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Fixed plot data by implementing it the numpy way :D

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This commit is contained in:
Jacob Holder 2021-08-11 01:08:28 +02:00
parent 519b248261
commit d812c00b7c
Signed by: jacob
GPG Key ID: 2194FC747048A7FD
1 changed files with 39 additions and 39 deletions
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78
plot_data.py
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@ -4,15 +4,19 @@ from datetime import datetime, timedelta
class PlotData():
def __init__(self):
self.refresh_rate = 1 # ms
self.timeout = 100 # cycles
self.data = {"time": np.array([0])}
#resolution * timeout must be at least 2-3 times higher then the slowest refresh rate
self.resolution = 100 # ms
self.timeout = 100 #cycles
self.data = {"time": np.array([])}
self.start_time = datetime.utcnow()
self.queues = {}
def clear(self):
print("clear")
for key in self.data:
self.data[key] = np.array([])
self.start_time = datetime.utcnow()
def get(self, key):
return self.data.get(key, np.full_like(self.data["time"], np.nan, dtype=np.double))
@ -22,45 +26,41 @@ class PlotData():
"""
if sensor_name not in self.data:
self.queues[sensor_name] = []
self.queues[sensor_name] = ([],[])
self.data[sensor_name] = np.full_like(self.data["time"], np.nan, dtype=np.double)
for time, dat in zip(data[0], data[1]):
self.queues[sensor_name].append((time, dat))
self.queues[sensor_name][0].append((time-self.start_time)/ timedelta(milliseconds=self.resolution))
self.queues[sensor_name][1].append(dat)
self.extend_timeline()
self.sort_in_queue()
#self.drop_old()
running = True
while running:
# TODO timeout clean and time clean
for sensor, que in self.queues.items():
index = -1
for time, _ in que:
if time < self.start_time \
+ timedelta(milliseconds=int(self.data["time"][-1]) + self.refresh_rate):
index += 1
if index >= 0:
self.queues[sensor] = que[index:]
#TODO timeout not working as intended
#if timeout is reached add empty values on sensors
#if self.start_time + timedelta(milliseconds=int(self.data["time"][-1])+self.timeout) < datetime.utcnow():
# for sensor, que in self.queues.items():
# if len(que) == 0:
# que.append((self.start_time,np.nan))
def extend_timeline(self):
#extend numpy arrays with passed time
#unknown values are filled with nans
end = (datetime.utcnow()-self.start_time)/timedelta(milliseconds=self.resolution)
print(end, self.start_time)
for que in self.queues.values():
if len(que) == 0:
running = False
return
self.data["time"] = np.arange(0, end, 1).astype(np.double)
for key in self.data:
if key != "time":
pad_length = self.data["time"].size-self.data[key].size
self.data[key] = np.pad(self.data[key], (0,pad_length), mode="constant", constant_values=np.nan)
for sensor, que in self.queues.items():
self.data[sensor] = np.append(self.data[sensor], que[0][1])
self.queues[sensor] = que[1:]
self.data["time"] = np.append(self.data["time"],self.data["time"][-1]+self.refresh_rate)
def sort_in_queue(self):
#linear interpolation and adding it to the array
for key in self.queues:
time = np.array(self.queues[key][0])
data = np.array(self.queues[key][1])
if time.size > 1:
inter = np.interp(self.data["time"], time, data)
self.data[key] = inter#np.where(np.isnan(inter), self.data[key], inter)
def drop_old(self):
for key in self.queues:
time = np.array(self.queues[key][0])
old = self.data["time"][-1]-(self.timeout)
if time.size>2:
drop_index = (np.where(time < old)[0])[-1]
self.queues[key] = (self.queues[key][0][drop_index:],self.queues[key][1][drop_index:])
"""
TODO
while true
clean delte all to old values
for q in que:
if q is empty
return
update np array
"""