Update 0.1.9

conda/meta.yaml

@@ -1,4 +1,4 @@
-{% set version = "0.1.8" %}
+{% set version = "0.1.9" %}
 
 package:
   name: audioflux

docs/changelog.rst

@@ -1,5 +1,12 @@
 ChangeLog
 =========
+v0.1.9
+------
+* New features:
+    * Add `audioflux.utils.synth_f0`.
+* Fix bug:
+    * `#37 <https://github.com/libAudioFlux/audioFlux/issues/37>`__: Fix `audioflux.display.fill_spec` bug.
+
 v0.1.8
 ------
 * New features:

docs/utils.rst

@@ -63,6 +63,7 @@ Utils
     audioflux.utils.midi_to_hz
     audioflux.utils.hz_to_note
     audioflux.utils.hz_to_midi
+    audioflux.utils.synth_f0
 
 Sample
 ------

python/audioflux/__version__.py

@@ -1,3 +1,3 @@
 __title__ = 'audioflux'
 __description__ = 'A library for audio and music analysis, feature extraction.'
-__version__ = '0.1.8'
+__version__ = '0.1.9'

python/audioflux/display/display.py

@@ -1,9 +1,9 @@
 import warnings
 
 import numpy as np
+import matplotlib as mpl
 import matplotlib.pyplot as plt
 import matplotlib.axes as plaxes
-from matplotlib import colormaps
 from matplotlib.ticker import Formatter, ScalarFormatter, MaxNLocator, SymmetricalLogLocator, FixedLocator
 from audioflux.utils import midi_to_note
 
@@ -190,7 +190,12 @@ def fill_spec(
     if y_axis == 'chroma':
         y_coords = np.arange(data.shape[-2] + 1)
 
-    cmap = colormaps['plasma']
+    if hasattr(mpl, 'colormaps'):
+        cmap = mpl.colormaps['plasma']
+    else:
+        from matplotlib.cm import get_cmap
+        cmap = get_cmap('plasma')
+
     collection = axes.pcolormesh(x_coords, y_coords, data, cmap=cmap)
 
     axes.set_xlim(np.min(x_coords), np.max(x_coords))

python/audioflux/mir/pitch_yin.py

@@ -52,6 +52,7 @@ class PitchYIN(Base):
     >>> fre_arr, v1_arr, v2_arr = pitch_obj.pitch(audio_arr)
 
     Show pitch plot
+
     >>> import matplotlib.pyplot as plt
     >>> times = np.arange(fre_arr.shape[-1]) * (pitch_obj.slide_length / sr)
     >>> fig, ax = plt.subplots(nrows=2, sharex=True)

python/audioflux/utils/util.py

@@ -1,13 +1,17 @@
 import warnings
 import numpy as np
+from ctypes import c_int, c_float, c_void_p, POINTER
+
+from audioflux.fftlib import get_fft_lib
 
 __all__ = [
     'ascontiguous_T',
     'ascontiguous_swapaxex',
     'format_channel',
     'revoke_channel',
     'check_audio',
-    'check_audio_length'
+    'check_audio_length',
+    'synth_f0'
 ]
 
 
@@ -104,3 +108,76 @@ def check_audio_length(X, radix2_exp):
                       f'only the first fft_length={fft_length} data are valid')
         X = X[..., :fft_length].copy()
     return X
+
+
+def synth_f0(times, frequencies, samplate, amplitudes=None):
+    """
+    Generate an audio array based on the frequency f0.
+
+    Parameters
+    ----------
+    times: ndarray  [shape=(n)]
+        Time points for each frequency, in seconds.
+
+    frequencies: ndarray [shape=(n)]
+        Array of frequencies, in Hz.
+
+    samplate: int
+        The output sampling rate.
+
+    amplitudes: ndarray [shape=(n)]
+        The amplitude of each frequency, ranging from 0 to 1.
+
+        Default is None, which means that the amplitude is 1. Like: `np.ones((n,))`
+
+    Returns
+    -------
+    out: ndarray
+        Return the audio array generated based on the frequencies
+
+
+    Examples
+    --------
+
+    >>> import audioflux as af
+    >>> import numpy as np
+    >>> f0_arr = np.ones((1024,)) * 220
+    >>> times = np.arange(0, f0_arr.shape[0]) * (1024 / 32000)
+    >>> amplitude_arr = np.ones_like(f0_arr) * 0.4
+    >>> audio_arr = af.utils.synth_f0(times, f0_arr, 32000, amplitude_arr)
+
+    """
+    times = np.asarray(times, dtype=np.float32, order='C')
+    if times.ndim != 1:
+        raise ValueError(f"times[ndim={times.ndim}] must be a 1D array")
+
+    frequencies = np.asarray(frequencies, dtype=np.float32, order='C')
+    if frequencies.ndim != 1:
+        raise ValueError(f"frequencies[ndim={frequencies.ndim}] must be a 1D array")
+
+    if times.shape[0] != frequencies.shape[0]:
+        raise ValueError(f"The lengths of times and frequencies must be the same.")
+
+    if amplitudes is not None:
+        amplitudes = np.asarray(amplitudes, dtype=np.float32, order='C')
+        if amplitudes.ndim != 1:
+            raise ValueError(f"amplitudes[ndim={amplitudes.ndim}] must be a 1D array")
+
+        if amplitudes.shape[0] != frequencies.shape[0]:
+            raise ValueError(f"The lengths of amplitudes and frequencies must be the same.")
+
+    fn = get_fft_lib()['util_synthF0']
+    fn.argtypes = [
+        np.ctypeslib.ndpointer(dtype=np.float32, ndim=1, flags='C_CONTIGUOUS'),
+        np.ctypeslib.ndpointer(dtype=np.float32, ndim=1, flags='C_CONTIGUOUS'),
+        c_int, c_int,
+        POINTER(c_void_p) if amplitudes is None else np.ctypeslib.ndpointer(dtype=np.float32, ndim=1, flags='C_CONTIGUOUS'),
+    ]
+    fn.restype = c_void_p
+
+    length = times.shape[0]
+    length1 = round(np.max(times) * samplate)
+
+    p = fn(times, frequencies, c_int(length), c_int(samplate), amplitudes)
+    ret = np.frombuffer((c_float * length1).from_address(p), np.float32).copy()
+    return ret

src/util/flux_util.h

@@ -82,7 +82,7 @@ void util_delta(float *dataArr1,int length,int order,float *dataArr2);
 void util_preEmphasis(float *vArr1,int length,float coef,float *vArr2);
 
 // synthesized f0; length1=floor(time*fs), ampArr can NULL, default is 1
-float *util_synthF0(float *timeArr,float *freArr,int samplate,int length,float *ampArr);
+float *util_synthF0(float *timeArr,float *freArr,int length,int samplate,float *ampArr);
 
 // wave
 int util_readWave(char *name,float **dataArr);