Hi I have a question for Matlab programming, I want to ask if I am using Mac OS and I have placed all my audio files in the same folder as Matlab, how do I read all the .wav audio files? I want to automate the process.
Example:
Firstly, I have an excel sheet with the audio file name and information.
Secondly, I want to extract the audio file names from the excel sheet (first column) and put it into the audioread function in MatLab.
I need to use the following audioread function.
[y,Fs]=audioread('audio1.wav');
I want to read audio1.wav and do some calculations on it. After finishing the calculation, I will proceed to read audio2.wav and do the same calculation for it. Can you teach me how to do this and show me the code for this?
Thank you.
In Matlab you can read xls files with readmatrix. You are maybe best to export your spreadsheet of audio files to a csv file first.
With regard to organising the data, it would be easiest for the spreadsheet to contain the full pathname to the file (i.e. /path/from/root/to/file.wav)
So, say you had a audio_files.csv of file paths like
/path/to/file1.wav, file1data
/path/to/file2.wav, file2data
/path/to/file3.wav, file3data
You could read each file with something like
filename = 'audio_files.csv';
audio_file_list = readmatrix(filename);
for audio_file = audio_file_list(:,1) % so long as the first column is the file paths
[y,Fs]=audioread(audio_file);
% do something to y
end
Of course, the % do something to y will depend entirely on what you want to achieve.
Related
I frequent a real estate website that shows recent transactions, from which I will download data to parse within a Pandas dataframe. Everything about this dataset remains identical every time I download it (regarding the column names, that is).
The name of the Excel output may change, though. For example, if I already have download a few of these in my Downloads folder, the file that's exported may read "Generic_File_(3)" or "Generic_File_(21)" if I already have a few older "Generic_File" exports in that folder from a previous export.
Ideally, I'd like my workflow to look like this: export this Excel file of real estate sales, then run a Python script to read in the most recent export as a Pandas dataframe. The catch is, I don't want to have to go in and change the filename in the script to match the appending number of the Excel export everytime. I want the pd.read_excel method to simply read the "Generic_File" that is appended with the largest number (which will obviously correspond to the most rent export).
I suppose I could always just delete old exports out of my Downloads folder so the newest, freshest export is always named the same ("Generic_File", in this case), but I'm looking for a way to ensure I don't have to do this. Are wildcards the best path forward, or is there some other method to always read in the most recently downloaded Excel file from my Downloads folder?
I would use the OS package and create a method to read to file names in the downloads folder. Parsing string filenames you could then find the file following your specified format with the highest copy number. Something like the following might help you get started.
import os
downloads = os.listdir('C:/Users/[username here]/Downloads/')
is_file = [True if '.' in item else False for item in downloads]
files = [item for keep, item in zip(is_file, downloads) if keep]
** INSERT CODE HERE TO IDENTIFY THE FILE OF INTEREST **
Regex might be the best way to find matches if you have a diverse listing of files in your downloads folder.
We have to perform a CSV transformation into another CSV (1 file to 1 file). We are looking for a cheap solution. The first idea that popped into my mind was Excel, but the file will be to big.
1) Is it possible to do a CSV to CSV conversion through XSLT? I can't seem to find a tool or google result which tells me how I could possibly do it.
2) Is there a better approach to do CSV transformations?
Edit:
It should be possible to automate/schedule the process
My answers below
1) No, XSLT only transforms XML files.
2) Yes, as the answer to question 1 is "No", it is reasonable to assert there are better approaches. As CSV is not a standardised format there are a plethora of varied approaches to choose from.
Use Rscript to automate the transformation of CSV:
# Rscript --vanilla myscript.R
Where myscript.R is something like:
csv <- read.csv(file="input.csv",head=TRUE,sep=",")
# Modify your CSV ...
write.csv(data, file = "output.csv")
I use Windows 64bit with 8GB RAM and Matlab 64bit.
I tried to load a .xlsx file into matlab. The file size is around 700MB, containing a sheet with 673928 rows and 43 columns.
First I use the GUI tool 'uiimport'. After choosing the file path and name, the GUI tool needs around 3 minutes to read the .xlsx file, and then shows the data in a table. If I choose "cell array", it needs around 10 minutes to import the data into workspace.
>>whos
Name Size Bytes Class Attributes
NBPPdataV3YOS1 673928x43 3473588728 cell
It works very well, but I have many .xlsx files to import. It is impossible to import each file using GUI tool. So I use the GUI tool to generate function like this
function data = importfile(workbookFile, sheetName, range)
%% Import the data
[~, ~, data] = xlsread(workbookFile, sheetName, range);
data(cellfun(#(x) ~isempty(x) && isnumeric(x) && isnan(x),data)) = {''};
For simply, I ignore some irrelevant code. However, when I use this function to import the data, It does not work well. The used RAM by Matlab and Excel increases dramatically until almost all RAM is used. The data cannot be imported even after 30 minutes.
I also try to do it like this,
filename='E:\data.xlsx';
excelObj = actxserver('Excel.Application');
fileObj = excelObj.Workbooks.Open(filename);
sheetObj = fileObj.Worksheets.get('Item', 'sheet2');
%Read in ranges the same way as xlsread!
indata = sheetObj.Range('A1:AQ673928').Value;
The same problem occurs as xlsread().
My questions are:
1. Does the GUI import tool use xlsread() to read .xlsx file? If yes, why the generated function does not work? If no, which interface it uses?
2. Is there an efficient way to load Excel file into Matlab?
Thanks!
It sounds like you may be keeping the excel file in memory in Matlab. I would suggest looking into making sure you close the connection to each excel file after you have imported its data.
You may also find that the Matlab table class is more memory efficient than the cell class.
Good luck.
In the workspace I have many m-files containing data I'd like to plot.
I have to read them all and save their plot without showing the results (I'll see them after all is done).
The last part can be done this way?
f = figure('Visible', 'off');
plot(x,y);
saveas(f,'figure.fig');
but I don't want to load manually each m-file where x and y are stored.
So I need a way to explore the filesystem and run these statements for each file, manipulate their name and save a jpg with the same name of its m-file.
The dir function will return a structure containing info on the Folders and Files in the current directory
>> FileInfo = dir
Then you need to write code to use that info to automatically navigate the directory structure (using cd for instance), and select the files you want to read.
The function what can also be useful if you're wanting to only look for certain file types, e.g. .mat files.
Not surprisingly, similar questions to this have been asked before, for instance see here
I'm looking to combine a range of different audio files (mp3) in Python. One of the requirements is that I need to be able to specify a delay at the end of each file. To illustrate, something like:
[file1.mp3--------3 seconds----------][delay---------2 seconds--------][file2.mp3]-------------4 seconds][delay---------2 seconds][file3.mp3----------3 seconds---------]
Does anyone here know of any mp3 libraries that can accomplish this? Python isn't really a necessity here. If it'll be easier in another language, that'll be fine.
I think FFmpeg can do this, given the right arguments. No real need to use a library.
To combine wav or aiff files, you can do something like this: (inspiration from here)
import aifc
def concatenate(*items):
data = []
for item in items:
f = aifc.open(item, 'rb')
data.append([f.getparams(), f.readframes(f.getnframes())])
f.close()
output = aifc.open('output.aif', 'wb')
output.setparams(data[0][0])
for item in data:
output.writeframes(item[1])
output.close()
See the link for the wav format (it's pretty much the same, but with the wave library)
To add silence, I would just make a one second silent file using your favorite audio editor and then concatenate in the proper amount of silence.