop("disabled", false); + $("[name=fitting_ventilation_type]").prop("disabled", false); + plotCO2Data(endpoint); } - - // Method to download Excel template available on CERNBox - function downloadTemplate(uri = 'https://caimira-resources.web.cern.ch/CO2_template.xlsx', filename = 'CO2_template.xlsx') { - const link = document.createElement("a"); - link.download = filename; - link.href = uri; - document.body.appendChild(link); - link.click(); - document.body.removeChild(link); - delete link; +} + +// Method to download Excel template available on CERNBox +function downloadTemplate( + uri = "https://caimira-resources.web.cern.ch/CO2_template.xlsx", + filename = "CO2_template.xlsx" +) { + const link = document.createElement("a"); + link.download = filename; + link.href = uri; + document.body.appendChild(link); + link.click(); + document.body.removeChild(link); + delete link; +} + +function insertErrorFor(referenceNode, text) { + const element = $("") + .addClass("error_text text-danger") + .html("  " + text); + $(referenceNode).before(element); +} + +function validateFormInputs(obj) { + $("span.error_text").remove(); + let submit = true; + for (let i = 0; i < CO2_data_form.length; i++) { + const element = $(`[name=${CO2_data_form[i]}]`)[0]; + if (element.name !== "fitting_ventilation_states" && element.value === "") { + insertErrorFor( + $("#DIVCO2_data_dialog"), + `'${element.name}' must be defined.
    ` + ); + submit = false; + } } - - function insertErrorFor(referenceNode, text) { - const element = $('').addClass('error_text text-danger').html('  ' + text); - $(referenceNode).before(element); + if (submit) { + $($(obj).data("target")).modal("show"); + $("#upload-error").hide(); + $("#upload-file-extention-error").hide(); } - - function validateFormInputs(obj) { - $('span.error_text').remove(); - let submit = true; - for (let i = 0; i < CO2_data_form.length; i++) { - const element = $(`[name=${CO2_data_form[i]}]`)[0]; - if (element.name !== 'fitting_ventilation_states' && element.value === '') { - insertErrorFor($('#DIVCO2_data_dialog'), `'${element.name}' must be defined.
    `); - submit = false; - } - } - if (submit) { - $($(obj).data('target')).modal('show'); - $("#upload-error").hide(); - $('#upload-file-extention-error').hide(); - } - return submit; - } + return submit; +} function validateCO2Form() { - let submit = true; - if (validateFormInputs($('#button_fit_data'))) submit = true; - - // Check if natural ventilation is selected - if ($('input[name="fitting_ventilation_type"]:checked')[0].value == 'fitting_natural_ventilation') { - // Validate ventilation scheme - const element = $('[name=fitting_ventilation_states')[0] - if (element.value !== '') { - // validate input format - try { - const parsedValue = JSON.parse(element.value); - if (!Array.isArray(parsedValue)) { - insertErrorFor($('#DIVCO2_fitting_result'), `'${element.name}' must be a list.
    `); - submit = false; - }; - } catch { - insertErrorFor($('#DIVCO2_fitting_result'), `'${element.name}' must be a list of numbers.
    `); - submit = false; - }; - } else { - insertErrorFor($('#DIVCO2_fitting_result'), `'${element.name}' must be defined.
    `); - submit = false; - }; - }; - - return submit; + let submit = true; + if (validateFormInputs($("#button_fit_data"))) submit = true; + + // Check if natural ventilation is selected + if ( + $('input[name="fitting_ventilation_type"]:checked')[0].value == + "fitting_natural_ventilation" + ) { + // Validate ventilation scheme + const element = $("[name=fitting_ventilation_states")[0]; + if (element.value !== "") { + // validate input format + try { + const parsedValue = JSON.parse(element.value); + if (!Array.isArray(parsedValue)) { + insertErrorFor( + $("#DIVCO2_fitting_result"), + `'${element.name}' must be a list.
    ` + ); + submit = false; + } + } catch { + insertErrorFor( + $("#DIVCO2_fitting_result"), + `'${element.name}' must be a list of numbers.
    ` + ); + submit = false; + } + } else { + insertErrorFor( + $("#DIVCO2_fitting_result"), + `'${element.name}' must be defined.
    ` + ); + submit = false; + } + } + + return submit; } function displayTransitionTimesHourFormat(start, stop) { - var minutes_start = (start % 1 * 60).toPrecision(2); - var minutes_stop = (stop % 1 * 60).toPrecision(2); - return Math.floor(start) + ':' + ((minutes_start != '0.0') ? minutes_start : '00') + ' - ' + Math.floor(stop) + ':' + ((minutes_stop != '0.0') ? minutes_stop : '00'); + var minutes_start = ((start % 1) * 60).toPrecision(2); + var minutes_stop = ((stop % 1) * 60).toPrecision(2); + return ( + Math.floor(start) + + ":" + + (minutes_start != "0.0" ? minutes_start : "00") + + " - " + + Math.floor(stop) + + ":" + + (minutes_stop != "0.0" ? minutes_stop : "00") + ); } function displayFittingData(json_response) { - $("#DIVCO2_fitting_result").show(); - $("#CO2_data_plot").attr("src", json_response['CO2_plot']); - // Not needed for the form submission - delete json_response['CO2_plot']; - $("#CO2_fitting_result").val(JSON.stringify(json_response)); - $("#exhalation_rate_fit").html('Exhalation rate: ' + String(json_response['exhalation_rate'].toFixed(2)) + ' m³/h'); - let ventilation_table = "    "; - json_response['ventilation_values'].forEach((val, index) => { - let transition_times = displayTransitionTimesHourFormat(json_response['transition_times'][index], json_response['transition_times'][index + 1]); - ventilation_table += ``; - }); - $('#disable_fitting_algorithm').prop('disabled', false); - $("#ventilation_rate_fit").html(ventilation_table); - $("#generate_fitting_data").html('Fit data'); - $("#generate_fitting_data").hide(); - $("#save_and_dismiss_dialog").show(); + $("#DIVCO2_fitting_result").show(); + $("#CO2_data_plot").attr("src", json_response["CO2_plot"]); + // Not needed for the form submission + delete json_response["CO2_plot"]; + $("#CO2_fitting_result").val(JSON.stringify(json_response)); + $("#exhalation_rate_fit").html( + "Exhalation rate: " + + String(json_response["exhalation_rate"].toFixed(2)) + + " m³/h" + ); + let ventilation_table = + ""; + json_response["ventilation_values"].forEach((val, index) => { + let transition_times = displayTransitionTimesHourFormat( + json_response["transition_times"][index], + json_response["transition_times"][index + 1] + ); + ventilation_table += ``; + }); + $("#disable_fitting_algorithm").prop("disabled", false); + $("#ventilation_rate_fit").html(ventilation_table); + $("#generate_fitting_data").html("Fit data"); + $("#generate_fitting_data").hide(); + $("#save_and_dismiss_dialog").show(); } function formatCO2DataForm(CO2_data_form) { - let CO2_mapping = {}; - CO2_data_form.map(el => { - let element = $(`[name=${el}]`); - // Validate checkboxes - if (element[0].type == 'checkbox') { - CO2_mapping[element[0].name] = String(+element[0].checked); - } - // Validate radio buttons - else if (element[0].type == 'radio') CO2_mapping[element[0].name] = $(`[name=${element[0].name}]:checked`)[0].value; - else CO2_mapping[element[0].name] = element[0].value; - }); - return CO2_mapping; + let CO2_mapping = {}; + CO2_data_form.map((el) => { + let element = $(`[name=${el}]`); + // Validate checkboxes + if (element[0].type == "checkbox") { + CO2_mapping[element[0].name] = String(+element[0].checked); + } + // Validate radio buttons + else if (element[0].type == "radio") + CO2_mapping[element[0].name] = $( + `[name=${element[0].name}]:checked` + )[0].value; + else CO2_mapping[element[0].name] = element[0].value; + }); + return CO2_mapping; } function plotCO2Data(url) { - if (validateFormInputs()) { - let CO2_mapping = formatCO2DataForm(CO2_data_form); - fetch(url, { - method: "POST", - body: JSON.stringify(CO2_mapping), - }) - .then((response) => - response.json() - .then(json_response => $("#CO2_data_plot").attr("src", json_response['CO2_plot'])) - .then($('#DIVCO2_fitting_to_submit').show()) - .catch(error => console.log(error)) - ); - } + if (validateFormInputs()) { + let CO2_mapping = formatCO2DataForm(CO2_data_form); + fetch(url, { + method: "POST", + body: JSON.stringify(CO2_mapping), + }).then((response) => + response + .json() + .then((json_response) => + $("#CO2_data_plot").attr("src", json_response["CO2_plot"]) + ) + .then($("#DIVCO2_fitting_to_submit").show()) + .catch((error) => console.log(error)) + ); + } } function submitFittingAlgorithm(url) { - if (validateCO2Form()) { - // Disable all the ventilation inputs - $('#fitting_ventilation_states, [name=fitting_ventilation_type]').prop('disabled', true); - - // Prepare data for submission - const CO2_mapping = formatCO2DataForm(CO2_data_form); - $('#CO2_input_data_div').show(); - $('#disable_fitting_algorithm').prop('disabled', true); - $('#generate_fitting_data') - .html('Loading...') - .prop('disabled', true); - $('#CO2_input_data').html(JSON.stringify(CO2_mapping, null, '\t')); - - fetch(url, { - method: 'POST', - body: JSON.stringify(CO2_mapping), - }) - .then((response) => response.json()) - .then((json_response) => { - displayFittingData(json_response); - }); - } - } - - function clearFittingResultComponent() { - // Remove all the previously generated fitting elements - $('#generate_fitting_data').prop('disabled', true); - $('#CO2_fitting_result').val(''); - $('#CO2_data').val('{}'); - $('#fitting_ventilation_states').val(''); - $('span.error_text').remove(); - $('#DIVCO2_fitting_result, #CO2_input_data_div').hide(); - $('#DIVCO2_fitting_to_submit').hide(); - $('#CO2_data_plot').attr('src', ''); - - // Update the ventilation scheme components - $('#fitting_ventilation_states, [name=fitting_ventilation_type]').prop('disabled', false); - - // Update the bottom right buttons - $('#generate_fitting_data').show(); - $('#save_and_dismiss_dialog').hide(); - } - - function disableFittingAlgorithm() { - clearFittingResultComponent(); - $('#CO2_data_no').click(); + if (validateCO2Form()) { + // Disable all the ventilation inputs + $("#fitting_ventilation_states, [name=fitting_ventilation_type]").prop( + "disabled", + true + ); + + // Prepare data for submission + const CO2_mapping = formatCO2DataForm(CO2_data_form); + $("#CO2_input_data_div").show(); + $("#disable_fitting_algorithm").prop("disabled", true); + $("#generate_fitting_data") + .html( + 'Loading...' + ) + .prop("disabled", true); + $("#CO2_input_data").html(JSON.stringify(CO2_mapping, null, "\t")); + + fetch(url, { + method: "POST", + body: JSON.stringify(CO2_mapping), + }) + .then((response) => response.json()) + .then((json_response) => { + displayFittingData(json_response); + }); } +} + +function clearFittingResultComponent() { + // Remove all the previously generated fitting elements + $("#generate_fitting_data").prop("disabled", true); + $("#CO2_fitting_result").val(""); + $("#CO2_data").val("{}"); + $("#fitting_ventilation_states").val(""); + $("span.error_text").remove(); + $("#DIVCO2_fitting_result, #CO2_input_data_div").hide(); + $("#DIVCO2_fitting_to_submit").hide(); + $("#CO2_data_plot").attr("src", ""); + + // Update the ventilation scheme components + $("#fitting_ventilation_states, [name=fitting_ventilation_type]").prop( + "disabled", + false + ); + + // Update the bottom right buttons + $("#generate_fitting_data").show(); + $("#save_and_dismiss_dialog").hide(); +} + +function disableFittingAlgorithm() { + clearFittingResultComponent(); + $("#CO2_data_no").click(); +} diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index 91be606c..7b7d0d6b 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -330,8 +330,7 @@ - - +

    diff --git a/caimira/apps/templates/base/layout.html.j2 b/caimira/apps/templates/base/layout.html.j2 index 73d7637d..5ea37537 100644 --- a/caimira/apps/templates/base/layout.html.j2 +++ b/caimira/apps/templates/base/layout.html.j2 @@ -110,7 +110,10 @@ - + + + + {% block body_scripts %} {% endblock body_scripts %} From 296e45b07344d553ca282e4b11452780a87d1664 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Mon, 24 Jul 2023 13:56:18 +0200 Subject: [PATCH 37/61] back-end optimizations using heritage --- .../apps/calculator/co2_model_generator.py | 382 ++++++------------ caimira/apps/calculator/static/js/co2_form.js | 2 +- caimira/models.py | 8 +- 3 files changed, 120 insertions(+), 272 deletions(-) diff --git a/caimira/apps/calculator/co2_model_generator.py b/caimira/apps/calculator/co2_model_generator.py index 063fc6a2..1a935577 100644 --- a/caimira/apps/calculator/co2_model_generator.py +++ b/caimira/apps/calculator/co2_model_generator.py @@ -4,48 +4,42 @@ import typing from caimira import models -from caimira import data from . import model_generator -import caimira.monte_carlo as mc -from caimira.monte_carlo.data import activity_distributions, virus_distributions, mask_distributions, short_range_distances +from .defaults import DEFAULT_MC_SAMPLE_SIZE, NO_DEFAULT, COFFEE_OPTIONS_INT minutes_since_midnight = typing.NewType('minutes_since_midnight', int) LOG = logging.getLogger(__name__) -# 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() - @dataclasses.dataclass -class CO2FormData: +class CO2FormData(model_generator.FormData): CO2_data: dict exposed_coffee_break_option: str exposed_coffee_duration: int - exposed_finish: minutes_since_midnight - exposed_lunch_finish: minutes_since_midnight + exposed_finish: model_generator.minutes_since_midnight + exposed_lunch_finish: model_generator.minutes_since_midnight exposed_lunch_option: bool - exposed_lunch_start: minutes_since_midnight - exposed_start: minutes_since_midnight + exposed_lunch_start: model_generator.minutes_since_midnight + exposed_start: model_generator.minutes_since_midnight fitting_ventilation_states: list fitting_ventilation_type: str infected_coffee_break_option: str #Used if infected_dont_have_breaks_with_exposed infected_coffee_duration: int #Used if infected_dont_have_breaks_with_exposed infected_dont_have_breaks_with_exposed: bool - infected_finish: minutes_since_midnight - infected_lunch_finish: minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed + infected_finish: model_generator.minutes_since_midnight + infected_lunch_finish: model_generator.minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed infected_lunch_option: bool #Used if infected_dont_have_breaks_with_exposed - infected_lunch_start: minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed + infected_lunch_start: model_generator.minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed infected_people: int - infected_start: minutes_since_midnight + infected_start: model_generator.minutes_since_midnight room_volume: float total_people: int - ventilation_type: str #: The default values for undefined fields. Note that the defaults here #: and the defaults in the html form must not be contradictory. _DEFAULTS: typing.ClassVar[typing.Dict[str, typing.Any]] = { + 'activity_type': 'office', 'CO2_data': '{}', 'exposed_coffee_break_option': 'coffee_break_0', 'exposed_coffee_duration': 5, @@ -54,6 +48,7 @@ class CO2FormData: 'exposed_lunch_option': True, 'exposed_lunch_start': '12:30', 'exposed_start': '08:30', + 'mask_wearing_option': False, 'fitting_ventilation_states': '[]', 'fitting_ventilation_type': 'fitting_natural_ventilation', 'infected_coffee_break_option': 'coffee_break_0', @@ -65,13 +60,21 @@ class CO2FormData: 'infected_lunch_start': '12:30', 'infected_people': 1, 'infected_start': '08:30', - 'room_volume': _NO_DEFAULT, - 'total_people': _NO_DEFAULT, - 'ventilation_type': 'no_ventilation', + 'room_volume': NO_DEFAULT, + 'specific_breaks': '{}', + 'total_people': NO_DEFAULT, + 'vaccine_option': False, + 'ventilation_type': 'from_fitting', + 'virus_type': 'SARS_CoV_2', } + def __init__(self, **kwargs): + # Set default values defined in CO2FormData + for key, value in self._DEFAULTS.items(): + setattr(self, key, kwargs.get(key, value)) + @classmethod - def from_dict(cls, form_data: typing.Dict) -> "CO2FormData": + def from_dict(self, form_data: typing.Dict) -> "CO2FormData": # Take a copy of the form data so that we can mutate it. form_data = form_data.copy() form_data.pop('_xsrf', None) @@ -81,31 +84,96 @@ def from_dict(cls, form_data: typing.Dict) -> "CO2FormData": if isinstance(value, str): form_data[key] = html.escape(value) - for key, default_value in cls._DEFAULTS.items(): + for key, default_value in self._DEFAULTS.items(): if form_data.get(key, '') == '': - if default_value is _NO_DEFAULT: + if default_value is NO_DEFAULT: raise ValueError(f"{key} must be specified") form_data[key] = default_value for key, value in form_data.items(): - if key in _CAST_RULES_FORM_ARG_TO_NATIVE: - form_data[key] = _CAST_RULES_FORM_ARG_TO_NATIVE[key](value) + if key in model_generator._CAST_RULES_FORM_ARG_TO_NATIVE: + form_data[key] = model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[key](value) - if key not in cls._DEFAULTS: + if key not in self._DEFAULTS: raise ValueError(f'Invalid argument "{html.escape(key)}" given') - instance = cls(**form_data) - # instance.validate() + instance = self(**form_data) + instance.validate() return instance - - def build_model(self) -> models.CO2Data: - infected_population: models.Population = self.infected_population() - exposed_population: models.Population = self.exposed_population() - all_state_changes=self.population_present_interval() + + def validate(self): + # Validate number of infected <= number of total people + if self.infected_people >= self.total_people: + raise ValueError('Number of infected people cannot be more or equal than number of total people.') + + # Validate time intervals selected by user + time_intervals = [ + ['exposed_start', 'exposed_finish'], + ['infected_start', 'infected_finish'], + ] + if self.exposed_lunch_option: + time_intervals.append(['exposed_lunch_start', 'exposed_lunch_finish']) + if self.infected_dont_have_breaks_with_exposed and self.infected_lunch_option: + time_intervals.append(['infected_lunch_start', 'infected_lunch_finish']) + + for start_name, end_name in time_intervals: + start = getattr(self, start_name) + end = getattr(self, end_name) + if start > end: + raise ValueError( + f"{start_name} must be less than {end_name}. Got {start} and {end}.") + + def validate_lunch(start, finish): + lunch_start = getattr(self, f'{population}_lunch_start') + lunch_finish = getattr(self, f'{population}_lunch_finish') + return (start <= lunch_start <= finish and + start <= lunch_finish <= finish) + + def get_lunch_mins(population): + lunch_mins = 0 + if getattr(self, f'{population}_lunch_option'): + lunch_mins = getattr(self, f'{population}_lunch_finish') - getattr(self, f'{population}_lunch_start') + return lunch_mins + + def get_coffee_mins(population): + coffee_mins = 0 + if getattr(self, f'{population}_coffee_break_option') != 'coffee_break_0': + coffee_mins = COFFEE_OPTIONS_INT[getattr(self, f'{population}_coffee_break_option')] * getattr(self, f'{population}_coffee_duration') + return coffee_mins + + def get_activity_mins(population): + return getattr(self, f'{population}_finish') - getattr(self, f'{population}_start') + + populations = ['exposed', 'infected'] if self.infected_dont_have_breaks_with_exposed else ['exposed'] + for population in populations: + # Validate lunch time within the activity times. + if (getattr(self, f'{population}_lunch_option') and + not validate_lunch(getattr(self, f'{population}_start'), getattr(self, f'{population}_finish')) + ): + raise ValueError( + f"{population} lunch break must be within presence times." + ) + + # Length of breaks < length of activity + if (get_lunch_mins(population) + get_coffee_mins(population)) >= get_activity_mins(population): + raise ValueError( + f"Length of breaks >= Length of {population} presence." + ) + + validation_tuples = [('exposed_coffee_break_option', COFFEE_OPTIONS_INT), + ('infected_coffee_break_option', COFFEE_OPTIONS_INT),] + for attr_name, valid_set in validation_tuples: + if getattr(self, attr_name) not in valid_set: + raise ValueError(f"{getattr(self, attr_name)} is not a valid value for {attr_name}") + + def build_model(self, size=DEFAULT_MC_SAMPLE_SIZE) -> models.CO2DataModel: # type: ignore + infected_population: models.Population = self.infected_population().build_model(size) + exposed_population: models.Population = self.exposed_population().build_model(size) + all_state_changes=self.population_present_changes() total_people = [infected_population.people_present(stop) + exposed_population.people_present(stop) for _, stop in zip(all_state_changes[:-1], all_state_changes[1:])] - return models.CO2Data( + return models.CO2DataModel( room_volume=self.room_volume, number=models.IntPiecewiseConstant(transition_times=tuple(all_state_changes), values=tuple(total_people)), presence=None, @@ -114,227 +182,11 @@ def build_model(self) -> models.CO2Data: CO2_concentrations=self.CO2_data['CO2'], ) - def exposed_population(self) -> models.Population: - infected_occupants = self.infected_people - # The number of exposed occupants is the total number of occupants - # minus the number of infected occupants. - exposed_occupants = self.total_people - infected_occupants - - exposed = models.Population( - number=exposed_occupants, - presence=self.exposed_present_interval(), - activity=models.Activity.types['Seated'], - mask=models.Mask.types['No mask'], - host_immunity=0., - ) - return exposed - - def infected_population(self) -> models.Population: - infected_occupants = self.infected_people - - infected = models.Population( - number=infected_occupants, - presence=self.infected_present_interval(), - activity=models.Activity.types['Seated'], - mask=models.Mask.types['No mask'], - host_immunity=0., - ) - return infected - - def _compute_breaks_in_interval(self, start, finish, n_breaks, duration) -> models.BoundarySequence_t: - break_delay = ((finish - start) - (n_breaks * duration)) // (n_breaks+1) - break_times = [] - end = start - for n in range(n_breaks): - begin = end + break_delay - end = begin + duration - break_times.append((begin, end)) - return tuple(break_times) - - def exposed_lunch_break_times(self) -> models.BoundarySequence_t: - result = [] - if self.exposed_lunch_option: - result.append((self.exposed_lunch_start, self.exposed_lunch_finish)) - return tuple(result) - - def infected_lunch_break_times(self) -> models.BoundarySequence_t: - if self.infected_dont_have_breaks_with_exposed: - result = [] - if self.infected_lunch_option: - result.append((self.infected_lunch_start, self.infected_lunch_finish)) - return tuple(result) - else: - return self.exposed_lunch_break_times() - - def exposed_number_of_coffee_breaks(self) -> int: - return model_generator.COFFEE_OPTIONS_INT[self.exposed_coffee_break_option] - - def infected_number_of_coffee_breaks(self) -> int: - return model_generator.COFFEE_OPTIONS_INT[self.infected_coffee_break_option] - - def _coffee_break_times(self, activity_start, activity_finish, coffee_breaks, coffee_duration, lunch_start, lunch_finish) -> models.BoundarySequence_t: - time_before_lunch = lunch_start - activity_start - time_after_lunch = activity_finish - lunch_finish - before_lunch_frac = time_before_lunch / (time_before_lunch + time_after_lunch) - n_morning_breaks = round(coffee_breaks * before_lunch_frac) - breaks = ( - self._compute_breaks_in_interval( - activity_start, lunch_start, n_morning_breaks, coffee_duration - ) - + self._compute_breaks_in_interval( - lunch_finish, activity_finish, coffee_breaks - n_morning_breaks, coffee_duration - ) - ) - return breaks - - def exposed_coffee_break_times(self) -> models.BoundarySequence_t: - exposed_coffee_breaks = self.exposed_number_of_coffee_breaks() - if exposed_coffee_breaks == 0: - return () - if self.exposed_lunch_option: - breaks = self._coffee_break_times(self.exposed_start, self.exposed_finish, exposed_coffee_breaks, self.exposed_coffee_duration, self.exposed_lunch_start, self.exposed_lunch_finish) - else: - breaks = self._compute_breaks_in_interval(self.exposed_start, self.exposed_finish, exposed_coffee_breaks, self.exposed_coffee_duration) - return breaks - - def infected_coffee_break_times(self) -> models.BoundarySequence_t: - if self.infected_dont_have_breaks_with_exposed: - infected_coffee_breaks = self.infected_number_of_coffee_breaks() - if infected_coffee_breaks == 0: - return () - if self.infected_lunch_option: - breaks = self._coffee_break_times(self.infected_start, self.infected_finish, infected_coffee_breaks, self.infected_coffee_duration, self.infected_lunch_start, self.infected_lunch_finish) - else: - breaks = self._compute_breaks_in_interval(self.infected_start, self.infected_finish, infected_coffee_breaks, self.infected_coffee_duration) - return breaks - else: - return self.exposed_coffee_break_times() - - def generate_specific_break_times(self, population_breaks) -> models.BoundarySequence_t: - break_times = [] - for n in population_breaks: - # Parse break times. - begin = model_generator.time_string_to_minutes(n["start_time"]) - end = model_generator.time_string_to_minutes(n["finish_time"]) - for time in [begin, end]: - # For a specific break, the infected and exposed presence is the same. - if not getattr(self, 'infected_start') < time < getattr(self, 'infected_finish'): - raise ValueError(f'All breaks should be within the simulation time. Got {model_generator.time_minutes_to_string(time)}.') - - break_times.append((begin, end)) - return tuple(break_times) - - def present_interval( - self, - start: int, - finish: int, - breaks: typing.Optional[models.BoundarySequence_t] = None, - ) -> models.Interval: - """ - Calculate the presence interval given the start and end times (in minutes), and - a number of monotonic, non-overlapping, but potentially unsorted, breaks (also in minutes). - - """ - if not breaks: - # If there are no breaks, the interval is the start and end. - return models.SpecificInterval(((start/60, finish/60),)) - - # Order the breaks by their start-time, and ensure that they are monotonic - # and that the start of one break happens after the end of another. - break_boundaries: models.BoundarySequence_t = tuple(sorted(breaks, key=lambda break_pair: break_pair[0])) - - for break_start, break_end in break_boundaries: - if break_start >= break_end: - raise ValueError("Break ends before it begins.") - - prev_break_end = break_boundaries[0][1] - for break_start, break_end in break_boundaries[1:]: - if prev_break_end >= break_start: - raise ValueError(f"A break starts before another ends ({break_start}, {break_end}, {prev_break_end}).") - prev_break_end = break_end - - present_intervals = [] - - current_time = start - LOG.debug(f"starting time march at {model_generator._hours2timestring(current_time/60)} to {model_generator._hours2timestring(finish/60)}") - - # As we step through the breaks. For each break there are 6 important cases - # we must cover. Let S=start; E=end; Bs=Break start; Be=Break end: - # 1. The interval is entirely before the break. S < E <= Bs < Be - # 2. The interval straddles the start of the break. S < Bs < E <= Be - # 3. The break is entirely inside the interval. S < Bs < Be <= E - # 4. The interval is entirely inside the break. Bs <= S < E <= Be - # 5. The interval straddles the end of the break. Bs <= S < Be <= E - # 6. The interval is entirely after the break. Bs < Be <= S < E - - for current_break in break_boundaries: - if current_time >= finish: - break - - LOG.debug(f"handling break {model_generator._hours2timestring(current_break[0]/60)}-{model_generator._hours2timestring(current_break[1]/60)} " - f" (current time: {model_generator._hours2timestring(current_time/60)})") - - break_s, break_e = current_break - case1 = finish <= break_s - case2 = current_time < break_s < finish < break_e - case3 = current_time < break_s < break_e <= finish - case4 = break_s <= current_time < finish <= break_e - case5 = break_s <= current_time < break_e < finish - case6 = break_e <= current_time - - if case1: - LOG.debug(f"case 1: interval entirely before break") - present_intervals.append((current_time / 60, finish / 60)) - LOG.debug(f" + added interval {model_generator._hours2timestring(present_intervals[-1][0])} " - f"- {model_generator._hours2timestring(present_intervals[-1][1])}") - current_time = finish - elif case2: - LOG.debug(f"case 2: interval straddles start of break") - present_intervals.append((current_time / 60, break_s / 60)) - LOG.debug(f" + added interval {model_generator._hours2timestring(present_intervals[-1][0])} " - f"- {model_generator._hours2timestring(present_intervals[-1][1])}") - current_time = break_e - elif case3: - LOG.debug(f"case 3: break entirely inside interval") - # We add the bit before the break, but not the bit afterwards, - # as it may hit another break. - present_intervals.append((current_time / 60, break_s / 60)) - LOG.debug(f" + added interval {model_generator._hours2timestring(present_intervals[-1][0])} " - f"- {model_generator._hours2timestring(present_intervals[-1][1])}") - current_time = break_e - elif case4: - LOG.debug(f"case 4: interval entirely inside break") - current_time = finish - elif case5: - LOG.debug(f"case 5: interval straddles end of break") - current_time = break_e - elif case6: - LOG.debug(f"case 6: interval entirely after the break") - - if current_time < finish: - LOG.debug("trailing interval") - present_intervals.append((current_time / 60, finish / 60)) - return models.SpecificInterval(tuple(present_intervals)) - - def population_present_interval(self) -> typing.List[float]: + def population_present_changes(self) -> typing.List[float]: state_change_times = set(self.infected_present_interval().transition_times()) state_change_times.update(self.exposed_present_interval().transition_times()) return sorted(state_change_times) - def exposed_present_interval(self) -> models.Interval: - breaks = self.exposed_lunch_break_times() + self.exposed_coffee_break_times() - return self.present_interval( - self.exposed_start, self.exposed_finish, - breaks=breaks, - ) - - def infected_present_interval(self) -> models.Interval: - breaks = self.infected_lunch_break_times() + self.infected_coffee_break_times() - return self.present_interval( - self.infected_start, self.infected_finish, - breaks=breaks, - ) - def ventilation_transition_times(self) -> typing.Tuple[float, ...]: # Check what type of ventilation is considered for the fitting if self.fitting_ventilation_type == 'fitting_natural_ventilation': @@ -342,29 +194,21 @@ def ventilation_transition_times(self) -> typing.Tuple[float, ...]: else: return tuple((self.CO2_data['times'][0], self.CO2_data['times'][-1])) -#: Mapping of field name to a callable which can convert values from form -#: input (URL encoded arguments / string) into the correct type. -_CAST_RULES_FORM_ARG_TO_NATIVE: typing.Dict[str, typing.Callable] = {} - -#: Mapping of field name to callable which can convert native type to values -#: that can be encoded to URL arguments. -_CAST_RULES_NATIVE_TO_FORM_ARG: typing.Dict[str, typing.Callable] = {} - for _field in dataclasses.fields(CO2FormData): if _field.type is minutes_since_midnight: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.time_string_to_minutes - _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.time_minutes_to_string + model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.time_string_to_minutes + model_generator._CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.time_minutes_to_string elif _field.type is int: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator._safe_int_cast + model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator._safe_int_cast elif _field.type is float: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = float + model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = float elif _field.type is bool: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = lambda v: v == '1' - _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = int + model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = lambda v: v == '1' + model_generator._CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = int elif _field.type is list: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.string_to_list - _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.list_to_string + model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.string_to_list + model_generator._CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.list_to_string elif _field.type is dict: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.string_to_dict - _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.dict_to_string + model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.string_to_dict + model_generator._CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.dict_to_string diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index c87739ef..6a2128eb 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -70,6 +70,7 @@ function uploadFile(endpoint) { } } + const data = XLSX.utils.sheet_to_json(worksheet, { header: 1, raw: false }); // Check if there is any data below the header row if (data.length <= 1) { $("#upload-error") @@ -81,7 +82,6 @@ function uploadFile(endpoint) { } // Validate data in the columns - const data = XLSX.utils.sheet_to_json(worksheet, { header: 1, raw: false }); const timesColumnIndex = 0; const CO2ColumnIndex = 1; for (let i = 1; i < data.length; i++) { diff --git a/caimira/models.py b/caimira/models.py index c515144f..2f04a0bb 100644 --- a/caimira/models.py +++ b/caimira/models.py @@ -1485,8 +1485,12 @@ def _normed_interpolated_longrange_exposure_between_bounds( @dataclass(frozen=True) -class CO2Data: - # TODO - docstring +class CO2DataModel: + ''' + The CO2DataModel class models CO2 data based on room volume, ventilation transition times, and people presence. + It uses optimization techniques to fit the model's parameters and estimate the exhalation rate and ventilation + values that best match the measured CO2 concentrations. + ''' room_volume: float number: typing.Union[int, IntPiecewiseConstant] presence: typing.Optional[Interval] From 21129f4ee4a935ecdf550fb5afbbbd98442de062 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 26 Jul 2023 17:16:46 +0200 Subject: [PATCH 38/61] formatting issues and introduction of pelt algorithm to display suggested transition times --- caimira/apps/calculator/__init__.py | 51 +++++++++++++++---- caimira/apps/calculator/static/js/co2_form.js | 36 ++++++++++++- .../templates/base/calculator.form.html.j2 | 7 +-- 3 files changed, 81 insertions(+), 13 deletions(-) diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index 3002f6f1..5445e2e2 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -20,6 +20,7 @@ import zlib import matplotlib.pyplot as plt import numpy as np +import ruptures as rpt import jinja2 import loky @@ -352,14 +353,46 @@ def check_xsrf_cookie(self): """ pass - def generate_ventilation_plot(self, CO2Data, transition_times = None, ventilation_values = None): + def find_change_points_with_pelt(self, CO2_data: dict): + """ + Perform change point detection using Pelt algorithm from ruptures library with pen=15. + Returns a list of tuples containing (index, X-axis value) for the detected significant changes. + """ + + times = CO2_data['times'] + CO2_values = CO2_data['CO2'] + + if len(times) != len(CO2_values): + raise ValueError("times and CO2 values must have the same length.") + + # Convert the input lists to numpy arrays for use with the ruptures library + times_np = np.array(times) + CO2_np = np.array(CO2_values) + + # Define the model for change point detection (Radial Basis Function kernel) + model = "rbf" + + # Fit the Pelt algorithm to the data with the specified model + algo = rpt.Pelt(model=model).fit(CO2_np) + + # Predict change points using the Pelt algorithm with a penalty value of 15 + result = algo.predict(pen=15) + + return [times_np[idx] for idx in result[:-1]] + + def generate_ventilation_plot(self, CO2_data: dict, transition_times: typing.Optional[list] = None, ventilation_values: typing.Optional[list] = None): + times = CO2_data['times'] + CO2_data = CO2_data['CO2'] + fig = plt.figure(figsize=(7, 4), dpi=110) - plt.plot(CO2Data['times'], CO2Data['CO2']) - if (transition_times and ventilation_values): - for index, time in enumerate(transition_times[:-1]): + plt.plot(times, CO2_data) + + if (transition_times): + for index, time in enumerate(transition_times): plt.axvline(x = time, color = 'grey', linewidth=0.5, linestyle='--') - y_location = (CO2Data['CO2'][min(range(len(CO2Data['times'])), key=lambda i: abs(CO2Data['times'][i]-time))]) - plt.text(x = time + 0.04, y = y_location, s=round(ventilation_values[index], 2)) + if ventilation_values: + y_location = (CO2_data[min(range(len(times)), key=lambda i: abs(times[i]-time))]) + plt.text(x = time + 0.04, y = y_location, s="{:.2g}".format(ventilation_values[index])) plt.xlabel('Time of day') plt.ylabel('Concentration (ppm)') return img2base64(_figure2bytes(fig)) @@ -377,8 +410,8 @@ async def post(self, endpoint: str) -> None: self.finish(json.dumps(response_json)) return - if endpoint == 'plot': - self.finish({'CO2_plot': self.generate_ventilation_plot(form.CO2_data)}) + if endpoint.rstrip('/') == 'plot': + self.finish({'CO2_plot': self.generate_ventilation_plot(form.CO2_data, self.find_change_points_with_pelt(form.CO2_data))}) else: executor = loky.get_reusable_executor( max_workers=self.settings['handler_worker_pool_size'], @@ -392,7 +425,7 @@ async def post(self, endpoint: str) -> None: result = dict(report.CO2_fit_params()) result['fitting_ventilation_type'] = form.fitting_ventilation_type result['transition_times'] = report.ventilation_transition_times - result['CO2_plot'] = self.generate_ventilation_plot(form.CO2_data, report.ventilation_transition_times, result['ventilation_values']) + result['CO2_plot'] = self.generate_ventilation_plot(form.CO2_data, report.ventilation_transition_times[:-1], result['ventilation_values']) self.finish(result) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 6a2128eb..faac0474 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -194,7 +194,37 @@ function validateCO2Form() { // validate input format try { const parsedValue = JSON.parse(element.value); - if (!Array.isArray(parsedValue)) { + if (Array.isArray(parsedValue)) { + if (parsedValue.length <= 1) { + insertErrorFor( + $("#DIVCO2_fitting_result"), + `'${element.name}' must have more than one element.
    ` + ); + submit = false; + } + else { + const infected_finish = $(`[name=infected_finish]`)[0].value; + const exposed_finish = $(`[name=exposed_finish]`)[0].value; + + const [hours_infected, minutes_infected] = infected_finish.split(":").map(Number); + const elapsed_time_infected = hours_infected * 60 + minutes_infected; + + const [hours_exposed, minutes_exposed] = exposed_finish.split(":").map(Number); + const elapsed_time_exposed = hours_exposed * 60 + minutes_exposed; + + const max_presence_time = Math.max(elapsed_time_infected, elapsed_time_exposed); + const max_transition_time = parsedValue[parsedValue.length - 1] * 60; + + if (max_transition_time < max_presence_time) { + insertErrorFor( + $("#DIVCO2_fitting_result"), + `The last transition time (${parsedValue[parsedValue.length - 1]}) should be after the last presence time (${max_presence_time / 60}).
    ` + ); + submit = false; + } + } + } + else { insertErrorFor( $("#DIVCO2_fitting_result"), `'${element.name}' must be a list.
    ` @@ -325,11 +355,15 @@ function submitFittingAlgorithm(url) { .then((response) => response.json()) .then((json_response) => { displayFittingData(json_response); + // Hide the suggestion transition lines warning + $("#suggestion_lines_txt").hide(); }); } } function clearFittingResultComponent() { + // Add the warning suggestion line + $("#suggestion_lines_txt").show(); // Remove all the previously generated fitting elements $("#generate_fitting_data").prop("disabled", true); $("#CO2_fitting_result").val(""); diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index 7b7d0d6b..960b3e43 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -200,13 +200,13 @@
    - +
    -
    +
    - +
    @@ -339,6 +339,7 @@ From 37bc93007dc1d1f0b22821d450d354798c9cbac5 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Tue, 8 Aug 2023 16:03:45 +0200 Subject: [PATCH 42/61] added correct pelt suggestion for transition times --- caimira/apps/calculator/__init__.py | 20 +++++++++++++------ .../apps/calculator/co2_model_generator.py | 4 +++- caimira/apps/calculator/static/js/co2_form.js | 14 ++++++++----- 3 files changed, 26 insertions(+), 12 deletions(-) diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index 5445e2e2..ea869fec 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -359,14 +359,13 @@ def find_change_points_with_pelt(self, CO2_data: dict): Returns a list of tuples containing (index, X-axis value) for the detected significant changes. """ - times = CO2_data['times'] - CO2_values = CO2_data['CO2'] + times: list = CO2_data['times'] + CO2_values: list = CO2_data['CO2'] if len(times) != len(CO2_values): raise ValueError("times and CO2 values must have the same length.") - # Convert the input lists to numpy arrays for use with the ruptures library - times_np = np.array(times) + # Convert the input list to a numpy array for use with the ruptures library CO2_np = np.array(CO2_values) # Define the model for change point detection (Radial Basis Function kernel) @@ -378,7 +377,14 @@ def find_change_points_with_pelt(self, CO2_data: dict): # Predict change points using the Pelt algorithm with a penalty value of 15 result = algo.predict(pen=15) - return [times_np[idx] for idx in result[:-1]] + # Find local minima and maxima + segments = np.split(np.arange(len(CO2_values)), result) + merged_segments = [np.hstack((segments[i], segments[i + 1])) for i in range(len(segments) - 1)] + result_set = set() + for segment in merged_segments[:-2]: + result_set.add(times[CO2_values.index(min(CO2_np[segment]))]) + result_set.add(times[CO2_values.index(max(CO2_np[segment]))]) + return list(result_set) def generate_ventilation_plot(self, CO2_data: dict, transition_times: typing.Optional[list] = None, ventilation_values: typing.Optional[list] = None): times = CO2_data['times'] @@ -411,7 +417,9 @@ async def post(self, endpoint: str) -> None: return if endpoint.rstrip('/') == 'plot': - self.finish({'CO2_plot': self.generate_ventilation_plot(form.CO2_data, self.find_change_points_with_pelt(form.CO2_data))}) + transition_times = self.find_change_points_with_pelt(form.CO2_data) + self.finish({'CO2_plot': self.generate_ventilation_plot(form.CO2_data, transition_times), + 'transition_times': [round(el, 2) for el in transition_times]}) else: executor = loky.get_reusable_executor( max_workers=self.settings['handler_worker_pool_size'], diff --git a/caimira/apps/calculator/co2_model_generator.py b/caimira/apps/calculator/co2_model_generator.py index 1a935577..0187535b 100644 --- a/caimira/apps/calculator/co2_model_generator.py +++ b/caimira/apps/calculator/co2_model_generator.py @@ -190,7 +190,9 @@ def population_present_changes(self) -> typing.List[float]: def ventilation_transition_times(self) -> typing.Tuple[float, ...]: # Check what type of ventilation is considered for the fitting if self.fitting_ventilation_type == 'fitting_natural_ventilation': - return tuple(self.fitting_ventilation_states) + vent_states = self.fitting_ventilation_states + vent_states.append(self.CO2_data['times'][-1]) + return tuple(vent_states) else: return tuple((self.CO2_data['times'][0], self.CO2_data['times'][-1])) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 01e073f0..ddbbfd36 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -215,10 +215,10 @@ function validateCO2Form() { const max_presence_time = Math.max(elapsed_time_infected, elapsed_time_exposed); const max_transition_time = parsedValue[parsedValue.length - 1] * 60; - if (max_transition_time < max_presence_time) { + if (max_transition_time > max_presence_time) { insertErrorFor( $("#DIVCO2_fitting_result"), - `The last transition time (${parsedValue[parsedValue.length - 1]}) should be after the last presence time (${max_presence_time / 60}).
    ` + `The last transition time (${parsedValue[parsedValue.length - 1]}) should be before the last presence time (${max_presence_time / 60}).
    ` ); submit = false; } @@ -297,6 +297,7 @@ function formatCO2DataForm(CO2_data_form) { let CO2_mapping = {}; CO2_data_form.map((el) => { let element = $(`[name=${el}]`).first(); + // Validate checkboxes if (element.prop('type') == "checkbox") { CO2_mapping[element.attr('name')] = String(+element.prop('checked')); @@ -306,7 +307,9 @@ function formatCO2DataForm(CO2_data_form) { CO2_mapping[element.attr('name')] = $( `[name=${element.attr('name')}]:checked` ).first().val(); - else CO2_mapping[element.attr('name')] = element.val(); + else { + CO2_mapping[element.attr('name')] = element.val(); + } }); return CO2_mapping; } @@ -320,9 +323,10 @@ function plotCO2Data(url) { }).then((response) => response .json() - .then((json_response) => + .then((json_response) => { $("#CO2_data_plot").attr("src", json_response["CO2_plot"]) - ) + $("#fitting_ventilation_states").val(`[${json_response["transition_times"]}]`) + }) .then($("#DIVCO2_fitting_to_submit").show()) .catch((error) => console.log(error)) ); From 3e38322ccc30014b2dbd100244b2e8456051ccd1 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 9 Aug 2023 16:35:28 +0100 Subject: [PATCH 43/61] added predictive CO2 line and time labels --- caimira/apps/calculator/__init__.py | 25 +++++++++++++++++++++---- caimira/models.py | 4 ++-- 2 files changed, 23 insertions(+), 6 deletions(-) diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index ea869fec..1ce280fe 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -386,21 +386,33 @@ def find_change_points_with_pelt(self, CO2_data: dict): result_set.add(times[CO2_values.index(max(CO2_np[segment]))]) return list(result_set) - def generate_ventilation_plot(self, CO2_data: dict, transition_times: typing.Optional[list] = None, ventilation_values: typing.Optional[list] = None): + def generate_ventilation_plot(self, CO2_data: dict, + transition_times: typing.Optional[list] = None, + ventilation_values: typing.Optional[list] = None, + predictive_CO2: typing.Optional[list] = None): times = CO2_data['times'] CO2_data = CO2_data['CO2'] + def time_to_hour(time: float) -> str: + minutes = int(np.floor((time % 1) * 60)) + minutes_to_display = f'0{minutes}' if minutes < 10 else minutes + return f'{int(np.floor(time))}:{minutes_to_display}' + fig = plt.figure(figsize=(7, 4), dpi=110) - plt.plot(times, CO2_data) + plt.plot(times, CO2_data, label='Input CO₂') if (transition_times): for index, time in enumerate(transition_times): plt.axvline(x = time, color = 'grey', linewidth=0.5, linestyle='--') + plt.text(x = time + 0.04, y = max(predictive_CO2) if predictive_CO2 else max(CO2_data), s=time_to_hour(time)) if ventilation_values: y_location = (CO2_data[min(range(len(times)), key=lambda i: abs(times[i]-time))]) plt.text(x = time + 0.04, y = y_location, s="{:.2g}".format(ventilation_values[index])) + if (predictive_CO2): + plt.plot(times, predictive_CO2, label='Predictive CO₂') plt.xlabel('Time of day') plt.ylabel('Concentration (ppm)') + plt.legend(loc='lower right') return img2base64(_figure2bytes(fig)) async def post(self, endpoint: str) -> None: @@ -431,9 +443,14 @@ async def post(self, endpoint: str) -> None: report = await asyncio.wrap_future(report_task) result = dict(report.CO2_fit_params()) + ventilation_transition_times = report.ventilation_transition_times + result['fitting_ventilation_type'] = form.fitting_ventilation_type - result['transition_times'] = report.ventilation_transition_times - result['CO2_plot'] = self.generate_ventilation_plot(form.CO2_data, report.ventilation_transition_times[:-1], result['ventilation_values']) + result['transition_times'] = ventilation_transition_times + result['CO2_plot'] = self.generate_ventilation_plot(form.CO2_data, + ventilation_transition_times[:-1], + result['ventilation_values'], + result['predictive_CO2']) self.finish(result) diff --git a/caimira/models.py b/caimira/models.py index 2f04a0bb..4da916ce 100644 --- a/caimira/models.py +++ b/caimira/models.py @@ -1540,8 +1540,8 @@ def fun(x): exhalation_rate = res_dict['x'][0] ventilation_values = res_dict['x'][1:] - - return {"exhalation_rate": exhalation_rate, "ventilation_values": list(ventilation_values)} + predictive_CO2 = self.CO2_concentrations_from_params(exhalation_rate=exhalation_rate, ventilation_values=ventilation_values) + return {"exhalation_rate": exhalation_rate, "ventilation_values": list(ventilation_values), 'predictive_CO2': list(predictive_CO2)} @dataclass(frozen=True) From a94bc60455dd1a7583854e522530dbd7c2457639 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Fri, 11 Aug 2023 09:25:05 +0100 Subject: [PATCH 44/61] deleted input value (not necessary) --- caimira/apps/calculator/static/js/co2_form.js | 1 + 1 file changed, 1 insertion(+) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index ddbbfd36..92784f19 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -269,6 +269,7 @@ function displayFittingData(json_response) { $("#CO2_data_plot").attr("src", json_response["CO2_plot"]); // Not needed for the form submission delete json_response["CO2_plot"]; + delete json_response["predictive_CO2"]; $("#CO2_fitting_result").val(JSON.stringify(json_response)); $("#exhalation_rate_fit").html( "Exhalation rate: " + From e704cb00319aa6493f7326ec975e2001eaff68cd Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Fri, 11 Aug 2023 09:28:25 +0100 Subject: [PATCH 45/61] removed ventilation values from plot --- caimira/apps/calculator/__init__.py | 23 ++++++----------------- 1 file changed, 6 insertions(+), 17 deletions(-) diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index 1ce280fe..09688396 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -388,31 +388,21 @@ def find_change_points_with_pelt(self, CO2_data: dict): def generate_ventilation_plot(self, CO2_data: dict, transition_times: typing.Optional[list] = None, - ventilation_values: typing.Optional[list] = None, predictive_CO2: typing.Optional[list] = None): times = CO2_data['times'] CO2_data = CO2_data['CO2'] - def time_to_hour(time: float) -> str: - minutes = int(np.floor((time % 1) * 60)) - minutes_to_display = f'0{minutes}' if minutes < 10 else minutes - return f'{int(np.floor(time))}:{minutes_to_display}' - fig = plt.figure(figsize=(7, 4), dpi=110) plt.plot(times, CO2_data, label='Input CO₂') if (transition_times): - for index, time in enumerate(transition_times): + for time in transition_times: plt.axvline(x = time, color = 'grey', linewidth=0.5, linestyle='--') - plt.text(x = time + 0.04, y = max(predictive_CO2) if predictive_CO2 else max(CO2_data), s=time_to_hour(time)) - if ventilation_values: - y_location = (CO2_data[min(range(len(times)), key=lambda i: abs(times[i]-time))]) - plt.text(x = time + 0.04, y = y_location, s="{:.2g}".format(ventilation_values[index])) if (predictive_CO2): plt.plot(times, predictive_CO2, label='Predictive CO₂') plt.xlabel('Time of day') plt.ylabel('Concentration (ppm)') - plt.legend(loc='lower right') + plt.legend() return img2base64(_figure2bytes(fig)) async def post(self, endpoint: str) -> None: @@ -430,7 +420,7 @@ async def post(self, endpoint: str) -> None: if endpoint.rstrip('/') == 'plot': transition_times = self.find_change_points_with_pelt(form.CO2_data) - self.finish({'CO2_plot': self.generate_ventilation_plot(form.CO2_data, transition_times), + self.finish({'CO2_plot': self.generate_ventilation_plot(CO2_data=form.CO2_data, transition_times=transition_times), 'transition_times': [round(el, 2) for el in transition_times]}) else: executor = loky.get_reusable_executor( @@ -447,10 +437,9 @@ async def post(self, endpoint: str) -> None: result['fitting_ventilation_type'] = form.fitting_ventilation_type result['transition_times'] = ventilation_transition_times - result['CO2_plot'] = self.generate_ventilation_plot(form.CO2_data, - ventilation_transition_times[:-1], - result['ventilation_values'], - result['predictive_CO2']) + result['CO2_plot'] = self.generate_ventilation_plot(CO2_data=form.CO2_data, + transition_times=ventilation_transition_times[:-1], + predictive_CO2=result['predictive_CO2']) self.finish(result) From eb7f6ed93ab546ace8fd9ec90c155a738d31ef27 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Fri, 11 Aug 2023 09:37:56 +0100 Subject: [PATCH 46/61] updated no file error label --- caimira/apps/calculator/static/js/co2_form.js | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 92784f19..45f45941 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -28,7 +28,9 @@ function uploadFile(endpoint) { clearFittingResultComponent(); const files = $("#file_upload")[0].files; if (files.length === 0) { - $("#upload-error").show(); + $("#upload-error") + .text('Please choose a file.') + .show(); return; } const file = files[0]; From d51b7dc30afd2a43f723729058e5eacfbcac13c7 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Fri, 11 Aug 2023 11:13:46 +0100 Subject: [PATCH 47/61] optimised validation method --- .../apps/calculator/co2_model_generator.py | 105 ++++-------------- caimira/apps/calculator/model_generator.py | 32 ++++-- caimira/apps/calculator/report_generator.py | 3 +- caimira/apps/calculator/static/js/co2_form.js | 3 +- 4 files changed, 45 insertions(+), 98 deletions(-) diff --git a/caimira/apps/calculator/co2_model_generator.py b/caimira/apps/calculator/co2_model_generator.py index 0187535b..bc55ae4e 100644 --- a/caimira/apps/calculator/co2_model_generator.py +++ b/caimira/apps/calculator/co2_model_generator.py @@ -24,13 +24,13 @@ class CO2FormData(model_generator.FormData): exposed_start: model_generator.minutes_since_midnight fitting_ventilation_states: list fitting_ventilation_type: str - infected_coffee_break_option: str #Used if infected_dont_have_breaks_with_exposed - infected_coffee_duration: int #Used if infected_dont_have_breaks_with_exposed + infected_coffee_break_option: str + infected_coffee_duration: int infected_dont_have_breaks_with_exposed: bool infected_finish: model_generator.minutes_since_midnight - infected_lunch_finish: model_generator.minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed - infected_lunch_option: bool #Used if infected_dont_have_breaks_with_exposed - infected_lunch_start: model_generator.minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed + infected_lunch_finish: model_generator.minutes_since_midnight + infected_lunch_option: bool + infected_lunch_start: model_generator.minutes_since_midnight infected_people: int infected_start: model_generator.minutes_since_midnight room_volume: float @@ -98,73 +98,22 @@ def from_dict(self, form_data: typing.Dict) -> "CO2FormData": raise ValueError(f'Invalid argument "{html.escape(key)}" given') instance = self(**form_data) - instance.validate() + instance.validate_population_parameters() return instance - def validate(self): - # Validate number of infected <= number of total people - if self.infected_people >= self.total_people: - raise ValueError('Number of infected people cannot be more or equal than number of total people.') - - # Validate time intervals selected by user - time_intervals = [ - ['exposed_start', 'exposed_finish'], - ['infected_start', 'infected_finish'], - ] - if self.exposed_lunch_option: - time_intervals.append(['exposed_lunch_start', 'exposed_lunch_finish']) - if self.infected_dont_have_breaks_with_exposed and self.infected_lunch_option: - time_intervals.append(['infected_lunch_start', 'infected_lunch_finish']) - - for start_name, end_name in time_intervals: - start = getattr(self, start_name) - end = getattr(self, end_name) - if start > end: - raise ValueError( - f"{start_name} must be less than {end_name}. Got {start} and {end}.") - - def validate_lunch(start, finish): - lunch_start = getattr(self, f'{population}_lunch_start') - lunch_finish = getattr(self, f'{population}_lunch_finish') - return (start <= lunch_start <= finish and - start <= lunch_finish <= finish) - - def get_lunch_mins(population): - lunch_mins = 0 - if getattr(self, f'{population}_lunch_option'): - lunch_mins = getattr(self, f'{population}_lunch_finish') - getattr(self, f'{population}_lunch_start') - return lunch_mins - - def get_coffee_mins(population): - coffee_mins = 0 - if getattr(self, f'{population}_coffee_break_option') != 'coffee_break_0': - coffee_mins = COFFEE_OPTIONS_INT[getattr(self, f'{population}_coffee_break_option')] * getattr(self, f'{population}_coffee_duration') - return coffee_mins - - def get_activity_mins(population): - return getattr(self, f'{population}_finish') - getattr(self, f'{population}_start') - - populations = ['exposed', 'infected'] if self.infected_dont_have_breaks_with_exposed else ['exposed'] - for population in populations: - # Validate lunch time within the activity times. - if (getattr(self, f'{population}_lunch_option') and - not validate_lunch(getattr(self, f'{population}_start'), getattr(self, f'{population}_finish')) - ): - raise ValueError( - f"{population} lunch break must be within presence times." - ) - - # Length of breaks < length of activity - if (get_lunch_mins(population) + get_coffee_mins(population)) >= get_activity_mins(population): - raise ValueError( - f"Length of breaks >= Length of {population} presence." - ) - - validation_tuples = [('exposed_coffee_break_option', COFFEE_OPTIONS_INT), - ('infected_coffee_break_option', COFFEE_OPTIONS_INT),] - for attr_name, valid_set in validation_tuples: - if getattr(self, attr_name) not in valid_set: - raise ValueError(f"{getattr(self, attr_name)} is not a valid value for {attr_name}") + def population_present_changes(self) -> typing.List[float]: + state_change_times = set(self.infected_present_interval().transition_times()) + state_change_times.update(self.exposed_present_interval().transition_times()) + return sorted(state_change_times) + + def ventilation_transition_times(self) -> typing.Tuple[float, ...]: + # Check what type of ventilation is considered for the fitting + if self.fitting_ventilation_type == 'fitting_natural_ventilation': + vent_states = self.fitting_ventilation_states + vent_states.append(self.CO2_data['times'][-1]) + return tuple(vent_states) + else: + return tuple((self.CO2_data['times'][0], self.CO2_data['times'][-1])) def build_model(self, size=DEFAULT_MC_SAMPLE_SIZE) -> models.CO2DataModel: # type: ignore infected_population: models.Population = self.infected_population().build_model(size) @@ -180,21 +129,7 @@ def build_model(self, size=DEFAULT_MC_SAMPLE_SIZE) -> models.CO2DataModel: # typ ventilation_transition_times=self.ventilation_transition_times(), times=self.CO2_data['times'], CO2_concentrations=self.CO2_data['CO2'], - ) - - def population_present_changes(self) -> typing.List[float]: - state_change_times = set(self.infected_present_interval().transition_times()) - state_change_times.update(self.exposed_present_interval().transition_times()) - return sorted(state_change_times) - - def ventilation_transition_times(self) -> typing.Tuple[float, ...]: - # Check what type of ventilation is considered for the fitting - if self.fitting_ventilation_type == 'fitting_natural_ventilation': - vent_states = self.fitting_ventilation_states - vent_states.append(self.CO2_data['times'][-1]) - return tuple(vent_states) - else: - return tuple((self.CO2_data['times'][0], self.CO2_data['times'][-1])) + ) for _field in dataclasses.fields(CO2FormData): diff --git a/caimira/apps/calculator/model_generator.py b/caimira/apps/calculator/model_generator.py index 387b8e9d..51cfd91e 100644 --- a/caimira/apps/calculator/model_generator.py +++ b/caimira/apps/calculator/model_generator.py @@ -144,14 +144,11 @@ def to_dict(cls, form: "FormData", strip_defaults: bool = False) -> dict: if default is not NO_DEFAULT and value in [default, 'not-applicable']: form_dict.pop(attr) return form_dict - - def validate(self): - # Validate number of infected people == 1 when activity is Conference/Training. - if self.activity_type == 'training' and self.infected_people > 1: - raise ValueError('Conference/Training activities are limited to 1 infected.') + + def validate_population_parameters(self): # Validate number of infected <= number of total people - elif self.infected_people >= self.total_people: - raise ValueError('Number of infected people cannot be more or equal than number of total people.') + if self.infected_people >= self.total_people: + raise ValueError('Number of infected people cannot be more or equal than number of total people.') # Validate time intervals selected by user time_intervals = [ @@ -191,7 +188,7 @@ def get_coffee_mins(population): def get_activity_mins(population): return getattr(self, f'{population}_finish') - getattr(self, f'{population}_start') - populations = ['exposed', 'infected'] if self.infected_dont_have_breaks_with_exposed else ['exposed'] + populations = ['exposed', 'infected'] if self.infected_dont_have_breaks_with_exposed else ['exposed'] for population in populations: # Validate lunch time within the activity times. if (getattr(self, f'{population}_lunch_option') and @@ -206,10 +203,17 @@ def get_activity_mins(population): raise ValueError( f"Length of breaks >= Length of {population} presence." ) + + for attr_name, valid_set in [('exposed_coffee_break_option', COFFEE_OPTIONS_INT), + ('infected_coffee_break_option', COFFEE_OPTIONS_INT)]: + if getattr(self, attr_name) not in valid_set: + raise ValueError(f"{getattr(self, attr_name)} is not a valid value for {attr_name}") - validation_tuples = [('activity_type', ACTIVITY_TYPES), - ('exposed_coffee_break_option', COFFEE_OPTIONS_INT), - ('infected_coffee_break_option', COFFEE_OPTIONS_INT), + def validate(self): + # Validate population parameters + self.validate_population_parameters() + + validation_tuples = [('activity_type', ACTIVITY_TYPES), ('mechanical_ventilation_type', MECHANICAL_VENTILATION_TYPES), ('mask_type', MASK_TYPES), ('mask_wearing_option', MASK_WEARING_OPTIONS), @@ -222,10 +226,16 @@ def get_activity_mins(population): ('ascertainment_bias', CONFIDENCE_LEVEL_OPTIONS), ('vaccine_type', VACCINE_TYPE), ('vaccine_booster_type', VACCINE_BOOSTER_TYPE),] + for attr_name, valid_set in validation_tuples: if getattr(self, attr_name) not in valid_set: raise ValueError(f"{getattr(self, attr_name)} is not a valid value for {attr_name}") + + # Validate number of infected people == 1 when activity is Conference/Training. + if self.activity_type == 'training' and self.infected_people > 1: + raise ValueError('Conference/Training activities are limited to 1 infected.') + # Validate ventilation parameters if self.ventilation_type == 'natural_ventilation': if self.window_type == 'not-applicable': raise ValueError( diff --git a/caimira/apps/calculator/report_generator.py b/caimira/apps/calculator/report_generator.py index eb33791d..15f2cc8a 100644 --- a/caimira/apps/calculator/report_generator.py +++ b/caimira/apps/calculator/report_generator.py @@ -320,11 +320,12 @@ def readable_minutes(minutes: int) -> str: def hour_format(hour: float) -> str: + # Convert float hour to HH:MM format hours = int(hour) minutes = int(hour % 1 * 60) - return f"{hours}:{minutes if minutes != 0 else '00'}" + def percentage(absolute: float) -> float: return absolute * 100 diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 45f45941..d94fe6a0 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -1,3 +1,4 @@ +// Input data for CO2 fitting algorithm const CO2_data_form = [ "CO2_data", "exposed_coffee_break_option", @@ -104,7 +105,7 @@ function uploadFile(endpoint) { } } - // Call function to convert Excel file to JSON and further processing + // Convert Excel file to JSON and further processing try { generateJSONStructure(endpoint, data); // If all validations pass, process the file here or display a success message From 0ef54cddfbe13a2f23a381ddf37be5cb983b0c5e Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Tue, 26 Sep 2023 11:17:33 +0200 Subject: [PATCH 48/61] modified procedure to download CO2 template file --- caimira/apps/calculator/static/js/co2_form.js | 14 -------------- .../apps/templates/base/calculator.form.html.j2 | 2 +- 2 files changed, 1 insertion(+), 15 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index d94fe6a0..48dcdfbb 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -140,20 +140,6 @@ function generateJSONStructure(endpoint, jsonData) { } } -// Method to download Excel template available on CERNBox -function downloadTemplate( - uri = "https://caimira-resources.web.cern.ch/CO2_template.xlsx", - filename = "CO2_template.xlsx" -) { - const link = document.createElement("a"); - link.download = filename; - link.href = uri; - document.body.appendChild(link); - link.click(); - document.body.removeChild(link); - delete link; -} - function insertErrorFor(referenceNode, text) { const element = $("") .addClass("error_text text-danger") diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index 798fd845..a2179502 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -324,7 +324,7 @@
    Upload an Excel file to preview in HTML Table
    - + Download template

    From 7620f752f69170dc0d9c228254a62b4a3dcd4b1b Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Tue, 26 Sep 2023 16:37:57 +0200 Subject: [PATCH 49/61] updated jquery methods namely on the finding mechanism --- caimira/apps/calculator/static/js/co2_form.js | 70 ++++++++++--------- 1 file changed, 36 insertions(+), 34 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index 48dcdfbb..db6fb864 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -141,21 +141,20 @@ function generateJSONStructure(endpoint, jsonData) { } function insertErrorFor(referenceNode, text) { - const element = $("") - .addClass("error_text text-danger") - .html("  " + text); - $(referenceNode).before(element); + $(`${text}`).insertAfter(referenceNode) } function validateFormInputs(obj) { - $("span.error_text").remove(); + $("#ventilation_data").find("span.error_text").remove(); // Remove all error spans + let submit = true; + const $referenceNode = $("#DIVCO2_data_dialog"); for (let i = 0; i < CO2_data_form.length; i++) { - const element = $(`[name=${CO2_data_form[i]}]`).first(); - if (element.attr('name') !== "fitting_ventilation_states" && element.val() === "") { + const $requiredElement = $(`[name=${CO2_data_form[i]}]`).first(); + if ($requiredElement.attr('name') !== "fitting_ventilation_states" && $requiredElement.val() === "") { insertErrorFor( - $("#DIVCO2_data_dialog"), - `'${element.attr('name')}' must be defined.
    ` + $referenceNode, + `'${$requiredElement.attr('name')}' must be defined.
    ` ); submit = false; } @@ -172,22 +171,24 @@ function validateCO2Form() { let submit = true; if (validateFormInputs($("#button_fit_data"))) submit = true; + const $fittingToSubmit = $('#DIVCO2_fitting_to_submit'); // Check if natural ventilation is selected if ( - $('input[name="fitting_ventilation_type"]:checked').first().val() == + $fittingToSubmit.find('input[name="fitting_ventilation_type"]:checked').val() == "fitting_natural_ventilation" ) { // Validate ventilation scheme - const element = $("[name=fitting_ventilation_states").first(); - if (element.val() !== "") { + const $ventilationStates = $fittingToSubmit.find("input[name=fitting_ventilation_states]"); + const $referenceNode = $("#DIVCO2_fitting_result"); + if ($ventilationStates.val() !== "") { // validate input format try { - const parsedValue = JSON.parse(element.val()); + const parsedValue = JSON.parse($ventilationStates.val()); if (Array.isArray(parsedValue)) { if (parsedValue.length <= 1) { insertErrorFor( - $("#DIVCO2_fitting_result"), - `'${element.attr('name')}' must have more than one element.
    ` + $referenceNode, + `'${$ventilationStates.attr('name')}' must have more than one $ventilationStates.
    ` ); submit = false; } @@ -206,7 +207,7 @@ function validateCO2Form() { if (max_transition_time > max_presence_time) { insertErrorFor( - $("#DIVCO2_fitting_result"), + $referenceNode, `The last transition time (${parsedValue[parsedValue.length - 1]}) should be before the last presence time (${max_presence_time / 60}).
    ` ); submit = false; @@ -215,22 +216,22 @@ function validateCO2Form() { } else { insertErrorFor( - $("#DIVCO2_fitting_result"), - `'${element.attr('name')}' must be a list.
    ` + $referenceNode, + `'${$ventilationStates.attr('name')}' must be a list.
    ` ); submit = false; } } catch { insertErrorFor( - $("#DIVCO2_fitting_result"), - `'${element.attr('name')}' must be a list of numbers.
    ` + $referenceNode, + `'${$ventilationStates.attr('name')}' must be a list of numbers.
    ` ); submit = false; } } else { insertErrorFor( - $("#DIVCO2_fitting_result"), - `'${element.attr('name')}' must be defined.
    ` + $referenceNode, + `'${$ventilationStates.attr('name')}' must be defined.
    ` ); submit = false; } @@ -356,27 +357,28 @@ function submitFittingAlgorithm(url) { } function clearFittingResultComponent() { + const $referenceNode = $("#DIVCO2_data_dialog"); // Add the warning suggestion line - $("#suggestion_lines_txt").show(); + $referenceNode.find("#suggestion_lines_txt").show(); // Remove all the previously generated fitting elements - $("#generate_fitting_data").prop("disabled", true); - $("#CO2_fitting_result").val(""); - $("#CO2_data").val("{}"); - $("#fitting_ventilation_states").val(""); - $("span.error_text").remove(); - $("#DIVCO2_fitting_result, #CO2_input_data_div").hide(); - $("#DIVCO2_fitting_to_submit").hide(); - $("#CO2_data_plot").attr("src", ""); + $referenceNode.find("#generate_fitting_data").prop("disabled", true); + $referenceNode.find("#CO2_fitting_result").val(""); + $referenceNode.find("#CO2_data").val("{}"); + $referenceNode.find("#fitting_ventilation_states").val(""); + $referenceNode.find("span.error_text").remove(); + $referenceNode.find("#DIVCO2_fitting_result, #CO2_input_data_div").hide(); + $referenceNode.find("#DIVCO2_fitting_to_submit").hide(); + $referenceNode.find("#CO2_data_plot").attr("src", ""); // Update the ventilation scheme components - $("#fitting_ventilation_states, [name=fitting_ventilation_type]").prop( + $referenceNode.find("#fitting_ventilation_states, [name=fitting_ventilation_type]").prop( "disabled", false ); // Update the bottom right buttons - $("#generate_fitting_data").show(); - $("#save_and_dismiss_dialog").hide(); + $referenceNode.find("#generate_fitting_data").show(); + $referenceNode.find("#save_and_dismiss_dialog").hide(); } function disableFittingAlgorithm() { From 2a61b79eab2844f8bd5b2e064de3b259541d90ed Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Tue, 3 Oct 2023 16:11:40 +0200 Subject: [PATCH 50/61] updated blocking variable name --- caimira/apps/calculator/__init__.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index 09688396..38824ced 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -389,17 +389,17 @@ def find_change_points_with_pelt(self, CO2_data: dict): def generate_ventilation_plot(self, CO2_data: dict, transition_times: typing.Optional[list] = None, predictive_CO2: typing.Optional[list] = None): - times = CO2_data['times'] - CO2_data = CO2_data['CO2'] + times_values = CO2_data['times'] + CO2_values = CO2_data['CO2'] fig = plt.figure(figsize=(7, 4), dpi=110) - plt.plot(times, CO2_data, label='Input CO₂') + plt.plot(times_values, CO2_values, label='Input CO₂') if (transition_times): for time in transition_times: plt.axvline(x = time, color = 'grey', linewidth=0.5, linestyle='--') if (predictive_CO2): - plt.plot(times, predictive_CO2, label='Predictive CO₂') + plt.plot(times_values, predictive_CO2, label='Predictive CO₂') plt.xlabel('Time of day') plt.ylabel('Concentration (ppm)') plt.legend() From 7b3b6e671e0c2b8f3d99be7ea464ccca995b997f Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 1 Nov 2023 16:03:33 +0100 Subject: [PATCH 51/61] removed unused parameters --- caimira/apps/calculator/co2_model_generator.py | 6 +----- caimira/apps/calculator/static/js/co2_form.js | 2 +- 2 files changed, 2 insertions(+), 6 deletions(-) diff --git a/caimira/apps/calculator/co2_model_generator.py b/caimira/apps/calculator/co2_model_generator.py index bc55ae4e..cde150e3 100644 --- a/caimira/apps/calculator/co2_model_generator.py +++ b/caimira/apps/calculator/co2_model_generator.py @@ -34,12 +34,12 @@ class CO2FormData(model_generator.FormData): infected_people: int infected_start: model_generator.minutes_since_midnight room_volume: float + specific_breaks: dict total_people: int #: The default values for undefined fields. Note that the defaults here #: and the defaults in the html form must not be contradictory. _DEFAULTS: typing.ClassVar[typing.Dict[str, typing.Any]] = { - 'activity_type': 'office', 'CO2_data': '{}', 'exposed_coffee_break_option': 'coffee_break_0', 'exposed_coffee_duration': 5, @@ -48,7 +48,6 @@ class CO2FormData(model_generator.FormData): 'exposed_lunch_option': True, 'exposed_lunch_start': '12:30', 'exposed_start': '08:30', - 'mask_wearing_option': False, 'fitting_ventilation_states': '[]', 'fitting_ventilation_type': 'fitting_natural_ventilation', 'infected_coffee_break_option': 'coffee_break_0', @@ -63,9 +62,6 @@ class CO2FormData(model_generator.FormData): 'room_volume': NO_DEFAULT, 'specific_breaks': '{}', 'total_people': NO_DEFAULT, - 'vaccine_option': False, - 'ventilation_type': 'from_fitting', - 'virus_type': 'SARS_CoV_2', } def __init__(self, **kwargs): diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index db6fb864..e16cf39d 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -20,8 +20,8 @@ const CO2_data_form = [ "infected_people", "infected_start", "room_volume", + "specific_breaks", "total_people", - "ventilation_type", ]; // Method to upload a valid excel file From df5056c8c087774c5b71e04839af075abdce3474 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 1 Nov 2023 16:03:47 +0100 Subject: [PATCH 52/61] simplified logic for building a CO2 model --- .../apps/calculator/co2_model_generator.py | 31 +++++++++++++------ 1 file changed, 22 insertions(+), 9 deletions(-) diff --git a/caimira/apps/calculator/co2_model_generator.py b/caimira/apps/calculator/co2_model_generator.py index cde150e3..f278bb6c 100644 --- a/caimira/apps/calculator/co2_model_generator.py +++ b/caimira/apps/calculator/co2_model_generator.py @@ -97,9 +97,9 @@ def from_dict(self, form_data: typing.Dict) -> "CO2FormData": instance.validate_population_parameters() return instance - def population_present_changes(self) -> typing.List[float]: - state_change_times = set(self.infected_present_interval().transition_times()) - state_change_times.update(self.exposed_present_interval().transition_times()) + def population_present_changes(self, infected_presence: models.Interval, exposed_presence: models.Interval) -> typing.List[float]: + state_change_times = set(infected_presence.transition_times()) + state_change_times.update(exposed_presence.transition_times()) return sorted(state_change_times) def ventilation_transition_times(self) -> typing.Tuple[float, ...]: @@ -112,12 +112,25 @@ def ventilation_transition_times(self) -> typing.Tuple[float, ...]: return tuple((self.CO2_data['times'][0], self.CO2_data['times'][-1])) def build_model(self, size=DEFAULT_MC_SAMPLE_SIZE) -> models.CO2DataModel: # type: ignore - infected_population: models.Population = self.infected_population().build_model(size) - exposed_population: models.Population = self.exposed_population().build_model(size) - all_state_changes=self.population_present_changes() - - total_people = [infected_population.people_present(stop) + exposed_population.people_present(stop) - for _, stop in zip(all_state_changes[:-1], all_state_changes[1:])] + # Build a simple infected and exposed population for the case when presence + # intervals and number of people are dynamic. Activity type is not needed. + infected_presence = self.infected_present_interval() + infected_population = models.SimplePopulation( + number=self.infected_people, + presence=infected_presence, + activity=None, # type: ignore + ) + exposed_presence = self.exposed_present_interval() + exposed_population=models.SimplePopulation( + number=self.total_people - self.infected_people, + presence=exposed_presence, + activity=None, # type: ignore + ) + + all_state_changes=self.population_present_changes(infected_presence, exposed_presence) + total_people = [infected_population.people_present(stop) + exposed_population.people_present(stop) + for _, stop in zip(all_state_changes[:-1], all_state_changes[1:])] + return models.CO2DataModel( room_volume=self.room_volume, number=models.IntPiecewiseConstant(transition_times=tuple(all_state_changes), values=tuple(total_people)), From a00e6d1fbfcea4d3cab06fcae25a92f105dc6061 Mon Sep 17 00:00:00 2001 From: Luis Date: Tue, 14 Nov 2023 13:46:20 +0000 Subject: [PATCH 53/61] replaced Population class by simplePopulation on CO2DataModel method --- caimira/models.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/caimira/models.py b/caimira/models.py index 4da916ce..476a71b3 100644 --- a/caimira/models.py +++ b/caimira/models.py @@ -1505,13 +1505,11 @@ def CO2_concentrations_from_params(self, room=Room(volume=self.room_volume), ventilation=CustomVentilation(PiecewiseConstant( self.ventilation_transition_times, ventilation_values)), - CO2_emitters=Population( + CO2_emitters=SimplePopulation( number=self.number, presence=self.presence, - mask=Mask.types['No mask'], activity=Activity( exhalation_rate=exhalation_rate, inhalation_rate=exhalation_rate), - host_immunity=0. ) ) return [CO2_concentrations.concentration(time) for time in self.times] From 2e8f0f2d5e3aaf26abea57a566060b12fef543c3 Mon Sep 17 00:00:00 2001 From: Luis Date: Tue, 14 Nov 2023 13:51:06 +0000 Subject: [PATCH 54/61] updated validation error message --- caimira/apps/calculator/model_generator.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/caimira/apps/calculator/model_generator.py b/caimira/apps/calculator/model_generator.py index 51cfd91e..2e40b19c 100644 --- a/caimira/apps/calculator/model_generator.py +++ b/caimira/apps/calculator/model_generator.py @@ -148,7 +148,7 @@ def to_dict(cls, form: "FormData", strip_defaults: bool = False) -> dict: def validate_population_parameters(self): # Validate number of infected <= number of total people if self.infected_people >= self.total_people: - raise ValueError('Number of infected people cannot be more or equal than number of total people.') + raise ValueError('Number of infected people cannot be greater or equal to the number of total people.') # Validate time intervals selected by user time_intervals = [ From 0cf27f29db309705d3c092e8de9d8e78c42ebe8e Mon Sep 17 00:00:00 2001 From: Luis Date: Tue, 14 Nov 2023 14:09:43 +0000 Subject: [PATCH 55/61] moved interface methods from init file to co2_model_generator --- caimira/apps/calculator/__init__.py | 67 ++----------------- .../apps/calculator/co2_model_generator.py | 60 ++++++++++++++++- 2 files changed, 65 insertions(+), 62 deletions(-) diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index 38824ced..28a0839d 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -18,9 +18,6 @@ import typing import uuid import zlib -import matplotlib.pyplot as plt -import numpy as np -import ruptures as rpt import jinja2 import loky @@ -30,7 +27,7 @@ from . import markdown_tools from . import model_generator, co2_model_generator -from .report_generator import ReportGenerator, calculate_report_data, img2base64, _figure2bytes +from .report_generator import ReportGenerator, calculate_report_data from .user import AuthenticatedUser, AnonymousUser # The calculator version is based on a combination of the model version and the @@ -345,65 +342,13 @@ def get(self): )) -class CO2Data(BaseRequestHandler): +class CO2ModelResponse(BaseRequestHandler): def check_xsrf_cookie(self): """ This request handler implements a stateless API that returns report data in JSON format. Thus, XSRF cookies are disabled by overriding base class implementation of this method with a pass statement. """ pass - - def find_change_points_with_pelt(self, CO2_data: dict): - """ - Perform change point detection using Pelt algorithm from ruptures library with pen=15. - Returns a list of tuples containing (index, X-axis value) for the detected significant changes. - """ - - times: list = CO2_data['times'] - CO2_values: list = CO2_data['CO2'] - - if len(times) != len(CO2_values): - raise ValueError("times and CO2 values must have the same length.") - - # Convert the input list to a numpy array for use with the ruptures library - CO2_np = np.array(CO2_values) - - # Define the model for change point detection (Radial Basis Function kernel) - model = "rbf" - - # Fit the Pelt algorithm to the data with the specified model - algo = rpt.Pelt(model=model).fit(CO2_np) - - # Predict change points using the Pelt algorithm with a penalty value of 15 - result = algo.predict(pen=15) - - # Find local minima and maxima - segments = np.split(np.arange(len(CO2_values)), result) - merged_segments = [np.hstack((segments[i], segments[i + 1])) for i in range(len(segments) - 1)] - result_set = set() - for segment in merged_segments[:-2]: - result_set.add(times[CO2_values.index(min(CO2_np[segment]))]) - result_set.add(times[CO2_values.index(max(CO2_np[segment]))]) - return list(result_set) - - def generate_ventilation_plot(self, CO2_data: dict, - transition_times: typing.Optional[list] = None, - predictive_CO2: typing.Optional[list] = None): - times_values = CO2_data['times'] - CO2_values = CO2_data['CO2'] - - fig = plt.figure(figsize=(7, 4), dpi=110) - plt.plot(times_values, CO2_values, label='Input CO₂') - - if (transition_times): - for time in transition_times: - plt.axvline(x = time, color = 'grey', linewidth=0.5, linestyle='--') - if (predictive_CO2): - plt.plot(times_values, predictive_CO2, label='Predictive CO₂') - plt.xlabel('Time of day') - plt.ylabel('Concentration (ppm)') - plt.legend() - return img2base64(_figure2bytes(fig)) async def post(self, endpoint: str) -> None: requested_model_config = tornado.escape.json_decode(self.request.body) @@ -419,8 +364,8 @@ async def post(self, endpoint: str) -> None: return if endpoint.rstrip('/') == 'plot': - transition_times = self.find_change_points_with_pelt(form.CO2_data) - self.finish({'CO2_plot': self.generate_ventilation_plot(CO2_data=form.CO2_data, transition_times=transition_times), + transition_times = co2_model_generator.CO2FormData.find_change_points_with_pelt(form.CO2_data) + self.finish({'CO2_plot': co2_model_generator.CO2FormData.generate_ventilation_plot(form.CO2_data, transition_times), 'transition_times': [round(el, 2) for el in transition_times]}) else: executor = loky.get_reusable_executor( @@ -437,7 +382,7 @@ async def post(self, endpoint: str) -> None: result['fitting_ventilation_type'] = form.fitting_ventilation_type result['transition_times'] = ventilation_transition_times - result['CO2_plot'] = self.generate_ventilation_plot(CO2_data=form.CO2_data, + result['CO2_plot'] = co2_model_generator.CO2FormData.generate_ventilation_plot(CO2_data=form.CO2_data, transition_times=ventilation_transition_times[:-1], predictive_CO2=result['predictive_CO2']) self.finish(result) @@ -464,7 +409,7 @@ def make_app( base_urls: typing.List = [ (get_root_url(r'/?'), LandingPage), (get_root_calculator_url(r'/?'), CalculatorForm), - (get_root_calculator_url(r'/co2-fit/(.*)'), CO2Data), + (get_root_calculator_url(r'/co2-fit/(.*)'), CO2ModelResponse), (get_root_calculator_url(r'/report'), ConcentrationModel), (get_root_url(r'/static/(.*)'), StaticFileHandler, {'path': static_dir}), (get_root_calculator_url(r'/static/(.*)'), StaticFileHandler, {'path': calculator_static_dir}), diff --git a/caimira/apps/calculator/co2_model_generator.py b/caimira/apps/calculator/co2_model_generator.py index f278bb6c..0ca201c0 100644 --- a/caimira/apps/calculator/co2_model_generator.py +++ b/caimira/apps/calculator/co2_model_generator.py @@ -2,10 +2,14 @@ import html import logging import typing +import numpy as np +import ruptures as rpt +import matplotlib.pyplot as plt from caimira import models from . import model_generator -from .defaults import DEFAULT_MC_SAMPLE_SIZE, NO_DEFAULT, COFFEE_OPTIONS_INT +from .defaults import DEFAULT_MC_SAMPLE_SIZE, NO_DEFAULT +from .report_generator import img2base64, _figure2bytes minutes_since_midnight = typing.NewType('minutes_since_midnight', int) @@ -96,6 +100,60 @@ def from_dict(self, form_data: typing.Dict) -> "CO2FormData": instance = self(**form_data) instance.validate_population_parameters() return instance + + @classmethod + def find_change_points_with_pelt(self, CO2_data: dict): + """ + Perform change point detection using Pelt algorithm from ruptures library with pen=15. + Returns a list of tuples containing (index, X-axis value) for the detected significant changes. + """ + + times: list = CO2_data['times'] + CO2_values: list = CO2_data['CO2'] + + if len(times) != len(CO2_values): + raise ValueError("times and CO2 values must have the same length.") + + # Convert the input list to a numpy array for use with the ruptures library + CO2_np = np.array(CO2_values) + + # Define the model for change point detection (Radial Basis Function kernel) + model = "rbf" + + # Fit the Pelt algorithm to the data with the specified model + algo = rpt.Pelt(model=model).fit(CO2_np) + + # Predict change points using the Pelt algorithm with a penalty value of 15 + result = algo.predict(pen=15) + + # Find local minima and maxima + segments = np.split(np.arange(len(CO2_values)), result) + merged_segments = [np.hstack((segments[i], segments[i + 1])) for i in range(len(segments) - 1)] + result_set = set() + for segment in merged_segments[:-2]: + result_set.add(times[CO2_values.index(min(CO2_np[segment]))]) + result_set.add(times[CO2_values.index(max(CO2_np[segment]))]) + return list(result_set) + + @classmethod + def generate_ventilation_plot(self, CO2_data: dict, + transition_times: typing.Optional[list] = None, + predictive_CO2: typing.Optional[list] = None): + times_values = CO2_data['times'] + CO2_values = CO2_data['CO2'] + + fig = plt.figure(figsize=(7, 4), dpi=110) + plt.plot(times_values, CO2_values, label='Input CO₂') + + if (transition_times): + for time in transition_times: + plt.axvline(x = time, color = 'grey', linewidth=0.5, linestyle='--') + if (predictive_CO2): + plt.plot(times_values, predictive_CO2, label='Predictive CO₂') + plt.xlabel('Time of day') + plt.ylabel('Concentration (ppm)') + plt.legend() + return img2base64(_figure2bytes(fig)) def population_present_changes(self, infected_presence: models.Interval, exposed_presence: models.Interval) -> typing.List[float]: state_change_times = set(infected_presence.transition_times()) From 390f3e6b48d1601a884474ea3f27f9e0ddedac7f Mon Sep 17 00:00:00 2001 From: Luis Date: Tue, 14 Nov 2023 14:38:16 +0000 Subject: [PATCH 56/61] Added validation for the case the header is not a string --- caimira/apps/calculator/static/js/co2_form.js | 1 + caimira/tests/apps/calculator/test_model_generator.py | 4 ++-- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js index e16cf39d..ef21f010 100644 --- a/caimira/apps/calculator/static/js/co2_form.js +++ b/caimira/apps/calculator/static/js/co2_form.js @@ -64,6 +64,7 @@ function uploadFile(endpoint) { const cellValue = worksheet[headerCoordinates[header]]?.v; if ( !cellValue || + $.type(cellValue) !== "string" || cellValue.trim().toLowerCase() !== header.toLowerCase() ) { $("#upload-error") diff --git a/caimira/tests/apps/calculator/test_model_generator.py b/caimira/tests/apps/calculator/test_model_generator.py index 099a00d2..4d1f5756 100644 --- a/caimira/tests/apps/calculator/test_model_generator.py +++ b/caimira/tests/apps/calculator/test_model_generator.py @@ -171,8 +171,8 @@ def test_ventilation_window_hepa(baseline_form: model_generator.FormData): @pytest.mark.parametrize( ["activity", "total_people", "infected_people", "error"], [ - ['office', 10, 11, "Number of infected people cannot be more or equal than number of total people."], - ['office', 10, 10, "Number of infected people cannot be more or equal than number of total people."], + ['office', 10, 11, "Number of infected people cannot be greater or equal to the number of total people"], + ['office', 10, 10, "Number of infected people cannot be greater or equal to the number of total people"], ['training', 10, 2, "Conference/Training activities are limited to 1 infected."], ] ) From 9d140eb2ad3e80cd78376bd7f30fe0ec8b993dfe Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Fri, 17 Nov 2023 11:22:41 +0100 Subject: [PATCH 57/61] add superclass FormData for CO2FormData and VirusFormData --- caimira/apps/calculator/__init__.py | 6 +- .../apps/calculator/co2_model_generator.py | 106 ++--- caimira/apps/calculator/form_data.py | 440 ++++++++++++++++++ caimira/apps/calculator/model_generator.py | 418 +---------------- caimira/apps/calculator/report_generator.py | 18 +- caimira/tests/apps/calculator/conftest.py | 2 +- .../apps/calculator/test_model_generator.py | 87 ++-- .../test_specific_model_generator.py | 10 +- 8 files changed, 543 insertions(+), 544 deletions(-) create mode 100644 caimira/apps/calculator/form_data.py diff --git a/caimira/apps/calculator/__init__.py b/caimira/apps/calculator/__init__.py index 28a0839d..b5a11900 100644 --- a/caimira/apps/calculator/__init__.py +++ b/caimira/apps/calculator/__init__.py @@ -106,7 +106,7 @@ async def post(self) -> None: start = datetime.datetime.now() try: - form = model_generator.FormData.from_dict(requested_model_config) + form = model_generator.VirusFormData.from_dict(requested_model_config) except Exception as err: if self.settings.get("debug", False): import traceback @@ -157,7 +157,7 @@ async def post(self) -> None: pprint(requested_model_config) try: - form = model_generator.FormData.from_dict(requested_model_config) + form = model_generator.VirusFormData.from_dict(requested_model_config) except Exception as err: if self.settings.get("debug", False): import traceback @@ -178,7 +178,7 @@ async def post(self) -> None: class StaticModel(BaseRequestHandler): async def get(self) -> None: - form = model_generator.FormData.from_dict(model_generator.baseline_raw_form_data()) + form = model_generator.VirusFormData.from_dict(model_generator.baseline_raw_form_data()) base_url = self.request.protocol + "://" + self.request.host report_generator: ReportGenerator = self.settings['report_generator'] executor = loky.get_reusable_executor(max_workers=self.settings['handler_worker_pool_size']) diff --git a/caimira/apps/calculator/co2_model_generator.py b/caimira/apps/calculator/co2_model_generator.py index 0ca201c0..3d90fb99 100644 --- a/caimira/apps/calculator/co2_model_generator.py +++ b/caimira/apps/calculator/co2_model_generator.py @@ -1,13 +1,13 @@ import dataclasses -import html import logging import typing import numpy as np import ruptures as rpt import matplotlib.pyplot as plt +import re from caimira import models -from . import model_generator +from .form_data import FormData, cast_class_fields from .defaults import DEFAULT_MC_SAMPLE_SIZE, NO_DEFAULT from .report_generator import img2base64, _figure2bytes @@ -17,29 +17,10 @@ @dataclasses.dataclass -class CO2FormData(model_generator.FormData): +class CO2FormData(FormData): CO2_data: dict - exposed_coffee_break_option: str - exposed_coffee_duration: int - exposed_finish: model_generator.minutes_since_midnight - exposed_lunch_finish: model_generator.minutes_since_midnight - exposed_lunch_option: bool - exposed_lunch_start: model_generator.minutes_since_midnight - exposed_start: model_generator.minutes_since_midnight fitting_ventilation_states: list fitting_ventilation_type: str - infected_coffee_break_option: str - infected_coffee_duration: int - infected_dont_have_breaks_with_exposed: bool - infected_finish: model_generator.minutes_since_midnight - infected_lunch_finish: model_generator.minutes_since_midnight - infected_lunch_option: bool - infected_lunch_start: model_generator.minutes_since_midnight - infected_people: int - infected_start: model_generator.minutes_since_midnight - room_volume: float - specific_breaks: dict - total_people: int #: The default values for undefined fields. Note that the defaults here #: and the defaults in the html form must not be contradictory. @@ -73,33 +54,37 @@ def __init__(self, **kwargs): for key, value in self._DEFAULTS.items(): setattr(self, key, kwargs.get(key, value)) - @classmethod - def from_dict(self, form_data: typing.Dict) -> "CO2FormData": - # Take a copy of the form data so that we can mutate it. - form_data = form_data.copy() - form_data.pop('_xsrf', None) - - # Don't let arbitrary unescaped HTML through the net. - for key, value in form_data.items(): - if isinstance(value, str): - form_data[key] = html.escape(value) - - for key, default_value in self._DEFAULTS.items(): - if form_data.get(key, '') == '': - if default_value is NO_DEFAULT: - raise ValueError(f"{key} must be specified") - form_data[key] = default_value - - for key, value in form_data.items(): - if key in model_generator._CAST_RULES_FORM_ARG_TO_NATIVE: - form_data[key] = model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[key](value) - - if key not in self._DEFAULTS: - raise ValueError(f'Invalid argument "{html.escape(key)}" given') - - instance = self(**form_data) - instance.validate_population_parameters() - return instance + def validate(self): + # Validate population parameters + self.validate_population_parameters() + + # Validate specific inputs - breaks (exposed and infected) + if self.specific_breaks != {}: + if type(self.specific_breaks) is not dict: + raise TypeError('The specific breaks should be in a dictionary.') + + dict_keys = list(self.specific_breaks.keys()) + if "exposed_breaks" not in dict_keys: + raise TypeError(f'Unable to fetch "exposed_breaks" key. Got "{dict_keys[0]}".') + if "infected_breaks" not in dict_keys: + raise TypeError(f'Unable to fetch "infected_breaks" key. Got "{dict_keys[1]}".') + + for population_breaks in ['exposed_breaks', 'infected_breaks']: + if self.specific_breaks[population_breaks] != []: + if type(self.specific_breaks[population_breaks]) is not list: + raise TypeError(f'All breaks should be in a list. Got {type(self.specific_breaks[population_breaks])}.') + for input_break in self.specific_breaks[population_breaks]: + # Input validations. + if type(input_break) is not dict: + raise TypeError(f'Each break should be a dictionary. Got {type(input_break)}.') + dict_keys = list(input_break.keys()) + if "start_time" not in input_break: + raise TypeError(f'Unable to fetch "start_time" key. Got "{dict_keys[0]}".') + if "finish_time" not in input_break: + raise TypeError(f'Unable to fetch "finish_time" key. Got "{dict_keys[1]}".') + for time in input_break.values(): + if not re.compile("^(2[0-3]|[01]?[0-9]):([0-5]?[0-9])$").match(time): + raise TypeError(f'Wrong time format - "HH:MM". Got "{time}".') @classmethod def find_change_points_with_pelt(self, CO2_data: dict): @@ -196,23 +181,6 @@ def build_model(self, size=DEFAULT_MC_SAMPLE_SIZE) -> models.CO2DataModel: # typ ventilation_transition_times=self.ventilation_transition_times(), times=self.CO2_data['times'], CO2_concentrations=self.CO2_data['CO2'], - ) - - -for _field in dataclasses.fields(CO2FormData): - if _field.type is minutes_since_midnight: - model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.time_string_to_minutes - model_generator._CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.time_minutes_to_string - elif _field.type is int: - model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator._safe_int_cast - elif _field.type is float: - model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = float - elif _field.type is bool: - model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = lambda v: v == '1' - model_generator._CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = int - elif _field.type is list: - model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.string_to_list - model_generator._CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.list_to_string - elif _field.type is dict: - model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = model_generator.string_to_dict - model_generator._CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = model_generator.dict_to_string + ) + +cast_class_fields(CO2FormData) diff --git a/caimira/apps/calculator/form_data.py b/caimira/apps/calculator/form_data.py new file mode 100644 index 00000000..9d82af94 --- /dev/null +++ b/caimira/apps/calculator/form_data.py @@ -0,0 +1,440 @@ +import dataclasses +import datetime +import html +import logging +import typing +import ast +import json + +import numpy as np + +from caimira import models +from .defaults import DEFAULTS, NO_DEFAULT, COFFEE_OPTIONS_INT, DEFAULT_MC_SAMPLE_SIZE + +LOG = logging.getLogger(__name__) + +minutes_since_midnight = typing.NewType('minutes_since_midnight', int) + + +@dataclasses.dataclass +class FormData: + specific_breaks: dict + exposed_coffee_break_option: str + exposed_coffee_duration: int + exposed_finish: minutes_since_midnight + exposed_lunch_finish: minutes_since_midnight + exposed_lunch_option: bool + exposed_lunch_start: minutes_since_midnight + exposed_start: minutes_since_midnight + infected_coffee_break_option: str #Used if infected_dont_have_breaks_with_exposed + infected_coffee_duration: int #Used if infected_dont_have_breaks_with_exposed + infected_dont_have_breaks_with_exposed: bool + infected_finish: minutes_since_midnight + infected_lunch_finish: minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed + infected_lunch_option: bool #Used if infected_dont_have_breaks_with_exposed + infected_lunch_start: minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed + infected_people: int + infected_start: minutes_since_midnight + room_volume: float + total_people: int + + _DEFAULTS: typing.ClassVar[typing.Dict[str, typing.Any]] = DEFAULTS + + @classmethod + def from_dict(cls, form_data: typing.Dict): + # Take a copy of the form data so that we can mutate it. + form_data = form_data.copy() + form_data.pop('_xsrf', None) + + # Don't let arbitrary unescaped HTML through the net. + for key, value in form_data.items(): + if isinstance(value, str): + form_data[key] = html.escape(value) + + for key, default_value in cls._DEFAULTS.items(): + if form_data.get(key, '') == '': + if default_value is NO_DEFAULT: + raise ValueError(f"{key} must be specified") + form_data[key] = default_value + + for key, value in form_data.items(): + if key in _CAST_RULES_FORM_ARG_TO_NATIVE: + form_data[key] = _CAST_RULES_FORM_ARG_TO_NATIVE[key](value) + + if key not in cls._DEFAULTS: + raise ValueError(f'Invalid argument "{html.escape(key)}" given') + + instance = cls(**form_data) + instance.validate() + return instance + + @classmethod + def to_dict(cls, form: "FormData", strip_defaults: bool = False) -> dict: + form_dict = { + field.name: getattr(form, field.name) + for field in dataclasses.fields(form) + } + + for attr, value in form_dict.items(): + if attr in _CAST_RULES_NATIVE_TO_FORM_ARG: + form_dict[attr] = _CAST_RULES_NATIVE_TO_FORM_ARG[attr](value) + + if strip_defaults: + del form_dict['calculator_version'] + + for attr, value in list(form_dict.items()): + default = cls._DEFAULTS.get(attr, NO_DEFAULT) + if default is not NO_DEFAULT and value in [default, 'not-applicable']: + form_dict.pop(attr) + return form_dict + + def validate_population_parameters(self): + # Validate number of infected <= number of total people + if self.infected_people >= self.total_people: + raise ValueError('Number of infected people cannot be greater or equal to the number of total people.') + + # Validate time intervals selected by user + time_intervals = [ + ['exposed_start', 'exposed_finish'], + ['infected_start', 'infected_finish'], + ] + if self.exposed_lunch_option: + time_intervals.append(['exposed_lunch_start', 'exposed_lunch_finish']) + if self.infected_dont_have_breaks_with_exposed and self.infected_lunch_option: + time_intervals.append(['infected_lunch_start', 'infected_lunch_finish']) + + for start_name, end_name in time_intervals: + start = getattr(self, start_name) + end = getattr(self, end_name) + if start > end: + raise ValueError( + f"{start_name} must be less than {end_name}. Got {start} and {end}.") + + def validate_lunch(start, finish): + lunch_start = getattr(self, f'{population}_lunch_start') + lunch_finish = getattr(self, f'{population}_lunch_finish') + return (start <= lunch_start <= finish and + start <= lunch_finish <= finish) + + def get_lunch_mins(population): + lunch_mins = 0 + if getattr(self, f'{population}_lunch_option'): + lunch_mins = getattr(self, f'{population}_lunch_finish') - getattr(self, f'{population}_lunch_start') + return lunch_mins + + def get_coffee_mins(population): + coffee_mins = 0 + if getattr(self, f'{population}_coffee_break_option') != 'coffee_break_0': + coffee_mins = COFFEE_OPTIONS_INT[getattr(self, f'{population}_coffee_break_option')] * getattr(self, f'{population}_coffee_duration') + return coffee_mins + + def get_activity_mins(population): + return getattr(self, f'{population}_finish') - getattr(self, f'{population}_start') + + populations = ['exposed', 'infected'] if self.infected_dont_have_breaks_with_exposed else ['exposed'] + for population in populations: + # Validate lunch time within the activity times. + if (getattr(self, f'{population}_lunch_option') and + not validate_lunch(getattr(self, f'{population}_start'), getattr(self, f'{population}_finish')) + ): + raise ValueError( + f"{population} lunch break must be within presence times." + ) + + # Length of breaks < length of activity + if (get_lunch_mins(population) + get_coffee_mins(population)) >= get_activity_mins(population): + raise ValueError( + f"Length of breaks >= Length of {population} presence." + ) + + for attr_name, valid_set in [('exposed_coffee_break_option', COFFEE_OPTIONS_INT), + ('infected_coffee_break_option', COFFEE_OPTIONS_INT)]: + if getattr(self, attr_name) not in valid_set: + raise ValueError(f"{getattr(self, attr_name)} is not a valid value for {attr_name}") + + def validate(self): + raise NotImplementedError("Subclass must implement") + + def build_model(self, sample_size=DEFAULT_MC_SAMPLE_SIZE): + raise NotImplementedError("Subclass must implement") + + def _compute_breaks_in_interval(self, start, finish, n_breaks, duration) -> models.BoundarySequence_t: + break_delay = ((finish - start) - (n_breaks * duration)) // (n_breaks+1) + break_times = [] + end = start + for n in range(n_breaks): + begin = end + break_delay + end = begin + duration + break_times.append((begin, end)) + return tuple(break_times) + + def exposed_lunch_break_times(self) -> models.BoundarySequence_t: + result = [] + if self.exposed_lunch_option: + result.append((self.exposed_lunch_start, self.exposed_lunch_finish)) + return tuple(result) + + def infected_lunch_break_times(self) -> models.BoundarySequence_t: + if self.infected_dont_have_breaks_with_exposed: + result = [] + if self.infected_lunch_option: + result.append((self.infected_lunch_start, self.infected_lunch_finish)) + return tuple(result) + else: + return self.exposed_lunch_break_times() + + def exposed_number_of_coffee_breaks(self) -> int: + return COFFEE_OPTIONS_INT[self.exposed_coffee_break_option] + + def infected_number_of_coffee_breaks(self) -> int: + return COFFEE_OPTIONS_INT[self.infected_coffee_break_option] + + def _coffee_break_times(self, activity_start, activity_finish, coffee_breaks, coffee_duration, lunch_start, lunch_finish) -> models.BoundarySequence_t: + time_before_lunch = lunch_start - activity_start + time_after_lunch = activity_finish - lunch_finish + before_lunch_frac = time_before_lunch / (time_before_lunch + time_after_lunch) + n_morning_breaks = round(coffee_breaks * before_lunch_frac) + breaks = ( + self._compute_breaks_in_interval( + activity_start, lunch_start, n_morning_breaks, coffee_duration + ) + + self._compute_breaks_in_interval( + lunch_finish, activity_finish, coffee_breaks - n_morning_breaks, coffee_duration + ) + ) + return breaks + + def exposed_coffee_break_times(self) -> models.BoundarySequence_t: + exposed_coffee_breaks = self.exposed_number_of_coffee_breaks() + if exposed_coffee_breaks == 0: + return () + if self.exposed_lunch_option: + breaks = self._coffee_break_times(self.exposed_start, self.exposed_finish, exposed_coffee_breaks, self.exposed_coffee_duration, self.exposed_lunch_start, self.exposed_lunch_finish) + else: + breaks = self._compute_breaks_in_interval(self.exposed_start, self.exposed_finish, exposed_coffee_breaks, self.exposed_coffee_duration) + return breaks + + def infected_coffee_break_times(self) -> models.BoundarySequence_t: + if self.infected_dont_have_breaks_with_exposed: + infected_coffee_breaks = self.infected_number_of_coffee_breaks() + if infected_coffee_breaks == 0: + return () + if self.infected_lunch_option: + breaks = self._coffee_break_times(self.infected_start, self.infected_finish, infected_coffee_breaks, self.infected_coffee_duration, self.infected_lunch_start, self.infected_lunch_finish) + else: + breaks = self._compute_breaks_in_interval(self.infected_start, self.infected_finish, infected_coffee_breaks, self.infected_coffee_duration) + return breaks + else: + return self.exposed_coffee_break_times() + + def generate_specific_break_times(self, population_breaks) -> models.BoundarySequence_t: + break_times = [] + for n in population_breaks: + # Parse break times. + begin = time_string_to_minutes(n["start_time"]) + end = time_string_to_minutes(n["finish_time"]) + for time in [begin, end]: + # For a specific break, the infected and exposed presence is the same. + if not getattr(self, 'infected_start') < time < getattr(self, 'infected_finish'): + raise ValueError(f'All breaks should be within the simulation time. Got {time_minutes_to_string(time)}.') + + break_times.append((begin, end)) + return tuple(break_times) + + def present_interval( + self, + start: int, + finish: int, + breaks: typing.Optional[models.BoundarySequence_t] = None, + ) -> models.Interval: + """ + Calculate the presence interval given the start and end times (in minutes), and + a number of monotonic, non-overlapping, but potentially unsorted, breaks (also in minutes). + + """ + if not breaks: + # If there are no breaks, the interval is the start and end. + return models.SpecificInterval(((start/60, finish/60),)) + + # Order the breaks by their start-time, and ensure that they are monotonic + # and that the start of one break happens after the end of another. + break_boundaries: models.BoundarySequence_t = tuple(sorted(breaks, key=lambda break_pair: break_pair[0])) + + for break_start, break_end in break_boundaries: + if break_start >= break_end: + raise ValueError("Break ends before it begins.") + + prev_break_end = break_boundaries[0][1] + for break_start, break_end in break_boundaries[1:]: + if prev_break_end >= break_start: + raise ValueError(f"A break starts before another ends ({break_start}, {break_end}, {prev_break_end}).") + prev_break_end = break_end + + present_intervals = [] + + current_time = start + LOG.debug(f"starting time march at {_hours2timestring(current_time/60)} to {_hours2timestring(finish/60)}") + + # As we step through the breaks. For each break there are 6 important cases + # we must cover. Let S=start; E=end; Bs=Break start; Be=Break end: + # 1. The interval is entirely before the break. S < E <= Bs < Be + # 2. The interval straddles the start of the break. S < Bs < E <= Be + # 3. The break is entirely inside the interval. S < Bs < Be <= E + # 4. The interval is entirely inside the break. Bs <= S < E <= Be + # 5. The interval straddles the end of the break. Bs <= S < Be <= E + # 6. The interval is entirely after the break. Bs < Be <= S < E + + for current_break in break_boundaries: + if current_time >= finish: + break + + LOG.debug(f"handling break {_hours2timestring(current_break[0]/60)}-{_hours2timestring(current_break[1]/60)} " + f" (current time: {_hours2timestring(current_time/60)})") + + break_s, break_e = current_break + case1 = finish <= break_s + case2 = current_time < break_s < finish < break_e + case3 = current_time < break_s < break_e <= finish + case4 = break_s <= current_time < finish <= break_e + case5 = break_s <= current_time < break_e < finish + case6 = break_e <= current_time + + if case1: + LOG.debug(f"case 1: interval entirely before break") + present_intervals.append((current_time / 60, finish / 60)) + LOG.debug(f" + added interval {_hours2timestring(present_intervals[-1][0])} " + f"- {_hours2timestring(present_intervals[-1][1])}") + current_time = finish + elif case2: + LOG.debug(f"case 2: interval straddles start of break") + present_intervals.append((current_time / 60, break_s / 60)) + LOG.debug(f" + added interval {_hours2timestring(present_intervals[-1][0])} " + f"- {_hours2timestring(present_intervals[-1][1])}") + current_time = break_e + elif case3: + LOG.debug(f"case 3: break entirely inside interval") + # We add the bit before the break, but not the bit afterwards, + # as it may hit another break. + present_intervals.append((current_time / 60, break_s / 60)) + LOG.debug(f" + added interval {_hours2timestring(present_intervals[-1][0])} " + f"- {_hours2timestring(present_intervals[-1][1])}") + current_time = break_e + elif case4: + LOG.debug(f"case 4: interval entirely inside break") + current_time = finish + elif case5: + LOG.debug(f"case 5: interval straddles end of break") + current_time = break_e + elif case6: + LOG.debug(f"case 6: interval entirely after the break") + + if current_time < finish: + LOG.debug("trailing interval") + present_intervals.append((current_time / 60, finish / 60)) + return models.SpecificInterval(tuple(present_intervals)) + + def infected_present_interval(self) -> models.Interval: + if self.specific_breaks != {}: # It means the breaks are specific and not predefined + breaks = self.generate_specific_break_times(self.specific_breaks['infected_breaks']) + else: + breaks = self.infected_lunch_break_times() + self.infected_coffee_break_times() + return self.present_interval( + self.infected_start, self.infected_finish, + breaks=breaks, + ) + + def population_present_interval(self) -> models.Interval: + state_change_times = set(self.infected_present_interval().transition_times()) + state_change_times.update(self.exposed_present_interval().transition_times()) + all_state_changes = sorted(state_change_times) + return models.SpecificInterval(tuple(zip(all_state_changes[:-1], all_state_changes[1:]))) + + def exposed_present_interval(self) -> models.Interval: + if self.specific_breaks != {}: # It means the breaks are specific and not predefined + breaks = self.generate_specific_break_times(self.specific_breaks['exposed_breaks']) + else: + breaks = self.exposed_lunch_break_times() + self.exposed_coffee_break_times() + return self.present_interval( + self.exposed_start, self.exposed_finish, + breaks=breaks, + ) + + +def _hours2timestring(hours: float): + # Convert times like 14.5 to strings, like "14:30" + return f"{int(np.floor(hours)):02d}:{int(np.round((hours % 1) * 60)):02d}" + + +def time_string_to_minutes(time: str) -> minutes_since_midnight: + """ + Converts time from string-format to an integer number of minutes after 00:00 + :param time: A string of the form "HH:MM" representing a time of day + :return: The number of minutes between 'time' and 00:00 + """ + return minutes_since_midnight(60 * int(time[:2]) + int(time[3:])) + + +def time_minutes_to_string(time: int) -> str: + """ + Converts time from an integer number of minutes after 00:00 to string-format + :param time: The number of minutes between 'time' and 00:00 + :return: A string of the form "HH:MM" representing a time of day + """ + return "{0:0=2d}".format(int(time/60)) + ":" + "{0:0=2d}".format(time%60) + + +def string_to_list(s: str) -> list: + return list(ast.literal_eval(s.replace(""", "\""))) + + +def list_to_string(l: list) -> str: + return json.dumps(l) + + +def string_to_dict(s: str) -> dict: + return dict(ast.literal_eval(s.replace(""", "\""))) + + +def dict_to_string(d: dict) -> str: + return json.dumps(d) + + +def _safe_int_cast(value) -> int: + if isinstance(value, int): + return value + elif isinstance(value, float) and int(value) == value: + return int(value) + elif isinstance(value, str) and value.isdecimal(): + return int(value) + else: + raise TypeError(f"Unable to safely cast {value} ({type(value)} type) to int") + + +#: Mapping of field name to a callable which can convert values from form +#: input (URL encoded arguments / string) into the correct type. +_CAST_RULES_FORM_ARG_TO_NATIVE: typing.Dict[str, typing.Callable] = {} + +#: Mapping of field name to callable which can convert native type to values +#: that can be encoded to URL arguments. +_CAST_RULES_NATIVE_TO_FORM_ARG: typing.Dict[str, typing.Callable] = {} + +def cast_class_fields(cls): + for _field in dataclasses.fields(cls): + if _field.type is minutes_since_midnight: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = time_string_to_minutes + _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = time_minutes_to_string + elif _field.type is int: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = _safe_int_cast + elif _field.type is float: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = float + elif _field.type is bool: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = lambda v: v == '1' + _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = int + elif _field.type is list: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = string_to_list + _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = list_to_string + elif _field.type is dict: + _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = string_to_dict + _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = dict_to_string + +cast_class_fields(FormData) diff --git a/caimira/apps/calculator/model_generator.py b/caimira/apps/calculator/model_generator.py index 2e40b19c..19419b96 100644 --- a/caimira/apps/calculator/model_generator.py +++ b/caimira/apps/calculator/model_generator.py @@ -1,10 +1,7 @@ import dataclasses import datetime -import html import logging import typing -import ast -import json import re import numpy as np @@ -14,9 +11,10 @@ import caimira.data.weather import caimira.monte_carlo as mc from .. import calculator +from .form_data import FormData, cast_class_fields, time_string_to_minutes from caimira.monte_carlo.data import activity_distributions, virus_distributions, mask_distributions, short_range_distances from caimira.monte_carlo.data import expiration_distribution, expiration_BLO_factors, expiration_distributions, short_range_expiration_distributions -from .defaults import (NO_DEFAULT, DEFAULT_MC_SAMPLE_SIZE, DEFAULTS, ACTIVITIES, ACTIVITY_TYPES, COFFEE_OPTIONS_INT, CONFIDENCE_LEVEL_OPTIONS, +from .defaults import (DEFAULT_MC_SAMPLE_SIZE, DEFAULTS, ACTIVITIES, ACTIVITY_TYPES, CONFIDENCE_LEVEL_OPTIONS, MECHANICAL_VENTILATION_TYPES, MASK_TYPES, MASK_WEARING_OPTIONS, MONTH_NAMES, VACCINE_BOOSTER_TYPE, VACCINE_TYPE, VENTILATION_TYPES, VIRUS_TYPES, VOLUME_TYPES, WINDOWS_OPENING_REGIMES, WINDOWS_TYPES) from caimira.store.configuration import config @@ -27,37 +25,20 @@ @dataclasses.dataclass -class FormData: +class VirusFormData(FormData): activity_type: str air_changes: float air_supply: float arve_sensors_option: bool - specific_breaks: dict precise_activity: dict ceiling_height: float conditional_probability_plot: bool conditional_probability_viral_loads: bool CO2_fitting_result: dict - exposed_coffee_break_option: str - exposed_coffee_duration: int - exposed_finish: minutes_since_midnight - exposed_lunch_finish: minutes_since_midnight - exposed_lunch_option: bool - exposed_lunch_start: minutes_since_midnight - exposed_start: minutes_since_midnight floor_area: float hepa_amount: float hepa_option: bool humidity: str - infected_coffee_break_option: str #Used if infected_dont_have_breaks_with_exposed - infected_coffee_duration: int #Used if infected_dont_have_breaks_with_exposed - infected_dont_have_breaks_with_exposed: bool - infected_finish: minutes_since_midnight - infected_lunch_finish: minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed - infected_lunch_option: bool #Used if infected_dont_have_breaks_with_exposed - infected_lunch_start: minutes_since_midnight #Used if infected_dont_have_breaks_with_exposed - infected_people: int - infected_start: minutes_since_midnight inside_temp: float location_name: str location_latitude: float @@ -74,9 +55,7 @@ class FormData: event_month: str room_heating_option: bool room_number: str - room_volume: float simulation_name: str - total_people: int vaccine_option: bool vaccine_booster_option: bool vaccine_type: str @@ -96,119 +75,7 @@ class FormData: short_range_interactions: list _DEFAULTS: typing.ClassVar[typing.Dict[str, typing.Any]] = DEFAULTS - - @classmethod - def from_dict(cls, form_data: typing.Dict) -> "FormData": - # Take a copy of the form data so that we can mutate it. - form_data = form_data.copy() - form_data.pop('_xsrf', None) - - # Don't let arbitrary unescaped HTML through the net. - for key, value in form_data.items(): - if isinstance(value, str): - form_data[key] = html.escape(value) - - for key, default_value in cls._DEFAULTS.items(): - if form_data.get(key, '') == '': - if default_value is NO_DEFAULT: - raise ValueError(f"{key} must be specified") - form_data[key] = default_value - - for key, value in form_data.items(): - if key in _CAST_RULES_FORM_ARG_TO_NATIVE: - form_data[key] = _CAST_RULES_FORM_ARG_TO_NATIVE[key](value) - - if key not in cls._DEFAULTS: - raise ValueError(f'Invalid argument "{html.escape(key)}" given') - - instance = cls(**form_data) - instance.validate() - return instance - - @classmethod - def to_dict(cls, form: "FormData", strip_defaults: bool = False) -> dict: - form_dict = { - field.name: getattr(form, field.name) - for field in dataclasses.fields(form) - } - - for attr, value in form_dict.items(): - if attr in _CAST_RULES_NATIVE_TO_FORM_ARG: - form_dict[attr] = _CAST_RULES_NATIVE_TO_FORM_ARG[attr](value) - - if strip_defaults: - del form_dict['calculator_version'] - - for attr, value in list(form_dict.items()): - default = cls._DEFAULTS.get(attr, NO_DEFAULT) - if default is not NO_DEFAULT and value in [default, 'not-applicable']: - form_dict.pop(attr) - return form_dict - def validate_population_parameters(self): - # Validate number of infected <= number of total people - if self.infected_people >= self.total_people: - raise ValueError('Number of infected people cannot be greater or equal to the number of total people.') - - # Validate time intervals selected by user - time_intervals = [ - ['exposed_start', 'exposed_finish'], - ['infected_start', 'infected_finish'], - ] - if self.exposed_lunch_option: - time_intervals.append(['exposed_lunch_start', 'exposed_lunch_finish']) - if self.infected_dont_have_breaks_with_exposed and self.infected_lunch_option: - time_intervals.append(['infected_lunch_start', 'infected_lunch_finish']) - - for start_name, end_name in time_intervals: - start = getattr(self, start_name) - end = getattr(self, end_name) - if start > end: - raise ValueError( - f"{start_name} must be less than {end_name}. Got {start} and {end}.") - - def validate_lunch(start, finish): - lunch_start = getattr(self, f'{population}_lunch_start') - lunch_finish = getattr(self, f'{population}_lunch_finish') - return (start <= lunch_start <= finish and - start <= lunch_finish <= finish) - - def get_lunch_mins(population): - lunch_mins = 0 - if getattr(self, f'{population}_lunch_option'): - lunch_mins = getattr(self, f'{population}_lunch_finish') - getattr(self, f'{population}_lunch_start') - return lunch_mins - - def get_coffee_mins(population): - coffee_mins = 0 - if getattr(self, f'{population}_coffee_break_option') != 'coffee_break_0': - coffee_mins = COFFEE_OPTIONS_INT[getattr(self, f'{population}_coffee_break_option')] * getattr(self, f'{population}_coffee_duration') - return coffee_mins - - def get_activity_mins(population): - return getattr(self, f'{population}_finish') - getattr(self, f'{population}_start') - - populations = ['exposed', 'infected'] if self.infected_dont_have_breaks_with_exposed else ['exposed'] - for population in populations: - # Validate lunch time within the activity times. - if (getattr(self, f'{population}_lunch_option') and - not validate_lunch(getattr(self, f'{population}_start'), getattr(self, f'{population}_finish')) - ): - raise ValueError( - f"{population} lunch break must be within presence times." - ) - - # Length of breaks < length of activity - if (get_lunch_mins(population) + get_coffee_mins(population)) >= get_activity_mins(population): - raise ValueError( - f"Length of breaks >= Length of {population} presence." - ) - - for attr_name, valid_set in [('exposed_coffee_break_option', COFFEE_OPTIONS_INT), - ('infected_coffee_break_option', COFFEE_OPTIONS_INT)]: - if getattr(self, attr_name) not in valid_set: - raise ValueError(f"{getattr(self, attr_name)} is not a valid value for {attr_name}") - def validate(self): # Validate population parameters self.validate_population_parameters() @@ -591,212 +458,11 @@ def exposed_population(self) -> mc.Population: ) return exposed - def _compute_breaks_in_interval(self, start, finish, n_breaks, duration) -> models.BoundarySequence_t: - break_delay = ((finish - start) - (n_breaks * duration)) // (n_breaks+1) - break_times = [] - end = start - for n in range(n_breaks): - begin = end + break_delay - end = begin + duration - break_times.append((begin, end)) - return tuple(break_times) - - def exposed_lunch_break_times(self) -> models.BoundarySequence_t: - result = [] - if self.exposed_lunch_option: - result.append((self.exposed_lunch_start, self.exposed_lunch_finish)) - return tuple(result) - - def infected_lunch_break_times(self) -> models.BoundarySequence_t: - if self.infected_dont_have_breaks_with_exposed: - result = [] - if self.infected_lunch_option: - result.append((self.infected_lunch_start, self.infected_lunch_finish)) - return tuple(result) - else: - return self.exposed_lunch_break_times() - - def exposed_number_of_coffee_breaks(self) -> int: - return COFFEE_OPTIONS_INT[self.exposed_coffee_break_option] - - def infected_number_of_coffee_breaks(self) -> int: - return COFFEE_OPTIONS_INT[self.infected_coffee_break_option] - - def _coffee_break_times(self, activity_start, activity_finish, coffee_breaks, coffee_duration, lunch_start, lunch_finish) -> models.BoundarySequence_t: - time_before_lunch = lunch_start - activity_start - time_after_lunch = activity_finish - lunch_finish - before_lunch_frac = time_before_lunch / (time_before_lunch + time_after_lunch) - n_morning_breaks = round(coffee_breaks * before_lunch_frac) - breaks = ( - self._compute_breaks_in_interval( - activity_start, lunch_start, n_morning_breaks, coffee_duration - ) - + self._compute_breaks_in_interval( - lunch_finish, activity_finish, coffee_breaks - n_morning_breaks, coffee_duration - ) - ) - return breaks - - def exposed_coffee_break_times(self) -> models.BoundarySequence_t: - exposed_coffee_breaks = self.exposed_number_of_coffee_breaks() - if exposed_coffee_breaks == 0: - return () - if self.exposed_lunch_option: - breaks = self._coffee_break_times(self.exposed_start, self.exposed_finish, exposed_coffee_breaks, self.exposed_coffee_duration, self.exposed_lunch_start, self.exposed_lunch_finish) - else: - breaks = self._compute_breaks_in_interval(self.exposed_start, self.exposed_finish, exposed_coffee_breaks, self.exposed_coffee_duration) - return breaks - - def infected_coffee_break_times(self) -> models.BoundarySequence_t: - if self.infected_dont_have_breaks_with_exposed: - infected_coffee_breaks = self.infected_number_of_coffee_breaks() - if infected_coffee_breaks == 0: - return () - if self.infected_lunch_option: - breaks = self._coffee_break_times(self.infected_start, self.infected_finish, infected_coffee_breaks, self.infected_coffee_duration, self.infected_lunch_start, self.infected_lunch_finish) - else: - breaks = self._compute_breaks_in_interval(self.infected_start, self.infected_finish, infected_coffee_breaks, self.infected_coffee_duration) - return breaks - else: - return self.exposed_coffee_break_times() - - def generate_specific_break_times(self, population_breaks) -> models.BoundarySequence_t: - break_times = [] - for n in population_breaks: - # Parse break times. - begin = time_string_to_minutes(n["start_time"]) - end = time_string_to_minutes(n["finish_time"]) - for time in [begin, end]: - # For a specific break, the infected and exposed presence is the same. - if not getattr(self, 'infected_start') < time < getattr(self, 'infected_finish'): - raise ValueError(f'All breaks should be within the simulation time. Got {time_minutes_to_string(time)}.') - - break_times.append((begin, end)) - return tuple(break_times) - - def present_interval( - self, - start: int, - finish: int, - breaks: typing.Optional[models.BoundarySequence_t] = None, - ) -> models.Interval: - """ - Calculate the presence interval given the start and end times (in minutes), and - a number of monotonic, non-overlapping, but potentially unsorted, breaks (also in minutes). - - """ - if not breaks: - # If there are no breaks, the interval is the start and end. - return models.SpecificInterval(((start/60, finish/60),)) - - # Order the breaks by their start-time, and ensure that they are monotonic - # and that the start of one break happens after the end of another. - break_boundaries: models.BoundarySequence_t = tuple(sorted(breaks, key=lambda break_pair: break_pair[0])) - - for break_start, break_end in break_boundaries: - if break_start >= break_end: - raise ValueError("Break ends before it begins.") - - prev_break_end = break_boundaries[0][1] - for break_start, break_end in break_boundaries[1:]: - if prev_break_end >= break_start: - raise ValueError(f"A break starts before another ends ({break_start}, {break_end}, {prev_break_end}).") - prev_break_end = break_end - - present_intervals = [] - - current_time = start - LOG.debug(f"starting time march at {_hours2timestring(current_time/60)} to {_hours2timestring(finish/60)}") - - # As we step through the breaks. For each break there are 6 important cases - # we must cover. Let S=start; E=end; Bs=Break start; Be=Break end: - # 1. The interval is entirely before the break. S < E <= Bs < Be - # 2. The interval straddles the start of the break. S < Bs < E <= Be - # 3. The break is entirely inside the interval. S < Bs < Be <= E - # 4. The interval is entirely inside the break. Bs <= S < E <= Be - # 5. The interval straddles the end of the break. Bs <= S < Be <= E - # 6. The interval is entirely after the break. Bs < Be <= S < E - - for current_break in break_boundaries: - if current_time >= finish: - break - - LOG.debug(f"handling break {_hours2timestring(current_break[0]/60)}-{_hours2timestring(current_break[1]/60)} " - f" (current time: {_hours2timestring(current_time/60)})") - - break_s, break_e = current_break - case1 = finish <= break_s - case2 = current_time < break_s < finish < break_e - case3 = current_time < break_s < break_e <= finish - case4 = break_s <= current_time < finish <= break_e - case5 = break_s <= current_time < break_e < finish - case6 = break_e <= current_time - - if case1: - LOG.debug(f"case 1: interval entirely before break") - present_intervals.append((current_time / 60, finish / 60)) - LOG.debug(f" + added interval {_hours2timestring(present_intervals[-1][0])} " - f"- {_hours2timestring(present_intervals[-1][1])}") - current_time = finish - elif case2: - LOG.debug(f"case 2: interval straddles start of break") - present_intervals.append((current_time / 60, break_s / 60)) - LOG.debug(f" + added interval {_hours2timestring(present_intervals[-1][0])} " - f"- {_hours2timestring(present_intervals[-1][1])}") - current_time = break_e - elif case3: - LOG.debug(f"case 3: break entirely inside interval") - # We add the bit before the break, but not the bit afterwards, - # as it may hit another break. - present_intervals.append((current_time / 60, break_s / 60)) - LOG.debug(f" + added interval {_hours2timestring(present_intervals[-1][0])} " - f"- {_hours2timestring(present_intervals[-1][1])}") - current_time = break_e - elif case4: - LOG.debug(f"case 4: interval entirely inside break") - current_time = finish - elif case5: - LOG.debug(f"case 5: interval straddles end of break") - current_time = break_e - elif case6: - LOG.debug(f"case 6: interval entirely after the break") - - if current_time < finish: - LOG.debug("trailing interval") - present_intervals.append((current_time / 60, finish / 60)) - return models.SpecificInterval(tuple(present_intervals)) - - def infected_present_interval(self) -> models.Interval: - if self.specific_breaks != {}: # It means the breaks are specific and not predefined - breaks = self.generate_specific_break_times(self.specific_breaks['infected_breaks']) - else: - breaks = self.infected_lunch_break_times() + self.infected_coffee_break_times() - return self.present_interval( - self.infected_start, self.infected_finish, - breaks=breaks, - ) - - def population_present_interval(self) -> models.Interval: - state_change_times = set(self.infected_present_interval().transition_times()) - state_change_times.update(self.exposed_present_interval().transition_times()) - all_state_changes = sorted(state_change_times) - return models.SpecificInterval(tuple(zip(all_state_changes[:-1], all_state_changes[1:]))) - def short_range_interval(self, interaction) -> models.SpecificInterval: start_time = time_string_to_minutes(interaction['start_time']) duration = float(interaction['duration']) return models.SpecificInterval(present_times=((start_time/60, (start_time + duration)/60),)) - def exposed_present_interval(self) -> models.Interval: - if self.specific_breaks != {}: # It means the breaks are specific and not predefined - breaks = self.generate_specific_break_times(self.specific_breaks['exposed_breaks']) - else: - breaks = self.exposed_lunch_break_times() + self.exposed_coffee_break_times() - return self.present_interval( - self.exposed_start, self.exposed_finish, - breaks=breaks, - ) - def build_expiration(expiration_definition) -> mc._ExpirationBase: if isinstance(expiration_definition, str): @@ -875,80 +541,4 @@ def baseline_raw_form_data() -> typing.Dict[str, typing.Union[str, float]]: 'short_range_interactions': '[]', } - -def _hours2timestring(hours: float): - # Convert times like 14.5 to strings, like "14:30" - return f"{int(np.floor(hours)):02d}:{int(np.round((hours % 1) * 60)):02d}" - - -def time_string_to_minutes(time: str) -> minutes_since_midnight: - """ - Converts time from string-format to an integer number of minutes after 00:00 - :param time: A string of the form "HH:MM" representing a time of day - :return: The number of minutes between 'time' and 00:00 - """ - return minutes_since_midnight(60 * int(time[:2]) + int(time[3:])) - - -def time_minutes_to_string(time: int) -> str: - """ - Converts time from an integer number of minutes after 00:00 to string-format - :param time: The number of minutes between 'time' and 00:00 - :return: A string of the form "HH:MM" representing a time of day - """ - return "{0:0=2d}".format(int(time/60)) + ":" + "{0:0=2d}".format(time%60) - - -def string_to_list(s: str) -> list: - return list(ast.literal_eval(s.replace(""", "\""))) - - -def list_to_string(l: list) -> str: - return json.dumps(l) - - -def string_to_dict(s: str) -> dict: - return dict(ast.literal_eval(s.replace(""", "\""))) - - -def dict_to_string(d: dict) -> str: - return json.dumps(d) - - -def _safe_int_cast(value) -> int: - if isinstance(value, int): - return value - elif isinstance(value, float) and int(value) == value: - return int(value) - elif isinstance(value, str) and value.isdecimal(): - return int(value) - else: - raise TypeError(f"Unable to safely cast {value} ({type(value)} type) to int") - - -#: Mapping of field name to a callable which can convert values from form -#: input (URL encoded arguments / string) into the correct type. -_CAST_RULES_FORM_ARG_TO_NATIVE: typing.Dict[str, typing.Callable] = {} - -#: Mapping of field name to callable which can convert native type to values -#: that can be encoded to URL arguments. -_CAST_RULES_NATIVE_TO_FORM_ARG: typing.Dict[str, typing.Callable] = {} - - -for _field in dataclasses.fields(FormData): - if _field.type is minutes_since_midnight: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = time_string_to_minutes - _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = time_minutes_to_string - elif _field.type is int: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = _safe_int_cast - elif _field.type is float: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = float - elif _field.type is bool: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = lambda v: v == '1' - _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = int - elif _field.type is list: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = string_to_list - _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = list_to_string - elif _field.type is dict: - _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = string_to_dict - _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = dict_to_string +cast_class_fields(VirusFormData) diff --git a/caimira/apps/calculator/report_generator.py b/caimira/apps/calculator/report_generator.py index 15f2cc8a..e3757229 100644 --- a/caimira/apps/calculator/report_generator.py +++ b/caimira/apps/calculator/report_generator.py @@ -15,7 +15,7 @@ from caimira import models from caimira.apps.calculator import markdown_tools from ... import monte_carlo as mc -from .model_generator import FormData, DEFAULT_MC_SAMPLE_SIZE +from .model_generator import VirusFormData, DEFAULT_MC_SAMPLE_SIZE from ... import dataclass_utils from caimira.store.configuration import config @@ -102,7 +102,7 @@ def interesting_times(model: models.ExposureModel, approx_n_pts: typing.Optional return nice_times -def concentrations_with_sr_breathing(form: FormData, model: models.ExposureModel, times: typing.List[float], short_range_intervals: typing.List) -> typing.List[float]: +def concentrations_with_sr_breathing(form: VirusFormData, model: models.ExposureModel, times: typing.List[float], short_range_intervals: typing.List) -> typing.List[float]: lower_concentrations = [] for time in times: for index, (start, stop) in enumerate(short_range_intervals): @@ -114,7 +114,7 @@ def concentrations_with_sr_breathing(form: FormData, model: models.ExposureModel return lower_concentrations -def calculate_report_data(form: FormData, model: models.ExposureModel) -> typing.Dict[str, typing.Any]: +def calculate_report_data(form: VirusFormData, model: models.ExposureModel) -> typing.Dict[str, typing.Any]: times = interesting_times(model) short_range_intervals = [interaction.presence.boundaries()[0] for interaction in model.short_range] short_range_expirations = [interaction['expiration'] for interaction in form.short_range_interactions] if form.short_range_option == "short_range_yes" else [] @@ -175,8 +175,8 @@ def calculate_report_data(form: FormData, model: models.ExposureModel) -> typing } -def generate_permalink(base_url, get_root_url, get_root_calculator_url, form: FormData): - form_dict = FormData.to_dict(form, strip_defaults=True) +def generate_permalink(base_url, get_root_url, get_root_calculator_url, form: VirusFormData): + form_dict = VirusFormData.to_dict(form, strip_defaults=True) # Generate the calculator URL arguments that would be needed to re-create this # form. @@ -353,7 +353,7 @@ def manufacture_viral_load_scenarios_percentiles(model: mc.ExposureModel) -> typ return scenarios -def manufacture_alternative_scenarios(form: FormData) -> typing.Dict[str, mc.ExposureModel]: +def manufacture_alternative_scenarios(form: VirusFormData) -> typing.Dict[str, mc.ExposureModel]: scenarios = {} if (form.short_range_option == "short_range_no"): # Two special option cases - HEPA and/or FFP2 masks. @@ -424,7 +424,7 @@ def scenario_statistics(mc_model: mc.ExposureModel, sample_times: typing.List[fl def comparison_report( - form: FormData, + form: VirusFormData, report_data: typing.Dict[str, typing.Any], scenarios: typing.Dict[str, mc.ExposureModel], sample_times: typing.List[float], @@ -472,7 +472,7 @@ class ReportGenerator: def build_report( self, base_url: str, - form: FormData, + form: VirusFormData, executor_factory: typing.Callable[[], concurrent.futures.Executor], ) -> str: model = form.build_model() @@ -483,7 +483,7 @@ def prepare_context( self, base_url: str, model: models.ExposureModel, - form: FormData, + form: VirusFormData, executor_factory: typing.Callable[[], concurrent.futures.Executor], ) -> dict: now = datetime.utcnow().astimezone() diff --git a/caimira/tests/apps/calculator/conftest.py b/caimira/tests/apps/calculator/conftest.py index 7e46d0cf..e4eedb11 100644 --- a/caimira/tests/apps/calculator/conftest.py +++ b/caimira/tests/apps/calculator/conftest.py @@ -10,4 +10,4 @@ def baseline_form_data(): @pytest.fixture def baseline_form(baseline_form_data): - return model_generator.FormData.from_dict(baseline_form_data) + return model_generator.VirusFormData.from_dict(baseline_form_data) diff --git a/caimira/tests/apps/calculator/test_model_generator.py b/caimira/tests/apps/calculator/test_model_generator.py index 4d1f5756..697e962f 100644 --- a/caimira/tests/apps/calculator/test_model_generator.py +++ b/caimira/tests/apps/calculator/test_model_generator.py @@ -7,21 +7,22 @@ from retry import retry from caimira.apps.calculator import model_generator -from caimira.apps.calculator.model_generator import _hours2timestring -from caimira.apps.calculator.model_generator import minutes_since_midnight +from caimira.apps.calculator.form_data import (_hours2timestring, minutes_since_midnight, + _CAST_RULES_FORM_ARG_TO_NATIVE, _CAST_RULES_NATIVE_TO_FORM_ARG) from caimira import models from caimira.monte_carlo.data import expiration_distributions +from caimira.apps.calculator.defaults import NO_DEFAULT def test_model_from_dict(baseline_form_data): - form = model_generator.FormData.from_dict(baseline_form_data) + form = model_generator.VirusFormData.from_dict(baseline_form_data) assert isinstance(form.build_model(), models.ExposureModel) def test_model_from_dict_invalid(baseline_form_data): baseline_form_data['invalid_item'] = 'foobar' with pytest.raises(ValueError, match='Invalid argument "invalid_item" given'): - model_generator.FormData.from_dict(baseline_form_data) + model_generator.VirusFormData.from_dict(baseline_form_data) @retry(tries=10) @@ -44,7 +45,7 @@ def test_blend_expiration(mask_type): npt.assert_allclose(r.aerosols(mask).mean(), expected, rtol=TOLERANCE) -def test_ventilation_slidingwindow(baseline_form: model_generator.FormData): +def test_ventilation_slidingwindow(baseline_form: model_generator.VirusFormData): baseline_form.ventilation_type = 'natural_ventilation' baseline_form.windows_duration = 10 baseline_form.windows_frequency = 120 @@ -74,7 +75,7 @@ def test_ventilation_slidingwindow(baseline_form: model_generator.FormData): assert ventilation == baseline_vent -def test_ventilation_hingedwindow(baseline_form: model_generator.FormData): +def test_ventilation_hingedwindow(baseline_form: model_generator.VirusFormData): baseline_form.ventilation_type = 'natural_ventilation' baseline_form.windows_duration = 10 baseline_form.windows_frequency = 120 @@ -104,7 +105,7 @@ def test_ventilation_hingedwindow(baseline_form: model_generator.FormData): assert ventilation == baseline_vent -def test_ventilation_mechanical(baseline_form: model_generator.FormData): +def test_ventilation_mechanical(baseline_form: model_generator.VirusFormData): room = models.Room(volume=75, inside_temp=models.PiecewiseConstant((0, 24), (293,))) mech = models.HVACMechanical( active=models.PeriodicInterval(period=120, duration=120), @@ -119,7 +120,7 @@ def test_ventilation_mechanical(baseline_form: model_generator.FormData): np.array([baseline_form.ventilation().air_exchange(room, t) for t in ts])) -def test_ventilation_airchanges(baseline_form: model_generator.FormData): +def test_ventilation_airchanges(baseline_form: model_generator.VirusFormData): room = models.Room(75, inside_temp=models.PiecewiseConstant((0, 24), (293,))) airchange = models.AirChange( active=models.PeriodicInterval(period=120, duration=120), @@ -134,7 +135,7 @@ def test_ventilation_airchanges(baseline_form: model_generator.FormData): np.array([baseline_form.ventilation().air_exchange(room, t) for t in ts])) -def test_ventilation_window_hepa(baseline_form: model_generator.FormData): +def test_ventilation_window_hepa(baseline_form: model_generator.VirusFormData): baseline_form.ventilation_type = 'natural_ventilation' baseline_form.windows_duration = 10 baseline_form.windows_frequency = 120 @@ -177,7 +178,7 @@ def test_ventilation_window_hepa(baseline_form: model_generator.FormData): ] ) def test_infected_less_than_total_people(activity, total_people, infected_people, error, - baseline_form: model_generator.FormData): + baseline_form: model_generator.VirusFormData): baseline_form.activity_type = activity baseline_form.total_people = total_people baseline_form.infected_people = infected_people @@ -190,7 +191,7 @@ def present_times(interval: models.Interval) -> models.BoundarySequence_t: return interval.present_times -def test_infected_present_intervals(baseline_form: model_generator.FormData): +def test_infected_present_intervals(baseline_form: model_generator.VirusFormData): baseline_form.infected_dont_have_breaks_with_exposed = False baseline_form.exposed_coffee_duration = 15 baseline_form.exposed_coffee_break_option = 'coffee_break_2' @@ -204,7 +205,7 @@ def test_infected_present_intervals(baseline_form: model_generator.FormData): assert present_times(baseline_form.infected_present_interval()) == correct -def test_exposed_present_intervals(baseline_form: model_generator.FormData): +def test_exposed_present_intervals(baseline_form: model_generator.VirusFormData): baseline_form.exposed_coffee_duration = 15 baseline_form.exposed_coffee_break_option = 'coffee_break_2' baseline_form.exposed_start = minutes_since_midnight(9 * 60) @@ -215,7 +216,7 @@ def test_exposed_present_intervals(baseline_form: model_generator.FormData): assert present_times(baseline_form.exposed_present_interval()) == correct -def test_present_intervals_common_breaks(baseline_form: model_generator.FormData): +def test_present_intervals_common_breaks(baseline_form: model_generator.VirusFormData): 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' @@ -231,7 +232,7 @@ def test_present_intervals_common_breaks(baseline_form: model_generator.FormData assert present_times(baseline_form.infected_present_interval()) == correct_infected -def test_present_intervals_split_breaks(baseline_form: model_generator.FormData): +def test_present_intervals_split_breaks(baseline_form: model_generator.VirusFormData): 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' @@ -247,7 +248,7 @@ def test_present_intervals_split_breaks(baseline_form: model_generator.FormData) assert present_times(baseline_form.infected_present_interval()) == correct_infected -def test_exposed_present_intervals_starting_with_lunch(baseline_form: model_generator.FormData): +def test_exposed_present_intervals_starting_with_lunch(baseline_form: model_generator.VirusFormData): 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_finish = minutes_since_midnight(18 * 60) @@ -256,7 +257,7 @@ def test_exposed_present_intervals_starting_with_lunch(baseline_form: model_gene assert present_times(baseline_form.exposed_present_interval()) == correct -def test_exposed_present_intervals_ending_with_lunch(baseline_form: model_generator.FormData): +def test_exposed_present_intervals_ending_with_lunch(baseline_form: model_generator.VirusFormData): 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) @@ -265,7 +266,7 @@ def test_exposed_present_intervals_ending_with_lunch(baseline_form: model_genera assert present_times(baseline_form.exposed_present_interval()) == correct -def test_exposed_present_lunch_end_before_beginning(baseline_form: model_generator.FormData): +def test_exposed_present_lunch_end_before_beginning(baseline_form: model_generator.VirusFormData): baseline_form.exposed_coffee_break_option = 'coffee_break_0' baseline_form.exposed_lunch_start = minutes_since_midnight(14 * 60) baseline_form.exposed_lunch_finish = minutes_since_midnight(13 * 60) @@ -282,7 +283,7 @@ def test_exposed_present_lunch_end_before_beginning(baseline_form: model_generat [9, 20], # lunch_finish after the presence finishing ], ) -def test_exposed_presence_lunch_break(baseline_form: model_generator.FormData, exposed_lunch_start, exposed_lunch_finish): +def test_exposed_presence_lunch_break(baseline_form: model_generator.VirusFormData, exposed_lunch_start, exposed_lunch_finish): baseline_form.exposed_lunch_start = minutes_since_midnight(exposed_lunch_start * 60) baseline_form.exposed_lunch_finish = minutes_since_midnight(exposed_lunch_finish * 60) with pytest.raises(ValueError, match='exposed lunch break must be within presence times.'): @@ -298,14 +299,14 @@ def test_exposed_presence_lunch_break(baseline_form: model_generator.FormData, e [9, 20], # lunch_finish after the presence finishing ], ) -def test_infected_presence_lunch_break(baseline_form: model_generator.FormData, infected_lunch_start, infected_lunch_finish): +def test_infected_presence_lunch_break(baseline_form: model_generator.VirusFormData, infected_lunch_start, infected_lunch_finish): baseline_form.infected_lunch_start = minutes_since_midnight(infected_lunch_start * 60) baseline_form.infected_lunch_finish = minutes_since_midnight(infected_lunch_finish * 60) with pytest.raises(ValueError, match='infected lunch break must be within presence times.'): baseline_form.validate() -def test_exposed_breaks_length(baseline_form: model_generator.FormData): +def test_exposed_breaks_length(baseline_form: model_generator.VirusFormData): baseline_form.exposed_coffee_break_option = 'coffee_break_4' baseline_form.exposed_coffee_duration = 30 baseline_form.exposed_start = minutes_since_midnight(10 * 60) @@ -315,7 +316,7 @@ def test_exposed_breaks_length(baseline_form: model_generator.FormData): baseline_form.validate() -def test_infected_breaks_length(baseline_form: model_generator.FormData): +def test_infected_breaks_length(baseline_form: model_generator.VirusFormData): baseline_form.infected_start = minutes_since_midnight(9 * 60) baseline_form.infected_finish = minutes_since_midnight(12 * 60) baseline_form.infected_lunch_start = minutes_since_midnight(10 * 60) @@ -327,7 +328,7 @@ def test_infected_breaks_length(baseline_form: model_generator.FormData): @pytest.fixture -def coffee_break_between_1045_and_1115(baseline_form: model_generator.FormData): +def coffee_break_between_1045_and_1115(baseline_form: model_generator.VirusFormData): baseline_form.exposed_coffee_break_option = 'coffee_break_1' baseline_form.exposed_coffee_duration = 30 baseline_form.exposed_start = minutes_since_midnight(10 * 60) @@ -385,7 +386,7 @@ def assert_boundaries(interval, boundaries_in_time_string_form): @pytest.fixture -def breaks_every_25_mins_for_20_mins(baseline_form: model_generator.FormData): +def breaks_every_25_mins_for_20_mins(baseline_form: model_generator.VirusFormData): baseline_form.exposed_coffee_break_option = 'coffee_break_4' baseline_form.exposed_coffee_duration = 20 baseline_form.exposed_start = time2mins("10:00") @@ -430,7 +431,7 @@ def test_present_only_during_second_break(breaks_every_25_mins_for_20_mins): assert_boundaries(interval, []) -def test_valid_no_lunch(baseline_form: model_generator.FormData): +def test_valid_no_lunch(baseline_form: model_generator.VirusFormData): # Check that it is valid to have a 0 length lunch if no lunch is selected. baseline_form.exposed_lunch_option = False baseline_form.exposed_lunch_start = minutes_since_midnight(0) @@ -438,7 +439,7 @@ def test_valid_no_lunch(baseline_form: model_generator.FormData): assert baseline_form.validate() is None -def test_no_breaks(baseline_form: model_generator.FormData): +def test_no_breaks(baseline_form: model_generator.VirusFormData): # Check that the times are correct in the absence of breaks. baseline_form.infected_dont_have_breaks_with_exposed = False baseline_form.exposed_lunch_option = False @@ -453,7 +454,7 @@ def test_no_breaks(baseline_form: model_generator.FormData): assert present_times(baseline_form.infected_present_interval()) == infected_correct -def test_coffee_lunch_breaks(baseline_form: model_generator.FormData): +def test_coffee_lunch_breaks(baseline_form: model_generator.VirusFormData): baseline_form.exposed_coffee_duration = 30 baseline_form.exposed_coffee_break_option = 'coffee_break_4' baseline_form.exposed_start = minutes_since_midnight(9 * 60) @@ -465,7 +466,7 @@ def test_coffee_lunch_breaks(baseline_form: model_generator.FormData): 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): +def test_coffee_lunch_breaks_unbalance(baseline_form: model_generator.VirusFormData): baseline_form.exposed_coffee_duration = 30 baseline_form.exposed_coffee_break_option = 'coffee_break_2' baseline_form.exposed_start = minutes_since_midnight(9 * 60) @@ -476,7 +477,7 @@ def test_coffee_lunch_breaks_unbalance(baseline_form: model_generator.FormData): np.testing.assert_allclose(present_times(baseline_form.exposed_present_interval()), correct, rtol=1e-14) -def test_coffee_breaks(baseline_form: model_generator.FormData): +def test_coffee_breaks(baseline_form: model_generator.VirusFormData): baseline_form.exposed_coffee_duration = 10 baseline_form.exposed_coffee_break_option = 'coffee_break_4' baseline_form.exposed_start = minutes_since_midnight(9 * 60) @@ -489,24 +490,24 @@ def test_coffee_breaks(baseline_form: model_generator.FormData): def test_key_validation(baseline_form_data): baseline_form_data['activity_type'] = 'invalid key' with pytest.raises(ValueError): - model_generator.FormData.from_dict(baseline_form_data) + model_generator.VirusFormData.from_dict(baseline_form_data) def test_key_validation_natural_ventilation_window_type_na(baseline_form_data): baseline_form_data['ventilation_type'] = 'natural_ventilation' baseline_form_data['window_type'] = 'not-applicable' with pytest.raises(ValueError, match='window_type cannot be \'not-applicable\''): - model_generator.FormData.from_dict(baseline_form_data) + model_generator.VirusFormData.from_dict(baseline_form_data) def test_key_validation_natural_ventilation_window_opening_regime_na(baseline_form_data): baseline_form_data['ventilation_type'] = 'natural_ventilation' baseline_form_data['window_opening_regime'] = 'not-applicable' with pytest.raises(ValueError, match='window_opening_regime cannot be \'not-applicable\''): - model_generator.FormData.from_dict(baseline_form_data) + model_generator.VirusFormData.from_dict(baseline_form_data) -def test_natural_ventilation_window_opening_periodically(baseline_form: model_generator.FormData): +def test_natural_ventilation_window_opening_periodically(baseline_form: model_generator.VirusFormData): baseline_form.window_opening_regime = 'windows_open_periodically' baseline_form.windows_duration = 20 baseline_form.windows_frequency = 10 @@ -518,20 +519,20 @@ def test_key_validation_mech_ventilation_type_na(baseline_form_data): baseline_form_data['ventilation_type'] = 'mechanical_ventilation' baseline_form_data['mechanical_ventilation_type'] = 'not-applicable' with pytest.raises(ValueError, match='mechanical_ventilation_type cannot be \'not-applicable\''): - model_generator.FormData.from_dict(baseline_form_data) + model_generator.VirusFormData.from_dict(baseline_form_data) def test_key_validation_event_month(baseline_form_data): baseline_form_data['event_month'] = 'invalid month' with pytest.raises(ValueError, match='invalid month is not a valid value for event_month'): - model_generator.FormData.from_dict(baseline_form_data) + model_generator.VirusFormData.from_dict(baseline_form_data) def test_default_types(): - # Validate that FormData._DEFAULTS are complete and of the correct type. + # Validate that VirusFormData._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)} - for field, value in model_generator.FormData._DEFAULTS.items(): + fields = {field.name: field for field in dataclasses.fields(model_generator.VirusFormData)} + for field, value in model_generator.VirusFormData._DEFAULTS.items(): if field not in fields: raise ValueError(f"Unmatched default {field}") @@ -540,17 +541,17 @@ def test_default_types(): # Handle typing.NewType definitions. field_type = field_type.__supertype__ - if value is model_generator.NO_DEFAULT: + if value is NO_DEFAULT: continue - if field in model_generator._CAST_RULES_FORM_ARG_TO_NATIVE: - value = model_generator._CAST_RULES_FORM_ARG_TO_NATIVE[field](value) + if field in _CAST_RULES_FORM_ARG_TO_NATIVE: + value = _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)}') for field in fields.values(): - assert field.name in model_generator.FormData._DEFAULTS, f"No default set for field name {field.name}" + assert field.name in model_generator.VirusFormData._DEFAULTS, f"No default set for field name {field.name}" def test_form_to_dict(baseline_form): @@ -559,7 +560,7 @@ 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'] + baseline_form.exposed_coffee_break_option = model_generator.VirusFormData._DEFAULTS['exposed_coffee_break_option'] assert 'exposed_coffee_break_option' not in baseline_form.to_dict(baseline_form, strip_defaults=True) @@ -577,7 +578,7 @@ def test_form_timezone(baseline_form_data, longitude, latitude, month, expected_ baseline_form_data['location_latitude'] = latitude baseline_form_data['location_longitude'] = longitude baseline_form_data['event_month'] = month - form = model_generator.FormData.from_dict(baseline_form_data) + form = model_generator.VirusFormData.from_dict(baseline_form_data) name, offset = form.tz_name_and_utc_offset() assert name == expected_tz_name assert offset == expected_offset diff --git a/caimira/tests/apps/calculator/test_specific_model_generator.py b/caimira/tests/apps/calculator/test_specific_model_generator.py index e1d68e11..be2ac7dc 100644 --- a/caimira/tests/apps/calculator/test_specific_model_generator.py +++ b/caimira/tests/apps/calculator/test_specific_model_generator.py @@ -13,7 +13,7 @@ [{"exposed_breaks": [], "ifected_breaks": []}, 'Unable to fetch "infected_breaks" key. Got "ifected_breaks".'], ] ) -def test_specific_break_structure(break_input, error, baseline_form: model_generator.FormData): +def test_specific_break_structure(break_input, error, baseline_form: model_generator.VirusFormData): baseline_form.specific_breaks = break_input with pytest.raises(TypeError, match=error): baseline_form.validate() @@ -30,7 +30,7 @@ def test_specific_break_structure(break_input, error, baseline_form: model_gener [[{"start_time": "10:00", "finish_time": "11"}], 'Wrong time format - "HH:MM". Got "11".'], ] ) -def test_specific_population_break_data_structure(population_break_input, error, baseline_form: model_generator.FormData): +def test_specific_population_break_data_structure(population_break_input, error, baseline_form: model_generator.VirusFormData): baseline_form.specific_breaks = {'exposed_breaks': population_break_input, 'infected_breaks': population_break_input} with pytest.raises(TypeError, match=error): baseline_form.validate() @@ -45,7 +45,7 @@ def test_specific_population_break_data_structure(population_break_input, error, [[{"start_time": "08:00", "finish_time": "11:00"}, {"start_time": "14:00", "finish_time": "15:00"}, ], "All breaks should be within the simulation time. Got 08:00."], ] ) -def test_specific_break_time(break_input, error, baseline_form: model_generator.FormData): +def test_specific_break_time(break_input, error, baseline_form: model_generator.VirusFormData): with pytest.raises(ValueError, match=error): baseline_form.generate_specific_break_times(break_input) @@ -63,7 +63,7 @@ def test_specific_break_time(break_input, error, baseline_form: model_generator. [{"physical_activity": "Light activity", "respiratory_activity": [{"type": "Breathing", "percentag": 50}, {"type": "Speaking", "percentage": 50}]}, 'Unable to fetch "percentage" key. Got "percentag".'], ] ) -def test_precise_activity_structure(precise_activity_input, error, baseline_form: model_generator.FormData): +def test_precise_activity_structure(precise_activity_input, error, baseline_form: model_generator.VirusFormData): baseline_form.precise_activity = precise_activity_input with pytest.raises(TypeError, match=error): baseline_form.validate() @@ -78,7 +78,7 @@ def test_precise_activity_structure(precise_activity_input, error, baseline_form [{"physical_activity": "Light activity", "respiratory_activity": [{"type": "Breathing", "percentage": 50}]}, 'The sum of all respiratory activities should be 100. Got 50.'], ] ) -def test_sum_precise_activity(precise_activity_input, error, baseline_form: model_generator.FormData): +def test_sum_precise_activity(precise_activity_input, error, baseline_form: model_generator.VirusFormData): baseline_form.precise_activity = precise_activity_input with pytest.raises(ValueError, match=error): baseline_form.validate() \ No newline at end of file From 7b745f406960ff75f048f0572f427890a849d6b1 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Fri, 17 Nov 2023 11:34:36 +0100 Subject: [PATCH 58/61] added explanative text and tooltip question mark --- caimira/apps/calculator/defaults.py | 4 ++-- caimira/apps/templates/base/calculator.form.html.j2 | 8 ++++++-- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/caimira/apps/calculator/defaults.py b/caimira/apps/calculator/defaults.py index 339a2bed..82f1cf4a 100644 --- a/caimira/apps/calculator/defaults.py +++ b/caimira/apps/calculator/defaults.py @@ -104,8 +104,8 @@ VACCINE_TYPE = ['Ad26.COV2.S_(Janssen)', 'Any_mRNA_-_heterologous', 'AZD1222_(AstraZeneca)', 'AZD1222_(AstraZeneca)_and_any_mRNA_-_heterologous', 'AZD1222_(AstraZeneca)_and_BNT162b2_(Pfizer)', 'BBIBP-CorV_(Beijing_CNBG)', 'BNT162b2_(Pfizer)', 'BNT162b2_(Pfizer)_and_mRNA-1273_(Moderna)', 'CoronaVac_(Sinovac)', 'CoronaVac_(Sinovac)_and_AZD1222_(AstraZeneca)', 'Covishield', 'mRNA-1273_(Moderna)', 'Sputnik_V_(Gamaleya)', 'CoronaVac_(Sinovac)_and_BNT162b2_(Pfizer)'] -VENTILATION_TYPES = {'natural_ventilation', - 'mechanical_ventilation', 'no_ventilation'} +VENTILATION_TYPES = {'natural_ventilation', 'mechanical_ventilation', + 'no_ventilation', 'from_fitting'} VIRUS_TYPES: typing.List[str] = list(config.virus_distributions) VOLUME_TYPES = {'room_volume_explicit', 'room_volume_from_dimensions'} WINDOWS_OPENING_REGIMES = {'windows_open_permanently', diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index a2179502..788a06d2 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -339,7 +339,8 @@ From e1862388a81e8f9896e1c3a79f555d2448f95c83 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 22 Nov 2023 10:15:04 +0100 Subject: [PATCH 59/61] added test for natural and mechanical ventilation fitting algorithm --- .../tests/models/test_fitting_algorithm.py | 101 ++++++++++++++++++ 1 file changed, 101 insertions(+) create mode 100644 caimira/tests/models/test_fitting_algorithm.py diff --git a/caimira/tests/models/test_fitting_algorithm.py b/caimira/tests/models/test_fitting_algorithm.py new file mode 100644 index 00000000..6013e5d7 --- /dev/null +++ b/caimira/tests/models/test_fitting_algorithm.py @@ -0,0 +1,101 @@ +import numpy as np +import numpy.testing as npt +import pytest + +from caimira import models + + +@pytest.mark.parametrize( + "activity_type, ventilation_active, air_exch", [ + ['Seated', [8, 12, 13, 17], [0.25, 2.45, 0.25]], + ['Standing', [8, 10, 11, 12, 17], [1.25, 3.25, 1.45, 0.25]], + ['Light activity', [8, 12, 17], [1.25, 0.25]], + ['Moderate activity', [8, 13, 15, 16, 17], [2.25, 0.25, 3.45, 0.25]], + ['Heavy exercise', [8, 17], [0.25]], + ] +) +def test_fitting_algorithm_custom_ventilation(activity_type, ventilation_active, air_exch): + conc_model = models.CO2ConcentrationModel( + room=models.Room( + volume=75, inside_temp=models.PiecewiseConstant((0., 24.), (293,))), + ventilation=models.CustomVentilation(models.PiecewiseConstant( + tuple(ventilation_active), tuple(air_exch))), + CO2_emitters=models.SimplePopulation( + number=models.IntPiecewiseConstant(transition_times=tuple( + [8, 12, 13, 17]), values=tuple([2, 1, 2])), + presence=None, + activity=models.Activity.types[activity_type] + ), + ) + + times = np.linspace(8, 17, 100) + CO2_concentrations = [ + conc_model.concentration(float(time)) + for time in times + ] + + # Generate CO2DataModel + data_model = models.CO2DataModel( + room_volume=75, + number=models.IntPiecewiseConstant(transition_times=tuple( + [8, 12, 13, 17]), values=tuple([2, 1, 2])), + presence=None, + ventilation_transition_times=tuple(ventilation_active), + times=times, + CO2_concentrations=CO2_concentrations + ) + + fit_parameters = data_model.CO2_fit_params() + exhalation_rate = fit_parameters['exhalation_rate'] + npt.assert_almost_equal( + round(exhalation_rate, 2), conc_model.CO2_emitters.activity.exhalation_rate) + + ventilation_values = fit_parameters['ventilation_values'] + npt.assert_allclose([round(vent, 2) for vent in ventilation_values], air_exch) + + +@pytest.mark.parametrize( + "activity_type, air_exch", [ + ['Seated', 0.25], + ['Standing', 2.45], + ] +) +def test_fitting_algorithm_fixed_ventilation(activity_type, air_exch): + conc_model = models.CO2ConcentrationModel( + room=models.Room( + volume=75, inside_temp=models.PiecewiseConstant((0., 24.), (293,))), + ventilation=models.AirChange(active=models.PeriodicInterval(120, 120), air_exch=air_exch), + CO2_emitters=models.SimplePopulation( + number=models.IntPiecewiseConstant(transition_times=tuple( + [8, 12, 13, 17]), values=tuple([2, 1, 2])), + presence=None, + activity=models.Activity.types[activity_type] + ), + ) + + times = np.linspace(8, 17, 100) + CO2_concentrations = [ + conc_model.concentration(float(time)) + for time in times + ] + + # Generate CO2DataModel + data_model = models.CO2DataModel( + room_volume=75, + number=models.IntPiecewiseConstant(transition_times=tuple( + [8, 12, 13, 17]), values=tuple([2, 1, 2])), + presence=None, + ventilation_transition_times=tuple([8, 17]), + times=times, + CO2_concentrations=CO2_concentrations + ) + + fit_parameters = data_model.CO2_fit_params() + + exhalation_rate = fit_parameters['exhalation_rate'] + npt.assert_almost_equal( + round(exhalation_rate, 2), conc_model.CO2_emitters.activity.exhalation_rate) + + ventilation_values = fit_parameters['ventilation_values'] + npt.assert_almost_equal(round(ventilation_values[0], 2), air_exch) + \ No newline at end of file From 11cbc85fffc6fdf6b7962d9e112970fe535c4dd2 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Wed, 22 Nov 2023 14:45:26 +0100 Subject: [PATCH 60/61] modified UI text for CO2 file upload --- .../apps/templates/base/calculator.form.html.j2 | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2 index 788a06d2..3344183b 100644 --- a/caimira/apps/templates/base/calculator.form.html.j2 +++ b/caimira/apps/templates/base/calculator.form.html.j2 @@ -323,12 +323,18 @@
    -
    Upload an Excel file to preview in HTML Table
    +
    Upload an Excel file:
    Download template
    +
    +

    You may use the provided template and fill in the values.

    +
    + ? +
    +

    - +
    @@ -339,8 +345,9 @@
    Time (HH:MM)ACH value (h⁻¹)
    Time (HH:MM)ACH value (h⁻¹)
    ${transition_times}${val.toPrecision(2)}
    Time (HH:MM)ACH value (h⁻¹)
    ${transition_times}${val.toPrecision( + 2 + )}