The following are code examples for showing how to use . They are extracted from open source Python projects. You can vote up the examples you like or vote down the exmaples you don’t like. You can also save this page to your account.
Example 1
def read_wav_data(filename): ''' ????wav???????????????????? ''' wav = wave.open(filename,"rb") # ????wav???????? num_frame = wav.getnframes() # ???? num_channel=wav.getnchannels() # ????? framerate=wav.getframerate() # ????? num_sample_width=wav.getsampwidth() # ?????????????????? str_data = wav.readframes(num_frame) # ?????? wav.close() # ??? wave_data = np.fromstring(str_data, dtype = np.short) # ???????????????? wave_data.shape = -1, num_channel # ????????????????????????????????? wave_data = wave_data.T # ????? #wave_data = wave_data return wave_data, framerate
Example 2
def read_gzip_wave_file(filename):
if (not os.path.isfile(filename)):
raise ValueError("File does not exist")
with gzip.open(filename, 'rb') as wav_file:
with wave.open(wav_file, 'rb') as s:
if (s.getnchannels() != 1):
raise ValueError("Wave file should be mono")
#if (s.getframerate() != 22050):
#raise ValueError("Sampling rate of wave file should be 16000")
strsig = s.readframes(s.getnframes())
x = np.fromstring(strsig, np.short)
fs = s.getframerate()
s.close()
return fs, x Example 3
def read_wave_file(filename):
""" Read a wave file from disk
# Arguments
filename : the name of the wave file
# Returns
(fs, x) : (sampling frequency, signal)
"""
if (not os.path.isfile(filename)):
raise ValueError("File does not exist")
s = wave.open(filename, 'rb')
if (s.getnchannels() != 1):
raise ValueError("Wave file should be mono")
# if (s.getframerate() != 22050):
# raise ValueError("Sampling rate of wave file should be 16000")
strsig = s.readframes(s.getnframes())
x = np.fromstring(strsig, np.short)
fs = s.getframerate()
s.close()
x = x/32768.0
return fs, x Example 4
def read_wave_file_not_normalized(filename):
""" Read a wave file from disk
# Arguments
filename : the name of the wave file
# Returns
(fs, x) : (sampling frequency, signal)
"""
if (not os.path.isfile(filename)):
raise ValueError("File does not exist")
s = wave.open(filename, 'rb')
if (s.getnchannels() != 1):
raise ValueError("Wave file should be mono")
# if (s.getframerate() != 22050):
# raise ValueError("Sampling rate of wave file should be 16000")
strsig = s.readframes(s.getnframes())
x = np.fromstring(strsig, np.short)
fs = s.getframerate()
s.close()
return fs, x Example 5
def initializeGL(self):
self.sdf_shader = self.gls.shader_cache.get("image_vert", "tex_frag")
self.buffer_dtype = numpy.dtype([
("vertex", numpy.float32, 2),
("texpos", numpy.float32, 2)
])
self.b1 = vbobind(self.sdf_shader, self.buffer_dtype, "vertex")
self.b2 = vbobind(self.sdf_shader, self.buffer_dtype, "texpos")
self.tex = Texture()
# TODO: implement short-int caching
# build a De-bruijn sequence (shorted substring containing all substrings)
# self.int_seq = de_bruijn(4)
# self.int_seq += self.int_seq[:3] Example 6
def init_audio(self, wav=None, path=None, show_pic=False):
"""
??????
:param wav: ????????wave??
:param path: ??????
:param show_pic: ?????
:return: None
"""
if wav is None:
if path is None:
print('Error: ?????????')
self.__wav = wave.open(path, 'rb')
else:
self.__wav = wav
nframes = self.__wav.getnframes()
'''byte??????????'''
str_data = self.__wav.readframes(nframes)
'''????????'''
self.__wdata = np.fromstring(str_data, dtype=np.short)
'''???????'''
if self.__wav.getnchannels() == 2:
'''??????2????????'''
self.__wdata.shape = -1, 2
self.__wdata = self.__wdata.T
'''???????????????wdata[0]?'''
for _ in range(len(self.__wdata[0])):
if self.__wdata[0][_] < self.__wdata[1][_]:
self.__wdata[0][_] = self.__wdata[1][_]
self.__wdata = self.__wdata[0]
self.__wdata = np.delete(self.__wdata, np.where(self.__wdata == 0))
if show_pic:
x = [_ for _ in range(len(self.__wdata))]
pylab.plot(x, self.__wdata, 'b')
pylab.show() Example 7
def recode(self):
pa=PyAudio()
stream=pa.open(format=paInt16,channels=1,rate=self.SAMPLES_RATE,input=True,frames_per_buffer=self.NUM_SAMPLES)
save_count=0
save_buffer=[]
time_count=self.TIME_COUNT
print '\n\n\n??????????????'
while True:
time_count-=1
string_audio_data=stream.read(self.NUM_SAMPLES)
audio_data=numpy.fromstring(string_audio_data,dtype=numpy.short)
large_sample_count=numpy.sum(audio_data>self.LEVEL)
print(numpy.max(audio_data))
if large_sample_count>self.COUNT_NUM:
save_count=self.SAVE_LENGTH
else:
save_count-=1
if save_count<0:
save_count=0
if save_count>0:
save_buffer.append(string_audio_data)
else:
if len(save_buffer):
self.Voice_String=save_buffer
save_buffer=[]
print '????????'
return True
if not time_count:
if len(save_buffer):
self.Voice_String=save_buffer
save_buffer=[]
print '????????'
return True
else:
return False Example 8
def amean (inarray,dimension=None,keepdims=0):
"""
Calculates the arithmatic mean of the values in the passed array.
That is: 1/n * (x1 + x2 + ... + xn). Defaults to ALL values in the
passed array. Use dimension=None to flatten array first. REMEMBER: if
dimension=0, it collapses over dimension 0 ('rows' in a 2D array) only, and
if dimension is a sequence, it collapses over all specified dimensions. If
keepdims is set to 1, the resulting array will have as many dimensions as
inarray, with only 1 'level' per dim that was collapsed over.
Usage: amean(inarray,dimension=None,keepdims=0)
Returns: arithematic mean calculated over dim(s) in dimension
"""
if inarray.dtype in [N.int_, N.short,N.ubyte]:
inarray = inarray.astype(N.float_)
if dimension == None:
inarray = N.ravel(inarray)
sum = N.add.reduce(inarray)
denom = float(len(inarray))
elif type(dimension) in [IntType,FloatType]:
sum = asum(inarray,dimension)
denom = float(inarray.shape[dimension])
if keepdims == 1:
shp = list(inarray.shape)
shp[dimension] = 1
sum = N.reshape(sum,shp)
else: # must be a TUPLE of dims to average over
dims = list(dimension)
dims.sort()
dims.reverse()
sum = inarray *1.0
for dim in dims:
sum = N.add.reduce(sum,dim)
denom = N.array(N.multiply.reduce(N.take(inarray.shape,dims)),N.float_)
if keepdims == 1:
shp = list(inarray.shape)
for dim in dims:
shp[dim] = 1
sum = N.reshape(sum,shp)
return sum/denom Example 9
def atmean(a,limits=None,inclusive=(1,1)):
"""
Returns the arithmetic mean of all values in an array, ignoring values
strictly outside the sequence passed to 'limits'. Note: either limit
in the sequence, or the value of limits itself, can be set to None. The
inclusive list/tuple determines whether the lower and upper limiting bounds
(respectively) are open/exclusive (0) or closed/inclusive (1).
Usage: atmean(a,limits=None,inclusive=(1,1))
"""
if a.dtype in [N.int_, N.short,N.ubyte]:
a = a.astype(N.float_)
if limits == None:
return mean(a)
assert type(limits) in [ListType,TupleType,N.ndarray], "Wrong type for limits in atmean"
if inclusive[0]: lowerfcn = N.greater_equal
else: lowerfcn = N.greater
if inclusive[1]: upperfcn = N.less_equal
else: upperfcn = N.less
if limits[0] > N.maximum.reduce(N.ravel(a)) or limits[1] < N.minimum.reduce(N.ravel(a)):
raise ValueError, "No array values within given limits (atmean)."
elif limits[0]==None and limits[1]<>None:
mask = upperfcn(a,limits[1])
elif limits[0]<>None and limits[1]==None:
mask = lowerfcn(a,limits[0])
elif limits[0]<>None and limits[1]<>None:
mask = lowerfcn(a,limits[0])*upperfcn(a,limits[1])
s = float(N.add.reduce(N.ravel(a*mask)))
n = float(N.add.reduce(N.ravel(mask)))
return s/n Example 10
def asum (a, dimension=None,keepdims=0):
"""
An alternative to the Numeric.add.reduce function, which allows one to
(1) collapse over multiple dimensions at once, and/or (2) to retain
all dimensions in the original array (squashing one down to size.
Dimension can equal None (ravel array first), an integer (the
dimension over which to operate), or a sequence (operate over multiple
dimensions). If keepdims=1, the resulting array will have as many
dimensions as the input array.
Usage: asum(a, dimension=None, keepdims=0)
Returns: array summed along 'dimension'(s), same _number_ of dims if keepdims=1
"""
if type(a) == N.ndarray and a.dtype in [N.int_, N.short, N.ubyte]:
a = a.astype(N.float_)
if dimension == None:
s = N.sum(N.ravel(a))
elif type(dimension) in [IntType,FloatType]:
s = N.add.reduce(a, dimension)
if keepdims == 1:
shp = list(a.shape)
shp[dimension] = 1
s = N.reshape(s,shp)
else: # must be a SEQUENCE of dims to sum over
dims = list(dimension)
dims.sort()
dims.reverse()
s = a *1.0
for dim in dims:
s = N.add.reduce(s,dim)
if keepdims == 1:
shp = list(a.shape)
for dim in dims:
shp[dim] = 1
s = N.reshape(s,shp)
return s Example 11
def __init__(self, v_min, v_max, phase, pulse_shaper_interpolation):
gr.interp_block.__init__(self,
name="pulse_shaper_bs",
in_sig=[numpy.int8],
out_sig=[numpy.short], interp=pulse_shaper_interpolation)
self.min = v_min
self.max = v_max
self.phase = phase
self.ps_interpolation = pulse_shaper_interpolation Example 12
def my_record(self):
while self.start_flag == 1:
pa = PyAudio()
stream = pa.open(format=paInt16, channels=1, rate=self.framerate, input=True,
frames_per_buffer=self.NUM_SAMPLES)
save_buffer = []
count = 0
while count < self.TIME * 20:
string_audio_data = stream.read(self.NUM_SAMPLES)
audio_data = np.fromstring(string_audio_data, dtype=np.short)
large_sample_count = np.sum(audio_data > self.LEVEL)
print large_sample_count
if large_sample_count < self.mute_count_limit:
self.mute_begin = 1
else:
save_buffer.append(string_audio_data)
self.mute_begin = 0
self.mute_end = 1
count += 1
if (self.mute_end - self.mute_begin) > 9:
self.mute_begin = 0
self.mute_end = 1
break
if self.mute_begin:
self.mute_end += 1
print '.'
save_buffer = save_buffer[:]
# my_buf.append(string_audio_data)
# count+=1
# print '.'
if save_buffer:
if self.file_name_index < 11:
pass
else:
self.file_name_index = 1
filename = str(self.file_name_index) + '.wav'
self.save_wave_file(filename=filename, data=save_buffer)
self.writeQ(queue=self.wav_queue, data=filename)
self.file_name_index += 1
print filename, 'saved'
else:
print 'file not saved!'
# self.save_wave_file('01.wav',my_buf)
save_buffer = []
stream.close() Example 13
def recoder(self):
pa = PyAudio()
stream = pa.open(format=paInt16, channels=1, rate=self.SAMPLING_RATE, input=True,
frames_per_buffer=self.NUM_SAMPLES)
save_count = 0
save_buffer = []
time_count = self.TIME_COUNT
while True:
time_count -= 1
# print time_count
# ??NUM_SAMPLES???
string_audio_data = stream.read(self.NUM_SAMPLES)
# ???????????
audio_data = np.fromstring(string_audio_data, dtype=np.short)
# ????LEVEL??????
large_sample_count = np.sum( audio_data > self.LEVEL )
print(np.max(audio_data))
# ??????COUNT_NUM??????SAVE_LENGTH??
if large_sample_count > self.COUNT_NUM:
save_count = self.SAVE_LENGTH
else:
save_count -= 1
if save_count < 0:
save_count = 0
if save_count > 0 :
# ??????????save_buffer?
#print save_count > 0 and time_count >0
save_buffer.append( string_audio_data )
else:
#print save_buffer
# ?save_buffer??????WAV???WAV????????????
#print "debug"
if len(save_buffer) > 0 :
self.Voice_String = save_buffer
save_buffer = []
print("Recode a piece of voice successfully!")
return True
if time_count==0:
if len(save_buffer)>0:
self.Voice_String = save_buffer
save_buffer = []
print("Recode a piece of voice successfully!")
return True
else:
return False Example 14
def record_wave(self,temp):
while self.start_flag==1:
pa=PyAudio()
stream=pa.open(format=paInt16,channels=1,
rate=framerate,input=True,
frames_per_buffer=self.NUM_SAMPLES)
my_buf=[]
count=0
print "* start recoding *"
while count<self.TIME*20:
string_audio_data=stream.read(self.NUM_SAMPLES)
audio_data=np.fromstring(string_audio_data,dtype=np.short)
large_sample_count=np.sum(audio_data>self.LEVEL)
print large_sample_count
if large_sample_count<self.mute_count_limit:
self.mute_begin=1
else:
my_buf.append(string_audio_data)
self.mute_begin=0
self.mute_end=1
count+=1
if(self.mute_end-self.mute_begin)>9:
self.mute_begin=0
self.mute_end=1
break
if self.mute_begin:
self.mute_end+=1
print '.'
my_buf=my_buf[:]
if my_buf:
if self.file_name_index<11:
pass
else:
self.file_name_index=1
filename=str(self.file_name_index)+'.wav'
self.save_wave_file(filename=filename,data=my_buf)
self.writeQ(queue=self.wav_queue,data=filename)
self.file_name_index+=1
print filename,"saved"
else:
print '* Error: file not saved! *'
#self.save_wave_file(filename, my_buf)
my_buf=[]
stream.close() Example 15
def discretize(self, time_slice_length):
self.time_slice_length = time_slice_length
# clean the data directory
if os.path.exists('corpus'):
shutil.rmtree('corpus')
os.makedirs('corpus')
# compute the total number of time-slices
time_delta = (self.end_date - self.start_date)
time_delta = time_delta.total_seconds()/60
self.time_slice_count = int(time_delta // self.time_slice_length) + 1
self.tweet_count = np.zeros(self.time_slice_count)
print(' Number of time-slices: %d' % self.time_slice_count)
# create empty files
for time_slice in range(self.time_slice_count):
dummy_file = open('corpus/' + str(time_slice), 'w')
dummy_file.write('')
# compute word frequency
self.global_freq = dok_matrix((len(self.vocabulary), self.time_slice_count), dtype=np.short)
self.mention_freq = dok_matrix((len(self.vocabulary), self.time_slice_count), dtype=np.short)
with open(self.source_file_path, 'r') as input_file:
csv_reader = csv.reader(input_file, delimiter=self.separator)
header = next(csv_reader)
text_column_index = header.index('text')
date_column_index = header.index('date')
for line in csv_reader:
tweet_date = datetime.strptime(line[date_column_index], "%Y-%m-%d %H:%M:%S")
time_delta = (tweet_date - self.start_date)
time_delta = time_delta.total_seconds() / 60
time_slice = int(time_delta / self.time_slice_length)
self.tweet_count[time_slice] += 1
# tokenize the tweet and update word frequency
tweet_text = line[text_column_index]
words = self.tokenize(tweet_text)
mention = '@' in tweet_text
for word in set(words):
word_id = self.vocabulary.get(word)
if word_id is not None:
self.global_freq[word_id, time_slice] += 1
if mention:
self.mention_freq[word_id, time_slice] += 1
with open('corpus/' + str(time_slice), 'a') as time_slice_file:
time_slice_file.write(tweet_text+'\n')
self.global_freq = self.global_freq.tocsr()
self.mention_freq = self.mention_freq.tocsr() Example 16
def startAccord(self, Times=100):
# ??????
pa = PyAudio()
if not self.SAMPLING_RATE:
setAudio(self)
stream = pa.open(format=paInt16, channels=1, rate=self.SAMPLING_RATE, input=True,
frames_per_buffer=self.NUM_SAMPLES)
save_count = 0
save_buffer = []
while True:
#????
if Times != 100:
Times -=1
# ??NUM_SAMPLES???
string_audio_data = stream.read(self.NUM_SAMPLES)
# ???????????
audio_data = np.fromstring(string_audio_data, dtype=np.short)
# ????LEVEL??????
large_sample_count = np.sum( audio_data > self.LEVEL )
if self.debug:
print np.max(audio_data)
# ??????COUNT_NUM??????SAVE_LENGTH??
if large_sample_count > self.COUNT_NUM:
save_count = self.SAVE_LENGTH
else:
save_count -= 1
if save_count < 0:
save_count = 0
if save_count > 0:
# ??????????save_buffer?
save_buffer.append( string_audio_data )
else:
# ?save_buffer??????WAV???WAV????????????
if len(save_buffer) > 0:
filename = "tmp.wav"
cacheFile = save_wave_file(self, filename, save_buffer)
save_buffer = []
stream.close()
if self.debug:
print "saved audio stream"
return cacheFile
break
if Times < 0:
stream.close()
return False
break Example 17
def recode(self):
pa = PyAudio()
stream = pa.open(format=paInt16, channels=self.nchannel, rate=self.SAMPLING_RATE, input=True, frames_per_buffer=self.NUM_SAMPLES)
save_count = 0
save_buffer = []
time_out = self.TIME_OUT
NO_WORDS=self.NO_WORDS
while True and NO_WORDS:
time_out -= 1
print 'time_out in', time_out # ??NUM_SAMPLES???
string_audio_data = stream.read(self.NUM_SAMPLES) # ???????????
audio_data = np.fromstring(string_audio_data, dtype=np.short)
# ??????????
NO_WORDS -= 1
if np.max(audio_data) > self.UPPER_LEVEL:
NO_WORDS=self.NO_WORDS
print 'self.NO_WORDS ', NO_WORDS
print 'np.max(audio_data) ', np.max(audio_data)
# ????LOWER_LEVEL??????
large_sample_count = np.sum( audio_data > self.LOWER_LEVEL )
# ??????COUNT_NUM??????SAVE_LENGTH??
if large_sample_count > self.COUNT_NUM:
save_count = self.SAVE_LENGTH
else:
save_count -= 1
#print 'save_count',save_count
# ??????????save_buffer?
if save_count < 0:
save_count = 0
elif save_count > 0 :
save_buffer.append( string_audio_data )
else:
pass
# ?save_buffer??????WAV???WAV????????????
if len(save_buffer) > 0 and NO_WORDS==0:
self.Voice_String = save_buffer
save_buffer = []
rospy.loginfo( "Recode a piece of voice successfully!")
#return self.Voice_String
elif len(save_buffer) > 0 and time_out==0:
self.Voice_String = save_buffer
save_buffer = []
rospy.loginfo( "Recode a piece of voice successfully!")
#return self.Voice_String
else:
pass
#rospy.loginfo( '\n\n') 