diff --git a/cara/apps/calculator/report_generator.py b/cara/apps/calculator/report_generator.py
index 2f55e3eb..a4d88bd9 100644
--- a/cara/apps/calculator/report_generator.py
+++ b/cara/apps/calculator/report_generator.py
@@ -108,10 +108,15 @@ def calculate_report_data(model: models.ExposureModel):
er = np.array(model.concentration_model.infected.emission_rate_when_present()).mean()
exposed_occupants = model.exposed.number
expected_new_cases = np.array(model.expected_new_cases()).mean()
+ cumulative_doses = np.cumsum([
+ np.array(model.exposure_between_bounds(float(time1), float(time2))).mean()
+ for time1, time2 in zip(times[:-1], times[1:])
+ ])
return {
"times": list(times),
"exposed_presence_intervals": [list(interval) for interval in model.exposed.presence.boundaries()],
+ "cumulative_doses": list(cumulative_doses),
"concentrations": concentrations,
"highest_const": highest_const,
"prob_inf": prob,
@@ -303,11 +308,11 @@ class ReportGenerator:
context['permalink'] = generate_permalink(base_url, self.calculator_prefix, form)
context['calculator_prefix'] = self.calculator_prefix
context['scale_warning'] = {
- 'level': 'yellow-2',
+ 'level': 'yellow-2',
'incidence_rate': 'lower than 25 new cases per 100 000 inhabitants',
- 'onsite_access': 'of about 8000',
+ 'onsite_access': 'of about 8000',
'threshold': ''
- }
+ }
return context
def _template_environment(self) -> jinja2.Environment:
diff --git a/cara/apps/calculator/static/js/report.js b/cara/apps/calculator/static/js/report.js
index b815da2f..36e08e0d 100644
--- a/cara/apps/calculator/static/js/report.js
+++ b/cara/apps/calculator/static/js/report.js
@@ -1,34 +1,40 @@
/* Generate the concentration plot using d3 library. */
-function draw_concentration_plot(svg_id, times, concentrations, exposed_presence_intervals) {
+function draw_concentration_plot(svg_id, times, concentrations, cumulative_doses, exposed_presence_intervals) {
+
var visBoundingBox = d3.select(svg_id)
.node()
.getBoundingClientRect();
var time_format = d3.timeFormat('%H:%M');
- var data = []
- times.map((time, index) => data.push({ 'time': time, 'hour': new Date().setHours(Math.trunc(time), (time - Math.trunc(time)) * 60), 'concentration': concentrations[index] }))
+ var data_for_graphs = {
+ 'concentrations': [],
+ 'cumulative_doses': [],
+ }
+ times.map((time, index) => data_for_graphs.concentrations.push({ 'time': time, 'hour': new Date().setHours(Math.trunc(time), (time - Math.trunc(time)) * 60), 'concentration': concentrations[index]}));
+ times.map((time, index) => data_for_graphs.cumulative_doses.push({ 'time': time, 'hour': new Date().setHours(Math.trunc(time), (time - Math.trunc(time)) * 60), 'concentration': cumulative_doses[index]}));
var vis = d3.select(svg_id),
- width = visBoundingBox.width - 300,
+ width = visBoundingBox.width - 400,
height = visBoundingBox.height,
margins = { top: 30, right: 20, bottom: 50, left: 50 },
// H:M time format for x axis.
- xRange = d3.scaleTime().range([margins.left, width - margins.right]).domain([data[0].hour, data[data.length - 1].hour]),
- xTimeRange = d3.scaleLinear().range([margins.left, width - margins.right]).domain([data[0].time, data[data.length - 1].time]),
+ xRange = d3.scaleTime().range([margins.left, width - margins.right]).domain([data_for_graphs.concentrations[0].hour, data_for_graphs.concentrations[data_for_graphs.concentrations.length - 1].hour]),
+ xTimeRange = d3.scaleLinear().range([margins.left, width - margins.right]).domain([data_for_graphs.concentrations[0].time, data_for_graphs.concentrations[data_for_graphs.concentrations.length - 1].time]),
bisecHour = d3.bisector((d) => { return d.hour; }).left,
yRange = d3.scaleLinear().range([height - margins.bottom, margins.top]).domain([0., Math.max(...concentrations)]),
+ yCumulatedRange = d3.scaleLinear().range([height - margins.bottom, margins.top]).domain([0., Math.max(...cumulative_doses)*1.1]),
xAxis = d3.axisBottom(xRange).tickFormat(d => time_format(d)),
- yAxis = d3.axisLeft(yRange);
-
- // Plot tittle.
- plot_title(vis, width, margins.top, 'Mean concentration of virions');
+ yAxis = d3.axisLeft(yRange).ticks(4),
+ yCumulatedAxis = d3.axisRight(yCumulatedRange).ticks(4);
// Line representing the mean concentration.
- plot_scenario_data(vis, data, xTimeRange, yRange, '#1f77b4');
+ plot_scenario_data(vis, data_for_graphs.concentrations, xTimeRange, yRange, '#1f77b4');
+ // Line representing the cumulative concentration.
+ plot_cumulative_data(vis, data_for_graphs.cumulative_doses, xTimeRange, yCumulatedRange, '#1f77b4');
// X axis.
plot_x_axis(vis, height, width, margins, xAxis, 'Time of day');
@@ -36,6 +42,24 @@ function draw_concentration_plot(svg_id, times, concentrations, exposed_presence
// Y axis
plot_y_axis(vis, height, width, margins, yAxis, 'Mean concentration (virions/m³)')
+ // Y cumulative concentration axis declaration.
+ vis.append('svg:g')
+ .attr('class', 'y axis')
+ .style('font-size', 14)
+ .style("stroke-dasharray", "5 5")
+ .attr('transform', 'translate(' + (width - margins.right) + ',0)')
+ .call(yCumulatedAxis);
+
+ // Y cumulated concentration axis label.
+ vis.append('svg:text')
+ .attr('class', 'y label')
+ .attr('fill', 'black')
+ .attr('transform', 'rotate(-90, 0,' + height + ')')
+ .attr('text-anchor', 'middle')
+ .attr('x', (height + margins.bottom) / 2)
+ .attr('y', 1.71 * width)
+ .text('Mean cumulative dose (virions)');
+
// Area representing the presence of exposed person(s).
exposed_presence_intervals.forEach(b => {
var curveFunc = d3.area()
@@ -44,7 +68,7 @@ function draw_concentration_plot(svg_id, times, concentrations, exposed_presence
.y1(d => yRange(d.concentration));
vis.append('svg:path')
- .attr('d', curveFunc(data.filter(d => {
+ .attr('d', curveFunc(data_for_graphs.concentrations.filter(d => {
return d.time >= b[0] && d.time <= b[1]
})))
.attr('fill', '#1f77b4')
@@ -54,39 +78,56 @@ function draw_concentration_plot(svg_id, times, concentrations, exposed_presence
// Legend for the plot elements - line and area.
var size = 20
vis.append('rect')
- .attr('x', width + size)
+ .attr('x', width + size + 50)
.attr('y', margins.top + size)
.attr('width', 20)
.attr('height', 3)
.style('fill', '#1f77b4');
+ vis.append('line')
+ .attr("x1", width + size + 50)
+ .attr("x2", width + 2 * size + 52)
+ .attr("y1", 3.5 * size)
+ .attr("y2", 3.5 * size)
+ .style("stroke-dasharray", "5 5") //dashed array for line
+ .attr('stroke-width', '2')
+ .style("stroke", '#1f77b4');
+
vis.append('rect')
- .attr('x', width + size)
- .attr('y', 3 * size)
+ .attr('x', width + size + 50)
+ .attr('y', 4 * size)
.attr('width', 20)
.attr('height', 20)
.attr('fill', '#1f77b4')
.attr('fill-opacity', '0.1');
vis.append('text')
- .attr('x', width + 3 * size)
+ .attr('x', width + 3 * size + 50)
.attr('y', margins.top + size)
- .text('Mean concentration')
+ .text('Viral concentration')
.style('font-size', '15px')
.attr('alignment-baseline', 'central');
vis.append('text')
- .attr('x', width + 3 * size)
+ .attr('x', width + 3 * size + 50)
.attr('y', margins.top + 2 * size)
+ .text('Cumulative dose')
+ .style('font-size', '15px')
+ .attr('alignment-baseline', 'central');
+
+ vis.append('text')
+ .attr('x', width + 3 * size + 50)
+ .attr('y', margins.top + 3 * size)
.text('Presence of exposed person(s)')
.style('font-size', '15px')
.attr('alignment-baseline', 'central');
+
// Legend bounding box.
vis.append('rect')
- .attr('width', 275)
- .attr('height', 50)
- .attr('x', width * 1.005)
+ .attr('width', 270)
+ .attr('height', 70)
+ .attr('x', width * 1.1)
.attr('y', margins.top + 5)
.attr('stroke', 'lightgrey')
.attr('stroke-width', '2')
@@ -96,50 +137,80 @@ function draw_concentration_plot(svg_id, times, concentrations, exposed_presence
.attr('fill', 'none');
// Tooltip.
- var focus = vis.append('svg:g')
- .style('display', 'none');
+ var focus = {}, tooltip_rect = {}, tooltip_time = {}, tooltip_concentration = {}, toolBox = {};
+ for (const [concentration, data] of Object.entries(data_for_graphs)) {
- focus.append('circle')
- .attr('r', 3);
+ focus[concentration] = vis.append('svg:g')
+ .style('display', 'none');
- focus.append('rect')
- .attr('fill', 'white')
- .attr('stroke', '#000')
- .attr('width', 80)
- .attr('height', 50)
- .attr('x', 10)
- .attr('y', -22)
- .attr('rx', 4)
- .attr('ry', 4);
+ focus[concentration].append('circle')
+ .attr('r', 3);
- focus.append('text')
- .attr('id', 'tooltip-time')
- .attr('x', 18)
- .attr('y', -2);
+ tooltip_rect[concentration] = focus[concentration].append('rect')
+ .attr('fill', 'white')
+ .attr('stroke', '#000')
+ .attr('width', 85)
+ .attr('height', 50)
+ .attr('x', 10)
+ .attr('y', -22)
+ .attr('rx', 4)
+ .attr('ry', 4);
- focus.append('text')
- .attr('id', 'tooltip-concentration')
- .attr('x', 18)
- .attr('y', 18);
+ tooltip_time[concentration] = focus[concentration].append('text')
+ .attr('id', 'tooltip-time')
+ .attr('x', 18)
+ .attr('y', -2);
- vis.append('rect')
- .attr('fill', 'none')
- .attr('pointer-events', 'all')
- .attr('width', width - margins.right)
- .attr('height', height)
- .on('mouseover', () => { focus.style('display', null); })
- .on('mouseout', () => { focus.style('display', 'none'); })
- .on('mousemove', mousemove);
+ tooltip_concentration[concentration] = focus[concentration].append('text')
+ .attr('id', 'tooltip-concentration')
+ .attr('x', 18)
+ .attr('y', 18);
+
+ toolBox[concentration] = vis.append('rect')
+ .attr('fill', 'none')
+ .attr('pointer-events', 'all')
+ .attr('width', width - margins.right)
+ .attr('height', height)
+ .on('mouseover', () => { for (const [concentration, data] of Object.entries(focus)) focus[concentration].style('display', null); })
+ .on('mouseout', () => { for (const [concentration, data] of Object.entries(focus)) focus[concentration].style('display', 'none'); })
+ .on('mousemove', mousemove);
+ }
function mousemove() {
+ for (const [scenario, data] of Object.entries(data_for_graphs)) {
+ if (d3.pointer(event)[0] < width / 2) {
+ tooltip_rect[scenario].attr('x', 10)
+ tooltip_time[scenario].attr('x', 18)
+ tooltip_concentration[scenario].attr('x', 18);
+ }
+ else {
+ tooltip_rect[scenario].attr('x', -90)
+ tooltip_time[scenario].attr('x', -82)
+ tooltip_concentration[scenario].attr('x', -82)
+ }
+ }
+ // Concentration line
var x0 = xRange.invert(d3.pointer(event, this)[0]),
- i = bisecHour(data, x0, 1),
- d0 = data[i - 1],
- d1 = data[i],
- d = x0 - d0.hour > d1.hour - x0 ? d1 : d0;
- focus.attr('transform', 'translate(' + xRange(d.hour) + ',' + yRange(d.concentration) + ')');
- focus.select('#tooltip-time').text('x = ' + time_format(d.hour));
- focus.select('#tooltip-concentration').text('y = ' + d.concentration.toFixed(2));
+ i = bisecHour(data_for_graphs.concentrations, x0, 1),
+ d0 = data_for_graphs.concentrations[i - 1],
+ d1 = data_for_graphs.concentrations[i];
+ if (d1) {
+ var d = x0 - d0.hour > d1.hour - x0 ? d1 : d0;
+ focus.concentrations.attr('transform', 'translate(' + xRange(d.hour) + ',' + yRange(d.concentration) + ')');
+ focus.concentrations.select('#tooltip-time').text('x = ' + time_format(d.hour));
+ focus.concentrations.select('#tooltip-concentration').text('y = ' + d.concentration.toFixed(2));
+ }
+ // Cumulative line
+ var x0 = xRange.invert(d3.pointer(event, this)[0]),
+ i = bisecHour(data_for_graphs.cumulative_doses, x0, 1),
+ d0 = data_for_graphs.cumulative_doses[i - 1],
+ d1 = data_for_graphs.cumulative_doses[i];
+ if (d1 && d1.concentration) {
+ var d = x0 - d0.hour > d1.hour - x0 ? d1 : d0;
+ focus.cumulative_doses.attr('transform', 'translate(' + xRange(d.hour) + ',' + yCumulatedRange(d.concentration) + ')');
+ focus.cumulative_doses.select('#tooltip-time').text('x = ' + time_format(d.hour));
+ focus.cumulative_doses.select('#tooltip-concentration').text('y = ' + d.concentration.toFixed(2));
+ }
}
}
@@ -155,7 +226,7 @@ function draw_alternative_scenarios_plot(svg_id, width, height, alternative_scen
// Variable for the highest concentration for all the scenarios
var highest_concentration = 0.
- var data_for_scenarios = {}
+ var data_for_graphs = {}
for (scenario in alternative_scenarios) {
scenario_concentrations = alternative_scenarios[scenario].concentrations
@@ -165,11 +236,11 @@ function draw_alternative_scenarios_plot(svg_id, width, height, alternative_scen
times.map((time, index) => data.push({ 'time': time, 'hour': new Date().setHours(Math.trunc(time), (time - Math.trunc(time)) * 60), 'concentration': scenario_concentrations[index] }))
// Add data into lines dictionary
- data_for_scenarios[scenario] = data
+ data_for_graphs[scenario] = data
}
// We need one scenario to get the time range
- var first_scenario = Object.values(data_for_scenarios)[0]
+ var first_scenario = Object.values(data_for_graphs)[0]
var vis = d3.select(svg_id),
width = width,
@@ -185,12 +256,9 @@ function draw_alternative_scenarios_plot(svg_id, width, height, alternative_scen
xAxis = d3.axisBottom(xRange).tickFormat(d => time_format(d)),
yAxis = d3.axisLeft(yRange);
- // Plot title.
- plot_title(vis, width, margins.top, 'Mean concentration of virions');
-
// Line representing the mean concentration for each scenario.
- for (const [scenario_name, data] of Object.entries(data_for_scenarios)) {
- var scenario_index = Object.keys(data_for_scenarios).indexOf(scenario_name)
+ for (const [scenario_name, data] of Object.entries(data_for_graphs)) {
+ var scenario_index = Object.keys(data_for_graphs).indexOf(scenario_name)
// Line representing the mean concentration.
plot_scenario_data(vis, data, xTimeRange, yRange, colors[scenario_index])
@@ -235,7 +303,7 @@ function draw_alternative_scenarios_plot(svg_id, width, height, alternative_scen
// Legend bounding box.
vis.append('rect')
.attr('width', 275)
- .attr('height', 25 * (Object.keys(data_for_scenarios).length))
+ .attr('height', 25 * (Object.keys(data_for_graphs).length))
.attr('x', width * 1.005)
.attr('y', margins.top + 5)
.attr('stroke', 'lightgrey')
@@ -249,22 +317,11 @@ function draw_alternative_scenarios_plot(svg_id, width, height, alternative_scen
// Functions used to build the plots' components
-function plot_title(vis, width, margin_top, title) {
- vis.append('svg:foreignObject')
- .attr('width', width)
- .attr('height', margin_top)
- .attr('fill', 'none')
- .append('xhtml:div')
- .style('text-align', 'center')
- .html(title);
-
- return vis;
-}
-
function plot_x_axis(vis, height, width, margins, xAxis, label) {
// X axis declaration
vis.append('svg:g')
.attr('class', 'x axis')
+ .style('font-size', 14)
.attr('transform', 'translate(0,' + (height - margins.bottom) + ')')
.call(xAxis);
@@ -284,6 +341,7 @@ function plot_y_axis(vis, height, width, margins, yAxis, label) {
// Y axis declaration.
vis.append('svg:g')
.attr('class', 'y axis')
+ .style('font-size', 14)
.attr('transform', 'translate(' + margins.left + ',0)')
.call(yAxis);
@@ -314,5 +372,22 @@ function plot_scenario_data(vis, data, xTimeRange, yRange, line_color) {
.attr('stroke-width', 2)
.attr('fill', 'none');
+ return vis;
+}
+
+function plot_cumulative_data(vis, data, xTimeRange, yCumulativeRange, line_color) {
+ var lineCumulativeFunc = d3.line()
+ .defined(d => !isNaN(d.concentration))
+ .x(d => xTimeRange(d.time))
+ .y(d => yCumulativeRange(d.concentration))
+ .curve(d3.curveBasis);
+
+ vis.append('svg:path')
+ .attr('d', lineCumulativeFunc(data))
+ .attr('stroke', line_color)
+ .attr('stroke-width', 2)
+ .style("stroke-dasharray", "5 5")
+ .attr('fill', 'none');
+
return vis;
}
\ No newline at end of file
diff --git a/cara/apps/calculator/templates/base/calculator.report.html.j2 b/cara/apps/calculator/templates/base/calculator.report.html.j2
index db13e693..e609c0b5 100644
--- a/cara/apps/calculator/templates/base/calculator.report.html.j2
+++ b/cara/apps/calculator/templates/base/calculator.report.html.j2
@@ -85,12 +85,13 @@
{% endblock report_summary_footnote %}
* The results are based on the parameters and assumptions published in the CERN Open Report CERN-OPEN-2021-004.
-
+
diff --git a/cara/models.py b/cara/models.py
index b7885768..c3f716d2 100644
--- a/cara/models.py
+++ b/cara/models.py
@@ -102,7 +102,6 @@ class Interval:
return True
return False
-
@dataclass(frozen=True)
class SpecificInterval(Interval):
#: A sequence of times (start, stop), in hours, that the infected person
@@ -922,9 +921,33 @@ class ExposureModel:
#: The fraction of viruses actually deposited in the respiratory tract
fraction_deposited: _VectorisedFloat = 0.6
+ def _normed_exposure_between_bounds(self, time1: float, time2: float) -> _VectorisedFloat:
+ """The number of virions per meter^3 between any two times, normalized
+ by the emission rate of the infected population"""
+ exposure = 0.
+ for start, stop in self.exposed.presence.boundaries():
+ if stop < time1:
+ continue
+ elif start > time2:
+ break
+ elif start <= time1 and time2<= stop:
+ exposure += self.concentration_model.normed_integrated_concentration(time1, time2)
+ elif start <= time1 and stop < time2:
+ exposure += self.concentration_model.normed_integrated_concentration(time1, stop)
+ elif time1 < start and time2 <= stop:
+ exposure += self.concentration_model.normed_integrated_concentration(start, time2)
+ elif time1 <= start and stop < time2:
+ exposure += self.concentration_model.normed_integrated_concentration(start, stop)
+ return exposure
+
+ def exposure_between_bounds(self, time1: float, time2: float) -> _VectorisedFloat:
+ """The number of virions per meter^3 between any two times."""
+ return (self._normed_exposure_between_bounds(time1, time2) *
+ self.concentration_model.infected.emission_rate_when_present())
+
def _normed_exposure(self) -> _VectorisedFloat:
"""
- The number of virus per meter^3, normalized by the emission rate
+ The number of virions per meter^3, normalized by the emission rate
of the infected population.
"""
normed_exposure = 0.0
@@ -935,7 +958,7 @@ class ExposureModel:
return normed_exposure * self.repeats
def exposure(self) -> _VectorisedFloat:
- """The number of virus per meter^3."""
+ """The number of virions per meter^3."""
return (self._normed_exposure() *
self.concentration_model.infected.emission_rate_when_present())
diff --git a/cara/tests/models/test_exposure_model.py b/cara/tests/models/test_exposure_model.py
index ac82dae3..2ce0e8e2 100644
--- a/cara/tests/models/test_exposure_model.py
+++ b/cara/tests/models/test_exposure_model.py
@@ -55,7 +55,6 @@ populations = [
),
]
-
def known_concentrations(func):
dummy_room = models.Room(50, 0.5)
dummy_ventilation = models._VentilationBase()
@@ -73,21 +72,21 @@ def known_concentrations(func):
@pytest.mark.parametrize(
- "population, cm, f_dep, expected_exposure, expected_probability", [
- [populations[1], known_concentrations(lambda t: 36.), 1.,
- np.array([432, 432]), np.array([99.6803184113, 99.5181053773])],
+ "population, cm, f_dep, expected_exposure, expected_probability",[
+ [populations[1], known_concentrations(lambda t: 36.), 1.,
+ np.array([432, 432]), np.array([99.6803184113, 99.5181053773])],
- [populations[2], known_concentrations(lambda t: 36.), 1.,
- np.array([432, 432]), np.array([97.4574432074, 98.3493482895])],
+ [populations[2], known_concentrations(lambda t: 36.), 1.,
+ np.array([432, 432]), np.array([97.4574432074, 98.3493482895])],
- [populations[0], known_concentrations(lambda t: np.array([36., 72.])), 1.,
- np.array([432, 864]), np.array([98.3493482895, 99.9727534893])],
+ [populations[0], known_concentrations(lambda t: np.array([36., 72.])), 1.,
+ np.array([432, 864]), np.array([98.3493482895, 99.9727534893])],
- [populations[1], known_concentrations(lambda t: np.array([36., 72.])), 1.,
- np.array([432, 864]), np.array([99.6803184113, 99.9976777757])],
+ [populations[1], known_concentrations(lambda t: np.array([36., 72.])), 1.,
+ np.array([432, 864]), np.array([99.6803184113, 99.9976777757])],
- [populations[0], known_concentrations(lambda t: 72.), np.array([0.5, 1.]),
- 864, np.array([98.3493482895, 99.9727534893])],
+ [populations[0], known_concentrations(lambda t: 72.), np.array([0.5, 1.]),
+ 864, np.array([98.3493482895, 99.9727534893])],
])
def test_exposure_model_ndarray(population, cm, f_dep,
expected_exposure, expected_probability):