photonpacket.frameseries module

photonpacket.frameseries.emptyframe(shape)

class photonpacket.frameseries.frameseries(photons, idxs, shape, cut=True, dtype=<class 'numpy.uint16'>)

Bases: object

Methods

accumautocoinc()	Accumulate autocoincidences
accumframes([first, nframes])	Accumulate all photons from frames ranging from first to first+nframes defaults to all frames
append(fs)	Append antoher frameseries to current frameseries
copy()	Copies the frameseries in memory and returns new object
cuttoshape(shape)	Cut frames to shape
delneighbours([r, metric])	Find photon pairs that are too close to each other and remove second photon from the frame args: radius, metric (c.f.
delsubsequent([Nf])	Delete Nf frames after photon is detected in one
delsubsmask([Nf])	Get the mask corresponding to delsubsequent function; does not alter the object
dtype	alias of numpy.uint16
from_dict(d)	Create frameseries object from dictionary
len()	Get total length fo series of frames Nframes
plot([samples])	Plot the series as a time series of photon number after resampling
rescale(scale, centerpoint)	Rescale coordinate system
rescalediv(factor)	rescale photon positions by factor = old_div / new_div
rotate(angle, centerpoint)	Rotate coordinate system
shift(n)	Shift frames
store(fname)	Store pickled frameseries
timeseries([samples])	Get photon numbers as resampled time series
transform(transform)	Affine tranformation of photons.

delframes
fs_frames
g2
imshow
maskframes
mean
std
thmodes
var

N = array([], dtype=float64)

Nframes = 0

accumautocoinc()

Accumulate autocoincidences

accumframes(first=0, nframes='all', **kwargs)

Accumulate all photons from frames ranging from first to first+nframes defaults to all frames

‘kwargs’ : minphotons, maxphotons (filters out frames), nphotons

Returns

accumnumpy.ndarray

append(fs)

Append antoher frameseries to current frameseries

copy()

Copies the frameseries in memory and returns new object

cuttoshape(shape)

Cut frames to shape

shape :

delframes(max_photons=20)

delneighbours(r=5, metric='euclidean')

Find photon pairs that are too close to each other and remove second photon from the frame args: radius, metric (c.f. scipy.spatial.distance.pdist)

delsubsequent(Nf=10)

Delete Nf frames after photon is detected in one

delsubsmask(Nf=10)

Get the mask corresponding to delsubsequent function; does not alter the object

dtype

alias of numpy.uint16

classmethod from_dict(d)

Create frameseries object from dictionary

photons : numpy.ndarray

idxs : numpy.ndarray

shape : tuple

cut : bool

dtype : data-type

class fs_frames(fs)

Bases: object

Methods

asarray

asarray()

g2(uncert=False)

idxs = array([], dtype=float64)

imshow(**kwargs)

len()

Get total length fo series of frames Nframes

maskframes(frame_mask)

mean(uncert=False)

photons = array([], dtype=float64)

plot(samples=1000)

Plot the series as a time series of photon number after resampling

rescale(scale, centerpoint)

Rescale coordinate system

factor :

axis :

rescalediv(factor)

rescale photon positions by factor = old_div / new_div

rotate(angle, centerpoint)

Rotate coordinate system

angle :

shape = ()

shift(n)

Shift frames

n :

std(uncert=False)

store(fname)

Store pickled frameseries

fnamestring

file name

thmodes(uncert=False)

timeseries(samples=1000)

Get photon numbers as resampled time series

transform(transform)

Affine tranformation of photons.

transformtuple

(a,b,c,d,e,f), where ((a,b), (c,d)) is transformation matrix and (e,f) is the added vector

var(uncert=False)

photonpacket.frameseries.fsconcat(fslist)

Concatenate frameseries

photonpacket.frameseries.fsmerge(fslist)

Merge frame-by-frame

photonpacket.frameseries.fsplot(fslist, samples=1000)

Plot mutltiple frameseries as photon number time series

photonpacket.frameseries.loadfs(fname)

Load frameseries from file

class photonpacket.frameseries.singleframe(photons, idxs, shape, cut=True, dtype=<class 'numpy.uint16'>)

Bases: photonpacket.frameseries.frameseries

Methods

accumautocoinc()	Accumulate autocoincidences
accumframes([first, nframes])	Accumulate all photons from frames ranging from first to first+nframes defaults to all frames
append(fs)	Append antoher frameseries to current frameseries
copy()	Copies the frameseries in memory and returns new object
cuttoshape(shape)	Cut frames to shape
delneighbours([r, metric])	Find photon pairs that are too close to each other and remove second photon from the frame args: radius, metric (c.f.
delsubsequent([Nf])	Delete Nf frames after photon is detected in one
delsubsmask([Nf])	Get the mask corresponding to delsubsequent function; does not alter the object
dtype	alias of numpy.uint16
from_dict(d)	Create frameseries object from dictionary
len()	Get total length fo series of frames Nframes
plot([samples])	Plot the series as a time series of photon number after resampling
rescale(scale, centerpoint)	Rescale coordinate system
rescalediv(factor)	rescale photon positions by factor = old_div / new_div
rotate(angle, centerpoint)	Rotate coordinate system
shift(n)	Shift frames
store(fname)	Store pickled frameseries
timeseries([samples])	Get photon numbers as resampled time series
transform(transform)	Affine tranformation of photons.

delframes
fs_frames
g2
imshow
maskframes
mean
scatter
std
thmodes
var

scatter()