Source code for immuneML.presentation.html.MLApplicationHTMLBuilder

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.util.PathBuilder import PathBuilder
from immuneML.util.StringHelper import StringHelper
from immuneML.workflows.instructions.ml_model_application.MLApplicationState import MLApplicationState




class MLApplicationHTMLBuilder:
    CSS_PATH = EnvironmentSettings.html_templates_path / "css/custom.css"



    @staticmethod
    def build(state: MLApplicationState = None) -> str:
        base_path = PathBuilder.build(state.path / "../HTML_output/")
        html_map = MLApplicationHTMLBuilder.make_html_map(state, base_path)
        result_file = base_path / "MLModelTraining_{state.name}.html"
        TemplateParser.parse(template_path=EnvironmentSettings.html_templates_path / "MLApplication.html",
                             template_map=html_map, result_path=result_file)
        return result_file




    @staticmethod
    def make_html_map(state: MLApplicationState, base_path: Path) -> dict:
        return {**Util.make_dataset_html_map(state.dataset), **{
            "css_style": Util.get_css_content(MLApplicationHTMLBuilder.CSS_PATH),
            "hp_setting": state.hp_setting.get_key(),
            'immuneML_version': MLUtil.get_immuneML_version(),
            "full_specs": Util.get_full_specs_path(base_path),
            "logfile": Util.get_logfile_path(base_path),
            "label": state.label_config.get_labels_by_name()[0],
            "labels": [{"name": label_name, "values": str(state.label_config.get_label_values(label_name))[1:-1]}
                       for label_name in state.label_config.get_labels_by_name()],
            "predictions": Util.get_table_string_from_csv(state.predictions_path),
            "predictions_download_link": os.path.relpath(state.predictions_path, base_path),
            "show_metrics": state.metrics_path is not None,
            "metrics": Util.get_table_string_from_csv(state.metrics_path) if state.metrics_path is not None else None,
            "metrics_download_link": os.path.relpath(state.metrics_path, base_path) if state.metrics_path is not None else None
        }}