本文整理匯總了Python中numpy.fix方法的典型用法代碼示例。如果您正苦於以下問題:Python numpy.fix方法的具體用法?Python numpy.fix怎麽用?Python numpy.fix使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類numpy
的用法示例。
在下文中一共展示了numpy.fix方法的15個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: fit
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def fit(self, magnitude, time, dt_bins, dm_bins):
def delta_calc(idx):
t0 = time[idx]
m0 = magnitude[idx]
deltat = time[idx + 1 :] - t0
deltam = magnitude[idx + 1 :] - m0
deltat[np.where(deltat < 0)] *= -1
deltam[np.where(deltat < 0)] *= -1
return np.column_stack((deltat, deltam))
lc_len = len(time)
n_vals = int(0.5 * lc_len * (lc_len - 1))
deltas = np.vstack(tuple(delta_calc(idx) for idx in range(lc_len - 1)))
deltat = deltas[:, 0]
deltam = deltas[:, 1]
bins = [dt_bins, dm_bins]
counts = np.histogram2d(deltat, deltam, bins=bins, normed=False)[0]
result = np.fix(255.0 * counts / n_vals + 0.999).astype(int)
return {"DMDT": result}
示例2: test_scalar
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def test_scalar(self):
x = np.inf
actual = np.isposinf(x)
expected = np.True_
assert_equal(actual, expected)
assert_equal(type(actual), type(expected))
x = -3.4
actual = np.fix(x)
expected = np.float64(-3.0)
assert_equal(actual, expected)
assert_equal(type(actual), type(expected))
out = np.array(0.0)
actual = np.fix(x, out=out)
assert_(actual is out)
示例3: test_fix_with_subclass
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def test_fix_with_subclass(self):
class MyArray(nx.ndarray):
def __new__(cls, data, metadata=None):
res = nx.array(data, copy=True).view(cls)
res.metadata = metadata
return res
def __array_wrap__(self, obj, context=None):
obj.metadata = self.metadata
return obj
a = nx.array([1.1, -1.1])
m = MyArray(a, metadata='foo')
f = ufl.fix(m)
assert_array_equal(f, nx.array([1, -1]))
assert_(isinstance(f, MyArray))
assert_equal(f.metadata, 'foo')
# check 0d arrays don't decay to scalars
m0d = m[0,...]
m0d.metadata = 'bar'
f0d = ufl.fix(m0d)
assert_(isinstance(f0d, MyArray))
assert_equal(f0d.metadata, 'bar')
示例4: convert_to_1x1
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def convert_to_1x1(boxes):
"""Convert detection boxes to 1:1 sizes
# Arguments
boxes: numpy array, shape (n,5), dtype=float32
# Returns
boxes_1x1
"""
boxes_1x1 = boxes.copy()
hh = boxes[:, 3] - boxes[:, 1] + 1.
ww = boxes[:, 2] - boxes[:, 0] + 1.
mm = np.maximum(hh, ww)
boxes_1x1[:, 0] = boxes[:, 0] + ww * 0.5 - mm * 0.5
boxes_1x1[:, 1] = boxes[:, 1] + hh * 0.5 - mm * 0.5
boxes_1x1[:, 2] = boxes_1x1[:, 0] + mm - 1.
boxes_1x1[:, 3] = boxes_1x1[:, 1] + mm - 1.
boxes_1x1[:, 0:4] = np.fix(boxes_1x1[:, 0:4])
return boxes_1x1
示例5: detect
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def detect(self, img, minsize=40):
"""detect()
This function handles rescaling of the input image if it's
larger than 1280x720.
"""
if img is None:
raise ValueError
img_h, img_w, _ = img.shape
scale = min(720. / img_h, 1280. / img_w)
if scale < 1.0:
new_h = int(np.ceil(img_h * scale))
new_w = int(np.ceil(img_w * scale))
img = cv2.resize(img, (new_w, new_h))
minsize = max(int(np.ceil(minsize * scale)), 40)
dets, landmarks = self._detect_1280x720(img, minsize)
if scale < 1.0:
dets[:, :-1] = np.fix(dets[:, :-1] / scale)
landmarks = np.fix(landmarks / scale)
return dets, landmarks
示例6: fix
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def fix(self):
if self.PITCH_HALF > 0:
nz_pitch = self.samp_values[self.samp_values > 0]
idx = self.samp_values < (np.mean(nz_pitch)-self.PITCH_HALF_SENS *
np.std(nz_pitch))
if self.PITCH_HALF == 1:
self.samp_values[idx] = 0
elif self.PITCH_HALF == 2:
self.samp_values[idx] = 2*self.samp_values[idx]
if self.PITCH_DOUBLE > 0:
nz_pitch = self.samp_values[self.samp_values > 0]
idx = self.samp_values > (np.mean(nz_pitch)+self.PITCH_DOUBLE_SENS *
np.std(nz_pitch))
if self.PITCH_DOUBLE == 1:
self.samp_values[idx] = 0
elif self.PITCH_DOUBLE == 2:
self.samp_values[idx] = 0.5*self.samp_values[idx]
示例7: filter_window_cartesian
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def filter_window_cartesian(img, wsize, fun, scale, **kwargs):
"""Apply a filter of square window size `fsize` on a given \
cartesian image `img`.
Parameters
----------
img : :class:`numpy:numpy.ndarray`
2d array of values to which the filter is to be applied
wsize : float
Half size of the window centred on the pixel [m]
fun : string
name of the 2d filter from :mod:`scipy:scipy.ndimage`
scale : tuple of 2 floats
x and y scale of the cartesian grid [m]
Returns
-------
output : :class:`numpy:numpy.ndarray`
Array with the same shape as `img`, containing the filter's results.
"""
fun = getattr(ndimage.filters, "%s_filter" % fun)
size = np.fix(wsize / scale + 0.5).astype(int)
data_filtered = fun(img, size, **kwargs)
return data_filtered
示例8: generateBoundingBox
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def generateBoundingBox(imap, reg, scale, t):
# use heatmap to generate bounding boxes
stride=2
cellsize=12
imap = np.transpose(imap)
dx1 = np.transpose(reg[:,:,0])
dy1 = np.transpose(reg[:,:,1])
dx2 = np.transpose(reg[:,:,2])
dy2 = np.transpose(reg[:,:,3])
y, x = np.where(imap >= t)
if y.shape[0]==1:
dx1 = np.flipud(dx1)
dy1 = np.flipud(dy1)
dx2 = np.flipud(dx2)
dy2 = np.flipud(dy2)
score = imap[(y,x)]
reg = np.transpose(np.vstack([ dx1[(y,x)], dy1[(y,x)], dx2[(y,x)], dy2[(y,x)] ]))
if reg.size==0:
reg = np.empty((0,3))
bb = np.transpose(np.vstack([y,x]))
q1 = np.fix((stride*bb+1)/scale)
q2 = np.fix((stride*bb+cellsize-1+1)/scale)
boundingbox = np.hstack([q1, q2, np.expand_dims(score,1), reg])
return boundingbox, reg
# function pick = nms(boxes,threshold,type)
示例9: test_fix
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def test_fix(self):
a = nx.array([[1.0, 1.1, 1.5, 1.8], [-1.0, -1.1, -1.5, -1.8]])
out = nx.zeros(a.shape, float)
tgt = nx.array([[1., 1., 1., 1.], [-1., -1., -1., -1.]])
res = ufl.fix(a)
assert_equal(res, tgt)
res = ufl.fix(a, out)
assert_equal(res, tgt)
assert_equal(out, tgt)
assert_equal(ufl.fix(3.14), 3)
示例10: test_fix_with_subclass
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def test_fix_with_subclass(self):
class MyArray(nx.ndarray):
def __new__(cls, data, metadata=None):
res = nx.array(data, copy=True).view(cls)
res.metadata = metadata
return res
def __array_wrap__(self, obj, context=None):
if isinstance(obj, MyArray):
obj.metadata = self.metadata
return obj
def __array_finalize__(self, obj):
self.metadata = getattr(obj, 'metadata', None)
return self
a = nx.array([1.1, -1.1])
m = MyArray(a, metadata='foo')
f = ufl.fix(m)
assert_array_equal(f, nx.array([1, -1]))
assert_(isinstance(f, MyArray))
assert_equal(f.metadata, 'foo')
# check 0d arrays don't decay to scalars
m0d = m[0,...]
m0d.metadata = 'bar'
f0d = ufl.fix(m0d)
assert_(isinstance(f0d, MyArray))
assert_equal(f0d.metadata, 'bar')
示例11: test_deprecated
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def test_deprecated(self):
# NumPy 1.13.0, 2017-04-26
assert_warns(DeprecationWarning, ufl.fix, [1, 2], y=nx.empty(2))
assert_warns(DeprecationWarning, ufl.isposinf, [1, 2], y=nx.empty(2))
assert_warns(DeprecationWarning, ufl.isneginf, [1, 2], y=nx.empty(2))
示例12: test_getitem_setitem_ellipsis
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def test_getitem_setitem_ellipsis():
s = Series(np.random.randn(10))
np.fix(s)
result = s[...]
assert_series_equal(result, s)
s[...] = 5
assert (result == 5).all()
示例13: fix
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def fix(x, out=None, **kwargs):
"""
Round to nearest integer towards zero.
Round a tensor of floats element-wise to nearest integer towards zero.
The rounded values are returned as floats.
Parameters
----------
x : array_like
An tensor of floats to be rounded
out : Tensor, optional
Output tensor
Returns
-------
out : Tensor of floats
The array of rounded numbers
See Also
--------
trunc, floor, ceil
around : Round to given number of decimals
Examples
--------
>>> import mars.tensor as mt
>>> mt.fix(3.14).execute()
3.0
>>> mt.fix(3).execute()
3.0
>>> mt.fix([2.1, 2.9, -2.1, -2.9]).execute()
array([ 2., 2., -2., -2.])
"""
op = TensorFix(**kwargs)
return op(x, out=out)
示例14: generateBoundingBox
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def generateBoundingBox(imap, reg, scale, t):
"""Use heatmap to generate bounding boxes"""
stride=2
cellsize=12
imap = np.transpose(imap)
dx1 = np.transpose(reg[:,:,0])
dy1 = np.transpose(reg[:,:,1])
dx2 = np.transpose(reg[:,:,2])
dy2 = np.transpose(reg[:,:,3])
y, x = np.where(imap >= t)
if y.shape[0]==1:
dx1 = np.flipud(dx1)
dy1 = np.flipud(dy1)
dx2 = np.flipud(dx2)
dy2 = np.flipud(dy2)
score = imap[(y,x)]
reg = np.transpose(np.vstack([ dx1[(y,x)], dy1[(y,x)], dx2[(y,x)], dy2[(y,x)] ]))
if reg.size==0:
reg = np.empty((0,3))
bb = np.transpose(np.vstack([y,x]))
q1 = np.fix((stride*bb+1)/scale)
q2 = np.fix((stride*bb+cellsize-1+1)/scale)
boundingbox = np.hstack([q1, q2, np.expand_dims(score,1), reg])
return boundingbox, reg
# function pick = nms(boxes,threshold,type)
示例15: two_max
# 需要導入模塊: import numpy [as 別名]
# 或者: from numpy import fix [as 別名]
def two_max(x, lowerbound, upperbound, unit_len):
"""Return up to two successive maximum peaks and their indices in x.
Return the magnitudes of the peaks and the indices as two lists.
If the first maximum is less than zero, just return it. Otherwise
look to the right of the first maximum, and if there is a second
maximum that is greater than zero, add that to the returned lists.
lowerbound and upperbound comprise a closed interval, unlike the
normal python half closed interval. [RDM XXX: fix this?]
"""
# XXX The above description is not completely accurate: there's a window to
# the search for the second peak, but I don't understand the goal well
# enough to describe it better, and the original comments are less precise.
max_index = min(upperbound, len(x)-1)
# "find the maximum value"
mag = np.array([np.amax(x[lowerbound:upperbound+1])])
index = np.where(x == mag)[0]
if mag < 0:
return mag, index
harmonics = 2
limit = 0.0625 # "1/8 octave"
startpos = index[0] + int(round(np.log2(harmonics-limit)/unit_len))
if startpos <= max_index:
# "for example, 100hz-200hz is one octave, 200hz-250hz is 1/4octave"
endpos = index[0] + int(round(np.log2(harmonics + limit)/unit_len))
endpos = min(max_index, endpos)
# "find the maximum value at right side of last maximum"
mag2 = np.amax(x[startpos:endpos+1])
index2 = np.where(x[startpos:] == mag2)[0][0] + startpos
if mag2 > 0:
mag = np.append(mag, mag2)
index = np.append(index, index2)
return mag, index
# ---- vda -----
# func_Get_SHRP does not use this, because CHECK_VOICING is always 0