exploration script

exploration.py

+# -*- coding: utf-8 -*-
+"""
+Created on Thu Feb  2 13:51:49 2023
+
+@author: adria036
+"""
+import os
+os.chdir(r"C:\Users\adria036\OneDrive - Wageningen University & Research\iAdriaens_doc\Projects\cKamphuis\nlas\scripts\uwb") 
+
+
+#%% import modules
+
+
+from datetime import date, timedelta,datetime
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+
+#%% set paths and constants and load data
+
+# path to per barn directories
+path = os.path.join("W:","\ASG","WLR_Dataopslag","DairyCampus","3406_Nlas","uwb_processed")
+
+# settings
+settings = {'barn' : [60,61,62,70,71,72,73],
+            'startdate' : date(2022,10,5),
+            'enddate' :  date(2022,12,30),
+            'cows' : [1790], # or specific cow number
+            }
+
+# files that comply with settings
+fn = []
+for b in range(0,len(settings["barn"])):
+    print("barn = " + str(settings["barn"][b]))
+    if settings["cows"] == 0:
+        fbarn = [f for f in os.listdir(path + "/barn" + str(settings["barn"][b])) \
+                if os.path.isfile(os.path.join(path,"barn"+str(settings["barn"][b]),f)) \
+                    and (datetime.strptime(f[5:13], '%Y%m%d').date() >= settings["startdate"]) \
+                    and (datetime.strptime(f[5:13], '%Y%m%d').date() <= settings["enddate"])]
+        fbarn.sort()
+    else:
+        fbarn = [f for f in os.listdir(path + "/barn" + str(settings["barn"][b])) \
+                if os.path.isfile(os.path.join(path,"barn"+str(settings["barn"][b]),f)) \
+                    and (int(f[26:-4]) in settings["cows"]) \
+                    and (datetime.strptime(f[5:13], '%Y%m%d').date() >= settings["startdate"]) \
+                    and (datetime.strptime(f[5:13], '%Y%m%d').date() <= settings["enddate"])]
+        fbarn.sort()
+    fn.extend(fbarn)
+    fn.sort()
+
+# find unique cows
+cows = list(set([int(f[26:-4]) for f in fn]))
+
+# read data
+data = pd.DataFrame([])
+for f in fn:
+    barn = f[19:21]
+    sub = pd.read_csv(path + "/barn" + barn + "/" + f, 
+                      usecols = ["cowid","barn","date","t","xnew","ynew","area","zone"],
+                      dtype = {"cowid" : "int64","barn" : "int64","date" : "object",
+                               "t" : "int64", "xnew":"float64","ynew":"float64",
+                               "area":"object","zone":"float64"})
+    sub["date"] = pd.to_datetime(sub["date"], format = "%Y-%m-%d") 
+    data = pd.concat([data,sub])
+data = data.sort_values(by = ["cowid","date","t"])
+
+
+
+
+#%% data exploration and visualisation
+
+#TODO
+"""
+     - explore the number of cows with data on each day
+     - explore when no areas are assigned and so, wrong barn is entered
+     - explore gaps and gapsize
+"""
+    
+    
+    
+