本文整理汇总了Python中scipy.array方法的典型用法代码示例。如果您正苦于以下问题:Python scipy.array方法的具体用法?Python scipy.array怎么用?Python scipy.array使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类scipy
的用法示例。
在下文中一共展示了scipy.array方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _break_points
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def _break_points(num, den):
"""Extract break points over real axis and gains given these locations"""
# type: (np.poly1d, np.poly1d) -> (np.array, np.array)
dnum = num.deriv(m=1)
dden = den.deriv(m=1)
polynom = den * dnum - num * dden
real_break_pts = polynom.r
# don't care about infinite break points
real_break_pts = real_break_pts[num(real_break_pts) != 0]
k_break = -den(real_break_pts) / num(real_break_pts)
idx = k_break >= 0 # only positives gains
k_break = k_break[idx]
real_break_pts = real_break_pts[idx]
if len(k_break) == 0:
k_break = [0]
real_break_pts = den.roots
return k_break, real_break_pts
示例2: readWav
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def readWav():
"""
Reads a sound wave from a standard input and finds its parameters.
"""
# Read the sound wave from the input.
sound_wave = wave.open(sys.argv[1], "r")
# Get parameters of the sound wave.
nframes = sound_wave.getnframes()
framerate = sound_wave.getframerate()
params = sound_wave.getparams()
duration = nframes / float(framerate)
print "frame rate: %d " % (framerate,)
print "nframes: %d" % (nframes,)
print "duration: %f seconds" % (duration,)
print scipy.array(sound_wave)
return (sound_wave, nframes, framerate, duration, params)
示例3: readWav
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def readWav():
"""
Reads a sound wave from a standard input and finds its parameters.
"""
# Read the sound wave from the input.
sound_wave = wave.open(sys.argv[1], "r")
# Get parameters of the sound wave.
nframes = sound_wave.getnframes()
framerate = sound_wave.getframerate()
params = sound_wave.getparams()
duration = nframes / float(framerate)
print "frame rate: %d " % (framerate,)
print "nframes: %d" % (nframes,)
print "duration: %f seconds" % (duration,)
print scipy.array(sound_wave)
return (sound_wave, nframes, framerate, duration, params)
示例4: test_fetch_one_column
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def test_fetch_one_column(tmpdata):
_urlopen_ref = datasets.mldata.urlopen
try:
dataname = 'onecol'
# create fake data set in cache
x = sp.arange(6).reshape(2, 3)
datasets.mldata.urlopen = mock_mldata_urlopen({dataname: {'x': x}})
dset = fetch_mldata(dataname, data_home=tmpdata)
for n in ["COL_NAMES", "DESCR", "data"]:
assert_in(n, dset)
assert_not_in("target", dset)
assert_equal(dset.data.shape, (2, 3))
assert_array_equal(dset.data, x)
# transposing the data array
dset = fetch_mldata(dataname, transpose_data=False, data_home=tmpdata)
assert_equal(dset.data.shape, (3, 2))
finally:
datasets.mldata.urlopen = _urlopen_ref
示例5: find_range
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def find_range(array, x):
"""
Function to calculate bounding intervals from array to do piecewise linear interpolation.
:param array: list of values
:param x: interpolation value
:return: boundary interval
Examples:
>>> array = [0, 1, 2, 3, 4]
>>>find_range(array, 1.5)
1, 2
"""
if x < max(array):
start = bisect_left(array, x)
return array[start-1], array[start]
else:
return min(array), max(array)
示例6: Regresion
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def Regresion(self):
t=array(self.KEq_Tab.getColumn(0)[:-1])
k=array(self.KEq_Tab.getColumn(1)[:-1])
if len(t)>=4:
if 4<=len(t)<8:
inicio=r_[0, 0, 0, 0]
f=lambda par, T: exp(par[0]+par[1]/T+par[2]*log(T)+par[3]*T)
resto=lambda par, T, k: k-f(par, T)
else:
inicio=r_[0, 0, 0, 0, 0, 0, 0, 0]
f=lambda par, T: exp(par[0]+par[1]/T+par[2]*log(T)+par[3]*T+par[4]*T**2+par[5]*T**3+par[6]*T**4+par[7]*T**5)
resto=lambda par, T, k: k-f(par, T)
ajuste=leastsq(resto,inicio,args=(t, k))
kcalc=f(ajuste[0], t)
error=(k-kcalc)/k*100
self.KEq_Dat.setColumn(0, ajuste[0])
self.KEq_Tab.setColumn(2, kcalc)
self.KEq_Tab.setColumn(3, error)
if ajuste[1] in [1, 2, 3, 4]:
self.ajuste=ajuste[0]
示例7: fill
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def fill(self, array):
"""Populate the widgets with the DIPPR coefficient in array in format
[eq, A, B, C, D, E, Tmin, Tmax]"""
if array[0] != 0:
for valor, entrada in zip(array[1:6], self.coeff):
entrada.setValue(valor)
self.tmin.setValue(array[6])
self.tmax.setValue(array[7])
self.eq.setValue(array[0])
latex = self.latex[array[0]]
tex = "$%s = %s$" % (self.proptex, latex)
self.eqformula.setTex(tex)
self.eq.setVisible(False)
self.eqformula.setVisible(True)
self.btnPlot.setEnabled(True)
self.equation = array[0]
示例8: complete_graph_dX
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def complete_graph_dX(X, t, tau, gamma, N):
r'''This system is given in Proposition 2.3, taking Q=S, T=I
f_{SI}(k) = f_{QT}= k*\tau
f_{IS}(k) = f_{TQ} = \gamma
\dot{Y}^0 = \gamma Y^1 - 0\\
\dot{Y}^1 = 2\gamma Y^2 + 0Y^0 - (\gamma + (N-1)\tau)Y^1
\dot{Y}^2 = 3\gamma Y^3 + (N-1)\tau Y^1 - (2\gamma+2(N-2))Y^2
...
\dot{Y}^N = (N-1)\tau Y^{N-1} - N\gamma Y^N
Note that X has length N+1
'''
#X[k] is probability of k infections.
dX = []
dX.append(gamma*X[1])
for k in range(1,N):
dX.append((k+1)*gamma*X[k+1]+ (N-k+1)*(k-1)*tau*X[k-1]
- ((N-k)*k*tau + k*gamma)*X[k])
dX.append((N-1)*tau*X[N-1] - N*gamma*X[N])
return scipy.array(dX)
示例9: star_graph_lumped
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def star_graph_lumped(N, tau, gamma, I0, tmin, tmax, tcount):
times = scipy.linspace(tmin, tmax, tcount)
# [[central node infected] + [central node susceptible]]
#X = [Y_1^1, Y_1^2, ..., Y_1^{N}, Y_2^0, Y_2^1, ..., Y_2^{N-1}]
X0 = scipy.zeros(2*N) #length 2*N of just 0 entries
X0[I0]=I0*1./N #central infected, + I0-1 periph infected prob
X0[N+I0] = 1-I0*1./N #central suscept + I0 periph infected
X = EoN.my_odeint(star_graph_dX, X0, times, args = (tau, gamma, N))
#X looks like [[central susceptible,k periph] [ central inf, k-1 periph]] x T
central_inf = X[:,:N]
central_susc = X[:,N:]
I = scipy.array([ sum(k*central_susc[t][k] for k in range(N))
+ sum((k+1)*central_inf[t][k] for k in range(N))
for t in range(len(X))])
S = N-I
return times, S, I
示例10: complete_graph_dX
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def complete_graph_dX(X, t, tau, gamma, N):
r'''This system is given in Proposition 2.3, taking Q=S, T=I
f_{SI}(k) = f_{QT}= k*\tau
f_{IS}(k) = f_{TQ} = \gamma
\dot{Y}^0 = \gamma Y^1 - 0\\
\dot{Y}^1 = 2\gamma Y^2 + 0Y^0 - (\gamma + (N-1)\tau)Y^1
\dot{Y}^2 = 3\gamma Y^3 + (N-1)\tau Y^1 - (2\gamma+2(N-2))Y^2
...
\dot{Y}^N = (N-1)\tau Y^{N-1} - N\gamma Y^N
Note that X has length N+1
'''
#X[k] is probability of k infections.
dX = []
dX.append(gamma*X[1])
for k in range(1,N):
dX.append((k+1)*gamma*X[k+1]+ (N-k+1)*(k-1)*tau*X[k-1]
- ((N-k)*k*tau + k*gamma)*X[k])
dX.append((N-1)*tau*X[N-1] - N*gamma*X[N])
return scipy.array(dX)
示例11: star_graph_lumped
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def star_graph_lumped(N, tau, gamma, I0, tmin, tmax, tcount):
times = scipy.linspace(tmin, tmax, tcount)
# [[central node infected] + [central node susceptible]]
#X = [Y_1^1, Y_1^2, ..., Y_1^{N}, Y_2^0, Y_2^1, ..., Y_2^{N-1}]
X0 = scipy.zeros(2*N) #length 2*N of just 0 entries
#X0[I0]=I0*1./N #central infected, + I0-1 periph infected prob
X0[N+I0] = 1#-I0*1./N #central suscept + I0 periph infected
X = EoN.my_odeint(star_graph_dX, X0, times, args = (tau, gamma, N))
#X looks like [[central susceptible,k periph] [ central inf, k-1 periph]] x T
central_susc = X[:,N:]
central_inf = X[:,:N]
print(central_susc[-1][:])
print(central_inf[-1][:])
I = scipy.array([ sum(k*central_susc[t][k] for k in range(N))
+ sum((k+1)*central_inf[t][k] for k in range(N))
for t in range(len(X))])
S = N-I
return times, S, I
示例12: get_HRRR_data
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def get_HRRR_data(filename):
grbs = pygrib.open(filename)
msgs = [str(grb) for grb in grbs]
string = 'Geopotential Height:gpm'
temp = [msg for msg in msgs if msg.find(string) > -1 and msg.find('isobaricInhPa') > -1]
pressure_levels_Pa = s.array([int(s.split(' ')[3]) for s in temp])
geo_pot_height_grbs = grbs.select(name = 'Geopotential Height', \
typeOfLevel='isobaricInhPa', level=lambda l: l > 0)
temperature_grbs = grbs.select(name = 'Temperature', \
typeOfLevel='isobaricInhPa', level=lambda l: l > 0)
rh_grbs = grbs.select(name = 'Relative humidity', \
typeOfLevel='isobaricInhPa', level=lambda l: l > 0)
lat, lon = geo_pot_height_grbs[0].latlons()
geo_pot_height = s.stack([grb.values for grb in geo_pot_height_grbs])
temperature = s.stack([grb.values for grb in temperature_grbs])
rh = s.stack([grb.values for grb in rh_grbs])
return lat, lon, geo_pot_height, temperature, rh, pressure_levels_Pa
示例13: _flat_field
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def _flat_field(X, uniformity_thresh):
"""."""
Xhoriz = _low_frequency_horiz(X, sigma=4.0)
Xhorizp = _low_frequency_horiz(X, sigma=3.0)
nl, nb, nc = X.shape
FF = s.zeros((nb, nc))
use_ff = s.ones((X.shape[0], X.shape[2])) > 0
for b in range(nb):
xsub = Xhoriz[:, b, :]
xsubp = Xhorizp[:, b, :]
mu = xsub.mean(axis=0)
dists = abs(xsub - mu)
distsp = abs(xsubp - mu)
thresh = _percentile(dists.flatten(), 90.0)
uthresh = dists * uniformity_thresh
#use = s.logical_and(dists<thresh, abs(dists-distsp) < uthresh)
use = dists < thresh
FF[b, :] = ((xsub*use).sum(axis=0)/use.sum(axis=0)) / \
((X[:, b, :]*use).sum(axis=0)/use.sum(axis=0))
use_ff = s.logical_and(use_ff, use)
return FF, Xhoriz, Xhorizp, s.array(use_ff)
示例14: calc_twostate_weights
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def calc_twostate_weights( data ):
weights=[0,0,0] # the change cannot have occurred in the last 3 points
means_mss=calc_mean_mss( data )
i=0
try:
for nA, mean2A, varA, nB, mean2B, varB in means_mss :
#print "computing for data", nA, mean2A, varA, nB, mean2B, varB
numf1 = calc_alpha( nA, mean2A, varA )
numf2 = calc_alpha( nB, mean2B, varB )
denom = (varA + varB) * (mean2A*mean2B)
weights.append( (numf1*numf2)/denom)
i += 1
except:
print "failed at data", i # means_mss[i]
print "---"
#print means_mss
print "---"
raise
weights.extend( [0,0] ) # the change cannot have occurred at the last 2 points
return array( weights )
示例15: tdft
# 需要导入模块: import scipy [as 别名]
# 或者: from scipy import array [as 别名]
def tdft(audio, srate, windowsize, windowshift,fftsize):
"""Calculate the real valued fast Fourier transform of a segment of audio multiplied by a
a Hamming window. Then, convert to decibels by multiplying by 20*log10. Repeat for all
segments of the audio."""
windowsamp = int(windowsize*srate)
shift = int(windowshift*srate)
window = scipy.hamming(windowsamp)
spectrogram = scipy.array([20*scipy.log10(abs(np.fft.rfft(window*audio[i:i+windowsamp],fftsize)))
for i in range(0, len(audio)-windowsamp, shift)])
return spectrogram