hotfix: sobol sensitivity anlaysis hanging bug

app/flows/run_abc.py

@@ -4,19 +4,38 @@
 # Imports
 ######################################
 
+
 import mlflow
-from prefect import context, flow, task
+import numpy as np
+import pandas as pd
+import plotly.express as px
+from joblib import dump as calibrator_dump
+from matplotlib import pyplot as plt
+from prefect import flow, task
+from prefect.artifacts import create_table_artifact
 from prefect.task_runners import ConcurrentTaskRunner
 
-from deeprootgen.data_model import RootCalibrationModel
-from deeprootgen.io import save_graph_to_db
-from deeprootgen.model import RootSystemSimulation
+from deeprootgen.calibration import (
+    SensitivityAnalysisModel,
+    calculate_summary_statistic_discrepancy,
+    get_calibration_summary_stats,
+    log_model,
+)
+from deeprootgen.data_model import RootCalibrationModel, SummaryStatisticsModel
 from deeprootgen.pipeline import (
     begin_experiment,
+    get_datetime_now,
+    get_outdir,
     log_config,
     log_experiment_details,
-    log_simulation,
 )
+from deeprootgen.statistics import DistanceMetricBase
+
+######################################
+# Constants
+######################################
+
+TASK = "abc"
 
 ######################################
 # Main
@@ -33,7 +52,12 @@ def run_abc(input_parameters: RootCalibrationModel, simulation_uuid: str) -> Non
         simulation_uuid (str):
             The simulation uuid.
     """
-    print("hello")
+    begin_experiment(TASK, simulation_uuid, input_parameters.simulation_tag)
+    log_experiment_details(simulation_uuid)
+
+    config = input_parameters.dict()
+    log_config(config, TASK)
+    mlflow.end_run()
 
 
 @flow(

app/flows/run_sensitivity_analysis.py

@@ -216,6 +216,13 @@ def log_task(
     for i, si_label in enumerate(["total_si", "first_si", "second_si"]):
         outfile = osp.join(outdir, f"{time_now}-{TASK}_{si_label}.csv")
         si_df = si_dfs[i]
+
+        if si_label != "second_si":
+            si_df["name"] = names
+            cols = list(si_df.columns)
+            cols = [cols[-1]] + cols[:-1]
+            si_df = si_df[cols]
+
         si_df.to_csv(outfile, index=False)
         mlflow.log_artifact(outfile)
 
@@ -225,11 +232,6 @@ def log_task(
     mlflow.log_artifact(outfile)
 
     total_si_df = si_dfs[0]
-    total_si_df["name"] = names
-    cols = list(total_si_df.columns)
-    cols = [cols[-1]] + cols[:-1]
-    total_si_df = total_si_df[cols]
-
     fig = px.bar(
         total_si_df,
         x="name",
@@ -241,6 +243,13 @@ def log_task(
     fig.write_image(outfile, width=1200, height=1200)
     mlflow.log_artifact(outfile)
 
+    st_confs = total_si_df.ST_conf.values
+    for i, sensitivity_index in enumerate(total_si_df.ST.values):
+        name = names[i]
+        st_conf = st_confs[i]
+        mlflow.log_metric(name, sensitivity_index)
+        mlflow.log_metric(f"{name}_conf", st_conf)
+
     create_table_artifact(
         key="sensitivity-analysis-indices",
         table=total_si_df.to_dict(orient="records"),

app/pages/eda_root_system.py

@@ -106,9 +106,9 @@ def toggle_external_links_collapse(n: int, is_open: bool) -> bool:
 
 
 @callback(
-    Output(f"{PAGE_ID}-observed-data-collapse", "is_open"),
-    [Input(f"{PAGE_ID}-observed-data-collapse-button", "n_clicks")],
-    [State(f"{PAGE_ID}-observed-data-collapse", "is_open")],
+    Output(f"{PAGE_ID}-simulated-data-collapse", "is_open"),
+    [Input(f"{PAGE_ID}-simulated-data-collapse-button", "n_clicks")],
+    [State(f"{PAGE_ID}-simulated-data-collapse", "is_open")],
 )
 def toggle_data_collapse(n: int, is_open: bool) -> bool:
     """Toggle the collapsible for statistics.

deeprootgen/calibration/summary_statistics.py

@@ -84,6 +84,7 @@ def run_calibration_simulation(
         simulation_tag=input_parameters.simulation_tag,  # type: ignore
         random_seed=input_parameters.random_seed,  # type: ignore
     )
+
     simulation.run(simulation_parameters)
     return simulation, simulation_parameters
 
@@ -113,6 +114,7 @@ def calculate_summary_statistic_discrepancy(
     simulation, simulation_parameters = run_calibration_simulation(
         parameter_specs, input_parameters
     )
+
     node_df, _ = simulation.G.as_df()
     observed_values = []
     simulated_values = []

deeprootgen/form/components.py

@@ -83,8 +83,13 @@ def build_common_components(
 
             if component_spec.handler == "dropdown":
                 options_func = locate(component_spec.options_func)
-                summary_statistics = options_func()  # type: ignore
-                component_instance.options = summary_statistics
+                options_list = options_func()  # type: ignore
+                component_instance.options = options_list
+                if len(options_list) > 0:
+                    if component_spec.kwargs["multi"]:
+                        component_instance.value = [options_list[0]]
+                    else:
+                        component_instance.value = options_list[0]
 
             if component_spec.handler == "range_slider":
                 component_instance.value = [

deeprootgen/model/root.py

@@ -6,6 +6,7 @@
 
 # mypy: ignore-errors
 
+import math
 from typing import Dict, List
 
 import networkx as nx
@@ -274,12 +275,14 @@ def construct_root(
     def add_child_organ(
         self, floor_threshold: float = 0.4, ceiling_threshold: float = 0.9
     ) -> "RootOrgan":
-        floor = int(len(self.segments) * floor_threshold)
-        ceiling = int(len(self.segments) * ceiling_threshold)
-        if floor > ceiling:
+        floor = math.ceil(len(self.segments) * floor_threshold)
+        ceiling = math.ceil(len(self.segments) * ceiling_threshold)
+        if floor >= ceiling:
             floor, ceiling = ceiling, floor
         if floor <= 0:
             floor = 1
+        if floor == ceiling:
+            ceiling += 1
 
         indx = self.rng.integers(floor, ceiling)
         parent_node = self.segments[indx]
@@ -891,6 +894,7 @@ def init_organs(
             order_type=RootType.PRIMARY.value,
             position_type=RootType.OUTER.value,
         )
+
         for _ in range(input_parameters.outer_root_num):
             organ = RootOrgan(
                 self.G.base_node,
@@ -939,7 +943,8 @@ def init_organs(
                 n_secondary_roots = self.rng.integers(
                     min_sec_root_num, max_sec_root_num
                 )
-                n_secondary_roots = int(n_secondary_roots * growth_sec_root)
+
+                n_secondary_roots = math.ceil(n_secondary_roots * growth_sec_root)
                 for _ in range(n_secondary_roots):
                     child_organ = parent_organ.add_child_organ(
                         floor_threshold=input_parameters.floor_threshold,