diff --git a/cara/apps/calculator/__init__.py b/cara/apps/calculator/__init__.py
index 17189304..e396ea8c 100644
--- a/cara/apps/calculator/__init__.py
+++ b/cara/apps/calculator/__init__.py
@@ -140,7 +140,6 @@ class StaticModel(BaseRequestHandler):
executor_factory=functools.partial(
concurrent.futures.ThreadPoolExecutor,
self.settings['report_generation_parallelism'],
- self.settings["template_environment"].globals['common_text'],
),
)
report: str = await asyncio.wrap_future(report_task)
@@ -150,7 +149,7 @@ class StaticModel(BaseRequestHandler):
class LandingPage(BaseRequestHandler):
def get(self):
template_environment = self.settings["template_environment"]
- template = self.settings["template_environment"].get_template(
+ template = template_environment.get_template(
"index.html.j2")
report = template.render(
user=self.current_user,
@@ -176,7 +175,7 @@ class AboutPage(BaseRequestHandler):
class CalculatorForm(BaseRequestHandler):
def get(self):
template_environment = self.settings["template_environment"]
- template = self.settings["template_environment"].get_template(
+ template = template_environment.get_template(
"calculator.form.html.j2")
report = template.render(
user=self.current_user,
@@ -203,7 +202,7 @@ class CompressedCalculatorFormInputs(BaseRequestHandler):
class ReadmeHandler(BaseRequestHandler):
def get(self):
template_environment = self.settings["template_environment"]
- template = self.settings['template_environment'].get_template("userguide.html.j2")
+ template = template_environment.get_template("userguide.html.j2")
readme = template.render(
active_page="calculator/user-guide",
user=self.current_user,
diff --git a/cara/apps/calculator/report_generator.py b/cara/apps/calculator/report_generator.py
index 1bbf967d..c06b63ee 100644
--- a/cara/apps/calculator/report_generator.py
+++ b/cara/apps/calculator/report_generator.py
@@ -12,6 +12,7 @@ import jinja2
import numpy as np
from cara import models
+from cara.apps.calculator import markdown_tools
from ... import monte_carlo as mc
from .model_generator import FormData, _DEFAULT_MC_SAMPLE_SIZE
from ... import dataclass_utils
@@ -315,6 +316,9 @@ class ReportGenerator:
loader=self.jinja_loader,
undefined=jinja2.StrictUndefined,
)
+ env.globals['common_text'] = markdown_tools.extract_rendered_markdown_blocks(
+ env.get_template('common_text.md.j2')
+ )
env.filters['non_zero_percentage'] = non_zero_percentage
env.filters['readable_minutes'] = readable_minutes
env.filters['minutes_to_time'] = minutes_to_time
@@ -325,4 +329,4 @@ class ReportGenerator:
def render(self, context: dict) -> str:
template = self._template_environment().get_template("calculator.report.html.j2")
- return template.render(**context)
+ return template.render(**context, text_blocks=template.globals['common_text'])
diff --git a/cara/apps/templates/base/calculator.form.html.j2 b/cara/apps/templates/base/calculator.form.html.j2
index a9403ec1..84b3e987 100644
--- a/cara/apps/templates/base/calculator.form.html.j2
+++ b/cara/apps/templates/base/calculator.form.html.j2
@@ -574,7 +574,7 @@
- {# {{ text_blocks['Disclaimer'] }} #}
+
{{ text_blocks['Disclaimer'] }}
{% block disclaimer %}
-
Disclaimer:
-
-
- CARA is a risk assessment tool developed to model the concentration of viruses in enclosed spaces, in order to inform space-management decisions.
-
-
- CARA models the concentration profile of potential infectious viruses in enclosed spaces with clear and intuitive graphs.
- The user can set a number of parameters, including room volume, exposure time, activity type, mask-wearing and ventilation.
- The report generated indicates how to avoid exceeding critical concentrations and chains of airborne transmission in spaces such as individual offices, meeting rooms and labs.
-
-
- The risk assessment tool simulates the long-range airborne spread SARS-CoV-2 virus in a finite volume, assuming a homogenous mixture, and estimates the risk of COVID-19 airborne transmission therein.
- The results DO NOT include short-range airborne exposure (where the physical distance is a significant factor) nor the other known modes of SARS-CoV-2 transmission.
- Hence, the output from this model is only valid when the other recommended public health & safety instructions are observed, such as adequate physical distancing, good hand hygiene and other barrier measures.
-
-
- The model used is based on scientific publications relating to airborne transmission of infectious diseases, dose-response exposures and aerosol science, as of February 2021.
- It can be used to compare the effectiveness of different airborne-related risk mitigation measures.
-
-
- Note that this model applies a deterministic approach, i.e., it is assumed at least one person is infected and shedding viruses into the simulated volume.
- Nonetheless, it is also important to understand that the absolute risk of infection is uncertain, as it will depend on the probability that someone infected attends the event.
- The model is most useful for comparing the impact and effectiveness of different mitigation measures such as ventilation, filtration, exposure time, physical activity and
- the size of the room, only considering long-range airborne transmission of COVID-19 in indoor settings.
-
-
- This tool is designed to be informative, allowing the user to adapt different settings and model the relative impact on the estimated infection probabilities.
- The objective is to facilitate targeted decision-making and investment through comparisons, rather than a singular determination of absolute risk.
- While the SARS-CoV-2 virus is in circulation among the population, the notion of 'zero risk' or 'completely safe scenario' does not exist.
- Each event modelled is unique, and the results generated therein are only as accurate as the inputs and assumptions.
-
-
- CARA has not undergone review, approval or certification by competent authorities, and as a result, it cannot be considered
- as a fully endorsed and reliable tool, namely in the assessment of potential viral emissions from infected hosts to be modelled.
-
-
+
Disclaimer:
+ {{ text_blocks['Disclaimer'] }}
{% endblock disclaimer %}
- {{ text_blocks['Disclaimer'] }}
+
{{ text_blocks['Disclaimer'] }}
-
- CARA is a risk assessment tool developed to model the concentration of viruses in enclosed spaces, in order to inform space-management decisions.
-
-
- CARA models the concentration profile of virions in enclosed spaces with clear and intuitive graphs.
- The user can set a number of parameters, including room volume, exposure time, activity type, mask-wearing and ventilation.
- The report generated indicates how to avoid exceeding critical concentrations and chains of airborne transmission in spaces such as individual offices, meeting rooms and labs.
-
-
- The risk assessment tool simulates the long-range airborne spread SARS-CoV-2 virus in a finite volume, assuming a homogenous mixture, and estimates the risk of COVID-19 airborne transmission therein.
- The results DO NOT include short-range airborne exposure (where the physical distance is a significant factor) nor the other known modes of SARS-CoV-2 transmission.
- Hence, the output from this model is only valid when the other recommended public health & safety instructions are observed, such as adequate physical distancing, good hand hygiene and other barrier measures.
-
-
- The model used is based on scientific publications relating to airborne transmission of infectious diseases, dose-response exposures and aerosol science, as of February 2021.
- It can be used to compare the effectiveness of different airborne-related risk mitigation measures.
-
-
- Note that this model applies a deterministic approach, i.e., it is assumed at least one person is infected and shedding viruses into the simulated volume.
- Nonetheless, it is also important to understand that the absolute risk of infection is uncertain, as it will depend on the probability that someone infected attends the event.
- The model is most useful for comparing the impact and effectiveness of different mitigation measures such as ventilation, filtration, exposure time, physical activity and
- the size of the room, only considering long-range airborne transmission of COVID-19 in indoor settings.
-
-
- This tool is designed to be informative, allowing the user to adapt different settings and model the relative impact on the estimated infection probabilities.
- The objective is to facilitate targeted decision-making and investment through comparisons, rather than a singular determination of absolute risk.
- While the SARS-CoV-2 virus is in circulation among the population, the notion of 'zero risk' or 'completely safe scenario' does not exist.
- Each event modelled is unique, and the results generated therein are only as accurate as the inputs and assumptions.
-
-
- CARA has not undergone review, approval or certification by competent authorities, and as a result, it cannot be considered
- as a fully endorsed and reliable tool, namely in the assessment of potential viral emissions from infected hosts to be modelled.
-
-
+ CARA is a risk assessment tool developed to model the concentration of viruses in enclosed spaces, in order to inform space-management decisions.
+
+
+ CARA models the concentration profile of virions in enclosed spaces with clear and intuitive graphs.
+ The user can set a number of parameters, including room volume, exposure time, activity type, mask-wearing and ventilation.
+ The report generated indicates how to avoid exceeding critical concentrations and chains of airborne transmission in spaces such as individual offices, meeting rooms and labs.
+
+
+ The risk assessment tool simulates the long-range airborne spread SARS-CoV-2 virus in a finite volume, assuming a homogenous mixture, and estimates the risk of COVID-19 airborne transmission therein.
+ The results DO NOT include short-range airborne exposure (where the physical distance is a significant factor) nor the other known modes of SARS-CoV-2 transmission.
+ Hence, the output from this model is only valid when the other recommended public health & safety instructions are observed, such as adequate physical distancing, good hand hygiene and other barrier measures.
+
+
+ The model used is based on scientific publications relating to airborne transmission of infectious diseases, dose-response exposures and aerosol science, as of February 2021.
+ It can be used to compare the effectiveness of different airborne-related risk mitigation measures.
+
+
+ Note that this model applies a deterministic approach, i.e., it is assumed at least one person is infected and shedding viruses into the simulated volume.
+ Nonetheless, it is also important to understand that the absolute risk of infection is uncertain, as it will depend on the probability that someone infected attends the event.
+ The model is most useful for comparing the impact and effectiveness of different mitigation measures such as ventilation, filtration, exposure time, physical activity and
+ the size of the room, only considering long-range airborne transmission of COVID-19 in indoor settings.
+
+
+ This tool is designed to be informative, allowing the user to adapt different settings and model the relative impact on the estimated infection probabilities.
+ The objective is to facilitate targeted decision-making and investment through comparisons, rather than a singular determination of absolute risk.
+ While the SARS-CoV-2 virus is in circulation among the population, the notion of 'zero risk' or 'completely safe scenario' does not exist.
+ Each event modelled is unique, and the results generated therein are only as accurate as the inputs and assumptions.
+
+
+ CARA has not undergone review, approval or certification by competent authorities, and as a result, it cannot be considered
+ as a fully endorsed and reliable tool, namely in the assessment of potential viral emissions from infected hosts to be modelled.
+
## References