Here are the examples of the python api numpy.floor taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.
172 Examples
6
Example 1
def GetElevation(self, latitude, longitude):
'''Returns the altitude (m ASL) of a given lat/long pair'''
if latitude == 0 or longitude == 0:
return 0
if self.database == 'srtm':
TileID = (numpy.floor(latitude), numpy.floor(longitude))
if TileID in self.tileDict:
alt = self.tileDict[TileID].getAltitudeFromLatLon(latitude, longitude)
else:
tile = self.downloader.getTile(numpy.floor(latitude), numpy.floor(longitude))
if tile == 0:
return -1
self.tileDict[TileID] = tile
alt = tile.getAltitudeFromLatLon(latitude, longitude)
if self.database == 'geoscience':
alt = self.mappy.getAltitudeAtPoint(latitude, longitude)
return alt
5
Example 2
def texture(xy):
x,y = xy
xa = numpy.floor(x * 512)
ya = numpy.floor(y * 512)
a = (512 * ya) + xa
safe = (0 <= x) & (0 <= y) & (x < 1) & (y < 1)
if 0:
a = numpy.where(safe, a, 0).astype(numpy.int)
return numpy.where(safe, numpy.take(lena, a), 0.0)
else:
xi = numpy.floor(x * 11).astype(numpy.int)
yi = numpy.floor(y * 11).astype(numpy.int)
inside = (1 <= xi) & (xi < 10) & (2 <= yi) & (yi < 9)
checker = (xi & 1) ^ (yi & 1)
final = numpy.where(inside, checker, 1.0)
return numpy.where(safe, final, 0.5)
3
Example 3
Project: GPflow Source File: test_custom_op.py
def np_vec_to_tri(vec):
ml = None
for svec in vec:
n = int(np.floor((vec.shape[1] * 8 + 1) ** 0.5 / 2.0 - 0.5))
m = np.zeros((n, n))
m[np.tril_indices(n, 0)] = svec
ml = m[:, :, None] if ml is None else np.dstack((ml, m))
return np.rollaxis(ml, 2, 0)
3
Example 4
Project: facerec Source File: feature.py
def spatially_enhanced_histogram(self, X):
# calculate the LBP image
L = self.lbp_operator(X)
# calculate the grid geometry
lbp_height, lbp_width = L.shape
grid_rows, grid_cols = self.sz
py = int(np.floor(lbp_height/grid_rows))
px = int(np.floor(lbp_width/grid_cols))
E = []
for row in range(0,grid_rows):
for col in range(0,grid_cols):
C = L[row*py:(row+1)*py,col*px:(col+1)*px]
H = np.histogram(C, bins=2**self.lbp_operator.neighbors, range=(0, 2**self.lbp_operator.neighbors), normed=True)[0]
# probably useful to apply a mapping?
E.extend(H)
return np.asarray(E)
3
Example 5
def mousePressEvent(self, event):
pos = event.pos()
if event.button() == Qt.LeftButton:
x_select = np.floor(pos.x() / float(self.width))
y_select = np.floor(pos.y() / float(self.width))
new_id = y_select * self.grid_size[0] + x_select
print('pos=(%d,%d) (x,y)=(%d,%d) image_id=%d' % (int(pos.x()), int(pos.y()), x_select, y_select, new_id))
if new_id != self.select_id:
self.select_id = new_id
self.update_vis()
self.update()
self.emit(SIGNAL('update_image_id'), self.select_id)
3
Example 6
def predict(self, X, cut_point=0.5):
"""Predicted class.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Returns
-------
T : array-like, shape = [n_samples]
Returns the prediction of the sample..
"""
return np.floor(self.predict_proba(X)[:, 1] + (1 - cut_point))
3
Example 7
Project: QSTK Source File: tradesim.py
def _nearest_interger(f_x):
"""
@summary Return the nearest integer to the float number
@param x: single float number
@return: nearest integer to x
"""
if f_x >= 0:
return np.floor(f_x)
else :
return np.ceil(f_x)
3
Example 8
Project: volumina Source File: patchAccessor.py
def getPatchBounds(self, blockNum, overlap = 0):
rest = blockNum % (self._cX*self._cY)
y = int(numpy.floor(rest / self._cX))
x = rest % self._cX
startx = max(0, x*self._blockSize - overlap)
endx = min(self.size_x, (x+1)*self._blockSize + overlap)
if x+1 >= self._cX:
endx = self.size_x
starty = max(0, y*self._blockSize - overlap)
endy = min(self.size_y, (y+1)*self._blockSize + overlap)
if y+1 >= self._cY:
endy = self.size_y
return [startx,endx,starty,endy]
3
Example 9
def JD(t):
Y, M = t.year, t.month
D = (
t.day
+ t.hour / (24.0)
+ t.minute / (24.0*60.0)
+ t.second / (24.0*60.0*60.0)
+ t.microsecond / (24.0 * 60.0 * 60.0 * 1e6)
)
if M <= 2:
Y = Y - 1
M = M + 12
A = np.floor(Y / 100.0)
B = 2 - A + np.floor(A / 4.0)
return np.floor(365.25*(Y+4716)) + np.floor(30.6001*(M+1)) + D + B - 1524.5
3
Example 10
Project: kwiklib Source File: selection.py
def slice_to_indices(indices, stop=None, lenindices=None, keys=None):
start, step = (indices.start or 0), (indices.step or 1)
if not stop:
assert lenindices is not None
# Infer stop such that indices and values have the same size.
stop = np.floor(start + step*lenindices)
indices = np.arange(start, stop, step).astype(np.int32)
if keys is not None:
indices = np.array(keys)[indices]
if not lenindices:
lenindices = len(indices)
assert len(indices) == lenindices
return indices
3
Example 11
def cache_sort(self, points, sorting_buckets):
if sorting_buckets < 1:
return points
if self.num_dim == 3:
points_discretized = np.floor(points * [sorting_buckets,-sorting_buckets, sorting_buckets])
indices_cache_space = np.array(points_discretized[:,2] * sorting_buckets * 4 + points_discretized[:,1] * sorting_buckets * 2 + points_discretized[:,0])
points = points[np.argsort(indices_cache_space)]
elif self.num_dim == 2:
points_discretized = np.floor(points * [sorting_buckets,-sorting_buckets])
indices_cache_space = np.array(points_discretized[:,1] * sorting_buckets * 2 + points_discretized[:,0])
points = points[np.argsort(indices_cache_space)]
else:
points_discretized = np.floor(points * [sorting_buckets])
indices_cache_space = np.array(points_discretized[:,0])
points = points[np.argsort(indices_cache_space)]
return points
3
Example 12
def isInt(x):
'''
Return True if x is an integer, or if x is a numpy array
with all integer elements, False otherwise
'''
if isinstance(x, (int, long, float)):
return abs(math.floor(x) - x) < epsilon
return (np.abs(np.floor(x) - x) < epsilon).all()
3
Example 13
Project: convolupy Source File: planes.py
@staticmethod
def _offsets_from_filter_size(fsize):
"""
Given filter size, calculate the offsets at the borders of
the input image.
"""
return [np.floor(dim / 2) for dim in fsize]
3
Example 14
Project: kaggle-galaxies Source File: load_data.py
def hms(seconds):
seconds = np.floor(seconds)
minutes, seconds = divmod(seconds, 60)
hours, minutes = divmod(minutes, 60)
return "%02d:%02d:%02d" % (hours, minutes, seconds)
3
Example 15
def gaussian_filter(kernel_shape):
x = zeros((kernel_shape, kernel_shape), dtype='float32')
def gauss(x, y, sigma=2.0):
Z = 2 * pi * sigma**2
return 1./Z * exp(-(x**2 + y**2) / (2. * sigma**2))
mid = floor(kernel_shape/ 2.)
for i in xrange(0,kernel_shape):
for j in xrange(0,kernel_shape):
x[i, j] = gauss(i-mid, j-mid)
return x / sum(x)
3
Example 16
def get_ticks(x0, x1):
nticks = NTICKS
r = nicenum(x1 - x0, False)
d = nicenum(r / (nticks - 1), True)
g0 = np.floor(x0 / d) * d
g1 = np.ceil(x1 / d) * d
nfrac = int(max(-np.floor(np.log10(d)), 0))
return np.arange(g0, g1 + .5 * d, d), nfrac
3
Example 17
Project: PySAR Source File: multi_looking.py
def multilook(ifg,lksy,lksx):
rows,cols=ifg.shape
lksx = int(lksx)
lksy = int(lksy)
rows_lowres=int(np.floor(rows/lksy))
cols_lowres=int(np.floor(cols/lksx))
#thr = np.floor(lksx*lksy/2)
ifg_Clowres=np.zeros((rows,cols_lowres))
ifg_lowres =np.zeros((rows_lowres,cols_lowres))
for c in range(int(cols_lowres)): ifg_Clowres[:,c]=np.sum(ifg[:,(c)*lksx:(c+1)*lksx],1)
for r in range(int(rows_lowres)): ifg_lowres[r,:] =np.sum(ifg_Clowres[(r)*lksy:(r+1)*lksy,:],0)
#for c in range(lksx): ifg_Clowres = ifg_Clowres + ifg[:,range(c,cols_lowres*lksx,lksx)]
#for r in range(lksy): ifg_lowres = ifg_lowres + ifg_Clowres[ range(r,rows_lowres*lksy,lksy),:]
ifg_lowres=ifg_lowres/(lksy*lksx)
return ifg_lowres
3
Example 18
def get_output_shape(self):
output_shape = list(self.input_layer.get_output_shape())
if self.ignore_border:
output_shape[-1] = int(numpy.floor(float(output_shape[-1]) /
self.ds_factor))
else:
output_shape[-1] = int(numpy.ceil(float(output_shape[-1]) /
self.ds_factor))
return tuple(output_shape)
3
Example 19
Project: kaggle_diabetic_retinopathy Source File: utils.py
def padtosquare(im):
w, l = im.shape
if w < l:
pad_size = (l - w) / 2.0
im_new = skimage.util.pad(im, pad_width=((int(np.floor(pad_size)),
int(np.ceil(pad_size))),
(0, 0)),
mode='constant',
constant_values=(1, 1))
else:
pad_size = (w - l) / 2.0
im_new = skimage.util.pad(im, pad_width=((0, 0),
(int(np.floor(pad_size)),
int(np.ceil(pad_size)))),
mode='constant',
constant_values=(1, 1))
return im_new
3
Example 20
Project: zipline Source File: position.py
def earn_stock_dividend(self, stock_dividend):
"""
Register the number of shares we held at this dividend's ex date so
that we can pay out the correct amount on the dividend's pay date.
"""
return {
'payment_asset': stock_dividend.payment_asset,
'share_count': np.floor(
self.amount * float(stock_dividend.ratio)
)
}
3
Example 21
def get_ticks(self, x0, x1):
x0 = self.interaction_manager.get_processor('viewport').normalizer.unnormalize_x(x0)
x1 = self.interaction_manager.get_processor('viewport').normalizer.unnormalize_x(x1)
r = self.nicenum(x1 - x0 - 1e-6, False)
d = self.nicenum(r / (self.parent.data_manager.nticks - 1), True)
g0 = np.floor(x0 / d) * d
g1 = np.ceil(x1 / d) * d
nfrac = int(max(-np.floor(np.log10(d)), 0))
return np.arange(g0, g1 + .5 * d, d), nfrac
3
Example 22
def handle_data(self, data):
if self.target_shares == 0:
assert 0 not in self.portfolio.positions
self.order(0, 10)
self.target_shares = 10
return
else:
assert self.portfolio.positions[0]['amount'] == \
self.target_shares, "Orders not filled immediately."
assert self.portfolio.positions[0]['last_sale_price'] == \
data[0].price, "Orders not filled at current price."
self.order_percent(0, .001)
self.target_shares += np.floor((.001 *
self.portfolio.portfolio_value)
/ data[0].price)
3
Example 23
Project: chemlab Source File: one.py
def A_array(l1,l2,PA,PB,CP,g):
"""
THO eq. 2.18 and 3.1
>>> A_array(0,0,0,0,0,1)
[1.0]
>>> A_array(0,1,1,1,1,1)
[1.0, -1.0]
>>> A_array(1,1,1,1,1,1)
[1.5, -2.5, 1.0]
"""
Imax = l1+l2+1
A = [0]*Imax
for i in range(Imax):
for r in range(int(floor(i/2)+1)):
for u in range(int(floor((i-2*r)/2)+1)):
I = i-2*r-u
A[I] = A[I] + A_term(i,r,u,l1,l2,PA,PB,CP,g)
return A
3
Example 24
@Operation.factory
def Floor(a):
"""
Floor round op.
"""
return np.floor(a),
3
Example 25
Project: abstract_rendering Source File: fast_project.py
def _project_element(viewxform, inputs, output):
tx, ty, sx, sy = viewxform
x, y, w, h = inputs
x2 = x + w
y2 = y + h
np.floor(sx * x + tx, out=output[0,:])
np.floor(sy * y + ty, out=output[1,:])
np.floor(sx * x2 + tx, out=output[2,:])
np.floor(sy * y2 + ty, out=output[3,:])
3
Example 26
Project: SimpleCV2 Source File: TemporalColorTracker.py
def _findSteadyState(self,windowSzPrct=0.05):
# slide a window across each of the signals
# find where the std dev of the window is minimal
# this is the steady state (e.g. where the
# assembly line has nothing moving)
# save the mean and sd of this value
# as a tuple in the steadyStateDict
self._steadyState = {}
for key in self.data.keys():
wndwSz = int(np.floor(windowSzPrct*len(self.data[key])))
signal = self.data[key]
# slide the window and get the std
data = [np.std(signal[i:i+wndwSz]) for i in range(0,len(signal)-wndwSz)]
# find the first spot where sd is minimal
index = np.where(data==np.min(data))[0][0]
# find the mean for the window
mean = np.mean(signal[index:index+wndwSz])
self._steadyState[key]=(mean,data[index])
3
Example 27
Project: pydem Source File: my_types.py
def _get_lon_dms(self):
deg = np.floor(abs(self.lon))
min = np.floor((abs(self.lon) - deg) * 60.0)
sec = np.round((abs(self.lon) - deg - min / 60.0) * 3600.0,
4) # round to 4 decimal places.
return (np.sign(self.lon) * deg, min, sec)
3
Example 28
def __init__(self, scale):
super(SpatialUpSamplingNearest, self).__init__()
self.scale_factor = scale
if self.scale_factor < 1:
raise Exception('scale_factor must be greater than 1')
if np.floor(self.scale_factor) != self.scale_factor:
raise Exception('scale_factor must be integer')
3
Example 29
Project: bdol-ml Source File: MLP.py
def dpp_dropout(self, dropoutProb):
if dropoutProb == 0:
return
W_n = self.W[0:-1, :]
L = (W_n.dot(W_n.T))**2
D, V = dpp.decompose_kernel(L)
k = int(np.floor((1-dropoutProb)*self.W.shape[0]))
J = dpp.sample_k(k, D, V)
d_idx = np.ones((self.W.shape[0]-1, 1))
d_idx[J.astype(int)] = 0
self.prevZ[:, 0:-1] = self.prevZ[:, 0:-1]*d_idx.T
3
Example 30
def predict(self, y_prob):
""" Calculate the prediction using the ThresholdingOptimization.
Parameters
----------
y_prob : array-like of shape = [n_samples, 2]
Predicted probabilities.
Returns
-------
y_pred : array-like of shape = [n_samples]
Predicted class
"""
y_pred = np.floor(y_prob[:, 1] + (1 - self.threshold_))
return y_pred
3
Example 31
def test_op(self):
n = tensor.lscalar()
f = theano.function([self.p, n], multinomial(n, self.p))
_n = 5
tested = f(self._p, _n)
assert tested.shape == self._p.shape
assert numpy.allclose(numpy.floor(tested.todense()), tested.todense())
assert tested[2, 1] == _n
n = tensor.lvector()
f = theano.function([self.p, n], multinomial(n, self.p))
_n = numpy.asarray([1, 2, 3, 4], dtype='int64')
tested = f(self._p, _n)
assert tested.shape == self._p.shape
assert numpy.allclose(numpy.floor(tested.todense()), tested.todense())
assert tested[2, 1] == _n[2]
3
Example 32
Project: bci-challenge-ner-2015 Source File: classif.py
def baggingIterator(opts,users):
mdls = opts['bagging']['models']
bag_size = 1-opts['bagging']['bag_size']
bag_size = numpy.floor(bag_size*len(users))
if bag_size == 0:
return [[u] for u in users]
else:
return [numpy.random.choice(users,size=bag_size,replace=False) for i in range(mdls)]
3
Example 33
Project: deep_recommend_system Source File: poisson_test.py
def testPoissonMode(self):
with self.test_session():
lam_v = [1.0, 3.0, 2.5, 3.2, 1.1, 0.05]
poisson = tf.contrib.distributions.Poisson(lam=lam_v)
self.assertEqual(poisson.mode().get_shape(), (6,))
self.assertAllClose(poisson.mode().eval(), np.floor(lam_v))
3
Example 34
Project: pycortex Source File: mayavi_aligner.py
@on_trait_change("epi_filter, filter_strength")
def update_epifilter(self):
if self.epi_filter is None:
self.epi = self.epi_orig.copy()
elif self.epi_filter == "median":
fstr = np.floor(self.filter_strength / 2)*2+1
self.epi = volume.detrend_median(self.epi_orig.T, fstr).T
elif self.epi_filter == "gradient":
self.epi = volume.detrend_gradient(self.epi_orig.T, self.filter_strength).T
self.update_brightness()
3
Example 35
Project: python-oceans Source File: RPSstuff.py
def s2hms(secs):
"""
Converts seconds to integer hour,minute,seconds
Usage: hour, min, sec = s2hms(secs)
Example
-------
>>> s2hms(3600 + 60 + 1)
(1.0, 1.0, 1)
"""
hr = np.floor(secs / 3600)
mi = np.floor(np.remainder(secs, 3600) / 60)
sc = np.round(np.remainder(secs, 60))
return hr, mi, sc
3
Example 36
Project: radiotool Source File: track.py
def loudest_time(self, start=0, duration=0):
"""Find the loudest time in the window given by start and duration
Returns frame number in context of entire track, not just the window.
:param integer start: Start frame
:param integer duration: Number of frames to consider from start
:returns: Frame number of loudest frame
:rtype: integer
"""
if duration == 0:
duration = self.sound.nframes
self.current_frame = start
arr = self.read_frames(duration)
# get the frame of the maximum amplitude
# different names for the same thing...
# max_amp_sample = a.argmax(axis=0)[a.max(axis=0).argmax()]
max_amp_sample = int(np.floor(arr.argmax()/2)) + start
return max_amp_sample
3
Example 37
Project: pyquante2 Source File: one.py
def overlap1d(l1,l2,PAx,PBx,gamma):
"""
The one-dimensional component of the overlap integral. Taken from THO eq. 2.12
>>> isclose(overlap1d(0,0,0,0,1),1.0)
True
"""
total = 0
for i in range(1+int(floor(0.5*(l1+l2)))):
total += binomial_prefactor(2*i,l1,l2,PAx,PBx)* \
fact2(2*i-1)/pow(2*gamma,i)
return total
3
Example 38
Project: refinery Source File: LearnAlg.py
def isFirstBatch(self, lapFrac):
''' Returns True/False for whether given batch is last (for current lap)
'''
if self.lapFracInc == 1.0: # Special case, nBatch == 1
isFirstBatch = True
else:
isFirstBatch = np.allclose(lapFrac - np.floor(lapFrac), self.lapFracInc)
return isFirstBatch
3
Example 39
def conv(X, w, b=None):
# z = dnn_conv(X, w, border_mode=int(np.floor(w.get_value().shape[-1]/2.)))
s = int(np.floor(w.get_value().shape[-1]/2.))
z = conv2d(X, w, border_mode='full')[:, :, s:-s, s:-s]
if b is not None:
z += b.dimshuffle('x', 0, 'x', 'x')
return z
3
Example 40
def asInt(self):
'''
Return a dictionary representing the rectangle with integer values
'''
x = int(np.floor(self.x))
y = int(np.floor(self.y))
w = int(np.floor(self.w))
h = int(np.floor(self.h))
return {'x':x,'y':y,'w':w,'h':h}
3
Example 41
Project: scikit-datasmooth Source File: regularsmooth.py
def _submatrix_of_integration_matrix(self, B):
"""Return integration matrix whose size matches derivative matrix."""
d = self.d
start = int(np.floor(d/2))
end = -start if is_even(d) else -(start + 1)
b_slice = slice(start, end)
return B[b_slice, b_slice]
3
Example 42
@jit(nopython=True,locals={'dp': numba.int64, 'df': numba.int64})
def mix_(x,f,p,tab):
n = len(x)
dp = int(np.floor(p*NT*(1<<50)))
df = int(np.floor(f*NT*(1<<50)))
for i in range(n):
idx = dp>>50
x[i] *= tab[idx&(NT-1)]
dp += df
3
Example 43
Project: MCEdit-Unified Source File: clone.py
def _draggingOrigin(self):
dragPos = map(int, map(numpy.floor, self.positionOnDraggingPlane()))
delta = map(lambda s, e: e - int(numpy.floor(s)), self.draggingStartPoint, dragPos)
if self.snapCloneKey == 1:
ad = map(abs, delta)
midx = ad.index(max(ad))
d = [0, 0, 0]
d[midx] = delta[midx]
dragY = self.draggingFace >> 1
d[dragY] = delta[dragY]
delta = d
p = self.destPoint + delta
if self.chunkAlign:
p = [i // 16 * 16 for i in p]
return Vector(*p)
3
Example 44
Project: FreqShow Source File: views.py
def render_spectrogram(self, screen):
# Grab spectrogram data.
freqs = self.model.get_data()
# Scale frequency values to fit on the screen based on the min and max
# intensity values.
x, y, width, height = screen.get_rect()
freqs = height-np.floor(((freqs-self.model.min_intensity)/self.model.range)*height)
# Render frequency graph.
screen.fill(freqshow.MAIN_BG)
# Draw line segments to join each FFT result bin.
ylast = freqs[0]
for i in range(1, width):
y = freqs[i]
pygame.draw.line(screen, freqshow.INSTANT_LINE, (i-1, ylast), (i, y))
ylast = y
3
Example 45
def fun(self, x, *args):
self.nfev += 1
d = [1., 1000., 10., 100.]
r = 0
for j in range(4):
zj = floor(abs(x[j] / 0.2) + 0.49999) * sign(x[j]) * 0.2
if abs(x[j] - zj) < 0.05:
r += 0.15 * ((zj - 0.05 * sign(zj)) ** 2) * d[j]
else:
r += d[j] * x[j] * x[j]
return r
3
Example 46
def code(prn,chips,frac,incr,n):
len = np.int(np.floor(n*incr)+5)
c = p_code(prn,chips,len).astype('int')
idx = frac + incr*np.arange(n)
idx = np.floor(idx).astype('int')
x = c[idx]
return 1.0 - 2.0*x
3
Example 47
Project: python-oceans Source File: RPSstuff.py
def h2hms(hours):
"""
Converts hours to hours, minutes, and seconds.
Example
-------
>>> h2hms(12.51)
(12.0, 30.0, 36.0)
"""
hour = np.floor(hours)
mins = np.remainder(hours, 1.) * 60.
mn = np.floor(mins)
secs = np.round(np.remainder(mins, 1.) * 60.)
return hour, mn, secs
3
Example 48
def test_op(self):
for sp_format in sparse.sparse_formats:
for o_type in sparse.float_dtypes:
f = theano.function(
self.inputs,
Binomial(sp_format, o_type)(*self.inputs))
tested = f(*self._inputs)
assert tested.shape == tuple(self._shape)
assert tested.format == sp_format
assert tested.dtype == o_type
assert numpy.allclose(numpy.floor(tested.todense()),
tested.todense())
3
Example 49
Project: qualityvis Source File: OWPCA.py
def on_cutoff_moved(self, value):
"""Cutoff curve was moved by the user.
"""
components = int(np.floor(value)) + 1
# Did the number of components actually change
self.max_components = components
self.variance_covered = self.variances_cuemsum[components - 1] * 100
if self.currently_selected != self.number_of_selected_components():
self.update_components_if()
3
Example 50
Project: gammatone Source File: gtgram.py
def gtgram_strides(fs, window_time, hop_time, filterbank_cols):
"""
Calculates the window size for a gammatonegram.
@return a tuple of (window_size, hop_samples, output_columns)
"""
nwin = int(round_half_away_from_zero(window_time * fs))
hop_samples = int(round_half_away_from_zero(hop_time * fs))
columns = (1
+ int(
np.floor(
(filterbank_cols - nwin)
/ hop_samples
)
)
)
return (nwin, hop_samples, columns)