User guide# Getting started Introduction to pynapple Importing pynapple Instantiating pynapple objects nap.Tsd: 1-dimensional time serie nap.TsdFrame: 2-dimensional time series nap.TsdTensor: n-dimensionals time series nap.IntervalSet: intervals nap.Ts: timestamps nap.TsGroup: group of timestamps Interaction between pynapple objects Time support : attribute of time series Restricting time series to epochs Numpy & pynapple Slicing objects Slicing time series and intervals Slicing TsGroup Core functions Binning : counting events Thresholding Time-bin averaging of data Loading data Loading NWB Overview of advanced analysis Input-output Input-output & lazy-loading NWB Saving as NPZ Memory map Numpy memory map Zarr Navigating a dataset JSON sidecar file Core methods Interaction with numpy Initialization Attributes Slicing Arithmetic Array operations Concatenating Spliting Modifying Sorting Core methods Interval sets methods Interaction between epochs union intersect set_diff split Drop intervals drop_short_intervals drop_long_intervals merge_close_intervals Metadata Time series method restrict count bin_average interpolate value_from threshold Mapping between TsGroup and Tsd Parameterizing a raster High-level analysis Correlograms of discrete events Autocorrelograms Cross-correlograms Event-correlograms Tuning curves from epochs from timestamps activity 1-dimension tuning curves 2-dimension tuning curves from continuous activity 1-dimension tuning curves 2-dimension tuning curves Decoding 1-dimensional decoding 2-dimensional decoding Perievent Peri-Event Time Histogram (PETH) Raster plot Event trigger average Peri-Event continuous time series Randomization Shift timestamps Shuffle timestamp intervals Jitter timestamps Resample timestamps Power spectral density Generating a signal Computing power spectral density (PSD) Computing mean PSD Wavelet decomposion Generating a Dummy Signal Visualizing the Morlet Wavelets Parametrizing the wavelets Continuous wavelet transform Effect of gaussian_width Effect of window_length Effect of L1 vs L2 normalization Filtering time series Basics Inspecting frequency fesponses of a filter Performances
