libcw/py : Initial commit.
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kevin
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a6754015fe
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38
py/dsp_recorder_plot.py
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38
py/dsp_recorder_plot.py
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# Plot the output of a libcw:cwDspTransform.cpp: 'recorder' object.
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import sys,os,json
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import matplotlib.pyplot as plt
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def plot_file( fname ):
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r = None
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with open(fname,"r") as f:
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r = json.load(f)
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idx = 0
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while True:
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label = "{}".format(idx)
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if label not in r:
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break
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plt.plot(r[label])
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idx += 1
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plt.show()
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if __name__ == "__main__":
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fname = os.path.expanduser("~/temp/temp_1.json")
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if len(sys.argv) > 1:
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fname = sys.argv[1]
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plot_file( fname )
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103
py/gen_midi_csv.py
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py/gen_midi_csv.py
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import csv,os
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def gen_sample_midi_csv(pitch,velA,note_on_sec,note_off_sec):
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markA = []
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msgA = []
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tpqn = 1260
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bpm = 60
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ticks_per_sec = tpqn * bpm / 60.0
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ticks_per_note_on = ticks_per_sec * note_on_sec
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ticks_per_note_off = ticks_per_sec * note_off_sec
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uid = 0
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dticks = 0
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cur_sec = 0;
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r = { 'uid':len(msgA),
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'tpQN':tpqn,
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'bpm':bpm,
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'dticks':0,
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'ch':None,
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'status':None,
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'd0':None,
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'd1':None }
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msgA.append(r);
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for vel in velA:
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ch = 0
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status = 0x90
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r = { 'uid':len(msgA),
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'tpQN':None,
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'bpm':None,
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'dticks':dticks,
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'ch':ch,
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'status':status,
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'd0':pitch,
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'd1':vel }
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msgA.append(r)
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dticks = ticks_per_note_on
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r = { 'uid':len(msgA),
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'tpQN':None,
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'bpm':None,
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'dticks':dticks,
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'ch':ch,
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'status':status,
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'd0':pitch,
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'd1':0 }
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msgA.append(r)
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dticks = ticks_per_note_off
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markA.append( (cur_sec, cur_sec+note_on_sec, vel) )
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cur_sec += note_on_sec + note_off_sec
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return msgA,markA
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def write_file( fname, msgA ):
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fieldnames = list(msgA[0].keys())
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with open(fname,"w") as f:
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wtr = csv.DictWriter(f, fieldnames=fieldnames)
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wtr.writeheader()
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for m in msgA:
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wtr.writerow(m)
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def write_marker_file(fname, markA ):
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with open(fname,"w") as f:
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for beg_sec,end_sec,vel in markA:
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f.write(f"{beg_sec}\t{end_sec}\t{vel}\n")
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if __name__ == "__main__":
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out_dir = "/home/kevin/temp/wt"
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note_on_sec = 1.0
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note_off_sec = 0.5
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pitch = 60
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velA = [1,8,15,22,29,36,42,49,56,63,70,77,84,91,98,105,112,119,126]
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msgA,markA = gen_sample_midi_csv(60,velA,note_on_sec,note_off_sec)
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midi_csv_fname = os.path.join(out_dir,f"{pitch}_sample.csv")
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mark_fname = os.path.join(out_dir,f"{pitch}_marker.txt")
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print(midi_csv_fname)
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print(mark_fname)
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write_file(midi_csv_fname,msgA)
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write_marker_file(mark_fname,markA)
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282
py/sample_looper.py
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282
py/sample_looper.py
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import math
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import json
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import wave as w
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import array
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import types
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import matplotlib.pyplot as plt
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import numpy as np
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def parse_marker_file( marker_fname ):
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markL = []
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with open(marker_fname) as f:
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for line in f:
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tokL = line.split("\t");
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assert( len(tokL) == 3 )
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markL.append( ( float(tokL[0]), float(tokL[1]), tokL[2] ) )
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return markL
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def parse_audio_file( audio_fname ):
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with w.open(audio_fname,"rb") as f:
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print(f"ch:{f.getnchannels()} bits:{f.getsampwidth()} srate:{f.getframerate()} frms:{f.getnframes()}")
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srate = f.getframerate()
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frmN = f.getnframes()
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data_bytes = f.readframes(frmN)
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smpM = np.array(array.array('i',data_bytes))
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smpM = np.reshape(smpM,(frmN,2))
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if 0:
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fig, ax = plt.subplots(1,1)
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ax.plot(smpM[0:48000*10,1])
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plt.show()
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return smpM,srate
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def plot_overlap( xV, bi, ei, wndN, smp_per_cycle, title ):
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fig, ax = plt.subplots(1,1)
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x0 = [ i for i in range(bi-wndN,bi+wndN) ]
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x1 = [ x-x0[0] for x in x0 ]
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ax.plot(x1,xV[x0])
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x0 = [ i for i in range(ei-wndN,ei+wndN) ]
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x1 = [ x-x0[0] for x in x0 ]
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ax.plot(x1,xV[x0])
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plt.title(title)
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plt.show()
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def sign(x):
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return x<0
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def find_zero_crossing( xV, si, inc ):
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while si > 0:
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if sign(xV[si-1]) != sign(xV[si]):
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break;
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si += inc
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return si
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def meas_fit(xV,ei,bi,wndN):
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v0 = xV[ei-wndN:ei+wndN]/0x7fffffff
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v1 = xV[bi-wndN:bi+wndN]/0x7fffffff
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dv = (v1-v0) * (v1-v0)
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return np.mean(dv)
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def find_loop_points( xV, bsi, esi, smp_per_cycle, wndN, est_N ):
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ei = find_zero_crossing(xV,esi,-1)
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min_d = None
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min_bi = None
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bi = bsi
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for i in range(0,est_N):
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bi = find_zero_crossing(xV,bi,1)
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d = meas_fit(xV,ei,bi,wndN)
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#print(i,bi,d)
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if min_bi is None or d < min_d:
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min_d = d
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min_bi = bi
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bi += int(wndN/2) #smp_per_cycle
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return min_bi, ei, min_d
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def process_all_samples_0( markL, smpM, srate, args ):
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wtL = []
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fund_hz = 13.75 * math.pow(2,(-9.0/12.0)) * math.pow(2.0,(args.midi_pitch / 12.0))
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end_offs_smp_idx = int(args.end_offset_ms * srate / 1000)
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loop_dur_smp = int(args.loop_dur_ms * srate / 1000)
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smp_per_cycle = int(srate / fund_hz)
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print(f"Hz:{fund_hz} smp/cycle:{smp_per_cycle}")
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for beg_sec,end_sec,vel_label in markL:
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for ch_idx in range(0,smpM.shape[1]):
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beg_smp_idx = int(beg_sec * srate)
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end_smp_idx = int(end_sec * srate)
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eli = end_smp_idx - end_offs_smp_idx
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bli = eli - loop_dur_smp
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#print(beg_smp_idx,bli,eli,end_smp_idx)
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xV = smpM[:,ch_idx]
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wndN = int(smp_per_cycle/3)
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bi,ei,cost = find_loop_points(xV,bli,eli,smp_per_cycle,wndN,args.guess_cnt)
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plot_title = f"vel:{vel_label} ch:{ch_idx} cost:{math.log(cost):.2f}"
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#plot_overlap(xV,bi,ei,wndN,smp_per_cycle,plot_title)
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wtL.append( {
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"pitch":args.midi_pitch,
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"vel": int(vel_label),
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"cost":cost,
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"ch_idx":ch_idx,
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"beg_smp_idx":beg_smp_idx,
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"end_smp_idx":end_smp_idx,
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"beg_loop_idx":bi,
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"end_loop_idx":ei })
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return wtL
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def process_all_samples( markL, smpM, srate, args ):
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wtL = []
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fund_hz = 13.75 * math.pow(2,(-9.0/12.0)) * math.pow(2.0,(args.midi_pitch / 12.0))
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end_offs_smp_idx = int(args.end_offset_ms * srate / 1000)
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loop_dur_smp = int(args.loop_dur_ms * srate / 1000)
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smp_per_cycle = int(srate / fund_hz)
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print(f"Hz:{fund_hz} smp/cycle:{smp_per_cycle}")
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for beg_sec,end_sec,vel_label in markL:
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beg_smp_idx = int(beg_sec * srate)
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end_smp_idx = int(end_sec * srate)
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r = {
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"instr":"piano",
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"pitch":args.midi_pitch,
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"vel": int(vel_label),
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"beg_smp_idx":beg_smp_idx,
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"end_smp_idx":None,
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"chL": []
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}
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eli = end_smp_idx - end_offs_smp_idx
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bli = eli - loop_dur_smp
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esi = beg_smp_idx;
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for ch_idx in range(0,smpM.shape[1]):
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xV = smpM[:,ch_idx]
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wndN = int(smp_per_cycle/3)
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bi,ei,cost = find_loop_points(xV,bli,eli,smp_per_cycle,wndN,args.guess_cnt)
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plot_title = f"vel:{vel_label} ch:{ch_idx} cost:{math.log(cost):.2f}"
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#plot_overlap(xV,bi,ei,wndN,smp_per_cycle,plot_title)
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r["chL"].append({
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"ch_idx":ch_idx,
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"segL":[] })
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r["chL"][ch_idx]["segL"].append({
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"cost":0,
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"bsi":beg_smp_idx,
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"esi":bi })
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r["chL"][ch_idx]["segL"].append({
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"cost":cost,
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"bsi":bi,
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"esi":ei })
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esi = max(esi,ei)
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r['end_smp_idx'] = esi
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wtL.append(r)
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return wtL
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def write_loop_label_file_0( fname, wtL, srate ):
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with open(fname,"w") as f:
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for r in wtL:
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beg_sec = r['beg_smp_idx'] / srate
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end_sec = r['end_smp_idx'] / srate
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# f.write(f"{beg_sec}\t{end_sec}\t{r['vel_label']}\n")
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beg_sec = r['beg_loop_idx'] / srate
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end_sec = r['end_loop_idx'] / srate
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cost = math.log(r['cost'])
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label = f"ch:{r['ch_idx']} {cost:.2f}"
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f.write(f"{beg_sec}\t{end_sec}\t{label}\n")
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def write_loop_label_file( fname, wtL, srate ):
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with open(fname,"w") as f:
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for r in wtL:
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for cr in r['chL']:
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for sr in cr['segL']:
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beg_sec = sr['bsi'] / srate
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end_sec = sr['esi'] / srate
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if sr['cost']!=0:
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cost = math.log(sr['cost'])
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label = f"ch:{cr['ch_idx']} {cost:.2f}"
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f.write(f"{r['vel']} {beg_sec}\t{end_sec}\t{label}\n")
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def write_wt_file( fname, audio_fname, wtL, srate ):
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r = {
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"audio_fname":audio_fname,
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"srate":srate,
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"wt":wtL
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}
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with open(fname,"w") as f:
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json.dump(r,f);
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if __name__ == "__main__":
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audio_fname = "/home/kevin/temp/wt/wav/60_samples.wav"
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marker_fname = "/home/kevin/temp/wt/60_marker.txt"
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loop_marker_fname = "/home/kevin/temp/wt/60_loop_mark.txt"
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wt_fname = "/home/kevin/temp/wt/bank/60_wt.json"
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midi_pitch = 60
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args = {
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'end_offset_ms':100,
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'loop_dur_ms':100,
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'midi_pitch':midi_pitch,
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'guess_cnt':40
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}
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args = types.SimpleNamespace(**args)
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markL = parse_marker_file(marker_fname)
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smpM,srate = parse_audio_file(audio_fname)
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chN = smpM.shape[1]
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wtL = process_all_samples(markL,smpM,srate,args)
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write_loop_label_file(loop_marker_fname, wtL, srate)
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write_wt_file(wt_fname,audio_fname, wtL,srate)
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