def filter(input, ratio=4, threshold=1, softness=1): import numpy as np output = np.zeros(input.shape, dtype=np.float64) input2 = input**2 in2filter = DoubleInPointerFilter(input2, False) in2filter.set_input_sampling_rate(sample_rate) infilter = DoubleInPointerFilter(input, False) infilter.set_input_sampling_rate(sample_rate) gainfilter = DoubleGainCompressorFilter(1) gainfilter.set_input_sampling_rate(sample_rate) gainfilter.set_input_port(0, in2filter, 0) gainfilter.set_threshold(threshold) gainfilter.set_ratio(ratio) gainfilter.set_softness(softness) applygainfilter = DoubleApplyGainFilter(1) applygainfilter.set_input_sampling_rate(sample_rate) applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, infilter, 0) outfilter = DoubleOutPointerFilter(output, False) outfilter.set_input_sampling_rate(sample_rate) outfilter.set_input_port(0, applygainfilter, 0) outfilter.process(input.shape[1]) return output
def filter(input, ratio=4, threshold=1, softness=1): import numpy as np output = np.zeros(input.shape, dtype=np.float64) input2 = input**2 in2filter = DoubleInPointerFilter(input2, False) in2filter.set_input_sampling_rate(sample_rate) infilter = DoubleInPointerFilter(input, False) infilter.set_input_sampling_rate(sample_rate) gainfilter = DoubleGainExpanderFilter(1) gainfilter.set_input_sampling_rate(sample_rate) gainfilter.set_input_port(0, in2filter, 0) gainfilter.set_threshold(threshold) gainfilter.set_ratio(ratio) gainfilter.set_softness(softness) applygainfilter = DoubleApplyGainFilter(1) applygainfilter.set_input_sampling_rate(sample_rate) applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, infilter, 0) outfilter = DoubleOutPointerFilter(output, False) outfilter.set_input_sampling_rate(sample_rate) outfilter.set_input_port(0, applygainfilter, 0) outfilter.process(input.shape[1]) return output
def max_filter(input, ratio=4, threshold=1, softness=1, max_reduction=0.1):
import numpy as np
output = np.zeros(input.shape, dtype=np.float64)
input2 = input**2
in2filter = DoubleInPointerFilter(input2, False)
in2filter.input_sampling_rate = sample_rate
infilter = DoubleInPointerFilter(input, False)
infilter.input_sampling_rate = sample_rate
gainfilter = DoubleGainMaxCompressorFilter(1)
gainfilter.input_sampling_rate = sample_rate
gainfilter.set_input_port(0, in2filter, 0)
gainfilter.threshold = threshold
gainfilter.ratio = ratio
gainfilter.softness = softness
gainfilter.max_reduction = max_reduction
applygainfilter = DoubleApplyGainFilter(1)
applygainfilter.input_sampling_rate = sample_rate
applygainfilter.set_input_port(0, gainfilter, 0)
applygainfilter.set_input_port(1, infilter, 0)
outfilter = DoubleOutPointerFilter(output, False)
outfilter.input_sampling_rate = sample_rate
outfilter.set_input_port(0, applygainfilter, 0)
outfilter.process(input.shape[1])
return output
def max_colored_filter(input, ratio=4, threshold=1, softness=1, quality=1, color=1, max_reduction=-10): import numpy as np output = np.zeros(input.shape, dtype=np.float64) input2 = input**2 in2filter = DoubleInPointerFilter(input2, False) in2filter.set_input_sampling_rate(sample_rate) infilter = DoubleInPointerFilter(input, False) infilter.set_input_sampling_rate(sample_rate) gainfilter = DoubleGainMaxColoredExpanderFilter(1) gainfilter.set_input_sampling_rate(sample_rate) gainfilter.set_input_port(0, in2filter, 0) gainfilter.set_threshold(threshold) gainfilter.set_ratio(ratio) gainfilter.set_color(color) gainfilter.set_softness(softness) gainfilter.set_quality(quality) gainfilter.set_max_reduction_db(max_reduction) applygainfilter = DoubleApplyGainFilter(1) applygainfilter.set_input_sampling_rate(sample_rate) applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, infilter, 0) outfilter = DoubleOutPointerFilter(output, False) outfilter.set_input_sampling_rate(sample_rate) outfilter.set_input_port(0, applygainfilter, 0) outfilter.process(input.shape[1]) return output
def colored_filter(input, ratio=4, threshold=1, softness=1, quality=1, color=1): import numpy as np output = np.zeros(input.shape, dtype=np.float64) input2 = input**2 in2filter = DoubleInPointerFilter(input2, False) in2filter.input_sampling_rate = sample_rate infilter = DoubleInPointerFilter(input, False) infilter.input_sampling_rate = sample_rate gainfilter = DoubleGainColoredExpanderFilter(1) gainfilter.input_sampling_rate = sample_rate gainfilter.set_input_port(0, in2filter, 0) gainfilter.threshold = threshold gainfilter.ratio = ratio gainfilter.color = color gainfilter.softness = softness gainfilter.quality = quality applygainfilter = DoubleApplyGainFilter(1) applygainfilter.input_sampling_rate = sample_rate applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, infilter, 0) outfilter = DoubleOutPointerFilter(output, False) outfilter.input_sampling_rate = sample_rate outfilter.set_input_port(0, applygainfilter, 0) outfilter.process(input.shape[1]) return output
def max_filter(input, ratio=4, threshold=1, softness=1, max_reduction=0.1): import numpy as np output = np.zeros(input.shape, dtype=np.float64) input2 = input**2 in2filter = DoubleInPointerFilter(input2, False) in2filter.input_sampling_rate = sample_rate infilter = DoubleInPointerFilter(input, False) infilter.input_sampling_rate = sample_rate gainfilter = DoubleGainMaxExpanderFilter(1) gainfilter.input_sampling_rate = sample_rate gainfilter.set_input_port(0, in2filter, 0) gainfilter.threshold = threshold gainfilter.ratio = ratio gainfilter.softness = softness gainfilter.max_reduction = max_reduction applygainfilter = DoubleApplyGainFilter(1) applygainfilter.input_sampling_rate = sample_rate applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, infilter, 0) outfilter = DoubleOutPointerFilter(output, False) outfilter.input_sampling_rate = sample_rate outfilter.set_input_port(0, applygainfilter, 0) outfilter.process(input.shape[1]) return output
def max_colored_filter(input,
ratio=4,
threshold=1,
softness=1,
quality=1,
color=1,
max_reduction=-10):
import numpy as np
output = np.zeros(input.shape, dtype=np.float64)
input2 = input**2
in2filter = DoubleInPointerFilter(input2, False)
in2filter.set_input_sampling_rate(sample_rate)
infilter = DoubleInPointerFilter(input, False)
infilter.set_input_sampling_rate(sample_rate)
gainfilter = DoubleGainMaxColoredExpanderFilter(1)
gainfilter.set_input_sampling_rate(sample_rate)
gainfilter.set_input_port(0, in2filter, 0)
gainfilter.set_threshold(threshold)
gainfilter.set_ratio(ratio)
gainfilter.set_color(color)
gainfilter.set_softness(softness)
gainfilter.set_quality(quality)
gainfilter.set_max_reduction_db(max_reduction)
applygainfilter = DoubleApplyGainFilter(1)
applygainfilter.set_input_sampling_rate(sample_rate)
applygainfilter.set_input_port(0, gainfilter, 0)
applygainfilter.set_input_port(1, infilter, 0)
outfilter = DoubleOutPointerFilter(output, False)
outfilter.set_input_sampling_rate(sample_rate)
outfilter.set_input_port(0, applygainfilter, 0)
outfilter.process(input.shape[1])
return output
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
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) powerfilter = DoublePowerFilter(1) powerfilter.set_input_sampling_rate(sample_rate) powerfilter.set_input_port(0, infilter, 0) powerfilter.set_memory(0) attackreleasefilter = DoubleAttackReleaseFilter(1) attackreleasefilter.set_input_sampling_rate(sample_rate) attackreleasefilter.set_input_port(0, powerfilter, 0) attackreleasefilter.set_attack(0) attackreleasefilter.set_release(np.exp(-1/(sample_rate*10e-3))) gainfilter = DoubleGainCompressorFilter(1) gainfilter.set_input_sampling_rate(sample_rate) gainfilter.set_input_port(0, attackreleasefilter, 0) gainfilter.set_threshold(0.0099) gainfilter.set_ratio(10000) gainfilter.set_softness(1) applygainfilter = DoubleApplyGainFilter(1) applygainfilter.set_input_sampling_rate(sample_rate) applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, infilter, 0) outfilter = DoubleOutPointerFilter(output, False) outfilter.set_input_sampling_rate(sample_rate) outfilter.set_input_port(0, applygainfilter, 0) outfilter.process(input.shape[1]) return output
def max_colored_filter(input,
ratio=4,
threshold=1,
softness=1,
quality=1,
color=1,
max_reduction=-10):
import numpy as np
output = np.zeros(input.shape, dtype=np.float64)
input2 = input**2
in2filter = DoubleInPointerFilter(input2, False)
in2filter.input_sampling_rate = sample_rate
infilter = DoubleInPointerFilter(input, False)
infilter.input_sampling_rate = sample_rate
gainfilter = DoubleGainMaxColoredExpanderFilter(1)
gainfilter.input_sampling_rate = sample_rate
gainfilter.set_input_port(0, in2filter, 0)
gainfilter.threshold = threshold
gainfilter.ratio = ratio
gainfilter.color = color
gainfilter.softness = softness
gainfilter.quality = quality
gainfilter.max_reduction = 10**(max_reduction / 20.)
applygainfilter = DoubleApplyGainFilter(1)
applygainfilter.input_sampling_rate = sample_rate
applygainfilter.set_input_port(0, gainfilter, 0)
applygainfilter.set_input_port(1, infilter, 0)
outfilter = DoubleOutPointerFilter(output, False)
outfilter.input_sampling_rate = sample_rate
outfilter.set_input_port(0, applygainfilter, 0)
outfilter.process(input.shape[1])
return output
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
def filter(input):
import numpy as np
output = np.zeros(input.shape, dtype=np.float64)
infilter = DoubleInPointerFilter(input, False)
infilter.input_sampling_rate = sample_rate
sinusfilter = DoubleSinusGeneratorFilter()
sinusfilter.input_sampling_rate = sample_rate
sinusfilter.offset = 0.5
sinusfilter.volume = 0.5
sinusfilter.frequency = 10
gainfilter = DoubleApplyGainFilter(1)
gainfilter.input_sampling_rate = sample_rate
gainfilter.set_input_port(0, infilter, 0)
gainfilter.set_input_port(1, sinusfilter, 1)
outfilter = DoubleOutPointerFilter(output, False)
outfilter.input_sampling_rate = sample_rate
outfilter.set_input_port(0, gainfilter, 0)
outfilter.process(input.shape[0])
return output
def filter(input):
import numpy as np
output = np.zeros(input.shape, dtype=np.float64)
infilter = DoubleInPointerFilter(input, False)
infilter.input_sampling_rate = sample_rate
powerfilter = DoublePowerFilter(1)
powerfilter.input_sampling_rate = sample_rate
powerfilter.set_input_port(0, infilter, 0)
powerfilter.memory = np.exp(-1 / (sample_rate * 1e-3))
attackreleasefilter = DoubleAttackReleaseFilter(1)
attackreleasefilter.input_sampling_rate = sample_rate
attackreleasefilter.set_input_port(0, powerfilter, 0)
attackreleasefilter.attack = np.exp(-1 / (sample_rate * 1e-3))
attackreleasefilter.release = np.exp(-1 / (sample_rate * 100e-3))
gainfilter = DoubleGainCompressorFilter(1)
gainfilter.input_sampling_rate = sample_rate
gainfilter.set_input_port(0, attackreleasefilter, 0)
gainfilter.threshold = 0.5
gainfilter.ratio = 4
gainfilter.softness = 1
applygainfilter = DoubleApplyGainFilter(1)
applygainfilter.input_sampling_rate = sample_rate
applygainfilter.set_input_port(0, gainfilter, 0)
applygainfilter.set_input_port(1, infilter, 0)
outfilter = DoubleOutPointerFilter(output, False)
outfilter.input_sampling_rate = sample_rate
outfilter.set_input_port(0, applygainfilter, 0)
outfilter.process(input.shape[1])
return output
def filter(input): import numpy as np output = np.zeros(input.shape, dtype=np.float64) infilter = DoubleInPointerFilter(input, False) infilter.input_sampling_rate = sample_rate powerfilter = DoublePowerFilter(1) powerfilter.input_sampling_rate = sample_rate powerfilter.set_input_port(0, infilter, 0) powerfilter.memory = np.exp(-1/(sample_rate*1e-3)) attackreleasefilter = DoubleAttackReleaseFilter(1) attackreleasefilter.input_sampling_rate = sample_rate attackreleasefilter.set_input_port(0, powerfilter, 0) attackreleasefilter.attack = np.exp(-1/(sample_rate*1e-3)) attackreleasefilter.release = np.exp(-1/(sample_rate*100e-3)) gainfilter = DoubleGainCompressorFilter(1) gainfilter.input_sampling_rate = sample_rate gainfilter.set_input_port(0, attackreleasefilter, 0) gainfilter.threshold = 0.5 gainfilter.ratio = 4 gainfilter.softness = 1 applygainfilter = DoubleApplyGainFilter(1) applygainfilter.input_sampling_rate = sample_rate applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, infilter, 0) outfilter = DoubleOutPointerFilter(output, False) outfilter.input_sampling_rate = sample_rate outfilter.set_input_port(0, applygainfilter, 0) outfilter.process(input.shape[1]) return output
def filter(input): import numpy as np output = np.zeros(input.shape, dtype=np.float64) infilter = DoubleInPointerFilter(input, False) infilter.input_sampling_rate = sample_rate sinusfilter = DoubleSinusGeneratorFilter() sinusfilter.input_sampling_rate = sample_rate sinusfilter.offset = 0.5 sinusfilter.volume = 0.5 sinusfilter.frequency = 10 gainfilter = DoubleApplyGainFilter(1) gainfilter.input_sampling_rate = sample_rate gainfilter.set_input_port(0, infilter, 0) gainfilter.set_input_port(1, sinusfilter, 1) outfilter = DoubleOutPointerFilter(output, False) outfilter.input_sampling_rate = sample_rate outfilter.set_input_port(0, gainfilter, 0) outfilter.process(input.shape[0]) return output
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
volumefilter.set_volume(-1) volumefilter.set_input_port(0, slowattackreleasefilter, 0) sumfilter = DoubleSumFilter() sumfilter.set_input_sampling_rate(sampling_rate) sumfilter.set_input_port(0, fastattackreleasefilter, 0) sumfilter.set_input_port(1, volumefilter, 0) gainfilter = DoubleGainCompressorFilter(1) gainfilter.set_input_sampling_rate(sampling_rate) gainfilter.set_input_port(0, sumfilter, 0) gainfilter.set_threshold(.01) gainfilter.set_ratio(.7) gainfilter.set_softness(1) applygainfilter = DoubleApplyGainFilter(1) applygainfilter.set_input_sampling_rate(sampling_rate) applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, infilter, 0) indata = np.zeros((processsize, 1), dtype=np.float32) inputfilter = FloatOutPointerFilter(indata, True) inputfilter.set_input_sampling_rate(sampling_rate) inputfilter.set_input_port(0, infilter, 0) outdata = np.zeros((processsize, 1), dtype=np.float32) outfilter = FloatOutPointerFilter(outdata, True) outfilter.set_input_sampling_rate(sampling_rate) outfilter.set_input_port(0, applygainfilter, 0) outdata_slow = np.zeros((processsize, 1), dtype=np.float32)
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
def filter(inputl, inputr): import numpy as np outputl = np.zeros(inputl.shape, dtype=np.float64) outputr = np.zeros(inputl.shape, dtype=np.float64) infilterL = DoubleInPointerFilter(inputl, False) infilterL.set_input_sampling_rate(sample_rate) infilterR = DoubleInPointerFilter(inputr, False) infilterR.set_input_sampling_rate(sample_rate) mssplitfilter = DoubleMiddleSideFilter() mssplitfilter.set_input_sampling_rate(sample_rate) mssplitfilter.set_input_port(0, infilterL, 0) mssplitfilter.set_input_port(1, infilterR, 0) adaptgainfilter = DoubleVolumeFilter(2) adaptgainfilter.set_input_sampling_rate(sample_rate) adaptgainfilter.set_input_port(0, mssplitfilter, 0) adaptgainfilter.set_input_port(1, mssplitfilter, 1) adaptgainfilter.set_volume(.5) powerfilter1 = DoublePowerFilter() powerfilter1.set_input_sampling_rate(sample_rate) powerfilter1.set_input_port(0, adaptgainfilter, 0) powerfilter1.set_memory(np.exp(-1/(sample_rate*.1e-3))) attackreleasefilter1 = DoubleAttackReleaseFilter() attackreleasefilter1.set_input_sampling_rate(sample_rate) attackreleasefilter1.set_input_port(0, powerfilter1, 0) attackreleasefilter1.set_attack(np.exp(-1/(sample_rate*1e-3))) attackreleasefilter1.set_release(np.exp(-1/(sample_rate*100e-3))) gainfilter1 = DoubleGainCompressorFilter() gainfilter1.set_input_sampling_rate(sample_rate) gainfilter1.set_input_port(0, attackreleasefilter1, 0) gainfilter1.set_threshold(thresholds) gainfilter1.set_ratio(ratios) gainfilter1.set_softness(1) applygainfilter = DoubleApplyGainFilter(2) applygainfilter.set_input_sampling_rate(sample_rate) applygainfilter.set_input_port(0, gainfilter1, 0) applygainfilter.set_input_port(1, mssplitfilter, 0) powerfilter2 = DoublePowerFilter(1) powerfilter2.set_input_sampling_rate(sample_rate) powerfilter2.set_input_port(0, adaptgainfilter, 1) powerfilter2.set_memory(np.exp(-1/(sample_rate*.1e-3))) attackreleasefilter2 = DoubleAttackReleaseFilter() attackreleasefilter2.set_input_sampling_rate(sample_rate) attackreleasefilter2.set_input_port(0, powerfilter1, 0) attackreleasefilter2.set_attack(np.exp(-1/(sample_rate*1e-3))) attackreleasefilter2.set_release(np.exp(-1/(sample_rate*100e-3))) gainfilter2 = DoubleGainCompressorFilter() gainfilter2.set_input_sampling_rate(sample_rate) gainfilter2.set_input_port(0, attackreleasefilter2, 0) gainfilter2.set_threshold(thresholds) gainfilter2.set_ratio(ratios) gainfilter2.set_softness(1) applygainfilter.set_input_port(2, gainfilter2, 0) applygainfilter.set_input_port(3, mssplitfilter, 1) msmergefilter = DoubleMiddleSideFilter() msmergefilter.set_input_sampling_rate(sample_rate) msmergefilter.set_input_port(0, applygainfilter, 0) msmergefilter.set_input_port(1, applygainfilter, 1) volumefilter = DoubleVolumeFilter(2) volumefilter.set_input_sampling_rate(sample_rate) volumefilter.set_volume(.5) volumefilter.set_input_port(0, msmergefilter, 0) volumefilter.set_input_port(1, msmergefilter, 1) outfilterl = DoubleOutPointerFilter(outputl, False) outfilterl.set_input_sampling_rate(sample_rate) outfilterl.set_input_port(0, volumefilter, 0) outfilterr = DoubleOutPointerFilter(outputr, False) outfilterr.set_input_sampling_rate(sample_rate) outfilterr.set_input_port(0, volumefilter, 1) pipelineend = PipelineGlobalSinkFilter() pipelineend.set_input_sampling_rate(sample_rate) pipelineend.add_filter(outfilterl) pipelineend.add_filter(outfilterr) pipelineend.process(inputl.shape[1]) return outputl, outputr
sumfilter.set_input_sampling_rate(sampling_rate) sumfilter.set_input_port(0, fastattackreleasefilter, 0) sumfilter.set_input_port(1, volumefilter, 0) gainfilter = DoubleGainSwellFilter(1) gainfilter.set_input_sampling_rate(sampling_rate) gainfilter.set_input_port(0, sumfilter, 0) gainfilter.set_threshold(.1) gainfilter.set_ratio(1) gainfilter.set_softness(1) oneminusfilter = DoubleOneMinusFilter(1) oneminusfilter.set_input_sampling_rate(sampling_rate) oneminusfilter.set_input_port(0, gainfilter, 0) applygainfilter = DoubleApplyGainFilter(2) applygainfilter.set_input_sampling_rate(sampling_rate) applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, infilter, 0) applygainfilter.set_input_port(2, oneminusfilter, 0) applygainfilter.set_input_port(3, infilter, 0) indata = np.zeros((processsize, 1), dtype=np.float32) inputfilter = FloatOutPointerFilter(indata, True) inputfilter.set_input_sampling_rate(sampling_rate) inputfilter.set_input_port(0, infilter, 0) outdata = np.zeros((processsize, 1), dtype=np.float32) outfilter = FloatOutPointerFilter(outdata, True) outfilter.set_input_sampling_rate(sampling_rate) outfilter.set_input_port(0, applygainfilter, 0)
volumefilter.set_volume(-1) volumefilter.set_input_port(0, slowattackreleasefilter, 0) sumfilter = DoubleSumFilter() sumfilter.set_input_sampling_rate(sampling_rate) sumfilter.set_input_port(0, fastattackreleasefilter, 0) sumfilter.set_input_port(1, volumefilter, 0) gainfilter = DoubleGainCompressorFilter(1) gainfilter.set_input_sampling_rate(sampling_rate) gainfilter.set_input_port(0, sumfilter, 0) gainfilter.set_threshold(.002) gainfilter.set_ratio(.7) gainfilter.set_softness(1) applygainfilter = DoubleApplyGainFilter(1) applygainfilter.set_input_sampling_rate(sampling_rate) applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, infilter, 0) indata = np.zeros((processsize, 1), dtype=np.float32) inputfilter = FloatOutPointerFilter(indata, True) inputfilter.set_input_sampling_rate(sampling_rate) inputfilter.set_input_port(0, infilter, 0) inhfdata = np.zeros((processsize, 1), dtype=np.float32) inputhffilter = FloatOutPointerFilter(inhfdata, True) inputhffilter.set_input_sampling_rate(sampling_rate) inputhffilter.set_input_port(0, hffilter, 0) outdata = np.zeros((processsize, 1), dtype=np.float32)
attackreleasefilters = DoubleAttackReleaseFilter(1) attackreleasefilters.set_input_sampling_rate(sampling_rate) attackreleasefilters.set_input_port(0, powerfilter, 1) attackreleasefilters.set_attack(np.exp(-1/(sampling_rate*10e-3))) attackreleasefilters.set_release(np.exp(-1/(sampling_rate*1000e-3))) gainfilter = DoubleGainCompressorFilter(2) gainfilter.set_input_sampling_rate(sampling_rate) gainfilter.set_input_port(0, attackreleasefilterm, 0) gainfilter.set_input_port(1, attackreleasefilters, 0) gainfilter.set_threshold(0.1) gainfilter.set_ratio(10) gainfilter.set_softness(1) applygainfilter = DoubleApplyGainFilter(2) applygainfilter.set_input_sampling_rate(sampling_rate) applygainfilter.set_input_port(0, gainfilter, 0) applygainfilter.set_input_port(1, msfilter, 0) applygainfilter.set_input_port(2, gainfilter, 1) applygainfilter.set_input_port(3, msfilter, 1) msmergefilter = FloatMiddleSideFilter() msmergefilter.set_input_sampling_rate(sampling_rate) msmergefilter.set_input_port(0, applygainfilter, 0) msmergefilter.set_input_port(1, applygainfilter, 1) volumefilter2 = FloatVolumeFilter(2) volumefilter2.set_input_sampling_rate(sampling_rate) volumefilter2.set_input_port(0, msmergefilter, 0) volumefilter2.set_input_port(1, msmergefilter, 1)
