Merge pull request #128 from marshall-lab/develop

Deploy floating point fix, random trial enrolled

README.md

@@ -1,5 +1,5 @@
 # TITAN Simulation
-
+[![DOI](https://zenodo.org/badge/80315242.svg)](https://zenodo.org/badge/latestdoi/80315242)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/marshall-lab/TITAN)](https://github.com/marshall-lab/TITAN/releases/latest/) [![](https://github.com/marshall-lab/TITAN/workflows/Unit%20Tests/badge.svg)](https://github.com/marshall-lab/TITAN/actions) [![codecov](https://codecov.io/gh/marshall-lab/TITAN/branch/develop/graph/badge.svg?token=wjkExshhyh)](https://codecov.io/gh/marshall-lab/TITAN) [![GitHub](https://img.shields.io/github/license/marshall-lab/TITAN)](https://github.com/marshall-lab/TITAN/blob/develop/LICENSE) [![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://marshall-lab.github.io/TITAN/)
 
 TITAN (Treatment of Infectious Transmissions through Agent-based Network) is an agent-based simulation model used to explore contact transmission in complex social networks. Starting with the initializing agent population, TITAN iterates over a series of stochastic interactions where agents can interact with one another, transmit infections through various medium, and enter and exit the care continuum. The purpose of TITAN is to evaluate the impact of prevention and treatment models on incidence and prevalence rates of the targeted disease(s) through the use of data fitting simulated trajectories and rich statistics of primary/sub-population attributable proportions.

run_titan.py

@@ -138,7 +138,7 @@ def drange(start, stop, step):
     while r < stop:
         yield r
         r += step
-        r = round(r, 3)
+        r = round(r, 6)
 
 
 def setup_sweeps(sweeps):
@@ -184,7 +184,7 @@ def setup_sweeps_file(sweepfile, rows):
                         val = int(v)
                     except ValueError:
                         try:
-                            val = float(v)
+                            val = round(float(v), 6)
                         except ValueError:
                             raise ValueError(
                                 "sweep values must be numbers (int or float)"

tests/params/basic.yml

@@ -1,6 +1,6 @@
 demographics:
   black:
-    ppl: 0.6
+    ppl: 0.600000000000567
     MSM:
       ppl: 0.3
       drug_type:

tests/params/setting_params.yml

@@ -5,5 +5,4 @@ partnership:
   sex:
     acquisition:
       MSM:
-        insertive: 0.0011
-
+        insertive: 0.0011000000000001

tests/parse_params_test.py

@@ -19,7 +19,9 @@ def test_create_params_base(tmpdir):
     assert "white" not in params.classes.races
     assert params.partnership.sex.acquisition.MSM.versatile == 0.00745  # from setting
     assert params.partnership.sex.acquisition.MSM.receptive == 0.0138  # from base
-    assert params.partnership.sex.acquisition.MSM.insertive == 0.0011  # from param
+    assert (
+        params.partnership.sex.acquisition.MSM.insertive == 0.0011
+    )  # from param, rounded
 
 
 @pytest.mark.unit

titan/model.py

@@ -441,13 +441,13 @@ def initialize_random_trial(self):
                     for ag in comp.nodes():
                         ag.random_trial_enrolled = True
                         if not ag.hiv and not ag.prep:
-                            ag.intervention_ever = True
                             if (
                                 self.run_random.random()
                                 < ag.location.params.prep.target
                                 and not ag.vaccine
                             ):
                                 self.initiate_prep(ag, force=True)
+                                ag.intervention_ever = True
                 elif self.params.prep.pca.choice == "eigenvector":
                     centrality = nx.algorithms.centrality.eigenvector_centrality(comp)
                     assert len(centrality) >= 1, "Empty centrality"

titan/parse_params.py

@@ -60,6 +60,10 @@ def check_item(val, d, key_path, keys=None, pops=None):
     if d["type"] == "float":
         if isinstance(val, int):
             val = float(val)
+
+        # avoid floating point errors by making numbers more reasonable
+        val = round(val, 6)
+
         assert isinstance(val, float), f"{val} must be a float [{key_path}]"
     if d["type"] == "boolean":
         assert isinstance(val, bool), f"{val} must be a bool [{key_path}]"