Source code for jscatter.mpl

# -*- coding: utf-8 -*-
# written by Ralf Biehl at the Forschungszentrum Jülich ,
# Jülich Center for Neutron Science 1 and Institute of Complex Systems 1
#    jscatter is a program to read, analyse and plot data
#    Copyright (C) 2015  Ralf Biehl
#
#    This program is free software: you can redistribute it and/or modify
#    it under the terms of the GNU General Public License as published by
#    the Free Software Foundation, either version 3 of the License, or
#    (at your option) any later version.
#
#    This program is distributed in the hope that it will be useful,
#    but WITHOUT ANY WARRANTY; without even the implied warranty of
#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#    GNU General Public License for more details.
#
#    You should have received a copy of the GNU General Public License
#    along with this program.  If not, see <http://www.gnu.org/licenses/>.
#
"""
This is a rudimentary interface to matplotlib to use dataArrays easier.
The standard way to use matplotlib is full available without using this module..

The intention is to allow fast/easy plotting (one command to plot) with some convenience function in relation to dataArrays
and in a non blocking mode of matplotlib.
E.g. to include automatically the value of an attribute in the legend::

 fig[0].Plot(mydataArray,legend='sqr=$qq ',sy=[2,3,-1],li=0)

With somehow shorter form to determine the marker (sy=symbol) and line (li)
and allow plotting in one line. Matplotlib is quite slow and looks for me ugly (really not paper ready).
For 2D plotting use xmgrace.
For 3D plotting this will give some simple plot options (planned).

* The new methods introduced all start with a big Letter to allow still the access of the original methods.
* By indexing as the axes subplots can be accessed as figure[i] which is figure.axes[i].
* Same for axes with lines figure[0][i] is figure.axes[0].lines[i].

Example 1::

    import jscatter as js
    import numpy as np
    i5=js.dL('exampleData/iqt_1hho.dat')
    p=js.mplot()
    p[0].Plot(i5,sy=[-1,4,-1],li=1,legend='Q= $q')
    p[0].Yaxis(scale='l')
    p[0].Title('intermediate scattering function')
    p[0].Legend()
    p[0].Yaxis(label='I(Q,t)/I(Q,0)')
    p[0].Xaxis(label='Q / 1/nm')

Example 2::

    import jscatter as js
    import numpy as np
    from matplotlib import pyplot
    # use this
    #fig=pyplot.figure(FigureClass=js.mpl.Figure)
    # or
    fig=js.mplot()
    fig.Multi(2,1)
    fig[0].SetView(0.1,0.25,0.8,0.7)
    fig[1].SetView(0.1,0.09,0.8,0.15)
    q=js.loglist(0.01,5,100)
    aa=js.dA(np.c_[q,np.sin(q),0.1*np.cos(q)].T)
    bb=js.dA(np.c_[q,q**2].T)
    bb.qq=123
    fig[0].Plot(aa,legend='sin',sy=2,li=3)
    for pp in range(10):  fig[0].Plot(aa.X,aa.Y*pp,legend='sin',sy=[-1,8,-1,''],li=0,markeredgewidth =1)
    fig[1].Plot(bb,legend='sqr=$qq ',sy=2,li=0)
    fig[0].Title('test')
    fig[0].Legend()
    fig[1].Legend()
    fig[0].Yaxis(label='y-axis')
    fig[1].Yaxis(label='Residuals')
    fig[1].Xaxis(label='x-axis')

"""
import numpy as np
from functools import reduce

import matplotlib
from matplotlib.projections import register_projection
from matplotlib import pyplot 
from matplotlib.lines import Line2D
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.cm as cm

lineStyles=('','-','--','-.',':')
linecolors=('w','k','r','b','g','c','m','y',)
fillstyles = ( 'none','full', 'left', 'right', 'bottom', 'top',)
symboldefault=[1,5,1,'']  # type,size,facecolor,edgecolor
linedefault=[1,0.5,1]    # type,size,color

#: gracefactor to get same scaling as in grace set to 10
gf=1

def _translate(axlen,kwargs,data=None):
    """
    This function transforms a short description as [1,2,3] for symbol and line to matplotlib compatible arguments.
    This allows a shorter description of the symbol and line formats.
    Additionally the replacement of $parname in dataArray attributes is done.
    
    
    """
    #split some special keywords in kwargs
    if 'legend' in kwargs:
        legend=kwargs['legend']
        del kwargs['legend']
    elif 'le' in kwargs:
        legend=kwargs['le']
        del kwargs['le']
    else:
        legend=''
    if 'line' in kwargs:
        line=kwargs['line']
        del kwargs['line']
    elif 'li' in kwargs:
        line=kwargs['li']
        del kwargs['li']
    else:
        line=''
    if 'symbol' in kwargs:
        symbol=kwargs['symbol']
        del kwargs['symbol']
    elif 'sy' in kwargs:
        symbol=kwargs['sy']
        del kwargs['sy']
    else:
        symbol=[-1,5,-1]
    if 'errorbar' in kwargs:
        errorbar=kwargs['errorbar']
        del kwargs['errorbar']
    elif 'er' in kwargs:
        errorbar=kwargs['er']
        del kwargs['er']
    else:
        errorbar=None
    #replace $attr by the value in data
    if '$' in legend and hasattr(data,'_isdataArray'):
        for par in data.attr:
            if '$'+par in legend or '$('+par+')' in legend:
                # noinspection PyBroadException
                try:
                    vall=np.array(getattr(data,par)).flatten()[0]
                    if isinstance(vall,(int,float)):
                        val='%.4g'%vall
                    else:
                        val=str(vall)
                    if '$('+par+')' in legend:
                        legend=legend.replace('$('+par+')',val)
                    else:
                        legend=legend.replace('$'+par,val)
                except:
                        pass
    #--------
    if isinstance(symbol,(int,str)):
        symbol=[symbol,5,1,''] # type,size,facecolor,edgecolor
    symbol=symbol+symboldefault[len(symbol):]
    # symbol marker
    if isinstance(symbol[0],(int,float)):
        if symbol[0]<0:symbol[0]=axlen
        if symbol[0]>0:
            symbol[0]=Line2D.filled_markers[divmod(symbol[0]-1,len(Line2D.filled_markers))[1]]
        else:
            symbol[0]=''
    # symbol color
    if isinstance(symbol[2],(int,float)):
        if symbol[2]<0:symbol[2]=axlen
        if symbol[2]>0:
            symbol[2]=linecolors[divmod(symbol[2]-1,len(linecolors)-1)[1]+1]
        else:
            symbol[2]=''
    if isinstance(symbol[3],(int,float)):
        if symbol[3]<0:symbol[3]=axlen
        if symbol[3]>0:
            symbol[3]=linecolors[divmod(symbol[3]-1,len(linecolors)-1)[1]+1]
        else:
            symbol[3]=linecolors[0]
    else:
        # synchronize with facecolor
        symbol[3]=symbol[2]
    if isinstance(line,(int,str)):
        line=[1,0.5,line] # type,size,color
    line=line+linedefault[len(line):]
    if isinstance(line[0],(int,float)): # type
        if line[0]<0:line[0]=axlen
        if line[0]>0:
            line[0]=lineStyles[divmod(line[0]-1,len(lineStyles)-1)[1]+1]
        else:
            line[0]=''
    if isinstance(line[2],(int,float)): # color
        if line[2]<0:line[2]=axlen
        if line[2]>0:
            line[2]=linecolors[divmod(line[2]-1,len(linecolors)-1)[1]+1]
        else:
            line[0]=''
            line[2]=''
        if symbol[0]=='' and line[2]!='':
            symbol[2]=line[2]
    #fmt=fmt,markersize=ssize, markerfacecolor=mfc,linewidth=lsize,label=legend
    for opt,val in zip(['fmt','markersize','markerfacecolor','markeredgecolor','linewidth','label','elinewidth'],
                       [symbol[2]+symbol[0]+line[0],symbol[1]*gf,symbol[2],symbol[3],line[1],legend,errorbar]):
        if opt not in kwargs:
            kwargs[opt]=val
    return kwargs


[docs]class paperAxes(matplotlib.axes.Axes): """ An Axes that default is close to paper quality output """ name='paper' #def __init__(self,*args,**kwargs): # super(matplotlib.axes.Axes, self).__init__(*args,**kwargs)
[docs] def SetView(self,xmin=None,ymin=None,xmax=None,ymax=None): """ this sets the viewport coords. Parameters ---------- xmin,xmax,ymin,ymax : float view range """ self.set_position([xmin, ymin, xmax-xmin, ymax-ymin]) # [left, bottom, width, height] self.figure.show()
def __getitem__(self, key): return self.lines[key] # noinspection PyIncorrectDocstring
[docs] def Plot(self,*datasets,**kwargs): """ plot dataArrays or array in matplotlib axes. Parameters ---------- datasets : dataArray, dataList,numpy array, lists of them several of (comma separated) nonkeyword arguments or as list if dimension of datasets is one a new Data object is created and plotted see Notes below for error plots symbol,sy : int, list of float - [symbol,size,color,fillcolor,fillpattern] as [1,1,1,-1]; - single integer to chose symbol eg symbol=3; symbol=0 switches off - negative increments from last - symbol => see Line2D.filled_markers - size => size in pixel - color => int in sequence = wbgrcmyk - fillcolor=None see color - fillpattern=None 0 empty, 1 full, ....test it line,li : int, list of float or Line object - [linestyle,linewidth,color] as [1,1,'']; - negative increments - single integer to chose linestyle line=1; line=0 switches of - linestyle int '-','--','-.',':' - linewidth float increasing thickness - color see symbol color legend,le : string - determines legend for all datasets - string replacement: attr name prepended by '$' (eg. '$par') is replaced by value str(par1.flatten()[0]) if possible. $(par) for not unique names errorbar,er : float - errorbar thickness, zero is no errorbar """ # concat dataList's if np.alltrue([hasattr(dset,'_isdataList') or (hasattr(dset,'_isdataArray') and np.ndim(dset)>1) for dset in datasets]): datasets=reduce(lambda a,b:a+b,datasets) if np.alltrue([np.ndim(dset)==1 for dset in datasets]): shape0=[np.shape(dset)[0] for dset in datasets] if shape0.count(shape0[0])==len(shape0): datasets=[np.asanyarray(datasets)] # self.lines is updated only after show so we need to count explicitly nlines=len(self.lines) showerr=True if 'comment' in kwargs: del kwargs['comment'] if 'errorbar' in kwargs: if kwargs['errorbar']==0: showerr=False elif 'er' in kwargs: if kwargs['er']==0: showerr=False for data in datasets: if hasattr(data,'_isdataArray'): if hasattr(data,'_iey') and showerr: yerr=data.eY else: yerr=None nkwargs=_translate(nlines+1,kwargs.copy(),data) self.errorbar(x=data.X,y=data.Y,yerr=yerr,**nkwargs) nlines+=1 elif hasattr(data,'_isdataList'): for da in data: if hasattr(data,'_iey') and showerr: yerr=data.eY else: yerr=None nkwargs=_translate(nlines+1,kwargs.copy(),da) self.errorbar(x=da.X,y=da.Y,yerr=yerr,**nkwargs) nlines+=1 elif isinstance(data,np.ndarray): if showerr: # noinspection PyBroadException try : yerr=data[2] except: yerr=None nkwargs=_translate(nlines+1,kwargs.copy()) self.errorbar(x=data[0],y=data[1],yerr=yerr,**nkwargs) nlines+=1 self.figure.show()
[docs] def Yaxis(self,label=None,scale=None,min=None,max=None,**kwargs): """ set Yaxis Parameters ---------- label : string label scale : 'log', 'normal' min,max : float min and max of scale kwargs : kwargs of axes.set_xscale any given kwarg overrides the previous """ if label is not None: self.set_ylabel(label) self.set_ylim(min,max) if scale is not None: if scale[0]=='l': val='log' kwargs['nonposx']='clip' elif scale[0]=='n': val='linear' if 'subsy' not in kwargs: kwargs['subsy']=[2, 3, 4, 5, 6, 7, 8, 9] self.set_yscale(val,**kwargs) self.figure.show()
[docs] def Xaxis(self,label=None,scale=None,min=None,max=None,**kwargs): """ set Xaxis Parameters ---------- label : string label scale : 'log', 'normal' min,max : float min and max of scale kwargs : kwargs of axes.set_xscale any given kwarg overrides the previous """ if label is not None: self.set_xlabel(label) self.set_xlim(min,max) if scale is not None: if scale[0]=='l': val='log' kwargs['nonposx']='clip' elif scale[0]=='n': val='linear' if 'subsx' not in kwargs: kwargs['subsx']=[2, 3, 4, 5, 6, 7, 8, 9] self.set_xscale(val,**kwargs) self.figure.show()
[docs] def Resetlast(self,): pass
[docs] def Legend(self,**kwargs): """ Set axis legend; see Figure.legend """ if 'charsize' in kwargs: kwargs['fontsize']=kwargs['charsize']*10. del kwargs['charsize'] if 'fontsize' not in kwargs:kwargs['fontsize']=12 if 'labelspacing' not in kwargs:kwargs['labelspacing']=0.2 if 'loc' not in kwargs:kwargs['loc']=2 # upper left x=None y=None if'x' in kwargs : x=kwargs['x'] del kwargs['x'] if 'y' in kwargs : y=kwargs['y'] del kwargs['y'] if x is not None and y is not None: kwargs['bbox_to_anchor']=(x,y) # upper left self.legend(**kwargs) self.figure.show()
[docs] def Title(self,title): """set Axes title""" self.set_title(title) self.figure.show()
[docs] def Subtitle(self,subtitle): """ Append subtitle to title """ subtitle=self.get_title()+'\n'+subtitle self.set_title(subtitle)
[docs] def Clear(self): """ Clear content of this axes """ self.clear() self.figure.show()
# register that it can be used as other Axes register_projection(paperAxes)
[docs]class Figure(matplotlib.figure.Figure): def __init__(self, *args, **kwargs): for opt,val in zip(['facecolor','frameon','facecolor','edgecolor'],['w',False,'w','w']): if opt not in kwargs: kwargs[opt]=val matplotlib.figure.Figure.__init__(self, *args, **kwargs) self.add_subplot(1,1,1,projection='paper') lastsymbol=[0,0.5,0,0,0] lastline=[0,0,0,0] lasterror=[0,0,0,0]
[docs] def Multi(self,n,m): """ Creates multiple subplots on grid n,m. with projection "paperAxes". Subplots can be accesses as fig[i] """ for ax in self.axes:self.delaxes(ax) nn=0 for ni in range(n): for mi in range(m): nn+=1 self.add_subplot(n,m,nn,projection='paper') self.show()
def __getitem__(self, key): return self.axes[key]
[docs] def Clear(self): """ Clear content of all axes to clear axes use fig.clear() """ for ax in self: ax.clear() self.show()
[docs] def Save(self,filename,format,size,dpi): """ Save with filename """ self.savefig(filename)
[docs] def is_open(self): """ Is the figure window still open. """ return pyplot.fignum_exists(self.number)
[docs] def Exit(self): pass
[docs] def Close(self): """ Close the figure """ pyplot.close(self)
[docs]def mplot(): """ Open matplotlib figure in interactive mode. Returns ------- pyplot figure Notes ----- - By indexing as the axes subplots can be accessed as figure[i] which is figure.axes[i]. - Same for axes with lines figure[0][i] is figure.axes[0].lines[i]. """ pyplot.ion() fig=pyplot.figure(FigureClass=Figure) return fig
[docs]def regrid(x,y,z,xdim=None): """ Make a meshgrid from XYZ data columns. Parameters ---------- x,y,z : arary like Array like data should be quadratic or rectangular. xdim : None, shape of first x dimension If None the number of unique values in x is used as first dimension Returns ------- 2dim arrays for x,y,z """ if xdim is None: xdim = len(np.unique(x)) try:xx = x.reshape(xdim,-1) except:xx=None try:yy = y.reshape(xdim, -1) except:yy=None try:zz = z.reshape(xdim, -1) except:zz=None return xx,yy,zz
[docs]def surface(x,y,z,xdim=None,levels=8, colorMap='jet',lineMap=None,alpha=0.7): """ Surface plot of x,y,z, data Parameters ---------- x,y,z : array Data as array xdim : integer First dimension of x levels : integer, array Levels for contour lines as number of levels or array of specific values. colorMap : string Color map name, see showColors. lineMap : string Color name for contour lines b: blue g: green r: red c: cyan m: magenta y: yellow k: black w: white alpha : float [0,1], default 0.7 Transparency of surface Returns ------- figure """ if np.ndim(x)<2: X,Y,Z=regrid(x,y,z,xdim) cmap = pyplot.get_cmap(colorMap) try: lmap = pyplot.get_cmap(lineMap) except ValueError: lmap=lineMap fig = pyplot.figure() ax = fig.add_subplot(111, projection='3d') surf=ax.plot_surface(X, Y, Z,cmap=cmap,linewidth=1, antialiased=True,alpha=alpha) try: contour=ax.contour3D(X,Y,Z,levels,linewidths=1,cmap=lmap) except: contour = ax.contour3D(X, Y, Z, levels, linewidths=1, colors=lmap) ax.set_xlim([min(x),max(x)]) ax.set_ylim([min(y),max(y)]) ax.set_zlim([min(z),max(z)]) ax.set_xlabel('X axis') ax.set_ylabel('Y axis') ax.set_zlabel('Z axis') fig.colorbar(surf,shrink=0.8) # note that colorbar is a method of the figure, not the axes pyplot.tight_layout() pyplot.show(block=False) return fig
[docs]def scatter3d(x,y,z, pointsize=3, color='k'): """ Scatter plot of X,Y,Z data Parameters ---------- x,y,z : arrays Data pointsize : float Size of points color : string Colors for points Returns ------- figure """ #cmap = pyplot.get_cmap(colorMap) fig = pyplot.figure() ax = fig.add_subplot(111, projection='3d') sc=ax.scatter(x, y, z, s=pointsize, color=color) mi = np.min([x,y,z]) ma = np.max([x, y, z]) ax.set_xlim(mi,ma) ax.set_ylim(mi,ma) ax.set_zlim(mi,ma) ax.set_xlabel('X axis') ax.set_ylabel('Y axis') ax.set_zlabel('Z axis') ax.set_aspect("equal") pyplot.tight_layout() #fig.colorbar(scatter ,shrink=0.8) # note that colorbar is a method of the figure, not the axes pyplot.show(block=False) return fig
[docs]def contourImage(x,y,z,xdim=None,levels=8,fontsize=8,colorMap='jet',lineMap=None): """ Image with contour lines of x,y,z arrays with ndim=1 or 2. Parameters ---------- x,y,z : arrays x,y,z coordinates for z display xdim : int If x,y,z are one dimensional xdim is dimension of first axis of x,y,z If None the number of unique values in x is used levels : in, sequence of values Number of contour lines between min and max or sequence of specific values. colorMap : string Get a colormap instance from name. Standard mpl colormap name (see Notes). lineMap : string Label color Colormap name as in colorMap, otherwise as cs in in Axes.clabel * if None, the color of each label matches the color of the corresponding contour * if one string color, e.g., colors = ‘r’ or colors = ‘red’, all labels will be plotted in this color * if a tuple of matplotlib color args (string, float, rgb, etc), different labels will be plotted in different colors in the order specified fontsize : int Size of line labels in pixel Returns ------- figure Notes ----- Colormaps Names Accent, Accent_r, Blues, Blues_r, BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens, Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy, RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, Spectral_r, Vega10, Vega10_r, Vega20, Vega20_r, Vega20b, Vega20b_r, Vega20c, Vega20c_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn, autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cool, cool_r, coolwarm, coolwarm_r, copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat, gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r, gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma, magma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, seismic, seismic_r, spectral, spectral_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, terrain, terrain_r, viridis, viridis_r, winter, winter_r """ if np.ndim(x)<2: x,y,z=regrid(x,y,z,xdim) cmap = pyplot.get_cmap(colorMap) try: lmap = pyplot.get_cmap(lineMap) except ValueError: lmap=lineMap fig = pyplot.figure() ax = fig.add_subplot(1, 1, 1) im = ax.imshow(z,cmap=cmap) # drawing the function # adding the Contour lines with labels try: im.cset = pyplot.contour(z,levels,linewidths=1,cmap=lmap) im.labels=pyplot.clabel(im.cset,inline=True,fmt='%1.1f',fontsize=10) except: im.cset = pyplot.contour(z,levels, linewidths=1) im.labels = pyplot.clabel(im.cset, inline=True, fmt='%1.1f', fontsize=fontsize,colors=lmap) im.set_xlabel('X axis') im.set_ylabel('Y axis') fig.colorbar(im) # note that colorbar is a method of the figure, not the axes pyplot.show(block=False) return fig
[docs]def showColors(): """ Get a list of the colormaps in matplotlib. Ignore the ones that end with '_r' because these are simply reversed versions of ones that don't end with '_r' Colormaps Names Accent, Accent_r, Blues, Blues_r, BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens, Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy, RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, Spectral_r, Vega10, Vega10_r, Vega20, Vega20_r, Vega20b, Vega20b_r, Vega20c, Vega20c_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn, autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cool, cool_r, coolwarm, coolwarm_r, copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat, gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r, gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma, magma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, seismic, seismic_r, spectral, spectral_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, terrain, terrain_r, viridis, viridis_r, winter, winter_r From https://matplotlib.org/1.2.1/examples/pylab_examples/show_colormaps.html """ a = np.linspace(0, 1, 256).reshape(1,-1) a = np.vstack((a,a)) # Get a list of the colormaps in matplotlib. Ignore the ones that end with # '_r' because these are simply reversed versions of ones that don't end # with '_r' maps = sorted(m for m in pyplot.cm.datad if not m.endswith("_r")) nmaps = len(maps) + 1 # fig = pyplot.figure(figsize=(5,10)) fig.subplots_adjust(top=0.99, bottom=0.01, left=0.2, right=0.99) for i,m in enumerate(maps): ax = pyplot.subplot(nmaps, 1, i+1) pyplot.axis("off") pyplot.imshow(a, aspect='auto', cmap=pyplot.get_cmap(m), origin='lower') pos = list(ax.get_position().bounds) fig.text(pos[0] - 0.01, pos[1], m, fontsize=10, horizontalalignment='right') # pyplot.show(block=False)
[docs]def test(keepopen=True): """ A small test if this is working """ import jscatter as js import numpy as np from matplotlib import pyplot # use this #fig=pyplot.figure(FigureClass=js.mpl.Figure) # or fig=js.mplot() fig.Multi(2,1) fig[0].SetView(0.1,0.25,0.8,0.9) fig[1].SetView(0.1,0.09,0.8,0.20) q=js.loglist(0.01,5,100) aa=js.dA(np.c_[q,np.sin(q),0.1*np.cos(q)].T) bb=js.dA(np.c_[q,q**2].T) bb.qq=123 fig[0].Plot(aa,legend='sin',sy=2,li=3) for pp in range(10): fig[0].Plot(aa.X,aa.Y*pp,legend='sin',sy=[-1,4,-1,''],li=0,markeredgewidth =1) fig[1].Plot(bb,legend='sqr=$qq ',sy=2,li=0) fig[0].Title('test') fig[0].Legend(x=1,y=1) fig[1].Legend(x=1,y=1) fig[0].Yaxis(label='y-axis') fig[1].Yaxis(label='Residuals') fig[1].Xaxis(label='x-axis') if keepopen: return fig else: fig.Close()