diff --git a/.gitignore b/.gitignore index f0ccc32..76e81f3 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,9 @@ .venv/ +.vscode/ __pycache__/ *.py[cod] +*.egg-info/ +.DS_Store +dist/ +build/ +*.egg diff --git a/app.py b/app.py deleted file mode 100644 index 650c4f4..0000000 --- a/app.py +++ /dev/null @@ -1,291 +0,0 @@ -import os -import yaml -import streamlit as st -import inspect - -from utils.model_loader import discover_models, load_model_from_file -from utils.parameter_loader import load_model_params, flatten_dict -from utils.section_renderer import render_sections -from utils.parameter_ui import render_parameters_with_indent, reset_parameters_to_defaults -from utils.excel_model_runner import ( - load_excel_params_defaults_with_computed, - run_excel_driven_model, - get_scenario_headers -) - -# DIRECTORY & CONFIG -base_dir = os.path.dirname(os.path.abspath(__file__)) - -with open(os.path.join(base_dir, "config/app.yaml")) as f: - app_config = yaml.safe_load(f) - -with open(os.path.join(base_dir, "config/paths.yaml")) as f: - path_config = yaml.safe_load(f) - - -# UI STYLES -def load_css(file_path: str): - if os.path.exists(file_path): - with open(file_path) as f: - st.markdown(f"", unsafe_allow_html=True) - - -load_css(os.path.join(base_dir, "styles/sidebar.css")) - -# MODEL SELECTION -st.sidebar.header("Simulation Controls") - -selected_path = os.path.join(base_dir, path_config["model_paths"]["selected_path"]) -default_custom_path = os.path.join(base_dir, path_config["model_paths"]["custom_path"]) - -user_custom_path = st.sidebar.text_input( - "Custom Models Folder", - value=default_custom_path -) - -selected_models = discover_models(selected_path) -custom_models = discover_models(user_custom_path) - -model_options = {} -model_options["Excel Driven Model"] = "__EXCEL_DRIVEN__" -model_options.update({name: file for name, file in selected_models.items()}) -model_options.update({f"Custom: {name}": file for name, file in custom_models.items()}) - -if not model_options: - st.sidebar.warning("No valid model files found.") - st.stop() - -selected_label = st.sidebar.selectbox( - "Select Model", - list(model_options.keys()) -) - -selected_model_file = model_options[selected_label] - -# MODEL CHANGE RESET -model_key = ( - "__EXCEL_DRIVEN__" - if selected_model_file == "__EXCEL_DRIVEN__" - else os.path.basename(selected_model_file) -) - -if "active_model_key" not in st.session_state: - st.session_state.active_model_key = model_key - st.session_state.params = {} - -elif st.session_state.active_model_key != model_key: - st.session_state.active_model_key = model_key - st.session_state.params = {} - -params = st.session_state.params -label_overrides = {} - -# PARAMETER INPUTS -st.sidebar.subheader("Input Parameters") - -# EXCEL-DRIVEN MODEL -if selected_model_file == "__EXCEL_DRIVEN__": - - uploaded_excel_model = st.sidebar.file_uploader( - "Upload Excel model file (.xlsx)", - type=["xlsx"], - key="excel_model_uploader" - ) - - if uploaded_excel_model: - - # reset params if Excel file changes - if ( - "excel_active_name" not in st.session_state - or st.session_state.excel_active_name != uploaded_excel_model.name - ): - st.session_state.excel_active_name = uploaded_excel_model.name - st.session_state.params = {} - - params = st.session_state.params - - # Load the defaults - editable_defaults, _ = load_excel_params_defaults_with_computed( - uploaded_excel_model, - sheet_name=None, - start_row=3 - ) - - # Load Headers - current_headers = get_scenario_headers(uploaded_excel_model) - - - # RESET CALLBACK - def handle_reset_excel(): - # 1. Reset Parameters - reset_parameters_to_defaults(editable_defaults, params, uploaded_excel_model.name) - # 2. Reset Header Labels - if current_headers: - for col_letter, default_text in current_headers.items(): - st.session_state[f"label_override_{col_letter}"] = default_text - - - # Display Button with Callback - st.sidebar.button("Reset Parameters", on_click=handle_reset_excel) - - # Outcome Headers (Column B-E) - if current_headers: - with st.sidebar.expander("Output Scenario Headers", expanded=False): - st.caption("Rename the output headers (B, C, D, E)") - - for col_letter in sorted(current_headers.keys()): - default_text = current_headers[col_letter] - widget_key = f"label_override_{col_letter}" - - # Robust Widget Logic - if widget_key in st.session_state: - new_text = st.text_input( - f"Column {col_letter} Label", - key=widget_key - ) - else: - new_text = st.text_input( - f"Column {col_letter} Label", - value=default_text, - key=widget_key - ) - label_overrides[col_letter] = new_text - - # Render Main Parameters - render_parameters_with_indent( - editable_defaults, - params, - model_id=uploaded_excel_model.name - ) - - else: - st.sidebar.info("Upload an Excel model file to edit parameters.") - -# PYTHON MODEL -else: - param_source = st.sidebar.radio( - "Parameter Source", - ["Model Default (YAML)", "Excel (.xlsx)", "YAML (.yaml)"], - horizontal=True - ) - - uploaded_excel = None - uploaded_yaml = None - - if param_source == "Excel (.xlsx)": - uploaded_excel = st.sidebar.file_uploader("Upload Excel parameter file", type=["xlsx"]) - elif param_source == "YAML (.yaml)": - uploaded_yaml = st.sidebar.file_uploader("Upload YAML parameter file", type=["yaml", "yml"]) - - # PARAMETER SOURCE RESET LOGIC - param_identity = ( - param_source, - uploaded_excel.name if uploaded_excel else None, - uploaded_yaml.name if uploaded_yaml else None, - ) - - if "active_param_identity" not in st.session_state: - st.session_state.active_param_identity = param_identity - st.session_state.params = {} - elif st.session_state.active_param_identity != param_identity: - st.session_state.active_param_identity = param_identity - st.session_state.params = {} - - params = st.session_state.params - - if param_source == "YAML (.yaml)" and uploaded_yaml: - raw = yaml.safe_load(uploaded_yaml) or {} - model_defaults = flatten_dict(raw) - else: - model_defaults = load_model_params( - selected_model_file, - uploaded_excel=uploaded_excel - ) - - # Load Python Model Module to check for Labels - model_module = load_model_from_file(selected_model_file) - # Check for SCENARIO_LABELS constant in the python file - current_headers = getattr(model_module, "SCENARIO_LABELS", None) - - if model_defaults: - # Define Python Model Reset Callback - def handle_reset_python(): - # 1. Reset Parameters - reset_parameters_to_defaults(model_defaults, params, model_key) - # 2. Reset Header Labels - if current_headers: - for key, default_text in current_headers.items(): - # We use a unique key format for python models to avoid conflicts - st.session_state[f"py_label_{model_key}_{key}"] = default_text - - - st.sidebar.button("Reset Parameters", on_click=handle_reset_python) - - # SCENARIO LABELS (PYTHON) - if current_headers: - with st.sidebar.expander("Output Scenario Headers", expanded=False): - st.caption("Rename the output headers") - - for key, default_text in current_headers.items(): - widget_key = f"py_label_{model_key}_{key}" - - if widget_key in st.session_state: - new_val = st.text_input(f"Label for '{default_text}'", key=widget_key) - else: - new_val = st.text_input(f"Label for '{default_text}'", value=default_text, key=widget_key) - - label_overrides[key] = new_val - - render_parameters_with_indent( - model_defaults, - params, - model_id=model_key - ) - else: - st.sidebar.info("No default parameters defined for this model.") - -# RUN SIMULATION -if st.sidebar.button("Run Simulation"): - - # EXCEL-DRIVEN MODEL RUN - if selected_model_file == "__EXCEL_DRIVEN__": - - uploaded_excel_model = st.session_state.get("excel_model_uploader") - - if not uploaded_excel_model: - st.error("Please upload an Excel model file first.") - st.stop() - - with st.spinner(f"Running Excel-driven model: {uploaded_excel_model.name}..."): - - results = run_excel_driven_model( - excel_file=uploaded_excel_model, - filename=uploaded_excel_model.name, - params=params, - sheet_name=None, - label_overrides=label_overrides - ) - - st.title(results.get("model_title", "Excel Driven Model")) - st.write(results.get("model_description", "")) - - render_sections(results["sections"]) - - # PYTHON MODEL RUN - else: - with st.spinner(f"Running {selected_label}..."): - # Load module again (or reuse) - model_module = load_model_from_file(selected_model_file) - - st.title(getattr(model_module, "model_title", app_config["title"])) - st.write(getattr(model_module, "model_description", app_config["description"])) - - # Check if run_model accepts label_overrides - sig = inspect.signature(model_module.run_model) - if "label_overrides" in sig.parameters: - results = model_module.run_model(params, label_overrides=label_overrides) - else: - results = model_module.run_model(params) - - sections = model_module.build_sections(results) - render_sections(sections) diff --git a/config/app.yaml b/config/app.yaml deleted file mode 100644 index 79c87bd..0000000 --- a/config/app.yaml +++ /dev/null @@ -1,2 +0,0 @@ -title: "TB Isolation Cost Calculator" -description: "Streamlit-based simulation tool for tuberculosis (TB) isolation scenarios." diff --git a/config/global_defaults.yaml b/config/global_defaults.yaml deleted file mode 100644 index 3050cab..0000000 --- a/config/global_defaults.yaml +++ /dev/null @@ -1,3 +0,0 @@ -Global Settings: - Decimal precision: 28 - UI theme: "dark" diff --git a/config/paths.yaml b/config/paths.yaml deleted file mode 100644 index 341f437..0000000 --- a/config/paths.yaml +++ /dev/null @@ -1,3 +0,0 @@ -model_paths: - selected_path: "models" - custom_path: "custom_models" diff --git a/models/measles_outbreak.py b/models/measles_outbreak.py deleted file mode 100644 index 4992c0d..0000000 --- a/models/measles_outbreak.py +++ /dev/null @@ -1,132 +0,0 @@ -from decimal import Decimal, ROUND_HALF_EVEN, getcontext -import pandas as pd - -""" -Measles outbreak simulation -""" - -model_title = "Measles Outbreak Cost Estimation" -model_description = "Estimates hospitalization, tracing, and productivity costs for measles outbreaks." - -SCENARIO_LABELS = { - "22_cases": "22 Cases", - "100_cases": "100 Cases", - "803_cases": "803 Cases" -} - - -def run_model(params, label_overrides: dict = None): - getcontext().prec = 28 - ONE = Decimal("1") - CENT = Decimal("0.01") - - if label_overrides is None: - label_overrides = {} - - lbl_22 = label_overrides.get("22_cases", SCENARIO_LABELS["22_cases"]) - lbl_100 = label_overrides.get("100_cases", SCENARIO_LABELS["100_cases"]) - lbl_803 = label_overrides.get("803_cases", SCENARIO_LABELS["803_cases"]) - - def q2(x: Decimal) -> Decimal: - """ - Conditional rounding: - - If absolute value > 10, round to whole number (0 decimal places). - - Otherwise, round to 2 decimal places. - """ - if abs(x) > 10: - return x.quantize(ONE, rounding=ROUND_HALF_EVEN) - return x.quantize(CENT, rounding=ROUND_HALF_EVEN) - - def getp(default, *names): - """ - Helper that searches for alternative parameter labels. - Returns Decimal. - """ - for n in names: - if n in params and params[n] != "": - try: - return Decimal(str(params[n])) - except: - pass - return Decimal(str(default)) - - # extract parameters - cost_hosp = getp(0, "Cost of measles hospitalization") - prop_hosp = getp(0, "Proportion of cases hospitalized") - - missed_ratio = getp(1.0, "Proportion of quarantine days that would be a missed day of work") - wage_worker = getp(0, "Hourly wage of worker (hourly_wage_worker)", "Hourly wage for worker") - - wage_tracer = getp(0, "Hourly wage for contract tracer") - hrs_tracing = getp(0, "Hours of contact tracing per contact") - - contacts = getp(0, "Number of contacts per case") - vacc_rate = getp(0, "Vaccination rate in community") - quarantine = int(getp(21, "Length of quarantine (days)")) - - # core calculations - - # hospitalizations - hosp_22 = q2(22 * prop_hosp * cost_hosp) - hosp_100 = q2(100 * prop_hosp * cost_hosp) - hosp_803 = q2(803 * prop_hosp * cost_hosp) - - # lost productivity - lost_22 = q2( - 22 * contacts * (1 - vacc_rate) * quarantine * - missed_ratio * wage_worker - ) - lost_100 = q2( - 100 * contacts * (1 - vacc_rate) * quarantine * - missed_ratio * wage_worker - ) - lost_803 = q2( - 803 * contacts * (1 - vacc_rate) * quarantine * - missed_ratio * wage_worker - ) - - # contact tracing cost - trace_22 = q2(22 * contacts * hrs_tracing * wage_tracer) - trace_100 = q2(100 * contacts * hrs_tracing * wage_tracer) - trace_803 = q2(803 * contacts * hrs_tracing * wage_tracer) - - # totals - total_22 = q2(hosp_22 + lost_22 + trace_22) - total_100 = q2(hosp_100 + lost_100 + trace_100) - total_803 = q2(hosp_803 + lost_803 + trace_803) - - # dataframe - df_costs = pd.DataFrame({ - "Cost Type": [ - "Hospitalization", - "Lost productivity", - "Contact tracing", - "TOTAL" - ], - lbl_22: [ - hosp_22, lost_22, trace_22, total_22 - ], - lbl_100: [ - hosp_100, lost_100, trace_100, total_100 - ], - lbl_803: [ - hosp_803, lost_803, trace_803, total_803 - ] - }) - - return { - "df_costs": df_costs - } - - -# ui -def build_sections(results): - df_costs = results["df_costs"] - - sections = [ - { - "title": "Measles Outbreak Costs", - "content": [df_costs] - } - ] - return sections diff --git a/models/tb_isolation.py b/models/tb_isolation.py deleted file mode 100644 index 85d581a..0000000 --- a/models/tb_isolation.py +++ /dev/null @@ -1,160 +0,0 @@ -from decimal import Decimal, ROUND_HALF_EVEN, getcontext -import pandas as pd - -""" -TB Isolation simulation. -""" - -model_title = "TB Isolation Cost Calculator" -model_description = "Streamlit-based simulation tool comparing 14-day and 5-day isolation scenarios." - -SCENARIO_LABELS = { - "14_day": "14-day Isolation", - "5_day": "5-day Isolation" -} - - -def run_model(params: dict, label_overrides: dict = None): - getcontext().prec = 28 - ONE = Decimal("1") - CENT = Decimal("0.01") - - if label_overrides is None: - label_overrides = {} - - lbl_14 = label_overrides.get("14_day", SCENARIO_LABELS["14_day"]) - lbl_5 = label_overrides.get("5_day", SCENARIO_LABELS["5_day"]) - - def q2(x: Decimal) -> Decimal: - """ - Conditional rounding: - - If absolute value > 10, round to whole number (0 decimal places). - - Otherwise, round to 2 decimal places. - """ - if abs(x) > 10: - return x.quantize(ONE, rounding=ROUND_HALF_EVEN) - return x.quantize(CENT, rounding=ROUND_HALF_EVEN) - - def q2n(x: Decimal) -> Decimal: - """Quantize numbers (counts/probabilities) to 2 dp.""" - return x.quantize(CENT, rounding=ROUND_HALF_EVEN) - - def getp(default, *names) -> Decimal: - normalized_params = {k.lower(): v for k, v in params.items()} - - for n in names: - n_lower = n.lower() - - if n_lower in normalized_params and normalized_params[n_lower] != "": - return Decimal(str(normalized_params[n_lower])) - - for key, val in normalized_params.items(): - if f"({n_lower})" in key and val != "": - return Decimal(str(val)) - return Decimal(str(default)) - - # parameter extraction - contacts_per_case = getp(0, "Number of contacts for each released TB case") - prob_latent_if_14day = getp(0, "Probability that contact develops latent TB if 14-day isolation") - infectiousness_multiplier = getp(1.5, "Multiplier for infectiousness with 5-day vs. 14-day isolation") - workday_ratio = getp(0.714, "Ratio of workdays to total days") - - # probabilities of progression - prob_latent_to_active_2yr = getp(0, "prob_latent_to_active_2yr", "First 2 years") - prob_latent_to_active_lifetime = getp(0, "prob_latent_to_active_lifetime", "Rest of lifetime") - - # secondary infection costs - cost_latent = getp(0, "cost_latent", "Cost of latent TB infection") - cost_active = getp(0, "cost_active", "Cost of active TB infection") - - # isolation scenario parameters - isolation_type = int(getp(3, "isolation_type", "Isolation type (1=hospital,2=motel,3=home)")) - daily_hosp_cost = getp(0, "isolation_cost", "Daily isolation cost") - direct_med_cost_day = getp(0, "Direct medical cost of a day of isolation") # Often used for hospital stay - - cost_motel_room = getp(0, "Cost of motel room per day") - hourly_wage_nurse = getp(0, "Hourly wage for nurse") - time_nurse_checkin = getp(0, "Time for nurse to check in w/ pt in motel or home (hrs)") - hourly_wage_worker = getp(0, "Hourly wage for worker") - - discount_rate = getp(0, "discount_rate", "Discount rate") - remaining_years = int(getp(40, "remaining_years", "Remaining years of life")) - - # determine daily isolation cost based on isolation type - if isolation_type == 1: - daily_cost = direct_med_cost_day if direct_med_cost_day > 0 else daily_hosp_cost - elif isolation_type == 2: - daily_cost = cost_motel_room + (hourly_wage_nurse * time_nurse_checkin) - else: - daily_cost = (hourly_wage_nurse * time_nurse_checkin) - - # core calculations - latent_14_day = q2n(contacts_per_case * prob_latent_if_14day) - latent_5_day = q2n(latent_14_day * infectiousness_multiplier) - - # progression math - active_14_day = q2n( - latent_14_day * prob_latent_to_active_2yr - + latent_14_day * (ONE - prob_latent_to_active_2yr) * prob_latent_to_active_lifetime - ) - active_5_day = q2n( - latent_5_day * prob_latent_to_active_2yr - + latent_5_day * (ONE - prob_latent_to_active_2yr) * prob_latent_to_active_lifetime - ) - - # outcomes dataframe - df_infections = pd.DataFrame({ - "Outcome": ["Latent TB infections", "Active TB disease"], - lbl_14: [latent_14_day, active_14_day], - lbl_5: [latent_5_day, active_5_day], - }) - - # costs - direct_cost_14_day = q2(daily_cost * Decimal(14)) - direct_cost_5_day = q2(daily_cost * Decimal(5)) - - # productivity loss - productivity_loss_14_day = q2(Decimal(14) * workday_ratio * hourly_wage_worker * Decimal(8)) - productivity_loss_5_day = q2(Decimal(5) * workday_ratio * hourly_wage_worker * Decimal(8)) - - # discounted secondary tb costs - base = ONE + discount_rate - discounted_2yr = (prob_latent_to_active_2yr / Decimal(2)) / (base ** 1) + ( - prob_latent_to_active_2yr / Decimal(2)) / (base ** 2) - - discounted_lifetime = sum( - (prob_latent_to_active_lifetime / Decimal(remaining_years)) / (base ** y) - for y in range(3, remaining_years + 1) - ) - - sec_cost_per_latent = q2(cost_latent + cost_active * (discounted_2yr + discounted_lifetime)) - - secondary_cost_14_day = q2(latent_14_day * sec_cost_per_latent) - secondary_cost_5_day = q2(latent_5_day * sec_cost_per_latent) - - total_14_day = q2(direct_cost_14_day + productivity_loss_14_day + secondary_cost_14_day) - total_5_day = q2(direct_cost_5_day + productivity_loss_5_day + secondary_cost_5_day) - - # cost dataframe - df_costs = pd.DataFrame({ - "Cost Type": [ - "Direct cost of isolation", - "Lost productivity for index case", - "Cost of secondary infections", - "Total cost", - ], - lbl_14: [direct_cost_14_day, productivity_loss_14_day, secondary_cost_14_day, total_14_day], - lbl_5: [direct_cost_5_day, productivity_loss_5_day, secondary_cost_5_day, total_5_day], - }) - - return { - "df_infections": df_infections, - "df_costs": df_costs, - } - - -def build_sections(results): - return [ - {"title": "Number of Secondary Infections", "content": [results["df_infections"]]}, - {"title": "Costs", "content": [results["df_costs"]]}, - ] diff --git a/pyproject.toml b/pyproject.toml index 95140ff..d504d4e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -6,11 +6,16 @@ dependencies = [ "streamlit>=1.55.0", "pandas>=2.3.0", "numpy>=2.4.0", - "pyyaml>=6.0.0", "openpyxl>=3.1.0", + "pydantic[email]>=2.12.5", + "ruamel-yaml>=0.19.1", ] [dependency-groups] dev = [ "ruff>=0.15.6", + "pytest>=8.0.0", ] + +[tool.pytest.ini_options] +pythonpath = ["src"] diff --git a/Measles Outbreak.xlsx b/sample/Measles Outbreak.xlsx similarity index 100% rename from Measles Outbreak.xlsx rename to sample/Measles Outbreak.xlsx diff --git a/TB Isolation.xlsx b/sample/TB Isolation.xlsx similarity index 100% rename from TB Isolation.xlsx rename to sample/TB Isolation.xlsx diff --git a/sample/~$TB Isolation.xlsx b/sample/~$TB Isolation.xlsx new file mode 100644 index 0000000..5e40a09 Binary files /dev/null and b/sample/~$TB Isolation.xlsx differ diff --git a/src/epicc/__main__.py b/src/epicc/__main__.py new file mode 100644 index 0000000..e678b8f --- /dev/null +++ b/src/epicc/__main__.py @@ -0,0 +1,232 @@ +import importlib.resources +from typing import Any + +import streamlit as st + +from epicc.config import CONFIG +from epicc.formats import VALID_PARAMETER_SUFFIXES +from epicc.model.base import BaseSimulationModel +from epicc.utils.excel_model_runner import ( + get_scenario_headers, + load_excel_params_defaults_with_computed, + run_excel_driven_model, +) +from epicc.utils.model_loader import get_built_in_models +from epicc.utils.parameter_loader import load_model_params +from epicc.utils.parameter_ui import ( + render_parameters_with_indent, + reset_parameters_to_defaults, +) +from epicc.utils.section_renderer import render_sections + + +def _load_styles() -> None: + with importlib.resources.files("epicc").joinpath("web/sidebar.css").open("rb") as f: + css_content = f.read().decode("utf-8") + st.markdown(f"", unsafe_allow_html=True) + + +def _sync_active_model(model_key: str) -> dict[str, Any]: + active_model_key = st.session_state.get("active_model_key") + if active_model_key != model_key: + st.session_state.active_model_key = model_key + st.session_state.params = {} + + if "params" not in st.session_state: + st.session_state.params = {} + + return st.session_state.params + + +def _render_excel_parameter_inputs( + params: dict[str, Any], +) -> tuple[dict[str, Any], dict[str, str]]: + label_overrides: dict[str, str] = {} + + uploaded_excel_model = st.sidebar.file_uploader( + "Upload Excel model file (.xlsx)", type=["xlsx"], key="excel_model_uploader" + ) + if not uploaded_excel_model: + st.sidebar.info("Upload an Excel model file to edit parameters.") + return params, label_overrides + + uploaded_excel_name = uploaded_excel_model.name + if st.session_state.get("excel_active_name") != uploaded_excel_name: + st.session_state.excel_active_name = uploaded_excel_name + st.session_state.params = {} + params = st.session_state.params + + editable_defaults, _ = load_excel_params_defaults_with_computed( + uploaded_excel_model, sheet_name=None, start_row=3 + ) + current_headers = get_scenario_headers(uploaded_excel_model) + + def handle_reset_excel() -> None: + reset_parameters_to_defaults(editable_defaults, params, uploaded_excel_name) + for col_letter, default_text in current_headers.items(): + st.session_state[f"label_override_{col_letter}"] = default_text + + st.sidebar.button("Reset Parameters", on_click=handle_reset_excel) + + if current_headers: + with st.sidebar.expander("Output Scenario Headers", expanded=False): + st.caption("Rename the output headers (B, C, D, E)") + for col_letter in sorted(current_headers.keys()): + default_text = current_headers[col_letter] + widget_key = f"label_override_{col_letter}" + if widget_key in st.session_state: + label_overrides[col_letter] = st.text_input( + f"Column {col_letter} Label", key=widget_key + ) + continue + + label_overrides[col_letter] = st.text_input( + f"Column {col_letter} Label", + value=default_text, + key=widget_key, + ) + + render_parameters_with_indent( + editable_defaults, params, model_id=uploaded_excel_name + ) + return params, label_overrides + + +def _render_python_parameter_inputs( + model: BaseSimulationModel, + model_key: str, + params: dict[str, Any], +) -> tuple[dict[str, Any], dict[str, str]]: + label_overrides: dict[str, str] = {} + + sorted_suffixes = sorted(VALID_PARAMETER_SUFFIXES) + uploaded_params = st.sidebar.file_uploader( + "Optional parameter override file", + type=sorted_suffixes, + help="If omitted, model defaults are used.", + ) + + param_identity = ( + "upload" if uploaded_params else "default", + uploaded_params.name if uploaded_params else None, + ) + if st.session_state.get("active_param_identity") != param_identity: + st.session_state.active_param_identity = param_identity + st.session_state.params = {} + params = st.session_state.params + + model_defaults = load_model_params( + model, + uploaded_params=uploaded_params or None, + uploaded_name=uploaded_params.name if uploaded_params else None, + ) + + if not model_defaults: + st.sidebar.info("No default parameters defined for this model.") + return params, label_overrides + + current_headers = model.scenario_labels + + def handle_reset_python() -> None: + reset_parameters_to_defaults(model_defaults, params, model_key) + if not current_headers: + return + + for key, default_text in current_headers.items(): + st.session_state[f"py_label_{model_key}_{key}"] = default_text + + st.sidebar.button("Reset Parameters", on_click=handle_reset_python) + + if current_headers: + with st.sidebar.expander("Output Scenario Headers", expanded=False): + st.caption("Rename the output headers") + for key, default_text in current_headers.items(): + widget_key = f"py_label_{model_key}_{key}" + default_label = str(default_text) + if widget_key in st.session_state: + label_overrides[key] = st.text_input( + f"Label for '{default_label}'", key=widget_key + ) + continue + + label_overrides[key] = st.text_input( + f"Label for '{default_label}'", + value=default_label, + key=widget_key, + ) + + render_parameters_with_indent(model_defaults, params, model_id=model_key) + return params, label_overrides + + +def _run_excel_simulation( + params: dict[str, Any], label_overrides: dict[str, str] +) -> None: + uploaded_excel_model = st.session_state.get("excel_model_uploader") + if not uploaded_excel_model: + st.error("Please upload an Excel model file first.") + st.stop() + + with st.spinner(f"Running Excel-driven model: {uploaded_excel_model.name}..."): + results = run_excel_driven_model( + excel_file=uploaded_excel_model, + filename=uploaded_excel_model.name, + params=params, + sheet_name=None, + label_overrides=label_overrides, + ) + st.title(results.get("model_title", "Excel Driven Model")) + st.write(results.get("model_description", "")) + render_sections(results["sections"]) + + +def _run_python_simulation( + selected_label: str, + model: BaseSimulationModel, + params: dict[str, Any], + label_overrides: dict[str, str], +) -> None: + with st.spinner(f"Running {selected_label}..."): + st.title(model.model_title or CONFIG.app.title) + st.write(model.model_description or CONFIG.app.description) + results = model.run(params, label_overrides=label_overrides) + render_sections(model.build_sections(results)) + + +_load_styles() + +st.sidebar.header("Simulation Controls") + +built_in_models = get_built_in_models() +model_registry: dict[str, BaseSimulationModel] = { + m.human_name(): m for m in built_in_models +} +model_labels = [*model_registry.keys(), "Excel Driven Model"] + +selected_label = st.sidebar.selectbox("Select Model", model_labels, index=0) +is_excel_model = selected_label == "Excel Driven Model" +model_key = selected_label + +params = _sync_active_model(model_key) + +st.sidebar.subheader("Input Parameters") + +if is_excel_model: + params, label_overrides = _render_excel_parameter_inputs(params) +else: + params, label_overrides = _render_python_parameter_inputs( + model_registry[selected_label], + model_key, + params, + ) + +if not st.sidebar.button("Run Simulation"): + st.stop() + +if is_excel_model: + _run_excel_simulation(params, label_overrides) + st.stop() + +_run_python_simulation( + selected_label, model_registry[selected_label], params, label_overrides +) diff --git a/src/epicc/config/__init__.py b/src/epicc/config/__init__.py new file mode 100644 index 0000000..8d96854 --- /dev/null +++ b/src/epicc/config/__init__.py @@ -0,0 +1,26 @@ +""" +TODO: A lot of of this stuff is very restrictive, since the calculator was initially built to be + deployed for handling one single model without being retargetable. In the future, we may want to + make this more flexible, but for now, it's good enough. +""" + +import importlib.resources +from pathlib import Path +from typing import Any, cast + +from epicc.config.schema import Config +from epicc.formats import read_from_format + + +def load_config(name: str) -> tuple[Config, Any]: + # We're okay to cast here because we know the file exists and Traversable is a supertype of + # Path, but mypy doesn't know that. + config_path = cast( + Path, importlib.resources.files("epicc").joinpath(f"config/{name}.yaml") + ) + return read_from_format(config_path, config_path.open("rb"), Config) + + +CONFIG, _ = load_config("default") + +__all__ = ["CONFIG"] diff --git a/src/epicc/config/default.yaml b/src/epicc/config/default.yaml new file mode 100644 index 0000000..e8b9b17 --- /dev/null +++ b/src/epicc/config/default.yaml @@ -0,0 +1,7 @@ +app: + title: TB Isolation Cost Calculator + description: Streamlit-based simulation tool for tuberculosis (TB) isolation scenarios. + +defaults: + decimal_precision: 4 + ui_theme: light diff --git a/src/epicc/config/schema.py b/src/epicc/config/schema.py new file mode 100644 index 0000000..daa1833 --- /dev/null +++ b/src/epicc/config/schema.py @@ -0,0 +1,33 @@ +from typing import Literal + +from pydantic import BaseModel, Field + + +class AppConfig(BaseModel): + title: str = Field(description="Display title of the application.") + + description: str = Field( + description="Brief description of the application and its purpose." + ) + + +class DefaultsConfig(BaseModel): + decimal_precision: int = Field( + default=4, # This used to be 28, not sure why, since that's very large. + ge=1, + le=16, + description="Number of decimal places used in cost and probability calculations.", + ) + + ui_theme: Literal["light", "dark"] = Field( + default="light", + description="UI theme. One of 'light' or 'dark'.", + ) + + +class Config(BaseModel): + app: AppConfig + defaults: DefaultsConfig + + +__all__ = ["Config"] diff --git a/src/epicc/formats/__init__.py b/src/epicc/formats/__init__.py new file mode 100644 index 0000000..b703e9f --- /dev/null +++ b/src/epicc/formats/__init__.py @@ -0,0 +1,99 @@ +""" +Tools for working with parameter files in heterogeneous formats. This module provides a common +interface for reading parameter files into a standardized dictionary format that can be used +by the rest of the application, as well as writing. + +Supported formats are denoted in _LOADERS. + +The rationale behind this abstraction is that, in order to support both effective serialization, +non-technical epidemiologists, and more technical users, we want to allow for multiple file +formats. For example, YAML files are more human-friendly and support nested structures, while +XLSX files are more familiar to epis who already work in spreadsheets and may find it easier to +organize parameters in that format. +""" + +from pathlib import Path +from typing import IO, Any, TypeVar + +from pydantic import BaseModel + +from epicc.formats.base import BaseFormat +from epicc.formats.template import generate_template +from epicc.formats.xlsx import XLSXFormat +from epicc.formats.yaml import YAMLFormat + +M = TypeVar("M", bound=BaseModel) +"""Type variable for Pydantic models used in validation.""" + +_FORMATS: dict[str, type[BaseFormat]] = { + ".yaml": YAMLFormat, + ".yml": YAMLFormat, + ".xlsx": XLSXFormat, +} + +VALID_PARAMETER_SUFFIXES = set(k[1:] for k in _FORMATS.keys()) +"""Set of valid file suffixes for parameter files. These do not begin with a dot.""" + + +def get_format(path: Path | str) -> BaseFormat: + """Return the appropriate reader for the given file path. + + Args: + path: Path to the file to read. If a string, it will be converted to a Path object. + + Returns: + A reader instance appropriate for the file format. + + Raises: + ValueError: If the file format is not supported. + """ + + suffix = Path(path).suffix.lower() # calling constructor to handle `str` case. + reader_class = _FORMATS.get(suffix) + if reader_class is None: + supported = ", ".join(_FORMATS.keys()) + raise ValueError( + f"Unsupported file format '{suffix}'. Supported formats: {supported}" + ) + + return reader_class(path) + + +def opaque_to_typed(data: dict, model: type[M]) -> M: + """ + Validate the given data against a given Pydantic model. + """ + + try: + return model.model_validate(data) + except Exception as e: + raise ValueError(f"Data validation failed: {e}") from e + + +def read_from_format(path: Path | str, data: IO, model: type[M]) -> tuple[M, Any]: + """ + Read parameters from the given file path, and validate. See get_format() and + opaque_to_typed() for details. + + The reason for needing both a path and a data stream is that, in some cases, we + may want to read from a file-like object (e.g. an uploaded file in Streamlit) that + doesn't have a path, but we still need to determine the file format based on the + original file name (which is what the path argument is for). + """ + + reader = get_format(path) + opaque, template = reader.read(data) + + return opaque_to_typed(opaque, model), template + + +__all__ = [ + "VALID_PARAMETER_SUFFIXES", + "BaseFormat", + "YAMLFormat", + "XLSXFormat", + "generate_template", + "get_format", + "opaque_to_typed", + "read_from_format", +] diff --git a/src/epicc/formats/base.py b/src/epicc/formats/base.py new file mode 100644 index 0000000..a0cfb50 --- /dev/null +++ b/src/epicc/formats/base.py @@ -0,0 +1,87 @@ +from typing import Any, IO, Generic, TypeVar +from pathlib import Path +from abc import ABC, abstractmethod + +from pydantic import BaseModel + +T = TypeVar("T") + +class BaseFormat(ABC, Generic[T]): + """ + Abstract base class for parameter file formats. + """ + + def __init__(self, path: Path | str) -> None: + """ + Initialize the reader. + + Parameters: + path: Path to the file to read. If a string, it will be converted to a Path object. + """ + + self.path = Path(path) if isinstance(path, str) else path + + @abstractmethod + def read(self, data: IO) -> tuple[dict[str, Any], T]: + """ + Read a stream and return its contents as a format-agnostic dictionary. + + Args: + data: some data input stream. + + Returns: + A tuple containing: + - Dictionary representation of the file contents. + - Template object of type T. This can be used to preserve formatting or other metadata + when writing back to the file. + + Raises: + FileNotFoundError: If the file does not exist. + ValueError: If the file cannot be parsed. + """ + + ... + + @abstractmethod + def write(self, data: dict[str, Any], template: T | None = None) -> bytes: + """ + Write a agnostic-dictionary dictionary to the appropriate format. + + Args: + data: Dictionary to write. + template: Optional template object to use when writing. This can be used to preserve + formatting or other metadata. + + Returns: + Byte array containing the data in the appropriate format. If the format is text-based, + this is UTF-8 encoded. Otherwise, for binary formats like XLSX, the encoding is format + specified. + + Raises: + ValueError: If the data cannot be serialized in the appropriate format. + """ + + ... + + @abstractmethod + def write_template(self, model: BaseModel) -> bytes: + """ + Generate a fill-in template from a populated model instance. + + The model will have been instantiated with defaults and placeholder + values. Each backend serialises it in a format-appropriate way, + including field descriptions where the format supports them. + + Args: + model: A ``BaseModel`` instance whose values serve as the template + defaults. Field metadata (descriptions, etc.) is available via + ``type(model).model_fields``. + + Returns: + Byte array of the template in the appropriate format. + """ + + ... + + +__all__ = ["BaseFormat"] diff --git a/src/epicc/formats/template.py b/src/epicc/formats/template.py new file mode 100644 index 0000000..aae219c --- /dev/null +++ b/src/epicc/formats/template.py @@ -0,0 +1,93 @@ +"""Utilities for generating fill-in templates from Pydantic models.""" + +from __future__ import annotations + +import types +import typing +from typing import Any, Literal, get_args, get_origin + +from pydantic import BaseModel +from pydantic.fields import FieldInfo +from pydantic_core import PydanticUndefined + +from epicc.formats.base import BaseFormat + + +def generate_template(model_cls: type[BaseModel], fmt: BaseFormat) -> bytes: + """Generate a fill-in template for the given Pydantic model. + + Instantiates ``model_cls`` with defaults and type-appropriate placeholders + for any required fields, then delegates serialisation to ``fmt``. + + Args: + model_cls: The Pydantic ``BaseModel`` subclass to template. + fmt: Any ``BaseFormat`` instance; determines the output format and + how field metadata (descriptions, etc.) is rendered. + + Returns: + Serialised bytes ready to write to a file. + """ + return fmt.write_template(_instantiate(model_cls)) + + +def _instantiate(model_cls: type[BaseModel]) -> BaseModel: + """Recursively build a model instance using defaults and placeholders.""" + kwargs: dict[str, Any] = {} + for name, field_info in model_cls.model_fields.items(): + kwargs[name] = _resolve(field_info) + + return model_cls.model_construct(**kwargs) + + +def _resolve(field_info: FieldInfo) -> Any: + if field_info.default is not PydanticUndefined: + return field_info.default + + if field_info.default_factory is not None: + return field_info.default_factory() + + return _placeholder(field_info.annotation) + + +def _placeholder(annotation: Any) -> Any: + inner = _unwrap_optional(annotation) + + if _is_model(inner): + return _instantiate(inner) + + origin = get_origin(inner) + if origin is Literal: + args = get_args(inner) + return args[0] if args else None + if origin is list: + return [] + if origin is dict: + return {} + if inner is str: + return "" + if inner is int: + return 0 + if inner is float: + return 0.0 + if inner is bool: + return False + return None + + +def _unwrap_optional(annotation: Any) -> Any: + origin = get_origin(annotation) + if origin is types.UnionType or origin is typing.Union: + non_none = [a for a in get_args(annotation) if a is not type(None)] + if len(non_none) == 1: + return non_none[0] + return annotation + + +def _is_model(annotation: Any) -> bool: + try: + return isinstance(annotation, type) and issubclass(annotation, BaseModel) + except TypeError: + return False + + +__all__ = ["generate_template"] diff --git a/src/epicc/formats/xlsx.py b/src/epicc/formats/xlsx.py new file mode 100644 index 0000000..5bca003 --- /dev/null +++ b/src/epicc/formats/xlsx.py @@ -0,0 +1,171 @@ +""" +Generic reader for XLSX parameter files. Expects a spreadsheet with at least two columns: + + - Column A: parameter name + - Column B: parameter value + - Column C (optional): description or notes, ignored during loading +""" + +from io import BytesIO +from typing import IO, Any + +import openpyxl +from openpyxl import Workbook +from pydantic import BaseModel + +from epicc.formats.base import BaseFormat + +# Expected column indices (0-based) +_COL_PARAMETER = 0 +_COL_VALUE = 1 + + +class XLSXFormat(BaseFormat[Workbook]): + """ + Reader for XLSX parameter files. + + Expects a spreadsheet with at least two columns: + - Column A: parameter name + - Column B: parameter value + - Column C (optional): description or notes, ignored during loading + + The first row is treated as a header and skipped. Empty rows are skipped. + Parameter names may use dot notation to represent nested structure, + e.g. "costs.latent" will be parsed into {"costs": {"latent": }}. + """ + + def read(self, data: IO) -> tuple[dict[str, Any], Workbook]: + """ + Read an XLSX file and return its contents as a dictionary. + + Args: + data: Input stream containing the XLSX data. + + Returns: + A tuple containing: + - Dictionary representation of the XLSX contents. + - Workbook object representing the XLSX file, which can be used as a template for writing. + + Raises: + FileNotFoundError: If the file does not exist. + ValueError: If the file cannot be parsed or is missing required columns. + """ + + try: + wb = openpyxl.load_workbook(data, data_only=False) + except Exception as e: + raise ValueError(f"Failed to open XLSX file {self.path}") from e + + ws = wb.active + if not ws or ws.max_column < 2: + raise ValueError( + f"XLSX file {self.path} must have at least 2 columns for parameters and values." + ) + + rows = list(ws.iter_rows(values_only=True)) + + if len(rows) < 2: + raise ValueError( + f"XLSX file {self.path} must have a header row and at least one data row." + ) + + opaque: dict[str, Any] = {} + + for row in rows[1:]: # skip header + if not row or row[_COL_PARAMETER] is None: + continue + + key = str(row[_COL_PARAMETER]).strip() + value = row[_COL_VALUE] if len(row) > _COL_VALUE else None + + if not key: + continue + + _set_nested(opaque, key, value) + + return opaque, wb + + def write(self, data: dict[str, Any], template: Workbook | None = None) -> bytes: + """ + Write a dictionary to an XLSX file. + + Args: + data: Dictionary to write. + template: Optional Workbook object to use as a template for writing. If provided, the + structure and formatting of the template will be preserved as much as possible. + + Returns: + Byte array containing the XLSX data. + """ + + wb = template or Workbook() + ws = wb.active + assert ws is not None, "Workbook must have an active worksheet (bug)." + + # Populate with the provided data piecewise. + for row in ws.iter_rows(): + key_cell = row[_COL_PARAMETER] + val_cell = row[_COL_VALUE] + if key_cell.value in data: + val_cell.value = data[key_cell.value] # type: ignore + + # Awful, but openpyxl is only capable of doing it this way. + output = BytesIO() + wb.save(output) + return output.getvalue() + + def write_template(self, model: BaseModel) -> bytes: + """Write an XLSX template from a model instance. + + Produces a three-column spreadsheet (Parameter, Value, Description). + Nested models are flattened to dot-notation keys. Descriptions come + from ``Field(description=...)`` on each field. + """ + wb = Workbook() + ws = wb.active + assert ws is not None + ws.append(["Parameter", "Value", "Description"]) + for key, value, description in _flatten(model): + ws.append([key, value, description]) + output = BytesIO() + wb.save(output) + return output.getvalue() + + +def _flatten( + model: BaseModel, prefix: str = "" +) -> list[tuple[str, Any, str]]: + """Recursively flatten a model instance to ``[(dot_key, value, description)]``.""" + rows: list[tuple[str, Any, str]] = [] + for name, field_info in type(model).model_fields.items(): + key = f"{prefix}.{name}" if prefix else name + value = getattr(model, name) + description = field_info.description or "" + if isinstance(value, BaseModel): + rows.extend(_flatten(value, prefix=key)) + else: + rows.append((key, value, description)) + return rows + + +def _set_nested(d: dict, key: str, value: Any) -> None: + """ + Set a value in a nested dictionary using dot-notation keys. + + For example, "costs.latent" with value 300.0 produces: + {"costs": {"latent": 300.0}} + + Args: + d: Dictionary to mutate. + key: Dot-separated key string. + value: Value to set. + """ + + parts = key.split(".") + for part in parts[:-1]: + d = d.setdefault(part, {}) + + d[parts[-1]] = value + + +__all__ = ["XLSXFormat"] diff --git a/src/epicc/formats/yaml.py b/src/epicc/formats/yaml.py new file mode 100644 index 0000000..71bb977 --- /dev/null +++ b/src/epicc/formats/yaml.py @@ -0,0 +1,76 @@ +""" +Generic reader for YAML parameter files. Excepts a YAML file with a mapping at the top level, which +is parsed into a dictionary. +""" + +from io import StringIO +from typing import IO, Any + +from pydantic import BaseModel +from ruamel.yaml import YAML + +from epicc.formats.base import BaseFormat + + +class YAMLFormat(BaseFormat[YAML]): + """Reader for YAML parameter files.""" + + def read(self, data: IO) -> tuple[dict[str, Any], YAML]: + """Read a YAML file and return its contents as a dictionary. + + Args: + data: Input stream containing the YAML data. + + Returns: + A tuple containing: + - Dictionary representation of the YAML contents. + - YAML object representing the YAML file, which can be used as a template for writing. + + Raises: + FileNotFoundError: If the file does not exist. + ValueError: If the file cannot be parsed as valid YAML, + or if the top-level structure is not a mapping. + """ + + yaml = YAML(typ="safe") + + try: + data = yaml.load(data) + except Exception as e: + raise ValueError(f"Failed to parse YAML data at {self.path}") from e + + if not isinstance(data, dict): + raise ValueError( + f"Expected a YAML mapping at the top level in {self.path}, got {type(data).__name__}" + ) + + return data, yaml + + def write(self, data: dict[str, Any], template: YAML | None = None) -> bytes: + """Write a dictionary to a YAML file. + + Args: + data: Dictionary to write. + template: Optional YAML object to use as a template when writing. This can be used to preserve + formatting or other metadata. + + Returns: + Byte array containing the YAML data, UTF-8 encoded. + """ + + yaml = template or YAML(typ="safe") + output = StringIO() + yaml.dump(data, output) + return output.getvalue().encode("utf-8") + + def write_template(self, model: BaseModel) -> bytes: + """Write a YAML template from a model instance. + + The model is dumped to a nested mapping; the natural YAML structure + is preserved without flattening. Descriptions are not embedded as + comments (YAML comment support is left to a future enhancement). + """ + return self.write(model.model_dump()) + + +__all__ = ["YAMLFormat"] diff --git a/src/epicc/model/__init__.py b/src/epicc/model/__init__.py new file mode 100644 index 0000000..c6bb181 --- /dev/null +++ b/src/epicc/model/__init__.py @@ -0,0 +1,19 @@ +import importlib.resources +from pathlib import Path +from typing import Any, cast + +from epicc.formats import read_from_format +from epicc.model.schema import Model + + +def load_model(name: str) -> tuple[Model, Any]: + # We're okay to cast here because we know the file exists and Traversable is a supertype of + # Path, but mypy doesn't know that. + config_path = cast( + Path, importlib.resources.files("epicc").joinpath(f"models/{name}.yaml") + ) + + return read_from_format(config_path, config_path.open("rb"), Model) + + +__all__ = ["load_model"] diff --git a/src/epicc/model/base.py b/src/epicc/model/base.py new file mode 100644 index 0000000..b1db798 --- /dev/null +++ b/src/epicc/model/base.py @@ -0,0 +1,43 @@ +from __future__ import annotations + +from abc import ABC, abstractmethod +from typing import Any + + +class BaseSimulationModel(ABC): + """Abstract contract for Python-defined simulation models.""" + + @abstractmethod + def human_name(self) -> str: + """Human-readable name shown in model selection UI.""" + + @property + @abstractmethod + def model_title(self) -> str: + """Page title displayed above simulation output.""" + + @property + @abstractmethod + def model_description(self) -> str: + """Short text describing the simulation.""" + + @property + @abstractmethod + def scenario_labels(self) -> dict[str, str]: + """Default scenario labels exposed for sidebar overrides.""" + + @abstractmethod + def run( + self, + params: dict[str, Any], + label_overrides: dict[str, str] | None = None, + ) -> dict[str, Any]: + """Run the model and return result payload for rendering.""" + + @abstractmethod + def default_params(self) -> dict[str, Any]: + """Return the model's default parameters as a raw (unflattened) dict.""" + + @abstractmethod + def build_sections(self, results: dict[str, Any]) -> list[dict[str, Any]]: + """Transform run results into section payloads for UI rendering.""" diff --git a/src/epicc/model/schema.py b/src/epicc/model/schema.py new file mode 100644 index 0000000..2df20b5 --- /dev/null +++ b/src/epicc/model/schema.py @@ -0,0 +1,78 @@ +from __future__ import annotations + +from typing import Literal, Optional + +from pydantic import BaseModel, EmailStr, Field + + +class Author(BaseModel): + name: str + email: Optional[EmailStr] = None + + +class Metadata(BaseModel): + title: str + description: str + authors: list[Author] = Field(default_factory=list) + introduction: Optional[str] = None + + +class Parameter(BaseModel): + type: Literal["integer", "number", "string", "boolean"] + label: str + description: Optional[str] = None + default: int | float | str | bool + min: Optional[int | float] = None + max: Optional[int | float] = None + unit: Optional[str] = None + references: list[str] = Field(default_factory=list) + + +class Equation(BaseModel): + label: str + unit: Optional[str] = None + output: Optional[Literal["integer", "number"]] = None + compute: str = Field( + ..., + description="Python-evaluable expression referencing parameter/scenario variable names.", + ) + + +class ScenarioVars(BaseModel): + model_config = {"extra": "allow"} # arbitrary vars like n_cases + + +class Scenario(BaseModel): + id: str + label: str + vars: ScenarioVars + + +class TableRow(BaseModel): + label: str + value: str = Field(..., description="Key into the equations dict.") + emphasis: Optional[Literal["strong", "em"]] = None + + +class Table(BaseModel): + scenarios: list[Scenario] = Field(default_factory=list) + rows: list[TableRow] = Field(default_factory=list) + + +class Figure(BaseModel): + title: str + alt_text: Optional[str] = Field(None, alias="alt-text") + py_code: Optional[str] = Field(None, alias="py-code") + + model_config = {"populate_by_name": True} + + +class Model(BaseModel): + metadata: Metadata + parameters: dict[str, Parameter] + equations: dict[str, Equation] + table: Table + figures: list[Figure] = Field(default_factory=list) + + +__all__ = ["Model"] diff --git a/src/epicc/models/measles_outbreak.py b/src/epicc/models/measles_outbreak.py new file mode 100644 index 0000000..e71ac01 --- /dev/null +++ b/src/epicc/models/measles_outbreak.py @@ -0,0 +1,125 @@ +import importlib.resources +from decimal import ROUND_HALF_EVEN, Decimal, getcontext +from typing import Any + +import pandas as pd +from ruamel.yaml import YAML + +from epicc.model.base import BaseSimulationModel + + +class MeaslesOutbreakModel(BaseSimulationModel): + def human_name(self) -> str: + return "Measles Outbreak" + + @property + def model_title(self) -> str: + return "Measles Outbreak Cost Estimation" + + @property + def model_description(self) -> str: + return "Estimates hospitalization, tracing, and productivity costs for measles outbreaks." + + @property + def scenario_labels(self) -> dict[str, str]: + return { + "22_cases": "22 Cases", + "100_cases": "100 Cases", + "803_cases": "803 Cases", + } + + def default_params(self) -> dict[str, Any]: + with ( + importlib.resources.files("epicc.models") + .joinpath("measles_outbreak.yaml") + .open("rb") as f + ): + return dict(YAML().load(f)) + + def run( + self, + params: dict[str, Any], + label_overrides: dict[str, str] | None = None, + ) -> dict[str, Any]: + getcontext().prec = 28 + one = Decimal("1") + cent = Decimal("0.01") + + if label_overrides is None: + label_overrides = {} + + lbl_22 = label_overrides.get("22_cases", self.scenario_labels["22_cases"]) + lbl_100 = label_overrides.get("100_cases", self.scenario_labels["100_cases"]) + lbl_803 = label_overrides.get("803_cases", self.scenario_labels["803_cases"]) + + def q2(x: Decimal) -> Decimal: + if abs(x) > 10: + return x.quantize(one, rounding=ROUND_HALF_EVEN) + return x.quantize(cent, rounding=ROUND_HALF_EVEN) + + def getp(default: float | int, *names: str) -> Decimal: + for n in names: + if n in params and params[n] != "": + try: + return Decimal(str(params[n])) + except Exception: + pass + return Decimal(str(default)) + + cost_hosp = getp(0, "Cost of measles hospitalization") + prop_hosp = getp(0, "Proportion of cases hospitalized") + missed_ratio = getp( + 1.0, + "Proportion of quarantine days that would be a missed day of work", + ) + wage_worker = getp( + 0, + "Hourly wage of worker (hourly_wage_worker)", + "Hourly wage for worker", + ) + wage_tracer = getp(0, "Hourly wage for contract tracer") + hrs_tracing = getp(0, "Hours of contact tracing per contact") + contacts = getp(0, "Number of contacts per case") + vacc_rate = getp(0, "Vaccination rate in community") + quarantine = int(getp(21, "Length of quarantine (days)")) + + hosp_22 = q2(22 * prop_hosp * cost_hosp) + hosp_100 = q2(100 * prop_hosp * cost_hosp) + hosp_803 = q2(803 * prop_hosp * cost_hosp) + + lost_22 = q2( + 22 * contacts * (1 - vacc_rate) * quarantine * missed_ratio * wage_worker + ) + lost_100 = q2( + 100 * contacts * (1 - vacc_rate) * quarantine * missed_ratio * wage_worker + ) + lost_803 = q2( + 803 * contacts * (1 - vacc_rate) * quarantine * missed_ratio * wage_worker + ) + + trace_22 = q2(22 * contacts * hrs_tracing * wage_tracer) + trace_100 = q2(100 * contacts * hrs_tracing * wage_tracer) + trace_803 = q2(803 * contacts * hrs_tracing * wage_tracer) + + total_22 = q2(hosp_22 + lost_22 + trace_22) + total_100 = q2(hosp_100 + lost_100 + trace_100) + total_803 = q2(hosp_803 + lost_803 + trace_803) + + df_costs = pd.DataFrame( + { + "Cost Type": [ + "Hospitalization", + "Lost productivity", + "Contact tracing", + "TOTAL", + ], + lbl_22: [hosp_22, lost_22, trace_22, total_22], + lbl_100: [hosp_100, lost_100, trace_100, total_100], + lbl_803: [hosp_803, lost_803, trace_803, total_803], + } + ) + + return {"df_costs": df_costs} + + def build_sections(self, results: dict[str, Any]) -> list[dict[str, Any]]: + return [{"title": "Measles Outbreak Costs", "content": [results["df_costs"]]}] diff --git a/models/measles_outbreak.yaml b/src/epicc/models/measles_outbreak.yaml similarity index 100% rename from models/measles_outbreak.yaml rename to src/epicc/models/measles_outbreak.yaml diff --git a/src/epicc/models/tb_isolation.py b/src/epicc/models/tb_isolation.py new file mode 100644 index 0000000..3a8f86b --- /dev/null +++ b/src/epicc/models/tb_isolation.py @@ -0,0 +1,215 @@ +import importlib.resources +from decimal import ROUND_HALF_EVEN, Decimal, getcontext +from typing import Any + +import pandas as pd +from ruamel.yaml import YAML + +from epicc.model.base import BaseSimulationModel + + +class TBIsolationModel(BaseSimulationModel): + def human_name(self) -> str: + return "TB Isolation" + + @property + def model_title(self) -> str: + return "TB Isolation Cost Calculator" + + @property + def model_description(self) -> str: + return "Estimates hospitalization, tracing, and productivity costs for TB isolation scenarios." + + @property + def scenario_labels(self) -> dict[str, str]: + return { + "14_day": "14-day Isolation", + "5_day": "5-day Isolation", + } + + def default_params(self) -> dict[str, Any]: + with ( + importlib.resources.files("epicc.models") + .joinpath("tb_isolation.yaml") + .open("rb") as f + ): + return dict(YAML().load(f)) + + def run( + self, + params: dict[str, Any], + label_overrides: dict[str, str] | None = None, + ) -> dict[str, Any]: + getcontext().prec = 28 + one = Decimal("1") + cent = Decimal("0.01") + + if label_overrides is None: + label_overrides = {} + + lbl_14 = label_overrides.get("14_day", self.scenario_labels["14_day"]) + lbl_5 = label_overrides.get("5_day", self.scenario_labels["5_day"]) + + def q2(x: Decimal) -> Decimal: + if abs(x) > 10: + return x.quantize(one, rounding=ROUND_HALF_EVEN) + return x.quantize(cent, rounding=ROUND_HALF_EVEN) + + def q2n(x: Decimal) -> Decimal: + return x.quantize(cent, rounding=ROUND_HALF_EVEN) + + def getp(default: float | int, *names: str) -> Decimal: + normalized_params = {k.lower(): v for k, v in params.items()} + + for n in names: + n_lower = n.lower() + + if n_lower in normalized_params and normalized_params[n_lower] != "": + return Decimal(str(normalized_params[n_lower])) + + for key, val in normalized_params.items(): + if f"({n_lower})" in key and val != "": + return Decimal(str(val)) + return Decimal(str(default)) + + contacts_per_case = getp(0, "Number of contacts for each released TB case") + prob_latent_if_14day = getp( + 0, + "Probability that contact develops latent TB if 14-day isolation", + ) + infectiousness_multiplier = getp( + 1.5, + "Multiplier for infectiousness with 5-day vs. 14-day isolation", + ) + workday_ratio = getp(0.714, "Ratio of workdays to total days") + + prob_latent_to_active_2yr = getp( + 0, "prob_latent_to_active_2yr", "First 2 years" + ) + prob_latent_to_active_lifetime = getp( + 0, + "prob_latent_to_active_lifetime", + "Rest of lifetime", + ) + + cost_latent = getp(0, "cost_latent", "Cost of latent TB infection") + cost_active = getp(0, "cost_active", "Cost of active TB infection") + + isolation_type = int( + getp(3, "isolation_type", "Isolation type (1=hospital,2=motel,3=home)") + ) + daily_hosp_cost = getp(0, "isolation_cost", "Daily isolation cost") + direct_med_cost_day = getp(0, "Direct medical cost of a day of isolation") + + cost_motel_room = getp(0, "Cost of motel room per day") + hourly_wage_nurse = getp(0, "Hourly wage for nurse") + time_nurse_checkin = getp( + 0, "Time for nurse to check in w/ pt in motel or home (hrs)" + ) + hourly_wage_worker = getp(0, "Hourly wage for worker") + + discount_rate = getp(0, "discount_rate", "Discount rate") + remaining_years = int(getp(40, "remaining_years", "Remaining years of life")) + + if isolation_type == 1: + daily_cost = ( + direct_med_cost_day if direct_med_cost_day > 0 else daily_hosp_cost + ) + elif isolation_type == 2: + daily_cost = cost_motel_room + (hourly_wage_nurse * time_nurse_checkin) + else: + daily_cost = hourly_wage_nurse * time_nurse_checkin + + latent_14_day = q2n(contacts_per_case * prob_latent_if_14day) + latent_5_day = q2n(latent_14_day * infectiousness_multiplier) + + active_14_day = q2n( + latent_14_day * prob_latent_to_active_2yr + + latent_14_day + * (one - prob_latent_to_active_2yr) + * prob_latent_to_active_lifetime + ) + active_5_day = q2n( + latent_5_day * prob_latent_to_active_2yr + + latent_5_day + * (one - prob_latent_to_active_2yr) + * prob_latent_to_active_lifetime + ) + + df_infections = pd.DataFrame( + { + "Outcome": ["Latent TB infections", "Active TB disease"], + lbl_14: [latent_14_day, active_14_day], + lbl_5: [latent_5_day, active_5_day], + } + ) + + direct_cost_14_day = q2(daily_cost * Decimal(14)) + direct_cost_5_day = q2(daily_cost * Decimal(5)) + + productivity_loss_14_day = q2( + Decimal(14) * workday_ratio * hourly_wage_worker * Decimal(8) + ) + productivity_loss_5_day = q2( + Decimal(5) * workday_ratio * hourly_wage_worker * Decimal(8) + ) + + base = one + discount_rate + discounted_2yr = (prob_latent_to_active_2yr / Decimal(2)) / (base**1) + ( + (prob_latent_to_active_2yr / Decimal(2)) / (base**2) + ) + discounted_lifetime = sum( + (prob_latent_to_active_lifetime / Decimal(remaining_years)) / (base**y) + for y in range(3, remaining_years + 1) + ) + + sec_cost_per_latent = q2( + cost_latent + cost_active * (discounted_2yr + discounted_lifetime) + ) + + secondary_cost_14_day = q2(latent_14_day * sec_cost_per_latent) + secondary_cost_5_day = q2(latent_5_day * sec_cost_per_latent) + + total_14_day = q2( + direct_cost_14_day + productivity_loss_14_day + secondary_cost_14_day + ) + total_5_day = q2( + direct_cost_5_day + productivity_loss_5_day + secondary_cost_5_day + ) + + df_costs = pd.DataFrame( + { + "Cost Type": [ + "Direct cost of isolation", + "Lost productivity for index case", + "Cost of secondary infections", + "Total cost", + ], + lbl_14: [ + direct_cost_14_day, + productivity_loss_14_day, + secondary_cost_14_day, + total_14_day, + ], + lbl_5: [ + direct_cost_5_day, + productivity_loss_5_day, + secondary_cost_5_day, + total_5_day, + ], + } + ) + + return { + "df_infections": df_infections, + "df_costs": df_costs, + } + + def build_sections(self, results: dict[str, Any]) -> list[dict[str, Any]]: + return [ + { + "title": "Number of Secondary Infections", + "content": [results["df_infections"]], + }, + {"title": "Costs", "content": [results["df_costs"]]}, + ] diff --git a/models/tb_isolation.yaml b/src/epicc/models/tb_isolation.yaml similarity index 100% rename from models/tb_isolation.yaml rename to src/epicc/models/tb_isolation.yaml diff --git a/utils/excel_model_runner.py b/src/epicc/utils/excel_model_runner.py similarity index 88% rename from utils/excel_model_runner.py rename to src/epicc/utils/excel_model_runner.py index 15d7aaf..1e5fdb5 100644 --- a/utils/excel_model_runner.py +++ b/src/epicc/utils/excel_model_runner.py @@ -1,15 +1,16 @@ from __future__ import annotations -import os -import re import ast +import re from dataclasses import dataclass -from typing import Any, Dict, Optional, List, Tuple +from typing import Any, Dict, List, Optional, Tuple import pandas as pd from openpyxl import load_workbook from openpyxl.worksheet.worksheet import Worksheet +from epicc.utils.parameter_loader import flatten_dict + _CELL_REF_RE = re.compile(r"(\$?[A-Z]{1,3}\$?\d+)") _RANGE_REF_RE = re.compile(r"(\$?[A-Z]{1,3}\$?\d+)\s*:\s*(\$?[A-Z]{1,3}\$?\d+)") @@ -173,10 +174,10 @@ def __rtruediv__(self, other): return self._binary_op(other, lambda a, b: b / a if a != 0 else 0.0) def __pow__(self, other): - return self._binary_op(other, lambda a, b: a ** b) + return self._binary_op(other, lambda a, b: a**b) def __rpow__(self, other): - return self._binary_op(other, lambda a, b: b ** a) + return self._binary_op(other, lambda a, b: b**a) def _binary_op(self, other, op): other_val = other.value if isinstance(other, ExcelValue) else other @@ -185,11 +186,17 @@ def _binary_op(self, other, op): other_is_list = isinstance(other_val, list) if self_is_list and other_is_list: - return ExcelValue([op(_to_float(a), _to_float(b)) for a, b in zip(self.value, other_val)]) + return ExcelValue( + [op(_to_float(a), _to_float(b)) for a, b in zip(self.value, other_val)] + ) elif self_is_list: - return ExcelValue([op(_to_float(a), _to_float(other_val)) for a in self.value]) + return ExcelValue( + [op(_to_float(a), _to_float(other_val)) for a in self.value] + ) elif other_is_list: - return ExcelValue([op(_to_float(self.value), _to_float(b)) for b in other_val]) + return ExcelValue( + [op(_to_float(self.value), _to_float(b)) for b in other_val] + ) else: return ExcelValue(op(_to_float(self.value), _to_float(other_val))) @@ -279,12 +286,7 @@ def cell_repl(m: re.Match) -> str: expr = expr.replace("<>", "!=") expr = re.sub(r"(?=!])=(?![<>=])", "==", expr) - - expr = re.sub( - r'(".*?")\s*\+\s*(VAL\(\"[A-Z]+\d+\"\))', - r'\1 + STR(\2)', - expr - ) + expr = re.sub(r'(".*?")\s*\+\s*(VAL\(\"[A-Z]+\d+\"\))', r"\1 + STR(\2)", expr) expr = expr.replace("^", "**") @@ -462,18 +464,6 @@ def VAL(r): return [float(_to_float(v)) for v in out] return float(_to_float(out)) -def flatten_dict(d: dict, level: int = 0) -> Dict[str, Any]: - flat: Dict[str, Any] = {} - for key, value in d.items(): - indented_key = ("\t" * level) + str(key) - - if isinstance(value, dict): - flat[indented_key] = None - flat.update(flatten_dict(value, level + 1)) - else: - flat[indented_key] = value - return flat - def excel_rows_to_nested_dict(rows: List[Tuple[int, str, Any]]) -> dict: root: Dict[str, Any] = {} @@ -490,13 +480,14 @@ def excel_rows_to_nested_dict(rows: List[Tuple[int, str, Any]]) -> dict: parent[name] = value return root + def apply_params_to_workbook( - ws: Worksheet, - params: Dict[str, Any], - name_col: str = "F", - value_col: str = "G", - start_row: int = 3, - overwrite_formulas: bool = True, + ws: Worksheet, + params: Dict[str, Any], + name_col: str = "F", + value_col: str = "G", + start_row: int = 3, + overwrite_formulas: bool = True, ): lookup: Dict[str, Any] = {} for k, v in params.items(): @@ -514,19 +505,25 @@ def apply_params_to_workbook( if not name: continue - if (isinstance(val_cell.value, str) and str(val_cell.value).startswith("=")) and not overwrite_formulas: + if ( + isinstance(val_cell.value, str) and str(val_cell.value).startswith("=") + ) and not overwrite_formulas: continue - if name in lookup and lookup[name] is not None and str(lookup[name]).strip() != "": + if ( + name in lookup + and lookup[name] is not None + and str(lookup[name]).strip() != "" + ): ws[f"{value_col}{r}"].value = lookup[name] def load_excel_params_defaults_with_computed( - excel_file, - sheet_name: Optional[str] = None, - name_col: str = "F", - value_col: str = "G", - start_row: int = 3 + excel_file, + sheet_name: Optional[str] = None, + name_col: str = "F", + value_col: str = "G", + start_row: int = 3, ) -> Tuple[Dict[str, Any], Dict[str, Any]]: wb = load_workbook(excel_file, data_only=False) ws = wb[sheet_name] if sheet_name else wb.active @@ -566,6 +563,7 @@ def load_excel_params_defaults_with_computed( return editable_defaults, computed_defaults + def _find_outcome_header_row(ws: Worksheet) -> Optional[int]: """ Looks for the start of the result table by finding the first @@ -578,7 +576,9 @@ def _find_outcome_header_row(ws: Worksheet) -> Optional[int]: return None -def _iter_outcome_rows(ws: Worksheet, header_row: int, scenario_cols: List[str]) -> List[int]: +def _iter_outcome_rows( + ws: Worksheet, header_row: int, scenario_cols: List[str] +) -> List[int]: rows: List[int] = [] blank_streak = 0 r = header_row + 1 @@ -609,8 +609,9 @@ def _iter_outcome_rows(ws: Worksheet, header_row: int, scenario_cols: List[str]) return rows -def _detect_active_scenario_columns(ws: Worksheet, header_row: int, scenario_cols: List[str], rows: List[int]) -> List[ - str]: +def _detect_active_scenario_columns( + ws: Worksheet, header_row: int, scenario_cols: List[str], rows: List[int] +) -> List[str]: active: List[str] = [] for col in scenario_cols: header = ws[f"{col}{header_row}"].value @@ -626,7 +627,9 @@ def _detect_active_scenario_columns(ws: Worksheet, header_row: int, scenario_col return active -def get_scenario_headers(excel_file, sheet_name: Optional[str] = None) -> Dict[str, str]: +def get_scenario_headers( + excel_file, sheet_name: Optional[str] = None +) -> Dict[str, str]: """ Reads the header row (found by _find_outcome_header_row) and extracts current values for columns B, C, D, E. @@ -651,14 +654,16 @@ def get_scenario_headers(excel_file, sheet_name: Optional[str] = None) -> Dict[s def build_sections_from_excel_outcomes( - ws: Worksheet, - engine: FormulaEngine, - header_row: int, - label_overrides: Dict[str, str] = None + ws: Worksheet, + engine: FormulaEngine, + header_row: int, + label_overrides: Dict[str, str] = None, ) -> List[dict]: scenario_cols_all = _scenario_columns_before_F(ws) outcome_rows = _iter_outcome_rows(ws, header_row, scenario_cols_all) - scenario_cols = _detect_active_scenario_columns(ws, header_row, scenario_cols_all, outcome_rows) + scenario_cols = _detect_active_scenario_columns( + ws, header_row, scenario_cols_all, outcome_rows + ) if label_overrides is None: label_overrides = {} @@ -672,7 +677,9 @@ def build_sections_from_excel_outcomes( col_titles[col] = label_overrides[col].strip() else: val = ws[f"{col}{header_row}"].value - col_titles[col] = str(val).strip() if val is not None and str(val).strip() != "" else col + col_titles[col] = ( + str(val).strip() if val is not None and str(val).strip() != "" else col + ) sections: List[dict] = [] current_title: Optional[str] = None @@ -693,7 +700,9 @@ def build_sections_from_excel_outcomes( if all_blank: if current_title and current_records: - sections.append({"title": current_title, "content": [pd.DataFrame(current_records)]}) + sections.append( + {"title": current_title, "content": [pd.DataFrame(current_records)]} + ) current_records = [] current_title = a_text continue @@ -705,13 +714,16 @@ def build_sections_from_excel_outcomes( current_records.append(rec) if current_title and current_records: - sections.append({"title": current_title, "content": [pd.DataFrame(current_records)]}) + sections.append( + {"title": current_title, "content": [pd.DataFrame(current_records)]} + ) if not sections and current_records: sections = [{"title": "Results", "content": [pd.DataFrame(current_records)]}] return sections + def _is_numberish(v: Any) -> bool: if v is None or v == "": return False @@ -736,7 +748,9 @@ def _cell_display(ws: Worksheet, engine: FormulaEngine, cell_ref: str) -> Any: return str(v).strip() -def build_sections_from_generic_tables(ws: Worksheet, engine: FormulaEngine) -> List[dict]: +def build_sections_from_generic_tables( + ws: Worksheet, engine: FormulaEngine +) -> List[dict]: max_scan_rows = min(ws.max_row, 250) max_scan_cols = _col_to_index("E") @@ -789,10 +803,20 @@ def cell_is_blank(v: Any) -> bool: tables.append((top, left_idx, bottom, right)) if not tables: - return [{ - "title": "Outputs", - "content": [pd.DataFrame([{"Error": "No Outcome found and no output table detected in A–E."}])] - }] + return [ + { + "title": "Outputs", + "content": [ + pd.DataFrame( + [ + { + "Error": "No Outcome found and no output table detected in A–E." + } + ] + ) + ], + } + ] tables.sort(key=lambda t: (t[2] - t[0] + 1) * (t[3] - t[1] + 1), reverse=True) top, left_idx, bottom, right_idx = tables[0] @@ -801,7 +825,11 @@ def cell_is_blank(v: Any) -> bool: headers = [] for c in range(left_idx, right_idx + 1): v = ws[f"{_index_to_col(c)}{header_row}"].value - headers.append(str(v).strip() if v is not None and str(v).strip() != "" else _index_to_col(c)) + headers.append( + str(v).strip() + if v is not None and str(v).strip() != "" + else _index_to_col(c) + ) records = [] for r in range(header_row + 1, bottom + 1): @@ -833,12 +861,13 @@ def col_is_effectively_empty(series: pd.Series) -> bool: # Main + def run_excel_driven_model( - excel_file, - filename: str, - params: Dict[str, Any], - sheet_name: Optional[str] = None, - label_overrides: Dict[str, str] = None + excel_file, + filename: str, + params: Dict[str, Any], + sheet_name: Optional[str] = None, + label_overrides: Dict[str, str] = None, ) -> Dict[str, Any]: wb = load_workbook(excel_file, data_only=False) ws = wb[sheet_name] if sheet_name else wb.active @@ -849,7 +878,9 @@ def run_excel_driven_model( header_row = _find_outcome_header_row(ws) if header_row is not None: - sections = build_sections_from_excel_outcomes(ws, engine, header_row, label_overrides) + sections = build_sections_from_excel_outcomes( + ws, engine, header_row, label_overrides + ) else: sections = build_sections_from_generic_tables(ws, engine) diff --git a/src/epicc/utils/model_loader.py b/src/epicc/utils/model_loader.py new file mode 100644 index 0000000..1bb09f8 --- /dev/null +++ b/src/epicc/utils/model_loader.py @@ -0,0 +1,7 @@ +from epicc.model.base import BaseSimulationModel +from epicc.models.measles_outbreak import MeaslesOutbreakModel +from epicc.models.tb_isolation import TBIsolationModel + + +def get_built_in_models() -> list[BaseSimulationModel]: + return [TBIsolationModel(), MeaslesOutbreakModel()] diff --git a/src/epicc/utils/parameter_loader.py b/src/epicc/utils/parameter_loader.py new file mode 100644 index 0000000..d1f64c3 --- /dev/null +++ b/src/epicc/utils/parameter_loader.py @@ -0,0 +1,50 @@ +from __future__ import annotations + +from pathlib import Path +from typing import IO, Any + +from pydantic import RootModel + +from epicc.formats import read_from_format +from epicc.model.base import BaseSimulationModel + + +class OpaqueParameters(RootModel[dict[str, Any]]): + """Minimal typed envelope for opaque parameter payloads.""" + + +def flatten_dict(data: dict[str, Any], level: int = 0) -> dict[str, Any]: + """Flatten nested dictionaries for the sidebar renderer using tab-indented labels.""" + + flat: dict[str, Any] = {} + for key, value in data.items(): + indented_key = ("\t" * level) + str(key) + if isinstance(value, dict): + flat[indented_key] = None + flat.update(flatten_dict(value, level + 1)) + continue + + flat[indented_key] = value + + return flat + + +def _load_typed_params(path: Path, data: IO[bytes]) -> dict[str, Any]: + typed, _ = read_from_format(path, data, OpaqueParameters) + return typed.root + + +def load_model_params( + model: BaseSimulationModel, + uploaded_params: IO[bytes] | None = None, + uploaded_name: str | None = None, +) -> dict[str, Any]: + """Load model parameters from upload or model defaults.""" + + if uploaded_params is not None: + if not uploaded_name: + raise ValueError("Uploaded parameter files must include a filename.") + uploaded_params.seek(0) + return flatten_dict(_load_typed_params(Path(uploaded_name), uploaded_params)) + + return flatten_dict(model.default_params()) diff --git a/src/epicc/utils/parameter_ui.py b/src/epicc/utils/parameter_ui.py new file mode 100644 index 0000000..c815084 --- /dev/null +++ b/src/epicc/utils/parameter_ui.py @@ -0,0 +1,109 @@ +from typing import Any + +import streamlit as st + + +def _item_level(key: str) -> int: + return len(key) - len(key.lstrip("\t")) + + +def _set_param_and_widget( + widget_key: str, params_key: str, value: Any, params: dict[str, str] +) -> None: + value_as_str = str(value) + st.session_state[widget_key] = value_as_str + params[params_key] = value_as_str + + +def reset_parameters_to_defaults( + param_dict: dict[str, Any], params: dict[str, str], model_id: str +) -> None: + """Reset session-state widgets and params to defaults from flattened parameter data.""" + + items = list(param_dict.items()) + i = 0 + n = len(items) + + while i < n: + key, value = items[i] + level = _item_level(key) + label = key.strip() + + if value is not None: + _set_param_and_widget(f"{model_id}:{label}", label, value, params) + i += 1 + continue + + j = i + 1 + while j < n: + subkey, subval = items[j] + sublevel = _item_level(subkey) + if sublevel <= level: + break + if sublevel == level + 1 and subval is not None: + sublabel = subkey.strip() + _set_param_and_widget( + f"{model_id}:{label}:{sublabel}", + sublabel, + subval, + params, + ) + j += 1 + + i = j + + +def render_parameters_with_indent( + param_dict: dict[str, Any], params: dict[str, str], model_id: str +) -> None: + """Render flattened parameter data as top-level controls and one-level nested expanders.""" + + items = list(param_dict.items()) + i = 0 + n = len(items) + + while i < n: + key, value = items[i] + level = _item_level(key) + label = key.strip() + + if value is not None: + widget_key = f"{model_id}:{label}" + if widget_key in st.session_state: + params[label] = st.sidebar.text_input(label, key=widget_key) + i += 1 + continue + + params[label] = st.sidebar.text_input( + label, + value=str(value), + key=widget_key, + ) + i += 1 + continue + + children: list[tuple[str, Any]] = [] + j = i + 1 + while j < n: + subkey, subval = items[j] + sublevel = _item_level(subkey) + if sublevel <= level: + break + if sublevel == level + 1 and subval is not None: + children.append((subkey.strip(), subval)) + j += 1 + + with st.sidebar.expander(label, expanded=False): + for sublabel, subval in children: + widget_key = f"{model_id}:{label}:{sublabel}" + if widget_key in st.session_state: + params[sublabel] = st.text_input(sublabel, key=widget_key) + continue + + params[sublabel] = st.text_input( + sublabel, + value=str(subval), + key=widget_key, + ) + + i = j diff --git a/src/epicc/utils/section_renderer.py b/src/epicc/utils/section_renderer.py new file mode 100644 index 0000000..94922ea --- /dev/null +++ b/src/epicc/utils/section_renderer.py @@ -0,0 +1,28 @@ +from typing import Any + +import streamlit as st + + +def _render_block(block: Any) -> None: + if hasattr(block, "columns"): + st.table(block) + return + + if isinstance(block, str): + st.markdown(block, unsafe_allow_html=True) + return + + st.write(block) + + +def render_sections(sections: list[dict[str, Any]]) -> None: + for i, section in enumerate(sections): + title = section.get("title", "") + content = section.get("content", []) + + st.markdown(f"## {title}") + for block in content: + _render_block(block) + + if i < len(sections) - 1: + st.markdown('
', unsafe_allow_html=True) diff --git a/styles/sidebar.css b/src/epicc/web/sidebar.css similarity index 100% rename from styles/sidebar.css rename to src/epicc/web/sidebar.css diff --git a/tests/epicc/test_formats.py b/tests/epicc/test_formats.py new file mode 100644 index 0000000..5cb1830 --- /dev/null +++ b/tests/epicc/test_formats.py @@ -0,0 +1,37 @@ +"""Tests for epicc.formats (get_format, read_from_format).""" + +from io import BytesIO + +import pytest +from pydantic import BaseModel + +from epicc.formats import ( + XLSXFormat, + YAMLFormat, + get_format, + read_from_format, +) + + +class _Simple(BaseModel): + x: int + y: str + + +def test_get_format_yaml_returns_yaml_format(): + assert isinstance(get_format("params.yaml"), YAMLFormat) + + +def test_get_format_xlsx_returns_xlsx_format(): + assert isinstance(get_format("params.xlsx"), XLSXFormat) + + +def test_get_format_unsupported_raises(): + with pytest.raises(ValueError, match="Unsupported file format"): + get_format("params.csv") + + +def test_read_from_format_yaml(): + model, _ = read_from_format("params.yaml", BytesIO(b"x: 10\ny: hello\n"), _Simple) + assert model.x == 10 + assert model.y == "hello" diff --git a/tests/epicc/test_formats_template.py b/tests/epicc/test_formats_template.py new file mode 100644 index 0000000..485153c --- /dev/null +++ b/tests/epicc/test_formats_template.py @@ -0,0 +1,93 @@ +"""Integration tests for epicc.formats.template (generate_template).""" + +from io import BytesIO +from typing import Literal, Optional + +import openpyxl +from pydantic import BaseModel, Field + +from epicc.formats.template import generate_template +from epicc.formats.xlsx import XLSXFormat +from epicc.formats.yaml import YAMLFormat + + +# --------------------------------------------------------------------------- +# Test models +# --------------------------------------------------------------------------- + +class _Inner(BaseModel): + rate: float + label: str = Field(default="default label", description="A label.") + + +class _Outer(BaseModel): + name: str = Field(description="The name.") + count: int = 5 + inner: _Inner + theme: Literal["light", "dark"] = "light" + note: Optional[str] = None + + +# --------------------------------------------------------------------------- +# YAML +# --------------------------------------------------------------------------- + +def test_yaml_template_contains_defaults(): + result = generate_template(_Outer, YAMLFormat("template.yaml")) + data, _ = YAMLFormat("template.yaml").read(BytesIO(result)) + + assert data["count"] == 5 + assert data["theme"] == "light" + assert data["note"] is None + + +def test_yaml_template_nested_model(): + result = generate_template(_Outer, YAMLFormat("template.yaml")) + data, _ = YAMLFormat("template.yaml").read(BytesIO(result)) + + assert isinstance(data["inner"], dict) + assert data["inner"]["label"] == "default label" + + +def test_yaml_template_placeholder_for_required_fields(): + result = generate_template(_Outer, YAMLFormat("template.yaml")) + data, _ = YAMLFormat("template.yaml").read(BytesIO(result)) + + assert data["name"] == "" + assert data["inner"]["rate"] == 0.0 + + +# --------------------------------------------------------------------------- +# XLSX +# --------------------------------------------------------------------------- + +def _read_xlsx_rows(data: bytes) -> dict[str, tuple]: + """Parse an XLSX template into {key: (value, description)}.""" + wb = openpyxl.load_workbook(BytesIO(data)) + rows = list(wb.active.iter_rows(values_only=True)) + return {r[0]: (r[1], r[2]) for r in rows[1:] if r[0] is not None} + + +def test_xlsx_template_flattens_nested(): + result = generate_template(_Outer, XLSXFormat("template.xlsx")) + rows = _read_xlsx_rows(result) + + assert "inner.rate" in rows + assert "inner.label" in rows + + +def test_xlsx_template_includes_descriptions(): + result = generate_template(_Outer, XLSXFormat("template.xlsx")) + rows = _read_xlsx_rows(result) + + assert rows["name"][1] == "The name." + assert rows["inner.label"][1] == "A label." + + +def test_xlsx_template_values_match_defaults(): + result = generate_template(_Outer, XLSXFormat("template.xlsx")) + rows = _read_xlsx_rows(result) + + assert rows["count"][0] == 5 + assert rows["theme"][0] == "light" + assert rows["inner.label"][0] == "default label" diff --git a/tests/epicc/test_formats_xlsx.py b/tests/epicc/test_formats_xlsx.py new file mode 100644 index 0000000..717327f --- /dev/null +++ b/tests/epicc/test_formats_xlsx.py @@ -0,0 +1,63 @@ +"""Tests for epicc.formats.xlsx (XLSXFormat).""" + +from io import BytesIO + +import openpyxl +import pytest + +from epicc.formats.xlsx import XLSXFormat + + +def _make_xlsx(rows: list[list]) -> BytesIO: + wb = openpyxl.Workbook() + ws = wb.active + for row in rows: + ws.append(row) + buf = BytesIO() + wb.save(buf) + buf.seek(0) + return buf + + +def _fmt() -> XLSXFormat: + return XLSXFormat("test.xlsx") + + +def test_read_dot_notation_creates_nested(): + buf = _make_xlsx([ + ["param", "value"], + ["costs.latent", 300], + ["costs.active", 500], + ]) + data, _ = _fmt().read(buf) + assert data == {"costs": {"latent": 300, "active": 500}} + + +def test_read_skips_empty_rows(): + buf = _make_xlsx([["param", "value"], ["a", 1], [None, None], ["b", 2]]) + data, _ = _fmt().read(buf) + assert data == {"a": 1, "b": 2} + + +def test_read_too_few_columns_raises(): + wb = openpyxl.Workbook() + ws = wb.active + ws.append(["only_one_col"]) + ws.append(["value"]) + buf = BytesIO() + wb.save(buf) + buf.seek(0) + with pytest.raises(ValueError, match="at least 2 columns"): + _fmt().read(buf) + + +def test_write_with_template_round_trips(): + buf = _make_xlsx([["param", "value"], ["x", 1], ["y", 2]]) + _, wb_template = _fmt().read(buf) + + result_bytes = _fmt().write({"x": 99}, wb_template) + + wb_out = openpyxl.load_workbook(BytesIO(result_bytes)) + rows = list(wb_out.active.iter_rows(values_only=True)) + row_dict = {r[0]: r[1] for r in rows[1:] if r[0] is not None} + assert row_dict["x"] == 99 diff --git a/tests/epicc/test_formats_yaml.py b/tests/epicc/test_formats_yaml.py new file mode 100644 index 0000000..faf7a93 --- /dev/null +++ b/tests/epicc/test_formats_yaml.py @@ -0,0 +1,42 @@ +"""Tests for epicc.formats.yaml (YAMLFormat).""" + +from io import BytesIO + +import pytest + +from epicc.formats.yaml import YAMLFormat + + +def _fmt() -> YAMLFormat: + return YAMLFormat("test.yaml") + + +def _stream(text: str) -> BytesIO: + return BytesIO(text.encode()) + + +def test_read_simple_mapping(): + data, _ = _fmt().read(_stream("a: 1\nb: hello\n")) + assert data == {"a": 1, "b": "hello"} + + +def test_read_nested_mapping(): + data, _ = _fmt().read(_stream("costs:\n latent: 300\n active: 500\n")) + assert data == {"costs": {"latent": 300, "active": 500}} + + +def test_read_non_mapping_raises(): + with pytest.raises(ValueError, match="Expected a YAML mapping"): + _fmt().read(_stream("- a\n- b\n")) + + +def test_read_invalid_yaml_raises(): + with pytest.raises(ValueError, match="Failed to parse YAML"): + _fmt().read(_stream("key: [unclosed")) + + +def test_write_round_trips(): + original = {"a": 1, "b": {"c": 2}} + result = _fmt().write(original) + data, _ = _fmt().read(BytesIO(result)) + assert data == original diff --git a/tests/epicc/test_model_loader.py b/tests/epicc/test_model_loader.py new file mode 100644 index 0000000..a0d1b99 --- /dev/null +++ b/tests/epicc/test_model_loader.py @@ -0,0 +1,101 @@ +"""Tests for epicc.model (load_model).""" + +import importlib.resources +import tempfile +import textwrap +from pathlib import Path +from unittest.mock import MagicMock, patch + +import pytest + +from epicc.model import load_model +from epicc.model.schema import Model + +_VALID_MODEL_YAML = textwrap.dedent("""\ + metadata: + title: Test Model + description: A minimal test model. + parameters: + rate: + type: number + label: Rate + default: 0.5 + equations: + total: + label: Total + compute: "rate * 100" + table: + scenarios: [] + rows: [] +""") + + +@pytest.fixture +def valid_model_path(): + with tempfile.NamedTemporaryFile(suffix=".yaml", mode="w", delete=False) as f: + f.write(_VALID_MODEL_YAML) + path = Path(f.name) + try: + yield path + finally: + path.unlink(missing_ok=True) + + +# --------------------------------------------------------------------------- +# load_model: patched to avoid relying on built-in model file format +# --------------------------------------------------------------------------- + +def test_load_model_returns_model_and_template(valid_model_path: Path): + with patch("epicc.model.importlib.resources") as mock_res: + mock_res.files.return_value.joinpath.return_value = valid_model_path + model, template = load_model("my_model") + + assert isinstance(model, Model) + assert model.metadata.title == "Test Model" + assert "rate" in model.parameters + assert "total" in model.equations + + +def test_load_model_has_parameters(valid_model_path: Path): + with patch("epicc.model.importlib.resources") as mock_res: + mock_res.files.return_value.joinpath.return_value = valid_model_path + model, _ = load_model("my_model") + + assert len(model.parameters) > 0 + + +def test_load_model_parameter_fields(valid_model_path: Path): + with patch("epicc.model.importlib.resources") as mock_res: + mock_res.files.return_value.joinpath.return_value = valid_model_path + model, _ = load_model("my_model") + + rate = model.parameters["rate"] + assert rate.type == "number" + assert rate.default == 0.5 + + +def test_load_model_equations(valid_model_path: Path): + with patch("epicc.model.importlib.resources") as mock_res: + mock_res.files.return_value.joinpath.return_value = valid_model_path + model, _ = load_model("my_model") + + assert model.equations["total"].compute == "rate * 100" + + +def test_load_model_nonexistent_file_raises(): + with tempfile.NamedTemporaryFile(suffix=".yaml") as f: + missing = Path(f.name + ".gone") + with patch("epicc.model.importlib.resources") as mock_res: + mock_res.files.return_value.joinpath.return_value = missing + with pytest.raises(Exception): + load_model("does_not_exist") + + +def test_load_model_invalid_schema_raises(): + with tempfile.NamedTemporaryFile(suffix=".yaml", mode="w", delete=False) as f: + f.write("just: a flat file\nwith: no structure\n") + bad_path = Path(f.name) + with patch("epicc.model.importlib.resources") as mock_res: + mock_res.files.return_value.joinpath.return_value = bad_path + with pytest.raises(ValueError, match="Data validation failed"): + load_model("bad_model") diff --git a/utils/model_loader.py b/utils/model_loader.py deleted file mode 100644 index 1ed89ea..0000000 --- a/utils/model_loader.py +++ /dev/null @@ -1,29 +0,0 @@ -import os -import importlib.util -import sys - -def discover_models(path): - """Return {model_name: file_path} for Python model files.""" - if not os.path.isdir(path): - return {} - models = {} - for f in os.listdir(path): - if f.endswith(".py") and not f.startswith("__"): - name = f[:-3] - models[name] = os.path.join(path, f) - return models - - -def load_model_from_file(filepath): - """ - Loads a Python model file dynamically and returns the module object. - The module must contain `run_model()` and `build_sections()`. - """ - module_name = os.path.splitext(os.path.basename(filepath))[0] - - spec = importlib.util.spec_from_file_location(module_name, filepath) - module = importlib.util.module_from_spec(spec) - sys.modules[module_name] = module - spec.loader.exec_module(module) - - return module diff --git a/utils/parameter_loader.py b/utils/parameter_loader.py deleted file mode 100644 index 902d0a6..0000000 --- a/utils/parameter_loader.py +++ /dev/null @@ -1,61 +0,0 @@ -import os -import yaml -import pandas as pd -from decimal import Decimal -import re - - -def load_params_from_excel(excel_file): - df = pd.read_excel( - excel_file, - usecols="F:H", - header=1 - ) - - df.columns = [str(c).strip().lower() for c in df.columns] - - if not {"parameter", "value"}.issubset(df.columns): - raise ValueError("Expected columns Parameter and Value in F:G") - - params = {} - for _, row in df.iterrows(): - if pd.isna(row["parameter"]) or pd.isna(row["value"]): - continue - - cleaned = re.sub(r"[^0-9.\-]", "", str(row["value"])) - if cleaned == "": - continue - - params[str(row["parameter"]).strip()] = Decimal(cleaned) - - return params - - -def flatten_dict(d, level=0): - flat = {} - for key, value in d.items(): - indented_key = ("\t" * level) + str(key) - - if isinstance(value, dict): - flat[indented_key] = None - flat.update(flatten_dict(value, level + 1)) - else: - flat[indented_key] = value - return flat - - -def load_model_params(model_file_path, uploaded_excel=None): - if uploaded_excel: - return load_params_from_excel(uploaded_excel) - - base = os.path.dirname(model_file_path) - name = os.path.basename(model_file_path).replace(".py", "") - yaml_path = os.path.join(base, f"{name}.yaml") - - if not os.path.exists(yaml_path): - return {} - - with open(yaml_path, "r") as f: - raw = yaml.safe_load(f) or {} - - return flatten_dict(raw) diff --git a/utils/parameter_ui.py b/utils/parameter_ui.py deleted file mode 100644 index 445796f..0000000 --- a/utils/parameter_ui.py +++ /dev/null @@ -1,111 +0,0 @@ -import streamlit as st - - -def reset_parameters_to_defaults(param_dict, params, model_id): - """ - Resets Streamlit session state widgets and params dict to values found in param_dict. - """ - items = list(param_dict.items()) - i = 0 - n = len(items) - - while i < n: - key, value = items[i] - level = len(key) - len(key.lstrip("\t")) - label = key.strip() - - if value is None: - # Handle Children - j = i + 1 - while j < n: - subkey, subval = items[j] - sublevel = len(subkey) - len(subkey.lstrip("\t")) - - if sublevel <= level: - break - - # Reset logic for child - if sublevel == level + 1 and subval is not None: - sublabel = subkey.strip() - widget_key = f"{model_id}:{label}:{sublabel}" - - st.session_state[widget_key] = str(subval) - params[sublabel] = str(subval) - j += 1 - i = j - continue - - # Reset logic for Top-level - widget_key = f"{model_id}:{label}" - st.session_state[widget_key] = str(value) - params[label] = str(value) - i += 1 - - -def render_parameters_with_indent(param_dict, params, model_id): - """ - Render hierarchical parameters with indentation-based expanders. - Checks session_state before setting 'value' to avoid DuplicateWidgetID/API warnings. - """ - items = list(param_dict.items()) - i = 0 - n = len(items) - - while i < n: - key, value = items[i] - - level = len(key) - len(key.lstrip("\t")) - label = key.strip() - - if value is None: - # Collect all children - children = [] - j = i + 1 - while j < n: - subkey, subval = items[j] - sublevel = len(subkey) - len(subkey.lstrip("\t")) - - if sublevel <= level: - break - - if sublevel == level + 1 and subval is not None: - sublabel = subkey.strip() - children.append((sublabel, subval)) - - j += 1 - - # Render the expander with all children inside - with st.sidebar.expander(label, expanded=False): - for sublabel, subval in children: - widget_key = f"{model_id}:{label}:{sublabel}" - if widget_key in st.session_state: - params[sublabel] = st.text_input( - sublabel, - key=widget_key - ) - else: - # First load: Pass the default value - params[sublabel] = st.text_input( - sublabel, - value=str(subval), - key=widget_key - ) - - i = j - continue - - # TOP-LEVEL PARAMS - widget_key = f"{model_id}:{label}" - - if widget_key in st.session_state: - params[label] = st.sidebar.text_input( - label, - key=widget_key - ) - else: - params[label] = st.sidebar.text_input( - label, - value=str(value), - key=widget_key - ) - i += 1 diff --git a/utils/section_renderer.py b/utils/section_renderer.py deleted file mode 100644 index 8e4be6b..0000000 --- a/utils/section_renderer.py +++ /dev/null @@ -1,20 +0,0 @@ -import streamlit as st - -def 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