oscplayer in python with more features

oscplayer/data.csv

@@ -6,9 +6,9 @@ time,heartrate,random
 1.0,83.910385,0.23544657
 1.25,83.910385,0.9030523
 1.5,83.910385,0.24920326
-1.75,83.910385,0.8914295
-2.0,83.910385,0.09346372
-2.25,83.910385,0.8276468
+1.75,,0.8914295
+2.0,,0.09346372
+2.25,,0.8276468
 2.5,88.35135,0.99510956
 2.75,88.35135,0.51485765
 3.0,88.35135,0.6635224

oscplayer/heart_cluster_max.csv

@@ -0,0 +1,276 @@
+time,value
+0,78
+1,78
+2,78
+3,78
+4,78
+5,50
+6,74
+7,73
+8,52
+9,51
+10,51
+11,79
+12,51
+13,51
+14,79
+15,51
+16,51
+17,72
+18,79
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+20,81
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+23,66
+24,82
+25,73
+26,66
+27,82
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+29,80
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+33,52
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+36,80
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+39,62
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+273,62
+274,74

oscplayer/oscplayer.py

@@ -0,0 +1,125 @@
+import argparse
+import random
+import time
+
+from pythonosc import udp_client
+
+import csv
+import numpy as np
+
+
+header=None
+rows=None
+rowid=0
+time_start=0
+
+client=None
+lastvalue=[]
+
+minvalues=[]
+maxvalues=[]
+meanvalues=[]
+
+basetopics=["/3/oscplayer","/oscplayer","/oscplayer"]
+
+def init():
+
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--ip", default="127.0.0.1", help="The ip of the OSC server")
+    parser.add_argument("--port", type=int, default=7000, help="The port the OSC server is listening on")
+    args = parser.parse_args()
+
+    global client
+    client = udp_client.SimpleUDPClient(args.ip, args.port)
+  
+    csvlist=None
+    with open('heart_cluster_max.csv', newline='') as csvfile:
+        csvreader = csv.reader(csvfile, delimiter=',', quotechar='|')
+        csvlist = list(csvreader)
+        '''for row in csvreader:
+            if header is None:
+                header=row
+            else:
+                rows.vstack(row)
+                '''
+    global header
+    header=csvlist[0]
+    global rows
+    rows=csvlist[1:]
+
+    global rowid
+    rowid=0 #waiting for this row to send
+
+    global lastvalue
+    lastvalue=np.zeros(len(rows)-1)
+
+    global minvalues
+    global maxvalues
+    global meanvalues
+
+    
+    minvalues=[float(min(x)) for x in filterEmpty(rows)]
+    maxvalues=[float(max(x)) for x in filterEmpty(rows)]
+
+    #print(np.mean(np.array((filterEmpty(rows))),axis=1))  #TODO: mittelwert ausrechnen funktioniert noch nicht
+    #exit()
+    #meanvalues=[float(np.mean(x)) for x in filterEmpty(rows)]
+
+    global time_start
+    time_start = time.time()
+    
+
+def update(ctime):
+    global minvalues
+    global maxvalues
+    global meanvalues
+    global rowid
+    global client
+    global lastvalue
+    if rowid>=len(rows): #ended?
+        return False
+
+    if ctime-time_start>=float(rows[rowid][0]):
+        #print(rows[rowid])
+        crow=rows[rowid]
+        for i in range(len(header)-1):
+            if len(crow[i+1])>0: #value not empty
+                value=float(crow[i+1])
+                send=False
+                if (i==0):
+                    value=int(mapRange(value,minvalues[i],maxvalues[i],1,40))
+                    send=True
+                if (i==1):
+                    send=True
+                if (i==2):
+                    send=True
+                if (i==3):
+                    send=True
+                if (i==4):
+                    send=True
+
+                if send:
+                    print(basetopics[i]+"/"+header[i+1]+": "+ str(value))
+                    client.send_message(basetopics[i]+"/"+header[i+1], value)
+
+                lastvalue[i]=value #save last value
+        rowid+=1
+    return True
+
+
+
+def filterEmpty(rows):
+    m=[np.array(rows)[:,i+1]  for i in range(np.shape(np.array(rows))[1]-1)]
+    n=[[x if len(x)>0 else None for x in y] for y in m]
+    n=[list(filter(None, x)) for x in n]
+    return n
+
+def mapRange(value, inMin, inMax, outMin, outMax):
+    return outMin + (((value - inMin) / (inMax - inMin)) * (outMax - outMin))
+
+if __name__ == "__main__":
+    init()
+    res=True
+    while res:
+        res=update(time.time())