This is a minor release with an important bug fix for histograms plots and other tweaks mostly for PAX. New “short notebooks” for common tasks have also been added.
Bug fixes:
BurstsGap
giving an error when being sliced
(see #62).Other changes:
skip_ch
to Data.collapse
and to dplot
.vmin=1
by default in alex_jointplot
and hexbin_alex
.Data.burst_sizes_pax_ich
)timetrace
.
See the new example notebook for timetrace plotting.This release adds support for periodic acceptor excitation (PAX) measurements. PAX is similar to μs-ALEX, with the difference that only the A laser is alternated (see references [pax] and [48spot]). There are also a few minor bug fixes and better support for 48-spot data.
To update to the latest version type conda install fretbursts -c conda-forge
.
For installation instructions see Getting Started.
The list of changes include:
bext.burst_data()
: bugfix, add tests and improve handling of multispot dataapionly
argument to init_notebook()
for setting up the notebook
plots without changing any plot style (see 958824).alex_jointplot
.Data
fields for E and S in alex_jointplot
.alex_jointplot
plots.hist_bg
(see Issue 61).
Many thanks to Danielis Rutkauskas for reporting the issue.d.E_
needs to be changed to d.E[0]
.
This syntax was causing difficulties during developing new features for PAX.
Please report if you would like for the syntax to be reintroduced.[pax] | Doose et al. European Biophysics Journal 36(6) p.669-674, 2007. DOI:10.1007/s00249-007-0133-7 |
[48spot] | Ingargiola et al. bioRxiv 156182, 2017. DOI:10.1101/156182 |
A few more small fixes in this release. If you have any installation issue please report it on github.
OpenFileDialog
when FRETBursts is imported (as in versions < 0.6.2)phconvert
to decode SM filesThis is a technical release that removes the hard dependency on QT and solves some installation issues due to QT pinning on conda-forge.
For this version of FRETBursts, conda packages are distributed for python 2.7, 3.5, 3.6 and numpy 1.11 and 1.12. FRETBursts still works with python 3.4 but conda packages are not provided anymore. Python 2.7 is now deprecated. Support for python 2.7 will be removed in a future version.
The current release includes the following changes:
L
argument in
burst search was ignored and submitted a fix to the problem in
PR #57.
Tests were added to avoid future regressions.loader.photon_hdf5()
.
See 201b5c.Ph_sel
string representation, added factory method Ph_sel.from_str
and added new tests.
See 3dc5f0.ondisk=True
and 30% speed increase
when using ondisk=False
.
Now all background rates are stored in the dictionary Data.bg
,
while the mean background rate in the dictionary Data.bg_mean
.
The old attributes Data.bg_*
and Data.rate_*
have been deprecated
and will be removed in a future release (see below).ondisk=True
. With this option timestamps are not
kept in RAM but loaded spot-by-spot when needed. This option has no effect
on single-spot measurements but will save RAM in multi-spot measurements.hist_bg
(and hist_bg_single
) did the same plot but required
the background to be fitted. hist_interphoton*
do not require any prior
background fit and also have a cleaner and improved API.Version 0.6 introduced a small change in how the auto-threshold for background estimation is computed. This results in slightly different background rates. As a consequence, burst searches setting a threshold as function of the background, will set a slightly different threshold and will find different number of bursts. The difference is not dramatic, but can result in slight numeric changes in estimated parameters.
The refactor included a change in how the background is computed when using
tail_min_us='auto'
. As before, with this setting, the background is
estimated iteratively in two steps. A first raw estimation with a fixed
threshold (250us), and second estimation with a threshold function of the
rate computed in the first step. Before version 0.6, the first step estimated
a single rate for the whole measurement. Now the first-step estimation is
performed in each background period separately. As before, the second step
computes the background separately in each background period.
This change was motivated by the need to simplify the internal logic
of background estimation, and to increase the computation efficiency
and accuracy.
The background refactor resulted in an incompatible change in the
Data.bg
attribute. Users upgrading to version 0.6, may need to replace
Data.bg
with Data.bg[Ph_sel('all')]
in their notebooks. Note that
no official FRETBursts notebook was using Data.bg
, so most users will not be
affected.
All the old background-related attributes (bg_dd, bg_ad, bg_da, bg_aa,
rate_dd, rate_ad, rate_da, rate_aa, rate_m) are still present but deprecated.
The same data is now contained in the dictionaries
Data.bg
and Data.bg_mean
.
When using the deprecated attributes, a message will indicate the new syntax.
If you see the deprecation warning, please update the notebook
to avoid future errors.
Before version 0.6, Data.bg
contained background rates
fitted for all-photons stream. Data.bg
was a list of arrays:
one array per spot, one array element per background period.
In version 0.6+, Data.bg
contains the background rates for all the fitted
photon streams. Data.bg
is now a dict using Ph_sel
objects as keys.
Each dict entry is a list of array, one array per spot and one array element
per background period. For more details please refer to the following
documentation Data.bg
and Data.bg_mean
.
There may still be some glitches when using the QT5 GUIs from the notebook, but installing (and importing) FRETBursts does not require QT4 anymore (QT5 is the current default in anaconda). Please report any issue.
Refactoring and expansion of gamma and beta corrections.
Briefly, in all the places where corrected burst sizes are being computed,
we removed the gamma1
argument and added a flag donor_ref
.
Additionally, the values Data.S
are now beta corrected.
These changes affected several components as described below.
Data.burst_sizes_ich
and Data.burst_sizes
now accept the
arguments gamma
, beta
and donor_ref
. The argument gamma1
was removed.
The two conventions of corrected burst sizes are chosen with the boolean
flag donor_ref
.
See the burst_sizes_ich docs
for details.get_naa_corrected
returns the array of naa
burst counts
corrected with the passed gamma
and beta
values. Like for the burst
size, the argument donor_ref
selects the convention for the correction.
See the get_naa_corrected docs
for details.Data
attribute beta
(default: 1) stores a beta value that is used
to compute the corrected S. This value is never implicitly used to compute
corrected burst sizes or naa (for these a beta
arguments needs to be
passed explicitly).Plot functions hist_size
and hist_brightness
accept the new arguments
for corrected burst size (gamma
, beta
and donor_ref
).
Burst selection by size
and naa
accept the new arguments
for corrected burst size (gamma
, beta
and donor_ref
).
Functions that accept weights don’t accept the gamma1 argument anymore,
but they don’t (yet) support the arguments donor_ref
and beta
.
As a result, for the purpose of weighting, there is only one expression
for corrected burst size (na + gamma*nd
), with the option to add naa
but without beta correction.
All these changes are covered by unit tests.
Since version 0.5.6 we started distributing conda packages for FRETBursts through the conda-forge channel (a community supported repository, as opposed to a private channel we were using before). To install or update FRETBursts you should now use:
conda install fretbursts -c conda-forge
Using the conda-forge channel simplifies our release process since their infrastructure automatically builds packages for multiple platforms and python versions. Please report any issues in installing or upgrading FRETBursts on the GitHub Issues page.
For more detailed installation instructions see the Getting Started documentation.
For older release notes see GitHub Releases Page.