Changelog
v0.2.0 (28.06.2025)
Moved to more modern development practices: automatic tests, linter, formatter, upload to PyPI
v0.1.9
removed the display-variable environment check. turned out to get in the way more often than helping.
removed large parts of the over-engineered logging (helps with dask)
we now simply use
logging.getLogger("mrestimator")to adjust the logging, call e.g.
logging.basicConfig(level="INFO")before importing mrestimatoruse
mre.enable_progressbar()andmre.disable_progressbar()to toggle tqdm, module-wide
no longer capturing numpy warnings into the logger. to manually readd this: .. code-block:
logging.captureWarnings(True) logging.getLogger("py.warnings")
v0.1.8 (18.10.2021)
Since a recent update of numba, coefficients are computed incorrectly when parallelizing. This version disables the numba parallelization.
v0.1.7 (07.05.2021)
Consistency fixes of the example scripts to comply with the paper
v0.1.6 (23.04.2020)
Changed: Now under BSD 3-Clause License
Changed: When the data has more than one trial, we now require the user to choose which coefficient method to use (
tsorsm) inmre.coefficients()andmre.full_analysis(). We showed that the resulting time scale that one finds can differ severely between the two methods. If unsure, compare results from both. We explain the difference in the paper and print some recommendation from the toolbox.Changed: Due to above,
methodis now the second positional argument (this might break scripts that gavesteps,dt, ordtunitas positonal arguments). Callmre.coefficients(data, 'ts')or as before via keywordmre.coefficients(data, method='ts')Fixed: Typo that caused
full_analysis()to crash when calling the consistency check.Fixed: Workaround to prevent a memory leak when calling
full_analysis()repeatedly. Always setshowoverview=Falsewhen usingfull_analysis()in for loops. We now temporarily setmatplotlib.rcParams['interactive'] = showoverviewto avoid opening a new figure every time. This should make the panel andshowoverviewargument feel more consistent. The same workaround can be used in your custom scripts when using theOutputHandler(that also opens figures): Nest the loop inside awith matplotlib.rc_context(rc={'interactive': False}):(or adjust your rc parameters) to avoid figures.Fixed: Various small bugs
New:
coefficientshas a new keyword argumentknownmeanto provide a known mean activity. If provdied, it will be used as the expectation value of the activity instead of calculating the mean as an approximation (both, instationarymeanandtrialseparatedmethod). This allows for custom estimates but, for instance,m>1will not be detectable as the covariance cannot diverge when the same (time independent) expectation value is used for<a_{t}>and<a_{t+k}>. As one example,knownmean=0restrains the fitted line (with sloper_k) to go through the origin(0,0). See Zierenberg et al., in press.
v0.1.5 (24.09.2019)
Changed: One-file spaghetti code was separated into submodules.
Fixed:
stationarymeanmethod for coefficients should work form>1(Note that this is a non-standard case. A detailed discussion will follow.)New: Optional Numba dependency to parallelize and precompile the computation of the correlation coefficients. To install numby along with mrestimator,
pip install -U mrestimator[numba]New: Uploading pre-release versions to pypi. To switch run
pip install -U --pre mrestimator[full]and to go back to stablepip install mrestimator==0.1.5.New: Basic unit tests.
python -m unittest mrestimator.test_suite
v0.1.4 (05.02.2019)
Changed:
full_analysis()argumentfitfunctionsrenamed tofitfuncsto be consistent withfit()andcoefficients()Changed:
full_analysis()was rewritten, now only has three required arguments:data,dtandkmax, wherekmaxcan be substituted bystepsortmax.Changed: concerning the
seedargument for various functions: all functions take eitherseed=None(no reseeding),seed='random'(reseeding to a random value - causing irreproducible resaults) or to a fixed valueseed=int(yourseed). Per default, analysis functions -full_analysis(),fit()andcoefficients()- produce same results by seeding to a fixed value each call. (only confidence intervals are affected by seeding) Per default,simulate_branching()andsimulate_subsampling()seed torandom.Fixed: when calling branching process with
subpand providing a seed, the subsampling no longer reseeds the rng device. (hence every call produces the same outcome, as expected)Fixed:
simulate_subsampling()now returns np arrays of correct dimensionsNew:
full_analysis()now shows a warning in the overview panel if consistency checks fail (so far only one).New: Version number is printed into the overview panel of
full_analysis()and into saved meta data
v0.1.3 (16.01.2019)
This is a bugfix version in preparation for the wrapper rewrite in 0.1.4.
Changed: If no
stepsare provided tocoefficients(), the default maxstep is (for now) 1/10 of the trial length. (Was hard coded to 1500 before)Changed: Default logs are less verbose to be clearer. The new function
mre._enable_detailed_logging()enables fully detailed output to console and logfile. This also calls the two new switches, see next point.mre._enable_detailed_logging()also enables console display of runtime warnings that are usually only printed into the log.Fixed: Crash due to logfiles. If the toolbox was used by more than one user on one machine, the logfile created in the temporary directory could not be overwritten by other users. We now try to set file permissions of the logfile and target directory to
777if they are not subfolders of the user folder. Also, per default, each user gets their own directory/tmp/mre_username. Logfilehandler is now rotating and creates a maximum of 10 logfiles, 50mb each.Fixed:
full_analysis()no longer crashes withsubstracttrialaverage=Truewhen the provided input is of integer type.Fixed:
fit()now returns a (mostly empty)FitResultwhen no fit converged instead of raising an exception. Helps with scripts that run multiple fits. The returned FitResult works with the OutputHandler in default settings and a note about the failed fit is added to the description and meta data.Fixed: Calling
coefficients()with custom steps e.g.steps=np.arange(0,100,5)is more robust and does not crash due tosteps < 1. Incorrect entries are replaced.Fixed:
OutputHandlernow has a deconstructor that closes the matplotlib figure if it was not provided as an arugment. Hence, opening many handlers (e.g. by reassigning a variable in a loopo = mre.OutputHandler()) does not keep the figure after reusing the variable. This used to cause a warning:More than 20 figures have been opened.New: Enable logging of function arguments to console and logfile with
mre._log_locals = True. Enable logging of stack traces to logfile viamre._log_trace = True. (Avoiding the console printout of stack traces on exceptions is not feasible at the moment). Per default, both options areFalse.
v0.1.2 (27.11.2018)
Changed:
coefficients()withtrialseparatemethod calculatesrkdifferently (now strictly linear regression). This should enablem>1estimates.Changed: builtin fitfunctions now use absolute values of the amplitude of the exponential term
Changed: fits drawn above data (again), otherwise, they get hidden if data is noisy
Fixed: maximum steps
kincoefficientscannot exceed half the trial length any longer. this could lead to strong fluctuations inr_kand fits would failFixed: Crashes when providing custom fitfunctions to
fit()due to unhandled request of default parametersNew: Rasterization of plots in the
OutputHandler. Especially timeseries grow large quickly. Now, if OutputHandlers create their own figures/axes elements (ax-argument not given on construction) all elements withzorder<0are rastered. Per default,add_ts()uses azorderof-1butadd_coefficients()andadd_fit()have values above one so they stay vectorized. Callax.set_rasterization_zorder(0)on your customaxaxes element if you want the same effect on customized figures.New: export as png option for
OutputHandler.save_plot()
v0.1.1 (01.11.2018)
Changed: We reworked the structure of
CoefficientResultto be more consistent. This is now a completely selfsimilar , where each child-entry has exactly the same structure as the parent. The new attributestrialcrsandbootstrapcrsreplacedsamples. Both are now lists containing againCoefficientResults, any (previously multidmensional) ndarrays are now 1d.Changed: Per default,
full_analysis()initialises the random number generator (used for bootstrapping) once per call and passesNoneto the seed arguments of lower functions so they do not reseed. We introduced the convention thatseed=Nonetells that function to use the current state of the rng without seeding. (Added anautooption for seeding where needed)Changed: All prints now use the logging module. Hopefully nothing broke :P.
Changed: Default log level to console is now ‘INFO’, and some logs that one could consider info go to ‘DEBUG’ to decrease the spam. Default loglevel to file is ‘DEBUG’ (logfile placed in the default temporary directory, which is also printed when loading the toolbox).
Changed: When providing no loglevel to
full_analysis()it uses the currently set level ofmre._logstreamhandler.Fixed: When calling
full_analysis()with one trial, a running average is shown instead of an empty plot.New: Added quantiles (and standard errors) to fit results if bootstrapping. The new default option,
numboot='auto'calculates 250 bootstrap samples for the exponential and exp+offset fit functions (which are decently fast) and skips error estimation for the builtin complex (and custom) fits.New: Added function
set_logfile(fname, loglevel='DEBUG')to change the path of the global logfile + level. This should allow running the toolbox in parallel, with a seperate logfile per thread and relatively silent/no console output when combining withmre._logstreamhandler.setLevel('ERROR')or callingfull_analysis(..., loglevel='ERROR')New: Undocumented way to change the respective loglevels is e.g.
mre._logstreamhandler.setLevel('WARNING')for console andmre._logfilehandler.setLevel('DEBUG')for fileNew: Added custom handler class that does not log ‘None Type’ Traces if
log.exception()is called without atrystatement
v0.1.0 (11.10.2018)
Changed: OutputHandlers set_xdata() now adjusts existing data and is slightly smarter. Now returns an array containing the indices where the x axis value is right for the provided data (wrt the existing context). See the example in the documentation.
Changed: When calling OutputHanlders
add_coefficients()oradd_ts(), the meta data and plot range will be extended usingset_xdata. Trying to add duplicates only changes their style to the new provided values (without adding meta).Changed: The parameters of
simulate_branching()are different.activityis nowa,mis no longer optional and it is possible to set a (time dependent) drive usingh.Fixed: Calling
fit()with only one trial does not crash anymore due to missing uncertaintiesFixed: Calling
fit()without specifyingstepsnow uses the range used incoefficients().New: added
full_analysis(), the wrapper function to chain individual tasks together.New: added
simulate_subsampling()New: Whenn adding time series to the
OutputHandlerin trial structure with more than one trial viaadd_ts(), they are drawn slightly transparent by default. Settingalphaoverwrites this.add_tsdoes not use the newset_xdata()yet.New: Versionbump so we have the last digit for bugfixes :)
New: Mr. Estimator came up with his logo.
v0.0.3 (19.09.2018)
Changed: Check for old numpy versions in
fit()Changed: Per default, fits are drawn solid (dashed) over the fitted (remaining) range
Fixed: Typos
(14.09.2018)
New: CoefficientResult constructor now has some default arguments. Still required:
stepsandcoefficients. Also added thedt, dtunitattributes.New: FitResult constructor now has some default arguments. Still required: ‘tau, mre, fitfunc’. Also added the
dt, dtunit, stepsattributes.New:
fit()takes argumentsteps=(minstep, maxstep)to specify a custom fitrange.OutputHandlerplots the fitted range opaque (excluded range has less alpha).Changed:
dtis no longer an argument forfit(). Settingdt(the step size) and its unitsdtunitis done via the equally named parameters ofcoefficients(). It is added to theCoefficientResult, sofitand theOutputHandlercan rely on it.
(13.09.2018)
Renamed: module from
mretomrestimator, useimport mrestimator as mreRenamed:
correlation_coefficients()tocoefficients()Renamed:
correlation_fit()tofit()Renamed:
CorrelationFitResulttoFitResult