Source code for paramonte.vis._BasePlot

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####   ParaMonte: plain powerful parallel Monte Carlo library.
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import os
import numpy as np
import typing as tp
import weakref as wref
import _paramonte as pm
import _pmutils as pmutils

Struct = pmutils.Struct
newline = pmutils.newline

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#### BasePlot class
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[docs]class BasePlot: """ This is the class for generating instances of basic plots with minimally one (X)-axis. It serves as the superclass for a wide variety of other multi-axes ParaMonte plots. **Parameters** plotType A string indicating the name of the plot that is to be constructed. dataFrame (optional) A pandas dataFrame whose data will be plotted. methodName (optional) The name of the ParaMonte sample requesting the BasePlot. reportEnabled (optional) A boolean whose value indicates whether guidelines should be printed in the standard output. resetPlot (optional) A function that resets the properties of the plot as desired from outside. If provided, a pointer to this function will be saved for future internal usage. **Attributes** _dfref A weak reference to the input dataFrame whose data is used to generate plots. rows A numeric vector that determines the rows of dataFrame to be visualized. It can be either: 1. a ``range(start,stop,step)``, or, 2. a list of row indices in ``dataFrame.index``. Examples: 1. ``rows = range(17,7,-2)`` 2. ``rows = [i for i in range(7,17)]`` If not provided, the default includes all rows of the dataframe. set A structure with two attributes: enabled A boolean indicating whether a call to the ``set()`` function of the seaborn library should be made or not. kws A structure whose components are directly passed as keyword arguments to the ``set()`` function. Example usage: .. code-block:: python set.kws.style = "darkgrid" **NOTE** If a desired property is missing among the ``kws`` attributes, simply add the field and its value to the component. axes (available only in 1D and 2D plots) A structure with one attribute: kws A structure whose components are directly passed as keyword arguments to the ``gca()`` function of the matplotlib library. Example usage: .. code-block:: python axes.kws.facecolor = "w" **NOTE** If a desired property is missing among the ``kws`` attributes, simply add the field and its value to the component. axes3d (available only in 3D plots) A structure with one attribute: kws A structure whose components are directly passed as keyword arguments to the ``Axes3D()`` function of the matplotlib library. Example usage: .. code-block:: python axes3d.kws.facecolor = "w" **NOTE** If a desired property is missing among the ``kws`` attributes, simply add the field and its value to the component. figure A structure with two attributes: enabled A boolean indicating whether a call to the ``figure()`` function of the matplotlib library should be made or not. If a call is made, a new figure will be generated. Otherwise, the current active figure will be used. kws A structure whose components are directly passed as keyword arguments to the ``figure()`` function of the matplotlib library. Example usage: .. code-block:: python figure.kws.facecolor = "w" **NOTE** If a desired property is missing among the ``kws`` attributes, simply add the field and its value to the component. legend (may not exist for some types of plots) A structure with two attributes: enabled A boolean indicating whether a call to the ``legend()`` function of the matplotlib library should be made or not. If a call is made, a new figure will be generated. Otherwise, the current active figure will be used. kws A structure whose components are directly passed as keyword arguments to the ``legend()`` function of the matplotlib library. Example usage: .. code-block:: python legend.kws.labels = ["Variable1", "Variable2"] **NOTE** If a desired property is missing among the ``kws`` attributes, simply add the field and its value to the component. A legend will be added to a plot only if no color-mappings are requested in the plot. currentFig A structure whose attributes are the outputs of various plotting tools used to make the current figure. These include the handle to the current figure, the handle to the current axes in the plot, the handle to the colorbar (if any exists), and other Python plotting tools used to make to generate the figure. **Returns** An object of ``BasePlot`` class. --------------------------------------------------------------------------- """ ################################################################################################################################ #### __init__ ################################################################################################################################ def __init__( self , plotType , dataFrame = None , methodName = "ParaMonte" , reportEnabled = True , resetPlot = None ): self._dfref = None if dataFrame is None else wref.ref(dataFrame) self._type = Struct() self._type.name = plotType plotTypeLower = plotType.lower() self._type.is3d = "3" in plotTypeLower self._type.isLine = "line" in plotTypeLower self._type.isScatter = "scatter" in plotTypeLower self._type.isHeatmap = "heatmap" in plotTypeLower self._type.isKdeplot1 = "kdeplot1" in plotTypeLower self._type.isKdeplot2 = "kdeplot2" in plotTypeLower self._type.isHistplot = "histplot" in plotTypeLower self._type.isJointplot = "jointplot" in plotTypeLower self._type.isEllipsoid = "covmat" in plotTypeLower self._type.isEllipsoid = "cormat" in plotTypeLower self._type.isGridPlot = "grid" in plotTypeLower self._type.isContour3 = "contour3" in plotTypeLower self._type.isContourf = "contourf" in plotTypeLower self._type.isContour = "contour" in plotTypeLower and not (self._type.isContour3 or self._type.isContourf) self._type.is1d = self._type.isKdeplot1 or self._type.isHistplot self._type.is2d = not (self._type.isGridPlot or self._type.is1d or self._type.is3d) self._type.isDiffusionPlot = self._type.isContour or self._type.isContourf or self._type.isContour3 self._methodName = methodName self._reportEnabled = reportEnabled self._progress = pm.utils.Progress ( msg = "creating a " + self._type.name + " plot object from scratch... " , methodName = methodName , reportEnabled = reportEnabled , end = "" ) self._reset() if resetPlot is None: self._resetPlot = self._reset else: self._resetPlot = resetPlot ################################################################################################################################ #### reset ################################################################################################################################
[docs] def reset ( self , resetType = "soft" , **kwargs ): """ Reset the properties of the plot to the original default settings. Use this method when you change many attributes of the plot and you want to clean up and go back to the default settings. **Parameters** resetType (optional) An optional string with possible value of ``"hard"``. If provided, the plot object will be regenerated from scratch. This includes reading the original data frame again and resetting everything. If not provided, then only the plot settings will be reset without reseting the dataFrame. **Returns** None **Example** .. code-block:: python :linenos: reset() # reset the plot to the default settings reset("soft") # reset the plot to the default settings reset("hard") # regenerate the plot from scratch """ try: self._resetPlot(resetType = resetType, plotNames = self._type.name) # call external reset function except: self._resetPlot(**kwargs) # call _reset(self)
################################################################################################################################ #### _reset ################################################################################################################################
[docs] def _reset(self): self.rows = None self._fnameOld = None # used in savefig() to generate unique random file names. self.set = Struct() self.set.enabled = True self.set.kws = Struct() if self._type.isKdeplot2 or self._type.isJointplot: self.set.kws.style = "ticks" elif self._type.is3d: self.set.kws.style = "white" else: self.set.kws.style = "darkgrid" self.figure = Struct() self.figure.enabled = True self.figure.kws = Struct() self.currentFig = Struct() if self._type.is3d: self.axes3d = Struct() self.axes3d.kws = Struct() self.axes3d.kws.alpha = 1 self.axes3d.kws.visible = True #self.axes3d.enabled = self.figure.enabled else: self.axes = Struct() self.axes.kws = Struct() self.axes.kws.alpha = 1 self.axes.kws.visible = True #self.axes.enabled = self.figure.enabled if not (self._type.isGridPlot or self._type.isHeatmap or self._type.isDiffusionPlot): self.legend = Struct() self.legend.enabled = False self.legend.kws = Struct()
################################################################################################################################ #### savefig ################################################################################################################################
[docs] def savefig ( self , reself = False , **savefig_kws ): """ Export the current figure to external file. **Parameters** reself A logical variable. If ``True``, the path to the output generated file will be returned. The default value is ``False``. **savefig_kws (optional) The set of input arguments to the ``savefig()`` function of the matplotlib library, including the ``fname``. If the file name is not provided, a unique random filename will be generated and used to save the figure to an output file. Example: .. code-block:: python savefig(fname = "gridplot.png") **Returns** None **Example** .. code-block:: python savefig() # use a unique random filename to output the plot. savefig(fname = "thisPlot.png") savefig(pad_inches = 0.0, bbox_inches = "tight") """ if "fname" not in savefig_kws.keys() or (isinstance(self._fnameOld,str) and isinstance(savefig_kws["fname"],str) and savefig_kws["fname"]==self._fnameOld): savefig_kws["fname"] = os.path.join( os.getcwd(), pm.utils.getRandomFilePrefix(prefix=self._type.name+"_") + ".png" ) self._fnameOld = savefig_kws["fname"] import matplotlib.pyplot as plt # xxx how is this figure activated? self._progress.note( msg = "saving the plot to file: \"" + savefig_kws["fname"] + "\"", end = "\n", pre = True ) plt.savefig(**savefig_kws) self._progress.note( end = "\n", pre = True )
################################################################################################################################ #### getLinSpace ################################################################################################################################
[docs] def getLinSpace ( self , skip = None , lowerLim : tp.Optional[ np.int32 ] = 1 , upperLim : tp.Optional[ np.int32 ] = None ): """ Generate linearly-spaced **unique** integer numbers between the input lowerLim and upperLim. These numbers can be used as the row indices in the plots. **Parameters** skip (optional) The linear spacing between the generated points. If ``skip`` is specified as input, any input value for ``npoint`` will be ignored. The default value is ``None``. lowerLim (optional) The natural (non-logarithmic) lower limit of the generated linearly-spaced integer numbers. If not provided, the default value is ``1``. upperLim (optional) The natural (non-logarithmic) upper limit of the generated linearly-spaced integer numbers. If not provided, the default value is the maximum of the number of the rows of the input dataframe to the ``BasePlot`` constructor. **Returns** A set of unique linearly-spaced integer numbers. **Example** .. code-block:: python rows = getLinSpace(3, 1, 10000) """ if upperLim is None and self._dfref is not None: upperLim = len(self._dfref().index) elif upperLim is None and self.rows is not None: upperLim = len(self.rows[-1]) else: pm.abort( msg = "Either the input argument ``upperLim`` or the dataFrame of the plot object" + newline + "must be given in order to generate a linear range of values. " + newline + "Here is the documentation of getLinSpace():" + newline + newline + self.getLinSpace.__doc__ + newline , marginTop = 1 , marginBot = 1 , methodName = self._methodName ) if skip is None: skip = (upperLim - lowerLim) // 256 if skip<1: skip = 1 return range(lowerLim,upperLim,skip)
################################################################################################################################ #### getLogLinSpace ################################################################################################################################
[docs] def getLogLinSpace ( self , base : tp.Optional[ np.float64 ] = 1.2 , logskip : tp.Optional[ np.int32 ] = 0.2 , lowerLim : tp.Optional[ np.int32 ] = 1 , upperLim : tp.Optional[ np.int32 ] = None ): """ Generate logarithmically-uniformly-spaced **unique** integer numbers between the input lowerLim and upperLim. These numbers are to be used as the row indices in the plots. **Parameters** base (optional) The base of the logarithm used for generating the logarithmically-uniform range of integers. The default value is ``1.2``. logskip (optional) The minimum logarithmic space jump between the generated log-linearly-spaced integer numbers. The default value is ``0.2``. lowerLim (optional) The natural (non-logarithmic) lower limit of the generated log-linearly-spaced integer numbers. If not provided, the default value is ``1``. upperLim (optional) The natural (non-logarithmic) upper limit of the generated log-linearly-spaced integer numbers. If not provided, the default value is the maximum of the number of the rows of the input dataframe to the BasePlot constructor. **Returns** A set of unique log-linearly-spaced integer numbers. **Example** .. code-block:: python rows = getLogLinSpace(1.01, 1, 1, 10000) """ if upperLim is None and self._dfref is not None: upperLim = len(self._dfref().index) elif upperLim is None and self.rows is not None: upperLim = len(self.rows[-1]) else: pm.abort( msg = "Either the input argument ``upperLim`` or the dataFrame of the plot object" + newline + "must be given in order to generate a log-linear range of values. " + newline + "Here is the documentation of getLogLinSpace():" + newline + newline + self.getLogLinSpace.__doc__ + newline , marginTop = 1 , marginBot = 1 , methodName = self._methodName ) return pm.utils.getLogIntSpace(base,logskip,lowerLim,upperLim)
################################################################################################################################ #### _constructBasePlot ################################################################################################################################
[docs] def _constructBasePlot(self): """ Generate Figure and Axes instances if needed and return nothing. **Parameters** None **Returns** None """ end = "\n" if "grid"==self._type.name else "" self._progress.note( msg = "making the " + self._type.name + " plot... ", end = end, pre = True ) import seaborn as sns from matplotlib import pyplot as plt plt.ion() # turn on the interactive mode. Used to detach the figure from the command line in ipython if self._type.is3d: from mpl_toolkits.mplot3d import Axes3D if self.set.enabled: sns.set( **vars(self.set.kws) ) if not (self._type.isJointplot or self._type.isGridPlot): # jointplot and gridplot create their own figure and axes if self.figure.enabled: self.currentFig.figure = plt.figure( **vars(self.figure.kws) ) if self._type.is3d: self.currentFig.axes = Axes3D(self.currentFig.figure, **vars(self.axes3d.kws) ) else: self.currentFig.axes = self.currentFig.figure.gca( **vars(self.axes.kws) ) else: self.currentFig.figure = plt.gcf() # self.currentFig.axes.get_figure() self.currentFig.axes = self.currentFig.figure.gca()
################################################################################################################################ #### _finalizeBasePlot ################################################################################################################################
[docs] def _finalizeBasePlot(self): """ Set the base Figure properties, such as legends, ... **Parameters** None **Returns** None """ ############################################################################################################################ #### _finalizeBasePlot ############################################################################################################################ if not (self._type.isGridPlot or self._type.isHeatmap or self._type.isDiffusionPlot) and self.legend.enabled: labelsNeeded = False if not hasattr(self.legend.kws, "labels"): labelsNeeded = True elif self.legend.kws.labels is None: labelsNeeded = True if labelsNeeded and hasattr(self.legend,"_labels") and self.legend._labels is not None: self.legend.kws.labels = self.legend._labels if self._type.isJointplot: self.currentFig.legend = self.currentFig.jointplot.ax_joint.legend( **vars(self.legend.kws) ) else: self.currentFig.legend = self.currentFig.axes.legend( **vars(self.legend.kws) ) self.currentFig.legend.set_zorder(20) # bring legend to the top if not self._type.is3d: import matplotlib.pyplot as plt plt.tight_layout() self._progress.note()
################################################################################################################################ #### _checkDataType ################################################################################################################################
[docs] def _checkDataType(self): """ Verify the integrity of the dataFrame and return nothing. **Parameters** None **Returns** None """ import pandas as pd fatalmsg = None if self._dfref is None: fatalmsg = "It appears that no data has been passed for plotting." + newline elif not isinstance(self._dfref,wref.ref): fatalmsg = "It appears that you have messed with the " + newline + " internal representation of data in the object." + newline elif not isinstance(self._dfref(), pd.DataFrame): fatalmsg = "" if fatalmsg is not None: raise Exception ( fatalmsg + "The input data must be a pandas' dataframe." + newline + "Please pass a dataFrame to the constructor or at" + newline + "the time of calling the object (which is callable with" + newline + "the same input arguments as the object's constructor." )
################################################################################################################################ #### _getDocString ################################################################################################################################
[docs] def _getDocString(self): docString = newline \ + "Here is the help information on the BasePlot class:" + newline \ + newline \ + self.__doc__ return docString
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