Merge pull request #32 from EzequielPuerta/31-filter-nan-values-from-…

…global-min-and-max

🐛 Filter nan values from global min and max

.circleci/config.yml

@@ -75,9 +75,9 @@ jobs:
           command: |
             export GITHUB_HOSTNAME="github.com"
             set -- "$@" --notes-file "./CHANGELOG.md"
-            set -- "$@" --title "simulab v0.0.15"
+            set -- "$@" --title "simulab v0.0.16"
             set -- "$@" --repo "$(git config --get remote.origin.url)"
-            gh release create "0.0.15" "$@"
+            gh release create "0.0.16" "$@"
 workflows:
   build_test_publish:
     jobs:

CHANGELOG.md

@@ -5,6 +5,12 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](http://keepachangelog.com/)
 and this project adheres to [Semantic Versioning](http://semver.org/).
 
+## [0.0.16] - 2024-06-30
+
+### Fixed
+
+Filter Nan values from global min and max
+
 ## [0.0.15] - 2024-06-29
 
 ### Fixed

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "simulab"
-version = "0.0.15"
+version = "0.0.16"
 description = "Simple simulation framework, created during a course of the Discrete Events Simulation Laboratory, from the University of Buenos Aires (https://modsimu.exp.dc.uba.ar/sed/)"
 authors = ["Armando Ezequiel Puerta <armando.ezequiel.puerta@gmail.com>"]
 license = "MIT License"

simulab/simulation/plotters/animated_lattice.py

@@ -1,5 +1,6 @@
 from typing import Any, Dict, List, Tuple
 
+import numpy as np
 import plotly.graph_objs as go
 
 from simulab.simulation.core.runner import Runner
@@ -159,9 +160,14 @@ def heatmap(
 
     @classmethod
     def calculate_global_min_max(cls, series: List[List[List[float]]]) -> Tuple[float, float]:
-        _min = _max = 0.0
-        iterations = [sum(lattice, []) for lattice in series]
-        maxs_mins = [(min(iteration), max(iteration)) for iteration in iterations]
-        _min = min(map(lambda each: each[0], maxs_mins))
-        _max = max(map(lambda each: each[1], maxs_mins))
+        current_min = current_max = 0.0
+        for iteration in series:
+            lattice = sum(iteration, [])
+            try:
+                _min = np.nanmin(lattice)
+                _max = np.nanmax(lattice)
+                current_min = min(current_min, _min)
+                current_max = max(current_max, _max)
+            except RuntimeWarning:
+                pass
         return _min, _max

simulab/simulation/plotters/categorical_animated_lattice.py

@@ -248,12 +248,14 @@ def frame_args(cls, duration: int) -> Dict[str, Any]:
     def calculate_global_min_max(
         cls, series: List[List[List[Tuple[float, int]]]]
     ) -> Tuple[float, float]:
-        _min = _max = 0.0
-        iterations = [sum(lattice, []) for lattice in series]
-        maxs_mins = [
-            (min(map(lambda x: x[0], iteration)), max(map(lambda x: x[0], iteration)))
-            for iteration in iterations
-        ]
-        _min = min(map(lambda each: each[0], maxs_mins))
-        _max = max(map(lambda each: each[1], maxs_mins))
+        current_min = current_max = 0.0
+        for iteration in series:
+            lattice = [cell[0] for cell in sum(iteration, [])]
+            try:
+                _min = np.nanmin(lattice)
+                _max = np.nanmax(lattice)
+                current_min = min(current_min, _min)
+                current_max = max(current_max, _max)
+            except RuntimeWarning:
+                pass
         return _min, _max