74 lines
2.7 KiB
Python
74 lines
2.7 KiB
Python
from datetime import datetime, timedelta
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import numpy as np
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class Plot_Data:
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def __init__(self):
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# resolution * timeout must be at least 2-3 times higher then the slowest refresh rate
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self.resolution = 100 # ms
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self.timeout = 100 # cycles
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self.data = {"time": np.array([])}
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self.start_time = datetime.utcnow()
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self.queues = {}
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def clear(self):
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print("clear")
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for key in self.data:
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self.data[key] = np.array([])
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self.start_time = datetime.utcnow()
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def get(self, key):
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return self.data.get(key, np.full_like(self.data["time"], np.nan, dtype=np.double))
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def append_data(self, sensor_name, data):
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""" """
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if sensor_name not in self.data:
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self.queues[sensor_name] = ([], [])
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self.data[sensor_name] = np.full_like(self.data["time"], np.nan, dtype=np.double)
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for time, dat in zip(data[0], data[1]):
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self.queues[sensor_name][0].append(
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(time - self.start_time) / timedelta(milliseconds=self.resolution)
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)
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self.queues[sensor_name][1].append(dat)
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self.extend_timeline()
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self.sort_in_queue()
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self.drop_old()
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def extend_timeline(self):
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# extend numpy arrays with passed time
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# unknown values are filled with nans
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end = (datetime.utcnow() - self.start_time) / timedelta(milliseconds=self.resolution)
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self.data["time"] = np.arange(0, end, 1).astype(np.double)
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for key in self.data:
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if key != "time":
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pad_length = self.data["time"].size - self.data[key].size
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self.data[key] = np.pad(
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self.data[key], (0, pad_length), mode="constant", constant_values=np.nan
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)
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def sort_in_queue(self):
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# linear interpolation and adding it to the array
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for key in self.queues:
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time = np.array(self.queues[key][0])
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data = np.array(self.queues[key][1])
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if time.size > 1:
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inter = np.interp(self.data["time"], time, data, left=np.nan, right=np.nan)
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self.data[key] = np.where(np.isnan(inter), self.data[key], inter)
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def drop_old(self):
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for key in self.queues:
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time = np.array(self.queues[key][0])
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old = self.data["time"][-1] - self.timeout
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if time.size > 2:
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drop_index = np.where(time < old)[0]
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if len(drop_index) is not 0:
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drop_index = drop_index[-1]
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self.queues[key] = (
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self.queues[key][0][drop_index:],
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self.queues[key][1][drop_index:],
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)
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print(drop_index)
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