def __coord_cqt_hz(n, fmin=None, bins_per_octave=12, **_kwargs):
'''Get CQT bin frequencies'''
if fmin is None:
fmin = core.note_to_hz('C1')
return core.cqt_frequencies(n + 1,
fmin=fmin,
bins_per_octave=bins_per_octave)
def __scale_axes(axes, ax_type, which):
"""Set the axis scaling"""
kwargs = dict()
if which == "x":
if version_parse(matplotlib.__version__) < version_parse("3.3.0"):
thresh = "linthreshx"
base = "basex"
scale = "linscalex"
else:
thresh = "linthresh"
base = "base"
scale = "linscale"
scaler = axes.set_xscale
limit = axes.set_xlim
else:
if version_parse(matplotlib.__version__) < version_parse("3.3.0"):
thresh = "linthreshy"
base = "basey"
scale = "linscaley"
else:
thresh = "linthresh"
base = "base"
scale = "linscale"
scaler = axes.set_yscale
limit = axes.set_ylim
# Map ticker scales
if ax_type == "mel":
mode = "symlog"
kwargs[thresh] = 1000.0
kwargs[base] = 2
elif ax_type in ["cqt", "cqt_hz", "cqt_note", "cqt_svara"]:
mode = "log"
kwargs[base] = 2
elif ax_type in ["log", "fft_note", "fft_svara"]:
mode = "symlog"
kwargs[base] = 2
kwargs[thresh] = core.note_to_hz("C2")
kwargs[scale] = 0.5
elif ax_type in ["tempo", "fourier_tempo"]:
mode = "log"
kwargs[base] = 2
limit(16, 480)
else:
return
scaler(mode, **kwargs)
def __scale_axes(axes, ax_type, which):
'''Set the axis scaling'''
kwargs = dict()
if which == 'x':
thresh = 'linthreshx'
base = 'basex'
scale = 'linscalex'
scaler = axes.set_xscale
limit = axes.set_xlim
else:
thresh = 'linthreshy'
base = 'basey'
scale = 'linscaley'
scaler = axes.set_yscale
limit = axes.set_ylim
# Map ticker scales
if ax_type == 'mel':
mode = 'symlog'
kwargs[thresh] = 1000.0
kwargs[base] = 2
elif ax_type == 'log':
mode = 'symlog'
kwargs[base] = 2
kwargs[thresh] = core.note_to_hz('C2')
kwargs[scale] = 0.5
elif ax_type in ['cqt', 'cqt_hz', 'cqt_note']:
mode = 'log'
kwargs[base] = 2
elif ax_type == 'tempo':
mode = 'log'
kwargs[base] = 2
limit(16, 480)
else:
return
scaler(mode, **kwargs)
def __coord_cqt_hz(n, fmin=None, bins_per_octave=12, sr=22050, **_kwargs):
"""Get CQT bin frequencies"""
if fmin is None:
fmin = core.note_to_hz("C1")
# Apply tuning correction
fmin = fmin * 2.0**(_kwargs.get("tuning", 0.0) / bins_per_octave)
# we drop by half a bin so that CQT bins are centered vertically
freqs = core.cqt_frequencies(
n + 1,
fmin=fmin / 2.0**(0.5 / bins_per_octave),
bins_per_octave=bins_per_octave,
)
if np.any(freqs > 0.5 * sr):
warnings.warn(
"Frequency axis exceeds Nyquist. "
"Did you remember to set all spectrogram parameters in specshow?")
return freqs
def __decorate_axis(axis,
ax_type,
key="C:maj",
Sa=None,
mela=None,
thaat=None):
"""Configure axis tickers, locators, and labels"""
if ax_type == "tonnetz":
axis.set_major_formatter(TonnetzFormatter())
axis.set_major_locator(FixedLocator(0.5 + np.arange(6)))
axis.set_label_text("Tonnetz")
elif ax_type == "chroma":
axis.set_major_formatter(ChromaFormatter(key=key))
degrees = core.key_to_degrees(key)
axis.set_major_locator(
FixedLocator(0.5 +
np.add.outer(12 * np.arange(10), degrees).ravel()))
axis.set_label_text("Pitch class")
elif ax_type == "chroma_h":
if Sa is None:
Sa = 0
axis.set_major_formatter(ChromaSvaraFormatter(Sa=Sa))
if thaat is None:
# If no thaat is given, show all svara
degrees = np.arange(12)
else:
degrees = core.thaat_to_degrees(thaat)
# Rotate degrees relative to Sa
degrees = np.mod(degrees + Sa, 12)
axis.set_major_locator(
FixedLocator(0.5 +
np.add.outer(12 * np.arange(10), degrees).ravel()))
axis.set_label_text("Svara")
elif ax_type == "chroma_c":
if Sa is None:
Sa = 0
axis.set_major_formatter(ChromaSvaraFormatter(Sa=Sa, mela=mela))
degrees = core.mela_to_degrees(mela)
# Rotate degrees relative to Sa
degrees = np.mod(degrees + Sa, 12)
axis.set_major_locator(
FixedLocator(0.5 +
np.add.outer(12 * np.arange(10), degrees).ravel()))
axis.set_label_text("Svara")
elif ax_type in ["tempo", "fourier_tempo"]:
axis.set_major_formatter(ScalarFormatter())
axis.set_major_locator(LogLocator(base=2.0))
axis.set_label_text("BPM")
elif ax_type == "time":
axis.set_major_formatter(TimeFormatter(unit=None, lag=False))
axis.set_major_locator(
MaxNLocator(prune=None, steps=[1, 1.5, 5, 6, 10]))
axis.set_label_text("Time")
elif ax_type == "s":
axis.set_major_formatter(TimeFormatter(unit="s", lag=False))
axis.set_major_locator(
MaxNLocator(prune=None, steps=[1, 1.5, 5, 6, 10]))
axis.set_label_text("Time (s)")
elif ax_type == "ms":
axis.set_major_formatter(TimeFormatter(unit="ms", lag=False))
axis.set_major_locator(
MaxNLocator(prune=None, steps=[1, 1.5, 5, 6, 10]))
axis.set_label_text("Time (ms)")
elif ax_type == "lag":
axis.set_major_formatter(TimeFormatter(unit=None, lag=True))
axis.set_major_locator(
MaxNLocator(prune=None, steps=[1, 1.5, 5, 6, 10]))
axis.set_label_text("Lag")
elif ax_type == "lag_s":
axis.set_major_formatter(TimeFormatter(unit="s", lag=True))
axis.set_major_locator(
MaxNLocator(prune=None, steps=[1, 1.5, 5, 6, 10]))
axis.set_label_text("Lag (s)")
elif ax_type == "lag_ms":
axis.set_major_formatter(TimeFormatter(unit="ms", lag=True))
axis.set_major_locator(
MaxNLocator(prune=None, steps=[1, 1.5, 5, 6, 10]))
axis.set_label_text("Lag (ms)")
elif ax_type == "cqt_note":
axis.set_major_formatter(NoteFormatter(key=key))
# Where is C1 relative to 2**k hz?
log_C1 = np.log2(core.note_to_hz("C1"))
C_offset = 2.0**(log_C1 - np.floor(log_C1))
axis.set_major_locator(LogLocator(base=2.0, subs=(C_offset, )))
axis.set_minor_formatter(NoteFormatter(key=key, major=False))
axis.set_minor_locator(
LogLocator(base=2.0,
subs=C_offset * 2.0**(np.arange(1, 12) / 12.0)))
axis.set_label_text("Note")
elif ax_type == "cqt_svara":
axis.set_major_formatter(SvaraFormatter(Sa=Sa, mela=mela))
# Find the offset of Sa relative to 2**k Hz
sa_offset = 2.0**(np.log2(Sa) - np.floor(np.log2(Sa)))
axis.set_major_locator(LogLocator(base=2.0, subs=(sa_offset, )))
axis.set_minor_formatter(SvaraFormatter(Sa=Sa, mela=mela, major=False))
axis.set_minor_locator(
LogLocator(base=2.0,
subs=sa_offset * 2.0**(np.arange(1, 12) / 12.0)))
axis.set_label_text("Svara")
elif ax_type in ["cqt_hz"]:
axis.set_major_formatter(LogHzFormatter())
log_C1 = np.log2(core.note_to_hz("C1"))
C_offset = 2.0**(log_C1 - np.floor(log_C1))
axis.set_major_locator(LogLocator(base=2.0, subs=(C_offset, )))
axis.set_major_locator(LogLocator(base=2.0))
axis.set_minor_formatter(LogHzFormatter(major=False))
axis.set_minor_locator(
LogLocator(base=2.0,
subs=C_offset * 2.0**(np.arange(1, 12) / 12.0)))
axis.set_label_text("Hz")
elif ax_type == "fft_note":
axis.set_major_formatter(NoteFormatter(key=key))
# Where is C1 relative to 2**k hz?
log_C1 = np.log2(core.note_to_hz("C1"))
C_offset = 2.0**(log_C1 - np.floor(log_C1))
axis.set_major_locator(SymmetricalLogLocator(axis.get_transform()))
axis.set_minor_formatter(NoteFormatter(key=key, major=False))
axis.set_minor_locator(
LogLocator(base=2.0, subs=2.0**(np.arange(1, 12) / 12.0)))
axis.set_label_text("Note")
elif ax_type == "fft_svara":
axis.set_major_formatter(SvaraFormatter(Sa=Sa, mela=mela))
# Find the offset of Sa relative to 2**k Hz
log_Sa = np.log2(Sa)
sa_offset = 2.0**(log_Sa - np.floor(log_Sa))
axis.set_major_locator(
SymmetricalLogLocator(axis.get_transform(),
base=2.0,
subs=[sa_offset]))
axis.set_minor_formatter(SvaraFormatter(Sa=Sa, mela=mela, major=False))
axis.set_minor_locator(
LogLocator(base=2.0,
subs=sa_offset * 2.0**(np.arange(1, 12) / 12.0)))
axis.set_label_text("Svara")
elif ax_type in ["mel", "log"]:
axis.set_major_formatter(ScalarFormatter())
axis.set_major_locator(SymmetricalLogLocator(axis.get_transform()))
axis.set_label_text("Hz")
elif ax_type in ["linear", "hz", "fft"]:
axis.set_major_formatter(ScalarFormatter())
axis.set_label_text("Hz")
elif ax_type in ["frames"]:
axis.set_label_text("Frames")
elif ax_type in ["off", "none", None]:
axis.set_label_text("")
axis.set_ticks([])
else:
raise ParameterError("Unsupported axis type: {}".format(ax_type))
import chromatemplate
midilist = find_files(C.PATH_MIDI, ext="mid")
itemcnt = len(midilist)
i = 5000
for midifile in midilist:
i += 1
print("Processing %d" % (i))
wav, sr = load(midifile, sr=C.SR)
try:
pm = pretty_midi.PrettyMIDI(midifile)
wav = pm.fluidsynth(fs=C.SR)
target = chromatemplate.GetConvnetTargetFromPianoroll(
utils.GetPianoroll(midifile))
fmin = note_to_hz("C1")
spec = np.vstack([
np.abs(
cqt(wav,
sr=C.SR,
hop_length=C.H,
n_bins=C.BIN_CNT,
bins_per_octave=C.OCT_BIN,
fmin=fmin * (h + 1))).T.astype(np.float32)
for h in range(C.CQT_H)
])
except (Exception):
print("Got error.Skip...")
continue
minsz = min([spec.shape[1], target.shape[1]])
def PlotPianoroll(P, min_note="C1"):
specshow(P, y_axis="cqt_note", fmin=note_to_hz(min_note))
