diff --git a/.github/workflows/python-package.yml b/.github/workflows/python-package.yml index 37f9f62..a840c0c 100644 --- a/.github/workflows/python-package.yml +++ b/.github/workflows/python-package.yml @@ -13,7 +13,7 @@ jobs: fail-fast: false matrix: os: ["ubuntu-latest"] - python-version: ["3.9"] + python-version: ["3.10"] steps: - uses: actions/checkout@v2 - uses: s-weigand/setup-conda@v1 diff --git a/docs/generate_templates.rst b/docs/generate_templates.rst index eb5e3c5..87f3062 100644 --- a/docs/generate_templates.rst +++ b/docs/generate_templates.rst @@ -14,7 +14,7 @@ A set of 13 cell models from layer 5 is included in the basic installation and c the `download `_ page, move them to the cell model folder (which can be retrieved with the :code:`mearec default-config` command or with the Python code: :code:`mr.get_default_cell_models_folder()`), and unzip them. -Note also custom models cane be used. In `this notebook `_ we show how to use models from the +Note also custom models cane be used. In `this notebook `_ we show how to use models from the `Allen database `_ to build templates (and recordings). Templates are generated in two steps: diff --git a/docs/usage.rst b/docs/usage.rst index 36fb250..b191dec 100644 --- a/docs/usage.rst +++ b/docs/usage.rst @@ -36,7 +36,7 @@ The :code:`recgen` is a :code:`RecordingGenerator` objects and contains the foll * spike_traces: (n_spiketrains, n_samples) clean spike trace for each spike train * info: dictionary with parameters used -There are several notebooks available `here `_ +There are several notebooks available `here `_ that show MEArec applications. Plotting diff --git a/docs/whatisnew.rst b/docs/whatisnew.rst index e18f015..84fc53b 100644 --- a/docs/whatisnew.rst +++ b/docs/whatisnew.rst @@ -5,11 +5,35 @@ Release notes ============= +Version 1.9.1 +============= + +6th April 2024 + +Bug fixes +--------- + +- Fix n_burst_spikes param (when missing from default dict) (#156) +- Fix jitter generation in drifting (#153) + +Improvements +------------ + +- Load templates as memmap rather than in memory (#167) +- Little clean of padding templates (#165) +- Do not remove resampled templates if not resampled enhancement (#163) +- Fix numpy deprecations (#162) +- Improve documentation (#159) + + Version 1.9.0 ============= +23rd May 2023 + -### Bug fixes +Bug fixes +--------- - Propagate filter order and add filter mode (#145) - Fix resampling timing (#141) @@ -18,7 +42,9 @@ Version 1.9.0 - Fix passing template_ids (#120) -### New features +New features +------------ + - Add option to control the drift linear gradient (#129) - Define external drifts (#128) @@ -26,11 +52,13 @@ Version 1.9.0 - Add extract_units_drift_vector (#122) -### Improvements +Improvements +------------ - Convolution computed in float for more precision (#118) -### Packaging +Packaging +--------- - Packaging: move to pyproject.toml, src structure, and black (#146) @@ -38,13 +66,17 @@ Version 1.9.0 Version 1.8.0 ============= -### New features +18th July 2022 + +New features +------------ - Refactored drift generation (#97) - Add LSB, ADC_BIT_DEPTH, and GAIN concepts (#104, #105) - Add smoothing step to templates to make sure they sart and end at 0 (#110) -### Improvements +Improvements +------------ - Pre-generate random positions at template generation to improve speed (#95) - Improve random seed management (#94) diff --git a/pyproject.toml b/pyproject.toml index a47be58..8c29004 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "MEArec" -version = "1.9.0" +version = "1.9.1" authors = [ { name="Alessio Buccino", email="alessiop.buccino@gmail.com" }, ] diff --git a/src/MEArec/generators/recgensteps.py b/src/MEArec/generators/recgensteps.py index d2dcfd6..a2fc693 100644 --- a/src/MEArec/generators/recgensteps.py +++ b/src/MEArec/generators/recgensteps.py @@ -312,7 +312,7 @@ def chunk_uncorrelated_noise_( if noise_color: # iir peak filter - b_iir, a_iir = scipy.signal.iirpeak(color_peak, Q=color_q, fs=fs) + b_iir, a_iir = scipy.signal.iirpeak(color_peak, Q=color_q, fs=float(fs)) additive_noise = scipy.signal.filtfilt(b_iir, a_iir, additive_noise, axis=0, padlen=1000) additive_noise += ( color_noise_floor @@ -354,7 +354,7 @@ def chunk_distance_correlated_noise_( additive_noise = noise_level * np.random.multivariate_normal(np.zeros(n_elec), cov_dist, size=length) if noise_color: # iir peak filter - b_iir, a_iir = scipy.signal.iirpeak(color_peak, Q=color_q, fs=fs) + b_iir, a_iir = scipy.signal.iirpeak(color_peak, Q=color_q, fs=float(fs)) additive_noise = scipy.signal.filtfilt(b_iir, a_iir, additive_noise, axis=0, padlen=1000) additive_noise = additive_noise + color_noise_floor * np.std(additive_noise) * np.random.multivariate_normal( np.zeros(n_elec), cov_dist, size=length