Skip to main content

Wrapper for the SDIF library for audio analysis

Project description

SDIF for Python

  • Author: Eduardo Moguillansky
  • Contact: eduardo.moguillansky@gmail.com

This is a python wrapper to IRCAM's sdif library to read and write SDIF files. It consists of a core written in Cython and some other utilities written in Python.


Build


Introduction

Sdif files are used to store time-based analysis. A Sdif file consists of time-tagged frames, each frame consisting of one or more matrices.

Read a Sdif file, read only selected matrices

    
from pysdif import *
sdif = SdifFile("path.sdif")
# get metadata
print(sdif.get_NVTs())
for frame in sdif:
    print(frame.time, frame.signature)
    for matrix in frame:
        if matrix.signature == b'1MAT':
            print(matrix.get_data())

Write a Sdif file modifying a previous one

from pysdif import *
infile = SdifFile("source.sdif")
outfile = SdifFile("out.sdif", "w").clone_definitions(infile)
for inframe in infile:
    if inframe.signature != b'1TRC':
        continue
    with outfile.new_frame(inframe.signature, inframe.time) as outframe:
        for matrix in inframe:
            # 1TRC has columns index, freq, amp, phase
            data = matrix.get_data(copy=True)
            # modify frequency
            data[:,1] *= 2
            outframe.add_matrix(matrix.signature, data)
outfile.close()

Write a SDIF file from scratch

from pysdif import *
import numpy as np

sdif = SdifFile("rbep.sdif", "w")

# Add some metadata. This is optional
sdif.add_NVT({'creator': 'pysdif3'})

# Add any matrix definitions. In this case we add only one definition
# This is a matrix named "RBEP" with 6 columns
# Each row in this matrix represents a breakpoint within a frame
# Index: partial index to which a breakpoint belongs
# Frequency: the freq. of the breakpoint
# Amplitude: the amplitude of the breakpoint
# Phase: the phase
# Bandwidth: the "noisyness" of the breakpoint
# Offset: the time offset in relation to the frame time
sdif.add_matrix_type("RBEP", "Index, Frequency, Amplitude, Phase, Bandwidth, Offset")

# After all matrix types are defined we define the frames. A frame is defined
# in terms of the matrices it accepts.
# Here we define a frame named "RBEP" which takes only matrices of type "RBEP"
sdif.add_frame_type("RBEP", ["RBEP ReassignedBandEnhancedPartials"])

# Now we need to add the data. Since there is just one matrix per frame
# in this sdif we can use the shortcut sdif.new_frame_one_matrix which 
# creates a frame and adds a matrix all at once
# The data is just fake data for the sake of an example
data = np.array([
    [1, 440, 0.1, 0, 0, 0],
    [2, 1000, 0.2, 0, 0, 0], 
], dtype=float)
sdif.new_frame_one_matrix(frame_sig="RBEP", time=0.5, matrix_sig="RBEP", data=data)

# A second frame
data = np.array([
    [1, 442, 0.1, 0, 0, 0],
    [2, 1100, 0.1, 0, 0, 0]
], dtype=float)
sdif.new_frame_one_matrix(frame_sig="RBEP", time=0.6, matrix_sig="RBEP", data=data)

sdif.close()

Documentation

https://pysdif3.readthedocs.io/

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pysdif3-0.5.2.tar.gz (57.8 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page