MATLAB到Python代码的转换（NumPy，SciPy，MatplotLib?）

Question

我正试图将下面的代码从一个EEG项目的MATLAB转换成Python（部分原因是Python稍微便宜！）

希望有人能给我指出正确的方向：我已经开始修改它，但陷入了困境：特别是试图找到等价的函数。

尝试过scipy.org（NumPy_for_Matlab_Users等），但我不确定我的参数是否是正确的格式/数字）

我最初使用的是pyserial

ser.read()

读取数据然后

ord()

把它转换成一个整数，但是这个MATLAB代码用另一种方式处理它（'uchar'）

我的主要问题是

fopen
fread
find
repmat

以及整个绘图部分，因为我对Python（MatPlotLib？）

MATLAB也倾向于从“1”开始，而Python使用的是0：我也尝试过修改它们，但遗漏了一些我不确定的地方。

Python对用冒号分隔的整个范围满意吗

...repmat(0:2:10, .....

还是不呢？

下面是MATLAB：

% EEG data grabber and plotter

N = 256;    % Required number of sample frames

% Read in a block of data from the OpenEEG board
hCom = serial('COM1','BaudRate',57600,'timeout',5);
fopen(hCom);
numBlocks = (ceil(17*N/256) + 1);
rawdata = zeros(numBlocks*256,1);
for n = 1:numBlocks
    rawdata((0:255) + n*256) = fread(hCom, 256, 'uchar');  % Read data
end
fclose(hCom);

% Convert raw data into a Matlab matrix
% First find the first frame start
startIndex = find(rawdata == 165);
while(rawdata(startIndex(1) + 1) ~= 90)
   startIndex = startIndex(2:end);
end
% Now extract the samples
frameStarts = (0:(N-1))'*17 + startIndex(1);
indices = 4 + repmat(frameStarts, 1, 6) + repmat(0:2:10, length(frameStarts), 1);
eegData = (rawdata(indices)*256 + rawdata(indices + 1)) - 512;
% eegData is now a N by 6 matrix, each column is a channel of sampled data

% Plot time-series data
figure(1)
subplot(2,1,1)
plot((0:255)/256,eegData(:,1:2))
xlabel('Time [s]');
ylabel('EEG data'); 
% Calculate FFT and plot spectra
subplot(2,1,2)
window = 0.5 - 0.5 * cos(2*pi*(0:255)/255); % Von-Hann Window
f = abs(fft(repmat(window',1,2) .* eegData(:,1:2)));
plot((0:127),f(1:128,:))
xlabel('Frequency [Hz]');
ylabel('EEG FFT');

这是我可怜的表弟版本

import scipy
import serial                       #Serial Module to read serial port
from numpy import ceil,zeros        #Ceil module & zeros for blank matrix

N = 256    #no of sample frames (256 = 1s)

#Reads a block of data from the serial port

ser = serial.Serial('COM18',57600,timeout=5)

scipy.fopen(ser)       #MATLAB CODE: fopen(ser)  is this correct????

numBlocks = (ceil(17*N/256) + 1)
rawdata = scipy.zeros(numBlocks*256,1)
for n = 1:numBlocks
    rawdata((0:255) + n*256) = numpyio.fread(ser,256,'i')  # read each byte as     unsigned integer
end
ser.close()


#convert raw data to MATLAB matrix
#find start of frame (1st Byte always 165, 2nd always 90)

startIndex = find(rawdata == 165);
while (rawdata(startIndex(0) + 1) ~=90) #confirms 165,90 sequence
    startIndex = startIndex(1:end) #uses rest of frame as data
end

#Extraction of sample values

#MATLAB CODE
frameStarts = (0: (N-1))'*17 + startIndex(1);      #'#how to transpose matrix('): zip()??
indices = 4 + (numpy.tile(frameStarts, 1,6)) + (numpy.tile(0:2:10,length(frameStarts), 1); 
eegData = (rawdata(indices)*256 + rawdata(indices +1)) - 512  #values are unsigned     integers 0-1023 and must subtract 512 for actual value
#eeg data now N*6 Matrix each column is a channel of data

#MATLAB CODE: plot time series data  (MatPlotLib?)

figure(1)
subplot (2,1,1)
plot((0:255)/256,eegData(:,1:2))
xlabel('Time [s]')
ylabel('EEG Voltage')
#fft
subplot(2,1,2)
window = 0.5 - 0.5*cos(2*pi*(0:255)/255);
f = abs(fft(repmat(window',1,2) .* eegData(:,1:2)))    '#repmat=tile()? matrix     transposition (')?
plot((0:127),f(1:128,:))
xlabel('Freq [Hz]')
ylabel('EEG FFT')

所有的建议都收到了！

戴夫！

Answer 1

这可能起作用，也可能不起作用，但您可能希望尝试使用Matlab到Python的转换器，例如mat2py。我从来没有试过，但可能会省点时间。另外，还有this page关于Matlab到Numpy的转换，可以帮助您了解两者之间的区别。