Esempio n. 1
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def filter(input, blend=0, feedback=0, feedforward=1):
    import numpy as np
    output = np.zeros(input.shape, dtype=np.float64)

    infilter = DoubleInPointerFilter(input, False)
    infilter.set_output_sampling_rate(sample_rate)

    generator = DoubleCachedSinusGeneratorFilter(1, 1)
    generator.set_output_sampling_rate(sample_rate)
    generator.set_volume(1e-3 * sample_rate)
    generator.set_offset(1.5e-3 * sample_rate)

    delayfilter = DoubleUniversalVariableDelayLineFilter(5000)
    delayfilter.set_input_sampling_rate(sample_rate)
    delayfilter.set_input_port(0, infilter, 0)
    delayfilter.set_input_port(1, generator, 0)
    delayfilter.set_blend(blend)
    delayfilter.set_feedback(feedback)
    delayfilter.set_feedforward(feedforward)

    outfilter = DoubleOutPointerFilter(output, False)
    outfilter.set_input_sampling_rate(sample_rate)
    outfilter.set_input_port(0, delayfilter, 0)
    outfilter.process(input.shape[1])

    return output
def filter(input, blend=0, feedback=0, feedforward=1):
    import numpy as np

    output = np.zeros(input.shape, dtype=np.float64)

    infilter = DoubleInPointerFilter(input, False)
    infilter.set_output_sampling_rate(sample_rate)

    generator = DoubleCachedSinusGeneratorFilter(1, 1)
    generator.set_output_sampling_rate(sample_rate)
    generator.set_volume(1e-3 * sample_rate)
    generator.set_offset(1.5e-3 * sample_rate)

    delayfilter = DoubleUniversalVariableDelayLineFilter(5000)
    delayfilter.set_input_sampling_rate(sample_rate)
    delayfilter.set_input_port(0, infilter, 0)
    delayfilter.set_input_port(1, generator, 0)
    delayfilter.set_blend(blend)
    delayfilter.set_feedback(feedback)
    delayfilter.set_feedforward(feedforward)

    outfilter = DoubleOutPointerFilter(output, False)
    outfilter.set_input_sampling_rate(sample_rate)
    outfilter.set_input_port(0, delayfilter, 0)
    outfilter.process(input.shape[1])

    return output
Esempio n. 3
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def filter(input, blend=0, feedback=0, feedforward=1):
  import numpy as np
  output = np.zeros(input.shape, dtype=np.float64)

  infilter = DoubleInPointerFilter(input, False)
  infilter.set_input_sampling_rate(sample_rate)

  noisefilter = DoubleCachedSinusGeneratorFilter(1, 2)
  noisefilter.set_input_sampling_rate(sample_rate)
  noisefilter.set_offset(10000)
  noisefilter.set_volume(2000)
  
  lowfilter = DoubleTimeVaryingBandPassCoefficientsIIRFilter()
  lowfilter.set_input_sampling_rate(sample_rate)
  lowfilter.set_Q(1)
  lowfilter.set_min_frequency(8000)
  lowfilter.set_max_frequency(12000)
  lowfilter.set_number_of_steps(10001)
  lowfilter.set_input_port(0, infilter, 0)
  lowfilter.set_input_port(1, noisefilter, 0)
  
  outfilter = DoubleOutPointerFilter(output, False)
  outfilter.set_input_sampling_rate(sample_rate)
  outfilter.set_input_port(0, lowfilter, 0)
  outfilter.process(input.shape[1])

  return output
Esempio n. 4
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def filter(input):
    import numpy as np
    output = np.zeros(input.shape, dtype=np.float64)

    infilter = DoubleInPointerFilter(input, False)
    infilter.set_input_sampling_rate(sample_rate)

    sinusfilter = DoubleCachedSinusGeneratorFilter(20, 5)
    sinusfilter.set_input_sampling_rate(sample_rate)
    sinusfilter.set_offset(0.5)
    sinusfilter.set_volume(0.5)

    gainfilter = DoubleApplyGainFilter(1)
    gainfilter.set_input_sampling_rate(sample_rate)
    gainfilter.set_input_port(0, infilter, 0)
    gainfilter.set_input_port(1, sinusfilter, 0)

    outfilter = DoubleOutPointerFilter(output, False)
    outfilter.set_input_sampling_rate(sample_rate)
    outfilter.set_input_port(0, gainfilter, 0)
    outfilter.process(input.shape[1])

    return output
Esempio n. 5
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def filter(input):
  import numpy as np
  output = np.zeros(input.shape, dtype=np.float64)

  infilter = DoubleInPointerFilter(input, False)
  infilter.set_input_sampling_rate(sample_rate)

  sinusfilter = DoubleCachedSinusGeneratorFilter(20, 5)
  sinusfilter.set_input_sampling_rate(sample_rate)
  sinusfilter.set_offset(0.5)
  sinusfilter.set_volume(0.5)
  
  gainfilter = DoubleApplyGainFilter(1)
  gainfilter.set_input_sampling_rate(sample_rate)
  gainfilter.set_input_port(0, infilter, 0)
  gainfilter.set_input_port(1, sinusfilter, 0)
  
  outfilter = DoubleOutPointerFilter(output, False)
  outfilter.set_input_sampling_rate(sample_rate)
  outfilter.set_input_port(0, gainfilter, 0)
  outfilter.process(input.shape[1])

  return output
Esempio n. 6
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def filter(input, blend=0, feedback=0, feedforward=1):
    import numpy as np
    output1 = np.zeros(input.shape, dtype=np.float64)
    output2 = np.zeros(input.shape, dtype=np.float64)

    infilter = DoubleInPointerFilter(input, False)
    infilter.set_input_sampling_rate(sample_rate)

    allpass1filter = DoubleCustomIIRFilter()
    allpass1filter.set_input_sampling_rate(sample_rate)
    allpass1filter.set_input_port(0, infilter, 0)
    allpass1filter.set_coefficients_in(
        (0.0000, 0.3855, 0.0000, 1.3313, 0.0000, 1.0000)[::-1])
    allpass1filter.set_coefficients_out(
        (-0.0000, -1.3313, 0.0000, -0.3855, 0)[::-1])

    allpass2filter = DoubleCustomIIRFilter()
    allpass2filter.set_input_sampling_rate(sample_rate)
    allpass2filter.set_input_port(0, infilter, 0)
    allpass2filter.set_coefficients_in(
        (0.0947, 0.0000, 0.8335, 0.0000, 1.0000)[::-1])
    allpass2filter.set_coefficients_out(
        (0.0000, -0.8335, 0.0000, -0.0947)[::-1])

    sinusfilter = DoubleCachedSinusGeneratorFilter(100, 1)
    sinusfilter.set_input_sampling_rate(sample_rate)

    cosinusfilter = DoubleCachedCosinusGeneratorFilter(100, 1)
    cosinusfilter.set_input_sampling_rate(sample_rate)

    applygainFilter = DoubleApplyGainFilter(2)
    applygainFilter.set_input_sampling_rate(sample_rate)
    applygainFilter.set_input_port(0, allpass1filter, 0)
    applygainFilter.set_input_port(1, sinusfilter, 0)
    applygainFilter.set_input_port(2, allpass2filter, 0)
    applygainFilter.set_input_port(3, cosinusfilter, 0)

    volumeFilter = DoubleVolumeFilter()
    volumeFilter.set_input_sampling_rate(sample_rate)
    volumeFilter.set_volume(-1)
    volumeFilter.set_input_port(0, applygainFilter, 1)

    sum1Filter = DoubleSumFilter()
    sum1Filter.set_input_sampling_rate(sample_rate)
    sum1Filter.set_input_port(0, applygainFilter, 0)
    sum1Filter.set_input_port(1, volumeFilter, 0)

    sum2Filter = DoubleSumFilter()
    sum2Filter.set_input_sampling_rate(sample_rate)
    sum2Filter.set_input_port(0, applygainFilter, 0)
    sum2Filter.set_input_port(1, applygainFilter, 1)

    out1filter = DoubleOutPointerFilter(output1, False)
    out1filter.set_input_sampling_rate(sample_rate)
    out1filter.set_input_port(0, sum1Filter, 0)

    out2filter = DoubleOutPointerFilter(output2, False)
    out2filter.set_input_sampling_rate(sample_rate)
    out2filter.set_input_port(0, sum2Filter, 0)

    pipelinesink = PipelineGlobalSinkFilter()
    pipelinesink.set_input_sampling_rate(sample_rate)
    pipelinesink.add_filter(out1filter)
    pipelinesink.add_filter(out2filter)
    pipelinesink.process(input.shape[1])

    return output1, output2
Esempio n. 7
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def filter(input, blend=0, feedback=0, feedforward=1):
  import numpy as np
  output1 = np.zeros(input.shape, dtype=np.float64)
  output2 = np.zeros(input.shape, dtype=np.float64)

  infilter = DoubleInPointerFilter(input, False)
  infilter.set_input_sampling_rate(sample_rate)

  allpass1filter = DoubleCustomIIRFilter()
  allpass1filter.set_input_sampling_rate(sample_rate)
  allpass1filter.set_input_port(0, infilter, 0)
  allpass1filter.set_coefficients_in((0.0000, 0.3855, 0.0000, 1.3313, 0.0000, 1.0000)[::-1])
  allpass1filter.set_coefficients_out((-0.0000, -1.3313, 0.0000, -0.3855, 0)[::-1])

  allpass2filter = DoubleCustomIIRFilter()
  allpass2filter.set_input_sampling_rate(sample_rate)
  allpass2filter.set_input_port(0, infilter, 0)
  allpass2filter.set_coefficients_in((0.0947, 0.0000, 0.8335, 0.0000, 1.0000)[::-1])
  allpass2filter.set_coefficients_out((0.0000, -0.8335, 0.0000, -0.0947)[::-1])

  sinusfilter = DoubleCachedSinusGeneratorFilter(100, 1)
  sinusfilter.set_input_sampling_rate(sample_rate)

  cosinusfilter = DoubleCachedCosinusGeneratorFilter(100, 1)
  cosinusfilter.set_input_sampling_rate(sample_rate)
  
  applygainFilter = DoubleApplyGainFilter(2)
  applygainFilter.set_input_sampling_rate(sample_rate)
  applygainFilter.set_input_port(0, allpass1filter, 0)
  applygainFilter.set_input_port(1, sinusfilter, 0)
  applygainFilter.set_input_port(2, allpass2filter, 0)
  applygainFilter.set_input_port(3, cosinusfilter, 0)

  volumeFilter = DoubleVolumeFilter()
  volumeFilter.set_input_sampling_rate(sample_rate)
  volumeFilter.set_volume(-1)
  volumeFilter.set_input_port(0, applygainFilter, 1)

  sum1Filter = DoubleSumFilter()
  sum1Filter.set_input_sampling_rate(sample_rate)
  sum1Filter.set_input_port(0, applygainFilter, 0)
  sum1Filter.set_input_port(1, volumeFilter, 0)

  sum2Filter = DoubleSumFilter()
  sum2Filter.set_input_sampling_rate(sample_rate)
  sum2Filter.set_input_port(0, applygainFilter, 0)
  sum2Filter.set_input_port(1, applygainFilter, 1)

  out1filter = DoubleOutPointerFilter(output1, False)
  out1filter.set_input_sampling_rate(sample_rate)
  out1filter.set_input_port(0, sum1Filter, 0)

  out2filter = DoubleOutPointerFilter(output2, False)
  out2filter.set_input_sampling_rate(sample_rate)
  out2filter.set_input_port(0, sum2Filter, 0)

  pipelinesink = PipelineGlobalSinkFilter()
  pipelinesink.set_input_sampling_rate(sample_rate)
  pipelinesink.add_filter(out1filter)
  pipelinesink.add_filter(out2filter)
  pipelinesink.process(input.shape[1])

  return output1, output2