def filter(input):
infilter = DoubleInPointerFilter(input)
infilter.output_sampling_rate = sampling_rate
attackreleasefilter = DoubleAttackReleaseFilter(1)
attackreleasefilter.input_sampling_rate = sampling_rate
attackreleasefilter.set_input_port(0, infilter, 0)
attackreleasefilter.attack = np.exp(-1 / (sampling_rate * 1e-3))
attackreleasefilter.release = np.exp(-1 / (sampling_rate * 10e-3))
outdata = np.zeros(processsize, dtype=np.float64)
outfilter = DoubleOutPointerFilter(outdata)
outfilter.input_sampling_rate = sampling_rate
outfilter.set_input_port(0, attackreleasefilter, 0)
attackreleasefilter2 = DoubleAttackReleaseHysteresisFilter(1)
attackreleasefilter2.input_sampling_rate = sampling_rate
attackreleasefilter2.set_input_port(0, infilter, 0)
attackreleasefilter2.attack = np.exp(-1 / (sampling_rate * 1e-3))
attackreleasefilter2.release = np.exp(-1 / (sampling_rate * 10e-3))
attackreleasefilter2.release_hysteresis = .5
attackreleasefilter2.attack_hysteresis = .9
outdata2 = np.zeros(processsize, dtype=np.float64)
outfilter_hyst = DoubleOutPointerFilter(outdata2)
outfilter_hyst.input_sampling_rate = sampling_rate
outfilter_hyst.set_input_port(0, attackreleasefilter2, 0)
pipelineend = PipelineGlobalSinkFilter()
pipelineend.input_sampling_rate = sampling_rate
pipelineend.add_filter(outfilter)
pipelineend.add_filter(outfilter_hyst)
pipelineend.process(processsize)
return outdata, outdata2
def process(input_l, input_r): # Populate the outputs output_l = np.zeros(size, dtype=np.float64) output_r = np.zeros(size, dtype=np.float64) # Create the inputs of the pipeline from the numpy arrays infilter_l = DoubleInPointerFilter(input_l, False) infilter_l.input_sampling_rate = sample_rate infilter_r = DoubleInPointerFilter(input_r, False) infilter_r.input_sampling_rate = sample_rate # Create the intermediate buffer and connect it to the inputs buffer = DoubleBufferFilter(2) buffer.input_sampling_rate = sample_rate buffer.set_input_port(0, infilter_l, 0) buffer.set_input_port(1, infilter_r, 0) # Create the outputs and connect them to the buffer outfilter_l = DoubleOutPointerFilter(output_l, False) outfilter_l.input_sampling_rate = sample_rate outfilter_l.set_input_port(0, buffer, 1) outfilter_r = DoubleOutPointerFilter(output_r, False) outfilter_r.input_sampling_rate = sample_rate outfilter_r.set_input_port(0, buffer, 0) # Create the sink of the pipeline sink = PipelineGlobalSinkFilter() sink.input_sampling_rate = sample_rate sink.add_filter(outfilter_l) sink.add_filter(outfilter_r) # Process the pipeline sink.process(size) return (output_l, output_r)
def DoubleConvertFilter2_new_test():
import numpy as np
from ATK.Core import DoubleComplexToRealFilter, PipelineGlobalSinkFilter
from ATK.Core import ComplexDoubleInPointerFilter, DoubleOutPointerFilter
from numpy.testing import assert_equal
input = np.ascontiguousarray(np.arange(1000, dtype=np.complex128))
output = np.ascontiguousarray(np.zeros(1000, dtype=np.float64))
output2 = np.ascontiguousarray(np.zeros(1000, dtype=np.float64))
inputfilter = ComplexDoubleInPointerFilter(input)
convertFilter = DoubleComplexToRealFilter()
outputfilter = DoubleOutPointerFilter(output)
output2filter = DoubleOutPointerFilter(output2)
convertFilter.set_input_port(0, inputfilter, 0)
outputfilter.set_input_port(0, convertFilter, 0)
output2filter.set_input_port(0, convertFilter, 1)
inputfilter.output_sampling_rate = 48000
convertFilter.input_sampling_rate = 48000
outputfilter.input_sampling_rate = 48000
output2filter.input_sampling_rate = 48000
sink = PipelineGlobalSinkFilter()
sink.add_filter(outputfilter)
sink.add_filter(output2filter)
sink.input_sampling_rate = 48000
sink.process(1000)
assert_equal(input, output)
assert_equal(0, output2)
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.input_sampling_rate = sample_rate
infilterR = DoubleInPointerFilter(inputr, False)
infilterR.input_sampling_rate = sample_rate
delayfilter = DoubleDualMultipleUniversalFixedDelayLineFilter(5000)
delayfilter.input_sampling_rate = sample_rate
delayfilter.set_input_port(0, infilterL, 0)
delayfilter.set_input_port(1, infilterR, 0)
delayfilter.set_delay(0, 4800) #50ms
delayfilter.set_delay(1, 3600) #37.5ms
delayfilter.set_blend(0, blend_ch1)
delayfilter.set_blend(1, blend_ch2)
delayfilter.set_feedback(0, 0, feedback_ch1_ch1)
delayfilter.set_feedback(0, 1, feedback_ch1_ch2)
delayfilter.set_feedback(1, 0, feedback_ch2_ch1)
delayfilter.set_feedback(1, 1, feedback_ch2_ch2)
delayfilter.set_feedforward(0, 0, feedforward_ch1_ch1)
delayfilter.set_feedforward(0, 1, feedforward_ch1_ch2)
delayfilter.set_feedforward(1, 0, feedforward_ch2_ch1)
delayfilter.set_feedforward(1, 1, feedforward_ch2_ch2)
outfilterl = DoubleOutPointerFilter(outputl, False)
outfilterl.input_sampling_rate = sample_rate
outfilterl.set_input_port(0, delayfilter, 0)
outfilterr = DoubleOutPointerFilter(outputr, False)
outfilterr.input_sampling_rate = sample_rate
outfilterr.set_input_port(0, delayfilter, 1)
pipelineend = PipelineGlobalSinkFilter()
pipelineend.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(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 PipelineGlobalSinkFilter_usage_test(): import numpy as np from ATK.Core import DoubleInPointerFilter, DoubleOutPointerFilter, PipelineGlobalSinkFilter from numpy.testing import assert_equal input = np.ascontiguousarray(np.arange(1000, dtype=np.float64)[None,:]) output = np.ascontiguousarray(np.zeros(1000, dtype=np.float64)[None,:]) inputfilter = DoubleInPointerFilter(input, False) outputfilter = DoubleOutPointerFilter(output, False) outputfilter.set_input_port(0, inputfilter, 0) inputfilter.output_sampling_rate = 48000 outputfilter.input_sampling_rate = 48000 sink = PipelineGlobalSinkFilter() sink.add_filter(outputfilter) sink.input_sampling_rate = 48000 sink.process(1000) assert_equal(input, output)
outdata_slow = np.zeros((processsize, 1), dtype=np.float32) 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
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 PipelineGlobalSinkFilter_new_test(): from ATK.Core import PipelineGlobalSinkFilter sink = PipelineGlobalSinkFilter() sink.input_sampling_rate = 48000 sink.process(100)
