diff trafficintelligence/storage.py @ 1287:76f5693b530c

updated tests for numpy 2
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Sat, 20 Jul 2024 20:35:21 -0400
parents 9562f5e8edf8
children 46a30ce1a2e4
line wrap: on
line diff
--- a/trafficintelligence/storage.py	Wed Jul 17 12:28:01 2024 -0400
+++ b/trafficintelligence/storage.py	Sat Jul 20 20:35:21 2024 -0400
@@ -7,7 +7,7 @@
 from copy import copy
 import sqlite3, logging
 
-from numpy import log, min as npmin, max as npmax, round as npround, array, sum as npsum, loadtxt, floor as npfloor, ceil as npceil, linalg, int32, int64, reshape, dot, vstack, transpose, ones, zeros_like, pi, NaN
+from numpy import log, min as npmin, max as npmax, round as npround, array, sum as npsum, loadtxt, floor as npfloor, ceil as npceil, linalg, int32, int64, reshape, dot, vstack, transpose, ones, zeros_like, pi, nan
 from pandas import read_csv, merge, concat, DataFrame
 
 from trafficintelligence import utils, moving, events, indicators
@@ -1359,7 +1359,7 @@
         if len(tmp) != interval.length(): #interpolate
             print(objNum, len(tmp), interval.length())
             instants = set(interval).difference(tmp.frame)
-            missing = concat([tmp[['frame']+header[10:]], DataFrame([[t]+[NaN]*(len(header)-10) for t in instants], columns = ['frame']+header[10:])], ignore_index=True).sort_values('frame')
+            missing = concat([tmp[['frame']+header[10:]], DataFrame([[t]+[nan]*(len(header)-10) for t in instants], columns = ['frame']+header[10:])], ignore_index=True).sort_values('frame')
             tmp = missing.interpolate()
         featureTrajectories = [moving.Trajectory() for i in range(4)]
         for i, r in tmp.iterrows():
@@ -1501,7 +1501,7 @@
         if len(tmp) != interval.length(): #interpolate
             print(objNum, len(tmp), interval.length())
             instants = set(interval).difference(tmp.frame)
-            missing = concat([tmp[['frame', 'x', 'y']], DataFrame([[t, NaN, NaN] for t in instants], columns = ['frame', 'x', 'y'])], ignore_index=True).sort_values('frame')
+            missing = concat([tmp[['frame', 'x', 'y']], DataFrame([[t, nan, nan] for t in instants], columns = ['frame', 'x', 'y'])], ignore_index=True).sort_values('frame')
             tmp = missing.interpolate()
             #print(tmp.info())
         if interval.length()>1: