import os
from pathlib import Path
from immuneML.environment.EnvironmentSettings import EnvironmentSettings
from immuneML.ml_methods.util.Util import Util as MLUtil
from immuneML.presentation.TemplateParser import TemplateParser
from immuneML.presentation.html.Util import Util
from immuneML.simulation.SimulationState import SimulationState
from immuneML.util.PathBuilder import PathBuilder
from immuneML.util.StringHelper import StringHelper
[docs]
class SimulationHTMLBuilder:
"""
A class that will make a HTML file(s) out of SimulationState object to show what analysis took place in
the SimulationInstruction.
"""
CSS_PATH = EnvironmentSettings.html_templates_path / "css/custom.css"
[docs]
@staticmethod
def build(state: SimulationState) -> str:
"""
Function that builds the HTML files based on the Simulation state.
Arguments:
state: SimulationState object including all details of the Simulation instruction
Returns:
path to the main HTML file (which is located under state.result_path)
"""
base_path = PathBuilder.build(state.result_path / "../HTML_output/")
html_map = SimulationHTMLBuilder.make_html_map(state, base_path)
result_file = base_path / f"Simulation_{state.name}.html"
TemplateParser.parse(template_path=EnvironmentSettings.html_templates_path / "Simulation.html",
template_map=html_map, result_path=result_file)
return result_file
[docs]
@staticmethod
def make_html_map(state: SimulationState, base_path: Path) -> dict:
html_map = {
"css_style": Util.get_css_content(SimulationHTMLBuilder.CSS_PATH),
"name": state.name,
'immuneML_version': MLUtil.get_immuneML_version(),
"full_specs": Util.get_full_specs_path(base_path),
"dataset_name": state.resulting_dataset.name if state.resulting_dataset.name is not None else state.resulting_dataset.identifier,
"dataset_type": StringHelper.camel_case_to_word_string(type(state.resulting_dataset).__name__),
"example_count": state.resulting_dataset.get_example_count(),
"dataset_size": f"{state.resulting_dataset.get_example_count()} {type(state.resulting_dataset).__name__.replace('Dataset', 's').lower()}",
"labels": [{"label_name": label} for label in state.resulting_dataset.get_label_names()],
"formats": [
{
"format_name": format_name,
"dataset_download_link": os.path.relpath(
path=Util.make_downloadable_zip(state.result_path, state.paths[state.resulting_dataset.name][format_name]),
start=base_path)
} for format_name in state.formats
],
"implantings": [Util.to_dict_recursive(implanting, base_path) for implanting in state.simulation.implantings]
}
return html_map