# -*- 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]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()