Attention
This documentation is for the Mesmerize legacy desktop application. Please see the home page or GitHub repo for information on the latest packages.
Nodes¶
Data¶
- class mesmerize.pyqtgraphCore.flowchart.library.Data.DropNa(*args, **kwargs)[source]¶
Drop NaNs from the DataFrame
- class mesmerize.pyqtgraphCore.flowchart.library.Data.LoadFile(name)[source]¶
Load Transmission data object from pickled file
- class mesmerize.pyqtgraphCore.flowchart.library.Data.LoadProjDF(name)[source]¶
Load raw project DataFrames as Transmission
- class mesmerize.pyqtgraphCore.flowchart.library.Data.NormRaw(name, ui=None, terminals=None, **kwargs)[source]¶
Normalize between raw min and max values.
- class mesmerize.pyqtgraphCore.flowchart.library.Data.PadArrays(name, ui=None, terminals=None, **kwargs)[source]¶
Pad 1-D numpy arrays in a particular column
- class mesmerize.pyqtgraphCore.flowchart.library.Data.Save(name)[source]¶
Save Transmission data object
- class mesmerize.pyqtgraphCore.flowchart.library.Data.SelectColumns(name, ui=None, terminals=None, **kwargs)[source]¶
- class mesmerize.pyqtgraphCore.flowchart.library.Data.SelectRows(name, ui=None, terminals=None, **kwargs)[source]¶
- class mesmerize.pyqtgraphCore.flowchart.library.Data.SpliceArrays(name, ui=None, terminals=None, **kwargs)[source]¶
Splice 1-D numpy arrays in a particular column.
- class mesmerize.pyqtgraphCore.flowchart.library.Data.TextFilter(name, ui=None, terminals=None, **kwargs)[source]¶
Simple string filtering in a specified column
- class mesmerize.pyqtgraphCore.flowchart.library.Data.ViewHistory(*args, **kwargs)[source]¶
View History Trace of the input Transmission
Display¶
- class mesmerize.pyqtgraphCore.flowchart.library.Display.AnalysisGraph(name)[source]¶
Graph of the analysis log
- class mesmerize.pyqtgraphCore.flowchart.library.Display.BeeswarmPlots(name)[source]¶
Beeswarm and Violin plots
- class mesmerize.pyqtgraphCore.flowchart.library.Display.FrequencyDomainMagnitude(name, ui=None, terminals=None, **kwargs)[source]¶
Plot Frequency vs. Frequency Domain Magnitude
- class mesmerize.pyqtgraphCore.flowchart.library.Display.Heatmap(name)[source]¶
Stack 1-D arrays and plot visually like a heatmap
- class mesmerize.pyqtgraphCore.flowchart.library.Display.Plot(name)[source]¶
Plot curves and/or scatter points
- class mesmerize.pyqtgraphCore.flowchart.library.Display.Proportions(name)[source]¶
Plot proportions of one categorical column vs another
- class mesmerize.pyqtgraphCore.flowchart.library.Display.ScatterPlot(name)[source]¶
Scatter Plot, useful for visualizing transformed data and clusters
Signal¶
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.ButterWorth(name, ui=None, terminals=None, **kwargs)[source]¶
Butterworth Filter
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.Normalize(name, ui=None, terminals=None, **kwargs)[source]¶
Normalize a column containing 1-D arrays such that values in each array are normalized between 0 and 1
Output Column -> Input Column
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.PeakDetect(name, **kwargs)[source]¶
Detect peaks & bases by finding local maxima & minima. Use this after the Derivative Filter
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.PeakFeatures(*args, **kwargs)[source]¶
Extract peak features after peak detection
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.PowerSpectralDensity(name, ui=None, terminals=None, **kwargs)[source]¶
Return the Power Spectral Density of a curve.
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.RFFT(name, ui=None, terminals=None, **kwargs)[source]¶
Uses fftpack.rfft, ‘Discrete Fourier transform of a real sequence.
https://docs.scipy.org/doc/scipy/reference/generated/scipy.fftpack.rfft.html#scipy.fftpack.rfft
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.Resample(name, ui=None, terminals=None, **kwargs)[source]¶
Resample 1D data, uses scipy.signal.resample. “Rs” is the new sampling rate in “Tu” units of time. If “Tu” = 1, then Rs is the new sampling rate in Hertz.
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.SavitzkyGolay(name, ui=None, terminals=None, **kwargs)[source]¶
Savitzky-Golay filter.
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.ScalerMeanVariance(name, ui=None, terminals=None, **kwargs)[source]¶
Scaler for time series. Scales time series so that their mean (resp. standard deviation) in each dimension is mu (resp. std).
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.SigmaMAD(name, ui=None, terminals=None, **kwargs)[source]¶
- class mesmerize.pyqtgraphCore.flowchart.library.Signal.iRFFT(name, ui=None, terminals=None, **kwargs)[source]¶
Uses fftpack.irfft, ‘Return inverse discrete Fourier transform of real sequence.’
https://docs.scipy.org/doc/scipy/reference/generated/scipy.fftpack.irfft.html#scipy.fftpack.irfft
Input must have an _RFFT column from the RFFT node.
Math¶
- class mesmerize.pyqtgraphCore.flowchart.library.Math.AbsoluteValue(name, ui=None, terminals=None, **kwargs)[source]¶
Performs numpy.abs(<input>). Returns root-mean-square value if <input> is complex
- class mesmerize.pyqtgraphCore.flowchart.library.Math.ArgGroupStat(name, ui=None, terminals=None, **kwargs)[source]¶
Group by a certain column and return value of another column based on a data column statistic
- class mesmerize.pyqtgraphCore.flowchart.library.Math.ArrayStats(name, ui=None, terminals=None, **kwargs)[source]¶
Perform various statistical functions
- class mesmerize.pyqtgraphCore.flowchart.library.Math.Derivative(name, ui=None, terminals=None, **kwargs)[source]¶
Return the Derivative of a curve.
- class mesmerize.pyqtgraphCore.flowchart.library.Math.Integrate(name, ui=None, terminals=None, **kwargs)[source]¶
- class mesmerize.pyqtgraphCore.flowchart.library.Math.LinRegress(name, ui=None, terminals=None, **kwargs)[source]¶
Linear Regression
- class mesmerize.pyqtgraphCore.flowchart.library.Math.LogTransform(name, ui=None, terminals=None, **kwargs)[source]¶
Can perform various log transforms
- class mesmerize.pyqtgraphCore.flowchart.library.Math.TVDiff(name, ui=None, terminals=None, **kwargs)[source]¶
Total Variation Regularized Numerical Differentiation, Chartrand 2011 method
Biology¶
- class mesmerize.pyqtgraphCore.flowchart.library.Biology.ExtractStim(name, ui=None, terminals=None, **kwargs)[source]¶
Extract portions of curves according to stimulus maps
- class mesmerize.pyqtgraphCore.flowchart.library.Biology.ManualDFoF(name, ui=None, terminals=None, **kwargs)[source]¶
Set Fo for dF/Fo using a particular time period. Useful for looking at stimulus responses
Clustering¶
- class mesmerize.pyqtgraphCore.flowchart.library.Clustering.KMeans(name, ui=None, terminals=None, **kwargs)[source]¶
KMeans clustering https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html
Output column -> KMEANS_CLUSTER_<data_column>
Hierarchical¶
- class mesmerize.pyqtgraphCore.flowchart.library.Hierarchical.FCluster(name, **kwargs)[source]¶
Basically scipy.cluster.hierarchy.fcluster. Form flat clusters from the hierarchical clustering defined by the given linkage matrix.
- class mesmerize.pyqtgraphCore.flowchart.library.Hierarchical.Inconsistent(name)[source]¶
Calculate inconsistency statistics on a linkage matrix. Returns inconsistency matrix
- class mesmerize.pyqtgraphCore.flowchart.library.Hierarchical.Linkage(name, ui=None, terminals=None, **kwargs)[source]¶
Basically scipy.cluster.hierarchy.linkage Compute a linkage matrix for Hierarchical clustering
Transform¶
- class mesmerize.pyqtgraphCore.flowchart.library.Transform.LDA(name, **kwargs)[source]¶
Linear Discriminant Analysis, uses sklearn
- class mesmerize.pyqtgraphCore.flowchart.library.Transform.Manifold(name, ui=None, terminals=None, **kwargs)[source]¶
Manifold learning
CtrlNode¶
Base for all nodes
- class mesmerize.pyqtgraphCore.flowchart.library.common.CtrlNode(name, ui=None, terminals=None, **kwargs)[source]¶
Abstract class for nodes with auto-generated control UI
- ctrlWidget()[source]¶
Return this Node’s control widget.
By default, Nodes have no control widget. Subclasses may reimplement this method to provide a custom widget. This method is called by Flowcharts when they are constructing their Node list.
- process(**kwargs)[source]¶
Process data through this node. This method is called any time the flowchart wants the node to process data. It will be called with one keyword argument corresponding to each input terminal, and must return a dict mapping the name of each output terminal to its new value.
This method is also called with a ‘display’ keyword argument, which indicates whether the node should update its display (if it implements any) while processing this data. This is primarily used to disable expensive display operations during batch processing.
- saveState()[source]¶
Return a dictionary representing the current state of this node (excluding input / output values). This is used for saving/reloading flowcharts. The default implementation returns this Node’s position, bypass state, and information about each of its terminals.
Subclasses may want to extend this method, adding extra keys to the returned dict.