def filter(inputl,
inputr,
blend_ch1=0,
blend_ch2=0,
feedback_ch1_ch1=0,
feedback_ch1_ch2=0,
feedback_ch2_ch1=0,
feedback_ch2_ch2=0,
feedforward_ch1_ch1=1,
feedforward_ch1_ch2=0,
feedforward_ch2_ch1=0,
feedforward_ch2_ch2=1):
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)
delayfilter = DoubleStereoUniversalFixedDelayLineFilter(100000)
delayfilter.set_input_sampling_rate(sample_rate)
delayfilter.set_input_port(0, infilterL, 0)
delayfilter.set_input_port(1, infilterR, 0)
delayfilter.set_delay_ch1(4800) #50ms
delayfilter.set_delay_ch2(3600) #37.5ms
delayfilter.set_blend_ch1(blend_ch1)
delayfilter.set_blend_ch1(blend_ch2)
delayfilter.set_feedback_ch1_ch1(feedback_ch1_ch1)
delayfilter.set_feedback_ch1_ch2(feedback_ch1_ch2)
delayfilter.set_feedback_ch2_ch1(feedback_ch2_ch1)
delayfilter.set_feedback_ch2_ch2(feedback_ch2_ch2)
delayfilter.set_feedforward_ch1_ch1(feedforward_ch1_ch1)
delayfilter.set_feedforward_ch1_ch2(feedforward_ch1_ch2)
delayfilter.set_feedforward_ch2_ch1(feedforward_ch2_ch1)
delayfilter.set_feedforward_ch2_ch2(feedforward_ch2_ch2)
outfilterl = DoubleOutPointerFilter(outputl, False)
outfilterl.set_input_sampling_rate(sample_rate)
outfilterl.set_input_port(0, delayfilter, 0)
outfilterr = DoubleOutPointerFilter(outputr, False)
outfilterr.set_input_sampling_rate(sample_rate)
outfilterr.set_input_port(0, delayfilter, 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
def filter(inputl, inputr, blend_ch1=0, blend_ch2=0,
feedback_ch1_ch1=0, feedback_ch1_ch2=0, feedback_ch2_ch1=0, feedback_ch2_ch2=0,
feedforward_ch1_ch1=1, feedforward_ch1_ch2=0, feedforward_ch2_ch1=0, feedforward_ch2_ch2=1):
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)
delayfilter = DoubleStereoUniversalFixedDelayLineFilter(5000)
delayfilter.set_input_sampling_rate(sample_rate)
delayfilter.set_input_port(0, infilterL, 0)
delayfilter.set_input_port(1, infilterR, 0)
delayfilter.set_delay_ch1(4800) #50ms
delayfilter.set_delay_ch2(3600) #37.5ms
delayfilter.set_blend_ch1(blend_ch1)
delayfilter.set_blend_ch1(blend_ch2)
delayfilter.set_feedback_ch1_ch1(feedback_ch1_ch1)
delayfilter.set_feedback_ch1_ch2(feedback_ch1_ch2)
delayfilter.set_feedback_ch2_ch1(feedback_ch2_ch1)
delayfilter.set_feedback_ch2_ch2(feedback_ch2_ch2)
delayfilter.set_feedforward_ch1_ch1(feedforward_ch1_ch1)
delayfilter.set_feedforward_ch1_ch2(feedforward_ch1_ch2)
delayfilter.set_feedforward_ch2_ch1(feedforward_ch2_ch1)
delayfilter.set_feedforward_ch2_ch2(feedforward_ch2_ch2)
outfilterl = DoubleOutPointerFilter(outputl, False)
outfilterl.set_input_sampling_rate(sample_rate)
outfilterl.set_input_port(0, delayfilter, 0)
outfilterr = DoubleOutPointerFilter(outputr, False)
outfilterr.set_input_sampling_rate(sample_rate)
outfilterr.set_input_port(0, delayfilter, 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
outfilter_slow = FloatOutPointerFilter(outdata_slow, True) outfilter_slow.set_input_sampling_rate(sampling_rate) outfilter_slow.set_input_port(0, slowattackreleasefilter, 0) outdata_fast = np.zeros((processsize, 1), dtype=np.float32) outfilter_fast = FloatOutPointerFilter(outdata_fast, True) outfilter_fast.set_input_sampling_rate(sampling_rate) outfilter_fast.set_input_port(0, fastattackreleasefilter, 0) outdata_gain = np.zeros((processsize, 1), dtype=np.float32) outfilter_gain = FloatOutPointerFilter(outdata_gain, True) outfilter_gain.set_input_sampling_rate(sampling_rate) outfilter_gain.set_input_port(0, gainfilter, 0) pipelineend = PipelineGlobalSinkFilter() pipelineend.set_input_sampling_rate(sampling_rate) pipelineend.add_filter(inputfilter) pipelineend.add_filter(inputhffilter) pipelineend.add_filter(outfilter) pipelineend.add_filter(outfilter_power) pipelineend.add_filter(outfilter_gain) pipelineend.add_filter(outfilter_slow) pipelineend.add_filter(outfilter_fast) pipelineend.process(processsize) start = 0 stop = processsize x = np.arange(stop, dtype=np.float32) / sampling_rate plt.figure()
attackreleasefilter2 = DoubleAttackReleaseHysteresisFilter(1)
attackreleasefilter2.set_input_sampling_rate(sampling_rate)
attackreleasefilter2.set_input_port(0, infilter, 0)
attackreleasefilter2.set_attack(np.exp(-1/(sampling_rate*1e-3)))
attackreleasefilter2.set_release(np.exp(-1/(sampling_rate*10e-3)))
attackreleasefilter2.set_release_hysteresis(.5)
attackreleasefilter2.set_attack_hysteresis(.9)
outdata2 = np.zeros((processsize, 1), dtype=np.float64)
outfilter_hyst = DoubleOutPointerFilter(outdata2, True)
outfilter_hyst.set_input_sampling_rate(sampling_rate)
outfilter_hyst.set_input_port(0, attackreleasefilter2, 0)
pipelineend = PipelineGlobalSinkFilter()
pipelineend.set_input_sampling_rate(sampling_rate)
pipelineend.add_filter(outfilter)
pipelineend.add_filter(outfilter_hyst)
pipelineend.process(processsize)
start = 0
stop = processsize
x = np.arange(stop, dtype=np.float32) / sampling_rate
plt.figure()
plt.suptitle("Attack Release filters")
plt.plot(x[start:], data[start:stop, 0], label="Original")
plt.plot(x[start:], outdata[start:stop, 0], label="AR filter")
plt.plot(x[start:], outdata2[start:stop, 0], label="AR filter with hysteresis (0.9, 0.5)")
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(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
