def hslice(self, value):
"""
slice a spectrogram at a given position along the y axis, maintains
variable names from spectrogram
Parameters
==========
value : float or datetime.datetime
the value to slice the spectrogram at
Returns
=======
out : datamodel.SpaceData
spacedata containing the slice
"""
# using bisect find the index of the spectrogram to use
if isinstance(value, datetime.datetime):
value = date2num(value)
ind = bisect.bisect_right(self['spectrogram']['yedges'], value)
ans = dm.SpaceData()
ans[self['spectrogram'].attrs['variables']
[0]] = tb.bin_edges_to_center(self['spectrogram']['xedges'])
ans['yedges'] = self['spectrogram']['yedges'][ind:ind + 2].copy()
ans['xedges'] = self['spectrogram']['xedges'].copy()
ans[self['spectrogram'].attrs['variables']
[2]] = self['spectrogram']['spectrogram'][ind, :]
return ans
def hslice(self, value):
"""
slice a spectrogram at a given position along the y axis, maintains
variable names from spectrogram
Parameters
==========
value : float or datetime.datetime
the value to slice the spectrogram at
Returns
=======
out : datamodel.SpaceData
spacedata containing the slice
"""
# using bisect find the index of the spectrogram to use
if isinstance(value, datetime.datetime):
value = date2num(value)
ind = bisect.bisect_right(self['spectrogram']['yedges'], value)
ans = dm.SpaceData()
ans[self['spectrogram'].attrs['variables'][0]] = tb.bin_edges_to_center(self['spectrogram']['xedges'])
ans['yedges'] = self['spectrogram']['yedges'][ind:ind+2].copy()
ans['xedges'] = self['spectrogram']['xedges'].copy()
ans[self['spectrogram'].attrs['variables'][2]] = self['spectrogram']['spectrogram'][ind, :]
return ans
def testBinEdgesToCenter(self):
"""Convert a set of bin edges to bin centers"""
inputs = [[1, 2, 3, 4, 5],
[1,2,3,7,10,20],
]
outputs = [[1.5, 2.5, 3.5, 4.5],
[1.5, 2.5, 5, 8.5, 15],]
for i, val in enumerate(inputs):
numpy.testing.assert_almost_equal(outputs[i], tb.bin_edges_to_center(val))
def testBinEdgesToCenter(self):
"""Convert a set of bin edges to bin centers"""
inputs = [[1, 2, 3, 4, 5],
[1,2,3,7,10,20],
]
outputs = [[1.5, 2.5, 3.5, 4.5],
[1.5, 2.5, 5, 8.5, 15],]
for i, val in enumerate(inputs):
numpy.testing.assert_almost_equal(outputs[i], tb.bin_edges_to_center(val))
def testBinEdgesToCenterToEdges_datetimeroundtrip(self):
"""Convert a set of datetime bin edges to centers and back to bin edges"""
inputs = [datetime.datetime(2012,9,3,n) for n in range(10)]
computedOut = tb.bin_edges_to_center(inputs)
roundtripResults = tb.bin_center_to_edges(computedOut)
self.assertTrue((inputs == roundtripResults).all())
def testBinEdgesToCenterToEdges_datetimeroundtrip(self):
"""Convert a set of datetime bin edges to centers and back to bin edges"""
inputs = [datetime.datetime(2012,9,3,n) for n in range(10)]
computedOut = tb.bin_edges_to_center(inputs)
roundtripResults = tb.bin_center_to_edges(computedOut)
self.assertTrue((inputs == roundtripResults).all())
for npts in tqdm.tqdm_notebook(range(1,102,40)):
d1 = sampledat[np.random.randint(0, len(sampledat), npts)]
with pm.Model() as model:
alpha = pm.Uniform('loc', -10, 10)
# beta = pm.Uniform('dist', 1, 1)
x = pm.Cauchy(name='x', alpha=alpha, beta=1, observed=d1)
trace = pm.sample(10000)
hists[npts] = np.histogram(trace['loc'], bins)
stats[npts] = np.percentile(trace['loc'], (1, 5, 25, 50, 75, 95, 99))
# In[40]:
keys = sorted(list(hists.keys()))
for k in keys:
p = plt.plot(tb.bin_edges_to_center(bins), hists[k][0]/np.max(hists[k][0]),
drawstyle='steps', label=str(k), lw=1)
c = p[0].get_color()
plt.axvline(stats[k][3], lw=3, color=c)
print(k, stats[k][2:5], stats[k][3]/(stats[k][4]-stats[k][2]), )
plt.legend()
plt.xlim((-2,2))
# ## if both are unknown
# In[65]:
# generate some data
bins = np.linspace(-4,4,100)
hists2 = {}