121 lines
4.4 KiB
Python
121 lines
4.4 KiB
Python
# -*-coding:utf-8 -*-
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"""
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范式buffer和滤波buffer, 以及滤波函数
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"""
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import numpy as np
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from scipy import signal
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import threading
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class ParadigmRingBuffer:
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def __init__(self, n_chan, n_points):
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self.n_chan = n_chan
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self.n_points = n_points
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self.buffer = np.zeros((n_chan, n_points))
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self.currentPtr = 0
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self.readPtr = 0
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self.nUpdate = 0
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self.rawData = np.zeros((n_chan, 1))
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## append buffer and update current pointer
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def appendBuffer(self, data):
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if self.nUpdate == self.n_points:
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raise Exception("Buffer is full")
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n = data.shape[1]
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# 计算可以写入的元素数量
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write_count = min(self.n_points - self.nUpdate, n)
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# 写入新数据
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self.buffer[:, np.mod(np.arange(self.currentPtr, self.currentPtr + write_count), self.n_points)] = data[:,:write_count]
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# 更新结束指针
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self.currentPtr = (self.currentPtr + write_count) % self.n_points
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# 更新大小
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self.nUpdate += write_count
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## get data from buffer
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def getData(self, count=50):
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# 确保不会尝试读取超过缓冲区当前大小的数据
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count = min(count, self.nUpdate)
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# 计算读取结束后的下一个位置
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next_read_ptr = (self.readPtr + count) % self.n_points
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if self.readPtr + count <= self.n_points:
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# 情况 1：不环绕，数据是连续的
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end_index = next_read_ptr if next_read_ptr != 0 else self.n_points
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data = self.buffer[:, self.readPtr:end_index]
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else:
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# 情况 2：发生环绕，数据被分成两部分
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# 第一部分：从 readPtr 到缓冲区末尾
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part1 = self.buffer[:, self.readPtr:]
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# 第二部分：从缓冲区开头到 (count - part1.shape[1]) 个点
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part2 = self.buffer[:, :next_read_ptr]
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# 将两部分在列方向上拼接
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data = np.concatenate((part1, part2), axis=1)
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# 更新读指针
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self.readPtr = next_read_ptr
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# 更新大小
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self.nUpdate -= count
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return data
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def GetDataLenCount(self):
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'''
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获取最新缓存中每个通道的数量
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@return:
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'''
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return self.nUpdate
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# ========== 各范式数据访问接口 ==========
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def get_MIData(self):
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"""获取MI导联数据 (21通道 + 事件)"""
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data = self.getData(self.GetDataLenCount())
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rows_to_extract = [8, 15, 12, 14, 18, 23, 16, 59, 50, 58, 17, 45, 29, 11, 10, 19, 20, 61, 51, 60, 21, 64, 65]
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row_to_select = np.array(rows_to_extract)
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if data.shape[1] > 0:
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return data[row_to_select, :]
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return np.zeros((len(rows_to_extract), 0))
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def get_SSMVEPData(self):
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"""获取SSMVEP导联数据 (8通道 + 事件)"""
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data = self.getData(self.GetDataLenCount())
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rows_to_extract = [13, 3, 2, 46, 9, 54, 47, 55, 64, 65]
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row_to_select = np.array(rows_to_extract)
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if data.shape[1] > 0:
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return data[row_to_select, :]
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return np.zeros((len(rows_to_extract), 0))
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def getDataViaSSVEP(self, count):
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"""获取SSVEP数据 (8通道 + 事件)"""
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data = self.getData(count)
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rows_to_extract = [13, 3, 2, 46, 9, 54, 47, 55, 64]
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row_to_select = np.array(rows_to_extract)
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if data.shape[1] > 0:
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return data[row_to_select, :]
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return np.zeros((len(rows_to_extract), 0))
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def get_concentrateData(self, count):
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"""获取专注力数据 (2通道)"""
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data = self.getData(count)
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rows_to_extract = [0, 1]
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row_to_select = np.array(rows_to_extract)
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if data.shape[1] > 0:
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return data[row_to_select, :]
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return np.zeros((len(rows_to_extract), 0))
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def get_blinkData(self, count):
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"""获取眨眼数据 (2通道)"""
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data = self.getData(count)
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rows_to_extract = [0, 1]
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row_to_select = np.array(rows_to_extract)
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if data.shape[1] > 0:
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return data[row_to_select, :]
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return np.zeros((len(rows_to_extract), 0))
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# reset buffer
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def resetAllPara(self):
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self.nUpdate = 0
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self.currentPtr = 0
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self.readPtr = 0 # add by lizhenhua 清空读指针
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self.buffer = np.zeros((self.n_chan, self.n_points)) # add by lizhenhua 清空环形缓冲区
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