Source code for yade.plot

# encoding: utf-8
# 2008 © Václav Šmilauer <eudoxos@arcig.cz> 
"""
Module containing utility functions for plotting inside yade. See :ysrc:`examples/simple-scene/simple-scene-plot.py` or :ysrc:`examples/concrete/uniax.py` for example of usage.

"""
from __future__ import print_function

## all exported names
from future import standard_library
standard_library.install_aliases()

from builtins import range
from builtins import object
__all__=['data','plots','labels','live','liveInterval','autozoom','plot','reset','resetData','splitData','reverseData','addData','addAutoData','saveGnuplot','saveDataTxt','savePlotSequence']

# multi-threaded support for Tk
# safe to import even if Tk will not be used
import mtTkinter as Tkinter

try:
	import Image
except:
  try:
    import PIL.Image
  except:
    import warnings
    warnings.warn("PIL (python-imaging package) must be installed to use yade.plot")


import matplotlib,os,time,math,itertools

# running in batch
#
# If GtkAgg is the default, X must be working, which is not the case
# with batches (DISPLAY is unset in such case) and importing pylab fails then.
#
# Agg does not require the GUI part and works without any DISPLAY active
# just fine.
#
# see http://www.mail-archive.com/yade-dev@lists.launchpad.net/msg04320.html 
# and https://lists.launchpad.net/yade-users/msg03289.html
#
import yade.runtime
if not yade.runtime.hasDisplay: matplotlib.use('Agg')

from minieigen import *

#matplotlib.use('TkAgg')
#matplotlib.use('GTKAgg')
##matplotlib.use('QtAgg')
matplotlib.rc('axes',grid=True) # put grid in all figures
import pylab

data={}
"Global dictionary containing all data values, common for all plots, in the form {'name':[value,...],...}. Data should be added using plot.addData function. All [value,...] columns have the same length, they are padded with NaN if unspecified."
imgData={}
"Dictionary containing lists of strings, which have the meaning of images corresponding to respective :yref:`yade.plot.data` rows. See :yref:`yade.plot.plots` on how to plot images."
plots={} # dictionary x-name -> (yspec,...), where yspec is either y-name or (y-name,'line-specification')
"dictionary x-name -> (yspec,...), where yspec is either y-name or (y-name,'line-specification'). If ``(yspec,...)`` is ``None``, then the plot has meaning of image, which will be taken from respective field of :yref:`yade.plot.imgData`."
labels={}
"Dictionary converting names in data to human-readable names (TeX names, for instance); if a variable is not specified, it is left untranslated."
xylabels={}
"Dictionary of 2-tuples specifying (xlabel,ylabel) for respective plots; if either of them is None, the default auto-generated title is used."

legendLoc=('upper left','upper right')
"Location of the y1 and y2 legends on the plot, if y2 is active."

live=True if yade.runtime.hasDisplay else False
"Enable/disable live plot updating. Disabled by default for now, since it has a few rough edges."
liveInterval=1
"Interval for the live plot updating, in seconds."
autozoom=True
"Enable/disable automatic plot rezooming after data update."
scientific=True if hasattr(pylab,'ticklabel_format') else False  ## safe default for older matplotlib versions
"Use scientific notation for axes ticks."
axesWd=0
"Linewidth (in points) to make *x* and *y* axes better visible; not activated if non-positive."
current=-1
"Point that is being tracked with a scatter point. -1 is for the last point, set to *nan* to disable."
afterCurrentAlpha=.2
"Color alpha value for part of lines after :yref:`yade.plot.current`, between 0 (invisible) to 1 (full color)"
scatterMarkerKw=dict(verts=[(0.,0.),(-30.,10.),(-25,0),(-30.,-10.)],marker=None)
"Parameters for the current position marker"


componentSeparator='_'
componentSuffixes={Vector2:{0:'x',1:'y'},Vector3:{0:'x',1:'y',2:'z'},Matrix3:{(0,0):'xx',(1,1):'yy',(2,2):'zz',(0,1):'xy',(0,2):'xz',(1,2):'yz',(1,0):'yx',(2,0):'zx',(2,1):'zy'}}
# if a type with entry in componentSuffixes is given in addData, columns for individual components are synthesized using indices and suffixes given for each type, e.g. foo=Vector3r(1,2,3) will result in columns foox=1,fooy=2,fooz=3

[docs]def reset(): "Reset all plot-related variables (data, plots, labels)" global data, plots, labels # plotLines data={}; plots={}; imgData={} # plotLines={}; pylab.close('all')
[docs]def resetData(): "Reset all plot data; keep plots and labels intact." global data data={}
from yade.wrapper import *
[docs]def splitData(): "Make all plots discontinuous at this point (adds nan's to all data fields)" addData({})
[docs]def reverseData(): """Reverse yade.plot.data order. Useful for tension-compression test, where the initial (zero) state is loaded and, to make data continuous, last part must *end* in the zero state. """ for k in data: data[k].reverse()
def addDataColumns(dd): '''Add new columns with NaN data, without adding anything to other columns. Does nothing for columns that already exist''' numSamples=len(data[list(data.keys())[0]]) if len(data)>0 else 0 for d in dd: if d in list(data.keys()): continue data[d]=[nan for i in range(numSamples)]
[docs]def addAutoData(): """Add data by evaluating contents of :yref:`yade.plot.plots`. Expressions rasing exceptions will be handled gracefully, but warning is printed for each. >>> from yade import plot >>> from pprint import pprint >>> O.reset() >>> plot.resetData() >>> plot.plots={'O.iter':('O.time',None,'numParticles=len(O.bodies)')} >>> plot.addAutoData() >>> pprint(plot.data) {'O.iter': [0], 'O.time': [0.0], 'numParticles': [0]} Note that each item in :yref:`yade.plot.plots` can be * an expression to be evaluated (using the ``eval`` builtin); * ``name=expression`` string, where ``name`` will appear as label in plots, and expression will be evaluated each time; * a dictionary-like object -- current keys are labels of plots and current values are added to :yref:`yade.plot.data`. The contents of the dictionary can change over time, in which case new lines will be created as necessary. A simple simulation with plot can be written in the following way; note how the energy plot is specified. >>> from yade import plot, utils >>> plot.plots={'i=O.iter':(O.energy,None,'total energy=O.energy.total()')} >>> # we create a simple simulation with one ball falling down >>> plot.resetData() >>> O.bodies.append(utils.sphere((0,0,0),1)) 0 >>> O.dt=utils.PWaveTimeStep() >>> O.engines=[ ... ForceResetter(), ... GravityEngine(gravity=(0,0,-10),warnOnce=False), ... NewtonIntegrator(damping=.4,kinSplit=True), ... # get data required by plots at every step ... PyRunner(command='yade.plot.addAutoData()',iterPeriod=1,initRun=True) ... ] >>> O.trackEnergy=True >>> O.run(2,True) >>> pprint(plot.data) #doctest: +ELLIPSIS {'gravWork': [0.0, -25.13274...], 'i': [0, 1], 'kinRot': [0.0, 0.0], 'kinTrans': [0.0, 7.5398...], 'nonviscDamp': [0.0, 10.0530...], 'total energy': [0.0, -7.5398...]} """ # this part of docstring does not work with Sphinx """ .. plot:: from yade import * from yade import plot,utils O.reset() O.engines=[ForceResetter(),GravityEngine(gravity=(0,0,-10),warnOnce=False),NewtonIntegrator(damping=.4,kinSplit=True),PyRunner(command='yade.plot.addAutoData()',iterPeriod=1,initRun=True)] O.bodies.append(utils.sphere((0,0,0),1)); O.dt=utils.PWaveTimeStep() plot.resetData() plot.plots={'i=O.iter':(O.energy,None,'total energy=O.energy.total()')} O.trackEnergy=True O.run(50,True) import pylab; pylab.grid(True) plot.legendLoc=('lower left','upper right') plot.plot(noShow=True) """ def colDictUpdate(col,dic): 'update *dic* with the value from col, which is a "expr" or "name=expr" string; all exceptions from ``eval`` are caught and warning is printed without adding any data.' name,expr=col.split('=',1) if '=' in col else (col,col) try: val=eval(expr) dic.update({name:val}) except: print('WARN: ignoring exception raised while evaluating auto-column `'+expr+"'%s."%('' if name==expr else ' ('+name+')')) cols={} for p in plots: pp=plots[p] colDictUpdate(p.strip(),cols) for y in tuplifyYAxis(plots[p]): # imgplot specifier if y==None: continue yy=addPointTypeSpecifier(y,noSplit=True)[0] # dict-like object if hasattr(yy,'keys'): cols.update(dict(yy)) # callable returning list sequence of expressions to evaluate #elif callable(yy): # for yyy in yy(): colDictUpdate(yyy,cols) # plain value else: colDictUpdate(yy,cols) addData(cols)
[docs]def addData(*d_in,**kw): """Add data from arguments name1=value1,name2=value2 to yade.plot.data. (the old {'name1':value1,'name2':value2} is deprecated, but still supported) New data will be padded with nan's, unspecified data will be nan (nan's don't appear in graphs). This way, equal length of all data is assured so that they can be plotted one against any other. >>> from yade import plot >>> from pprint import pprint >>> plot.resetData() >>> plot.addData(a=1) >>> plot.addData(b=2) >>> plot.addData(a=3,b=4) >>> pprint(plot.data) {'a': [1, nan, 3], 'b': [nan, 2, 4]} Some sequence types can be given to addData; they will be saved in synthesized columns for individual components. >>> plot.resetData() >>> plot.addData(c=Vector3(5,6,7),d=Matrix3(8,9,10, 11,12,13, 14,15,16)) >>> pprint(plot.data) {'c_x': [5.0], 'c_y': [6.0], 'c_z': [7.0], 'd_xx': [8.0], 'd_xy': [9.0], 'd_xz': [10.0], 'd_yx': [11.0], 'd_yy': [12.0], 'd_yz': [13.0], 'd_zx': [14.0], 'd_zy': [15.0], 'd_zz': [16.0]} """ import numpy if len(data)>0: numSamples=len(data[list(data.keys())[0]]) else: numSamples=0 # align with imgData, if there is more of them than data if len(imgData)>0 and numSamples==0: numSamples=max(numSamples,len(imgData[list(imgData.keys())[0]])) d=(d_in[0] if len(d_in)>0 else {}) d.update(**kw) # handle types composed of multiple values (vectors, matrices) dNames=list(d.keys())[:] # make copy, since dict cannot change size if iterated over directly for name in dNames: if type(d[name]) in componentSuffixes: val=d[name] suffixes=componentSuffixes[type(d[name])] for ix in suffixes: d[name+componentSeparator+suffixes[ix]]=d[name][ix] del d[name] elif hasattr(d[name],'__len__'): raise ValueError('plot.addData given unhandled sequence type (is a '+type(d[name]).__name__+', must be number or '+'/'.join([k.__name__ for k in componentSuffixes])+')') for name in d: if not name in list(data.keys()): data[name]=[] for name in data: data[name]+=(numSamples-len(data[name]))*[nan] data[name].append(d[name] if name in d else nan)
#print [(k,len(data[k])) for k in data.keys()] #numpy.array([nan for i in range(numSamples)]) #numpy.append(data[name],[d[name]],1) def addImgData(**kw): for k in kw: if k not in imgData: imgData[k]=[] # align imgData with data if len(list(data.keys()))>0 and len(list(imgData.keys()))>0: nData,nImgData=len(data[list(data.keys())[0]]),len(imgData[list(imgData.keys())[0]]) #if nImgData>nData-1: raise RuntimeError("imgData is already the same length as data?") if nImgData<nData-1: # repeat last value for k in list(imgData.keys()): lastValue=imgData[k][-1] if len(imgData[k])>0 else None imgData[k]+=(nData-len(imgData[k])-1)*[lastValue] elif nData<nImgData: for k in list(data.keys()): lastValue=data[k][-1] if len(data[k])>0 else nan data[k]+=(nImgData-nData)*[lastValue] # add one more, because we will append to imgData below # add values from kw newLen=(len(imgData[list(imgData.keys())[0]]) if imgData else 0)+1 # current length plus 1 for k in kw: if k in imgData and len(imgData[k])>0: imgData[k]+=(newLen-len(imgData[k])-1)*[imgData[k][-1]]+[kw[k]] # repeat last element as necessary else: imgData[k]=(newLen-1)*[None]+[kw[k]] # repeat None if no previous value # align values which were not in kw by repeating the last value for k in imgData: if len(imgData[k])<newLen: imgData[k]+=(newLen-len(imgData[k]))*[imgData[k][-1]] assert(len(set([len(i) for i in list(imgData.values())]))<=1) # no data or all having the same value # not public functions def addPointTypeSpecifier(o,noSplit=False): """Add point type specifier to simple variable name; optionally take only the part before '=' from the first item.""" if type(o) in [tuple,list]: if noSplit or not type(o[0])==str: return o else: return (o[0].split('=',1)[0],)+tuple(o[1:]) else: return (o if (noSplit or not type(o)==str) else (o.split('=',1)[0]),'') def tuplifyYAxis(pp): """convert one variable to a 1-tuple""" if type(pp) in [tuple,list]: return pp else: return (pp,) def xlateLabel(l): "Return translated label; return l itself if not in the labels dict." global labels if l in list(labels.keys()): return labels[l] else: return l class LineRef(object): """Holds reference to plot line and to original data arrays (which change during the simulation), and updates the actual line using those data upon request.""" def __init__(self,line,scatter,line2,xdata,ydata,dataName=None): self.line,self.scatter,self.line2,self.xdata,self.ydata,self.dataName=line,scatter,line2,xdata,ydata,dataName def update(self): if isinstance(self.line,matplotlib.image.AxesImage): # image name try: if len(self.xdata)==0 and self.dataName: self.xdata=imgData[self.dataName] # empty list reference an empty singleton, not the list we want; adjust here if self.xdata[current]==None: img=Image.new('RGBA',(1,1),(0,0,0,0)) else: img=Image.open(self.xdata[current]) self.line.set_data(img) except IndexError: pass else: # regular data import numpy # current==-1 avoids copy slicing data in the else part if current==None or current==-1 or afterCurrentAlpha==1: self.line.set_xdata(self.xdata); self.line.set_ydata(self.ydata) self.line2.set_xdata([]); self.line2.set_ydata([]) else: try: # try if we can extend the first part by one so that lines are connected self.xdata[:current+1]; preCurrEnd=current+1 except IndexError: preCurrEnd=current preCurrEnd=current+(1 if len(self.xdata)>current else 0) self.line.set_xdata(self.xdata[:preCurrEnd]); self.line.set_ydata(self.ydata[:preCurrEnd]) self.line2.set_xdata(self.xdata[current:]); self.line2.set_ydata(self.ydata[current:]) try: x,y=self.xdata[current],self.ydata[current] except IndexError: x,y=0,0 # this could be written in a nicer way, very likely try: pt=numpy.ndarray((2,),buffer=numpy.array([float(x),float(y)])) if self.scatter: self.scatter.set_offsets(pt) # change rotation of the marker (possibly incorrect) try: dx,dy=self.xdata[current]-self.xdata[current-1],self.ydata[current]-self.ydata[current-1] # smoothing from last n values, if possible # FIXME: does not show arrow at all if less than window values #try: # window=10 # dx,dy=[numpy.average(numpy.diff(dta[current-window:current])) for dta in self.xdata,self.ydata] #except IndexError: pass # there must be an easier way to find on-screen derivative angle, ask on the matplotlib mailing list axes=self.line.axes() p=axes.patch; xx,yy=p.get_verts()[:,0],p.get_verts()[:,1]; size=max(xx)-min(xx),max(yy)-min(yy) aspect=(size[1]/size[0])*(1./axes.get_data_ratio()) angle=math.atan(aspect*dy/dx) if dx<0: angle-=math.pi self.scatter.set_transform(matplotlib.transforms.Affine2D().rotate(angle)) except IndexError: pass except TypeError: pass # this happens at i386 with empty data, saying TypeError: buffer is too small for requested array currLineRefs=[] liveTimeStamp=0 # timestamp when live update was started, so that the old thread knows to stop if that changes nan=float('nan') def createPlots(subPlots=True,scatterSize=60,wider=False): global currLineRefs figs=set([l.line.axes.get_figure() for l in currLineRefs]) # get all current figures for f in figs: pylab.close(f) # close those currLineRefs=[] # remove older plots (breaks live updates of windows that are still open) if len(plots)==0: return # nothing to plot if subPlots: # compute number of rows and colums for plots we have subCols=int(round(math.sqrt(len(plots)))); subRows=int(math.ceil(len(plots)*1./subCols)) if wider: subRows,subCols=subCols,subRows for nPlot,p in enumerate(plots.keys()): pStrip=p.strip().split('=',1)[0] if not subPlots: pylab.figure() else: pylab.subplot(subRows,subCols,nPlot+1) if plots[p]==None: # image plot if not pStrip in list(imgData.keys()): imgData[pStrip]=[] # fake (empty) image if no data yet if len(imgData[pStrip])==0 or imgData[pStrip][-1]==None: img=Image.new('RGBA',(1,1),(0,0,0,0)) else: img=Image.open(imgData[pStrip][-1]) img=pylab.imshow(img,origin='lower') currLineRefs.append(LineRef(img,None,None,imgData[pStrip],None,pStrip)) pylab.gca().set_axis_off() continue plots_p=[addPointTypeSpecifier(o) for o in tuplifyYAxis(plots[p])] plots_p_y1,plots_p_y2=[],[]; y1=True missing=set() # missing data columns if pStrip not in list(data.keys()): missing.add(pStrip) for d in plots_p: if d[0]==None: y1=False; continue if y1: plots_p_y1.append(d) else: plots_p_y2.append(d) if d[0] not in list(data.keys()) and not callable(d[0]) and not hasattr(d[0],'keys'): missing.add(d[0]) if missing: if len(list(data.keys()))==0 or len(data[list(data.keys())[0]])==0: # no data at all yet, do not add garbage NaNs for m in missing: data[m]=[] else: print('Missing columns in plot.data, adding NaN: ',','.join(list(missing))) addDataColumns(missing) def createLines(pStrip,ySpecs,isY1=True,y2Exists=False): '''Create data lines from specifications; this code is common for y1 and y2 axes; it handles y-data specified as callables, which might create additional lines when updated with liveUpdate. ''' # save the original specifications; they will be smuggled into the axes object # the live updated will run yNameFuncs to see if there are new lines to be added # and will add them if necessary yNameFuncs=set([d[0] for d in ySpecs if callable(d[0])]) | set([d[0].keys for d in ySpecs if hasattr(d[0],'keys')]) yNames=set() ySpecs2=[] for ys in ySpecs: # ys[0]() must return list of strings, which are added to ySpecs2; line specifier is synthesized by tuplifyYAxis and cannot be specified by the user if callable(ys[0]): ySpecs2+=[(ret,ys[1]) for ret in ys[0]()] elif hasattr(ys[0],'keys'): ySpecs2+=[(yy,'') for yy in list(ys[0].keys())] else: ySpecs2.append(ys) if len(ySpecs2)==0: print('yade.plot: creating fake plot, since there are no y-data yet') line,=pylab.plot([nan],[nan]) line2,=pylab.plot([nan],[nan]) currLineRefs.append(LineRef(line,None,line2,[nan],[nan])) # set different color series for y1 and y2 so that they are recognizable if 'axes.color_cycle' in pylab.rcParams: pylab.rcParams['axes.color_cycle']='b,g,r,c,m,y,k' if not isY1 else 'm,y,k,b,g,r,c' for d in ySpecs2: yNames.add(d) line,=pylab.plot(data[pStrip],data[d[0]],d[1],label=xlateLabel(d[0])) line2,=pylab.plot([],[],d[1],color=line.get_color(),alpha=afterCurrentAlpha) # use (0,0) if there are no data yet scatterPt=[0,0] if len(data[pStrip])==0 else (data[pStrip][current],data[d[0]][current]) # if current value is NaN, use zero instead scatter=pylab.scatter(scatterPt[0] if not math.isnan(scatterPt[0]) else 0,scatterPt[1] if not math.isnan(scatterPt[1]) else 0,s=scatterSize,color=line.get_color(),**scatterMarkerKw) currLineRefs.append(LineRef(line,scatter,line2,data[pStrip],data[d[0]])) axes=line.axes labelLoc=(legendLoc[0 if isY1 else 1] if y2Exists>0 else 'best') l=pylab.legend(loc=labelLoc) if hasattr(l,'draggable'): l.draggable(True) if scientific: pylab.ticklabel_format(style='sci',scilimits=(0,0),axis='both') # fixes scientific exponent placement for y2: https://sourceforge.net/mailarchive/forum.php?thread_name=20101223174750.GD28779%40ykcyc&forum_name=matplotlib-users if not isY1: axes.yaxis.set_offset_position('right') if isY1: pylab.ylabel((', '.join([xlateLabel(_p[0]) for _p in ySpecs2])) if p not in xylabels or not xylabels[p][1] else xylabels[p][1]) pylab.xlabel(xlateLabel(pStrip) if (p not in xylabels or not xylabels[p][0]) else xylabels[p][0]) else: pylab.ylabel((', '.join([xlateLabel(_p[0]) for _p in ySpecs2])) if (p not in xylabels or len(xylabels[p])<3 or not xylabels[p][2]) else xylabels[p][2]) # if there are callable/dict ySpecs, save them inside the axes object, so that the live updater can use those if yNameFuncs: axes.yadeYNames,axes.yadeYFuncs,axes.yadeXName,axes.yadeLabelLoc=yNames,yNameFuncs,pStrip,labelLoc # prepend yade to avoid clashes createLines(pStrip,plots_p_y1,isY1=True,y2Exists=len(plots_p_y2)>0) if axesWd>0: pylab.axhline(linewidth=axesWd,color='k') pylab.axvline(linewidth=axesWd,color='k') # create y2 lines, if any if len(plots_p_y2)>0: pylab.twinx() # create the y2 axis createLines(pStrip,plots_p_y2,isY1=False,y2Exists=True) if 'title' in list(O.tags.keys()): pylab.title(O.tags['title']) def liveUpdate(timestamp): global liveTimeStamp liveTimeStamp=timestamp while True: if not live or liveTimeStamp!=timestamp: return figs,axes,linesData=set(),set(),set() for l in currLineRefs: l.update() figs.add(l.line.get_figure()) axes.add(l.line.axes) linesData.add(id(l.ydata)) # find callables in y specifiers, create new lines if necessary for ax in axes: if not hasattr(ax,'yadeYFuncs') or not ax.yadeYFuncs: continue # not defined of empty yy=set(); for f in ax.yadeYFuncs: if callable(f): yy.update(f()) elif hasattr(f,'keys'): yy.update(list(f.keys())) else: raise ValueError("Internal error: ax.yadeYFuncs items must be callables or dictionary-like objects and nothing else.") #print 'callables y names:',yy news=yy-ax.yadeYNames if not news: continue for new in news: ax.yadeYNames.add(new) if new in list(data.keys()) and id(data[new]) in linesData: continue # do not add when reloaded and the old lines are already there print('yade.plot: creating new line for',new) if not new in list(data.keys()): data[new]=len(data[ax.yadeXName])*[nan] # create data entry if necessary #print 'data',len(data[ax.yadeXName]),len(data[new]),data[ax.yadeXName],data[new] line,=ax.plot(data[ax.yadeXName],data[new],label=xlateLabel(new)) # no line specifier line2,=ax.plot([],[],color=line.get_color(),alpha=afterCurrentAlpha) scatterPt=(0 if len(data[ax.yadeXName])==0 or math.isnan(data[ax.yadeXName][current]) else data[ax.yadeXName][current]),(0 if len(data[new])==0 or math.isnan(data[new][current]) else data[new][current]) scatter=ax.scatter(scatterPt[0],scatterPt[1],s=60,color=line.get_color(),**scatterMarkerKw) currLineRefs.append(LineRef(line,scatter,line2,data[ax.yadeXName],data[new])) ax.set_ylabel(ax.get_ylabel()+(', ' if ax.get_ylabel() else '')+xlateLabel(new)) # it is possible that the legend has not yet been created l=ax.legend(loc=ax.yadeLabelLoc) if hasattr(l,'draggable'): l.draggable(True) if autozoom: for ax in axes: try: ax.relim() # recompute axes limits ax.autoscale_view() except RuntimeError: pass # happens if data are being updated and have not the same dimension at the very moment for fig in figs: try: fig.canvas.draw() except RuntimeError: pass # happens here too time.sleep(liveInterval)
[docs]def savePlotSequence(fileBase,stride=1,imgRatio=(5,7),title=None,titleFrames=20,lastFrames=30): '''Save sequence of plots, each plot corresponding to one line in history. It is especially meant to be used for :yref:`yade.utils.makeVideo`. :param stride: only consider every stride-th line of history (default creates one frame per each line) :param title: Create title frame, where lines of title are separated with newlines (``\\n``) and optional subtitle is separated from title by double newline. :param int titleFrames: Create this number of frames with title (by repeating its filename), determines how long the title will stand in the movie. :param int lastFrames: Repeat the last frame this number of times, so that the movie does not end abruptly. :return: List of filenames with consecutive frames. ''' createPlots(subPlots=True,scatterSize=60,wider=True) sqrtFigs=math.sqrt(len(plots)) pylab.gcf().set_size_inches(8*sqrtFigs,5*sqrtFigs) # better readable pylab.subplots_adjust(left=.05,right=.95,bottom=.05,top=.95) # make it more compact if len(plots)==1 and plots[list(plots.keys())[0]]==None: # only pure snapshot is there pylab.gcf().set_size_inches(5,5) pylab.subplots_adjust(left=0,right=1,bottom=0,top=1) #if not data.keys(): raise ValueError("plot.data is empty.") pltLen=max(len(data[list(data.keys())[0]]) if data else 0,len(imgData[list(imgData.keys())[0]]) if imgData else 0) if pltLen==0: raise ValueError("Both plot.data and plot.imgData are empty.") global current, currLineRefs ret=[] print('Saving %d plot frames, it can take a while...'%(pltLen)) for i,n in enumerate(range(0,pltLen,stride)): current=n for l in currLineRefs: l.update() out=fileBase+'-%03d.png'%i pylab.gcf().savefig(out) ret.append(out) if len(ret)==0: raise RuntimeError("No images created?!") if title: titleImgName=fileBase+'-title.png' createTitleFrame(titleImgName,Image.open(ret[-1]).size,title) ret=titleFrames*[titleImgName]+ret if lastFrames>1: ret+=(lastFrames-1)*[ret[-1]] return ret
def createTitleFrame(out,size,title): 'create figure with title and save to file; a figure object must be opened to get the right size' pylab.clf(); fig=pylab.gcf() #insize=fig.get_size_inches(); size=insize[1]*fig.get_dpi(),insize[0]*fig.get_dpi() # this gives wrong dimensions... #fig.set_facecolor('blue'); fig.patch.set_color('blue'); fig.patch.set_facecolor('blue'); fig.patch.set_alpha(None) title,subtitle=title.split('\n\n') lines=[(t,True) for t in title.split('\n')]+([(t,False) for t in subtitle.split('\n')] if subtitle else []) nLines=len(lines); fontSizes=size[1]/10.,size[1]/16. import matplotlib.mathtext def writeLine(text,vertPos,fontsize): rgba,depth=matplotlib.mathtext.MathTextParser('Bitmap').to_rgba(text,fontsize=fontsize,dpi=fig.get_dpi(),color='blue') textsize=rgba.shape[1],rgba.shape[0] if textsize[0]>size[0]: rgba,depth=matplotlib.mathtext.MathTextParser('Bitmap').to_rgba(text,fontsize=fontsize*size[0]/textsize[0],dpi=fig.get_dpi(),color='blue') textsize=rgba.shape[1],rgba.shape[0] fig.figimage(rgba.astype(float)/255.,xo=(size[0]-textsize[0])/2.,yo=vertPos-depth) ht=size[1]; y0=ht-2*fontSizes[0]; yStep=(ht-2.5*fontSizes[0])/len(lines) for i,(l,isTitle) in enumerate(lines): writeLine(l,y0-i*yStep,fontSizes[0 if isTitle else 1]) fig.savefig(out)
[docs]def plot(noShow=False,subPlots=True): """Do the actual plot, which is either shown on screen (and nothing is returned: if *noShow* is ``False`` - note that your yade compilation should present qt4 feature so that figures can be displayed) or, if *noShow* is ``True``, returned as matplotlib's Figure object or list of them. You can use >>> from yade import plot >>> plot.resetData() >>> plot.plots={'foo':('bar',)} >>> plot.plot(noShow=True).savefig('someFile.pdf') >>> import os >>> os.path.exists('someFile.pdf') True >>> os.remove('someFile.pdf') to save the figure to file automatically. .. note:: For backwards compatibility reasons, *noShow* option will return list of figures for multiple figures but a single figure (rather than list with 1 element) if there is only 1 figure. """ createPlots(subPlots=subPlots) global currLineRefs figs=set([l.line.axes.get_figure() for l in currLineRefs]) if not hasattr(list(figs)[0],'show') and not noShow: import warnings warnings.warn('plot.plot not showing figure (matplotlib using headless backend?)') noShow=True if not noShow: if not yade.runtime.hasDisplay: return # would error out with some backends, such as Agg used in batches if live: import _thread _thread.start_new_thread(liveUpdate,(time.time(),)) # pylab.show() # this blocks for some reason; call show on figures directly for f in figs: f.show() else: figs=list(set([l.line.get_figure() for l in currLineRefs])) if len(figs)==1: return figs[0] else: return figs
[docs]def saveDataTxt(fileName,vars=None, headers=None): """Save plot data into a (optionally compressed) text file. The first line contains a comment (starting with ``#``) giving variable name for each of the columns. This format is suitable for being loaded for further processing (outside yade) with ``numpy.genfromtxt`` function, which recognizes those variable names (creating numpy array with named entries) and handles decompression transparently. >>> from yade import plot >>> from pprint import pprint >>> plot.reset() >>> plot.addData(a=1,b=11,c=21,d=31) # add some data here >>> plot.addData(a=2,b=12,c=22,d=32) >>> pprint(plot.data) {'a': [1, 2], 'b': [11, 12], 'c': [21, 22], 'd': [31, 32]} >>> plot.saveDataTxt('/tmp/dataFile.txt.tar.gz',vars=('a','b','c')) >>> import numpy >>> d=numpy.genfromtxt('/tmp/dataFile.txt.tar.gz',dtype=None,names=True) >>> d['a'] array([1, 2]) >>> d['b'] array([11, 12]) :param fileName: file to save data to; if it ends with ``.bz2`` / ``.gz``, the file will be compressed using bzip2 / gzip. :param vars: Sequence (tuple/list/set) of variable names to be saved. If ``None`` (default), all variables in :yref:`yade.plot.plot` are saved. :param headers: Set of parameters to write on header """ import bz2,gzip if not vars: vars=list(data.keys()); vars.sort() write_bytemode=False if fileName.endswith('.bz2'): f=bz2.BZ2File(fileName,'w') ; write_bytemode=True elif fileName.endswith('.gz'): f=gzip.GzipFile(fileName,'w') ; write_bytemode=True else: f=open(fileName,'w') if headers: k = list(headers.keys()); for i in range(len(k)): out=("# "+k[i]+"=\t"+str(headers[k[i]])+"\n") if(write_bytemode): out=out.encode("utf-8") f.write(out) out=str("# "+"\t\t".join(vars)+"\n") if(write_bytemode): out=out.encode("utf-8") f.write(out) for i in range(len(data[vars[0]])): out="\t".join([str(data[var][i]) for var in vars])+"\n" if(write_bytemode): out=out.encode("utf-8") f.write(out) f.close()
def savePylab(baseName,timestamp=False,title=None): '''This function is not finished, do not use it.''' import time if len(list(data.keys()))==0: raise RuntimeError("No data for plotting were saved.") if timestamp: baseName+=_mkTimestamp() baseNameNoPath=baseName.split('/')[-1] saveDataTxt(fileName=baseName+'.data.bz2') if len(plots)==0: raise RuntimeError("No plots to save, only data saved.") py=open(baseName+'.py','w') py.write('#!/usr/bin/env python\n# encoding: utf-8\n# created '+time.asctime()+' ('+time.strftime('%Y%m%d_%H:%M')+')\n#\nimport pylab, numpy\n') py.write("data=numpy.genfromtxt('%s.data.bz2',dtype=None,names=True)\n"%baseName) subCols=int(round(math.sqrt(len(plots)))); subRows=int(math.ceil(len(plots)*1./subCols)) for nPlot,p in enumerate(plots.keys()): pStrip=p.strip().split('=',1)[0] if plots[p]==None: continue # image plots, which is not exported if len(plots)==1: py.write('pylab.figure()\n') else: py.write('pylab.subplot(%d,%d,%d)\n'%(subRows,subCols,nPlots+1)) def _mkTimestamp(): import time return time.strftime('_%Y%m%d_%H:%M')
[docs]def saveGnuplot(baseName,term='wxt',extension=None,timestamp=False,comment=None,title=None,varData=False): """Save data added with :yref:`yade.plot.addData` into (compressed) file and create .gnuplot file that attempts to mimick plots specified with :yref:`yade.plot.plots`. :param baseName: used for creating baseName.gnuplot (command file for gnuplot), associated ``baseName.data.bz2`` (data) and output files (if applicable) in the form ``baseName.[plot number].extension`` :param term: specify the gnuplot terminal; defaults to ``x11``, in which case gnuplot will draw persistent windows to screen and terminate; other useful terminals are ``png``, ``cairopdf`` and so on :param extension: extension for ``baseName`` defaults to terminal name; fine for png for example; if you use ``cairopdf``, you should also say ``extension='pdf'`` however :param bool timestamp: append numeric time to the basename :param bool varData: whether file to plot will be declared as variable or be in-place in the plot expression :param comment: a user comment (may be multiline) that will be embedded in the control file :return: name of the gnuplot file created. """ if len(list(data.keys()))==0: raise RuntimeError("No data for plotting were saved.") if timestamp: baseName+=_mkTimestamp() baseNameNoPath=baseName.split('/')[-1] vars=list(data.keys()); vars.sort() saveDataTxt(fileName=baseName+'.data.bz2',vars=vars) fPlot=open(baseName+".gnuplot",'w') fPlot.write('#!/usr/bin/env gnuplot\n#\n# created '+time.asctime()+' ('+time.strftime('%Y%m%d_%H:%M')+')\n#\n') if comment: fPlot.write('# '+comment.replace('\n','\n# ')+'#\n') dataFile='"< bzcat %s.data.bz2"'%(baseNameNoPath) if varData: fPlot.write('dataFile=%s'%dataFile); dataFile='dataFile' if not extension: extension=term i=0 for p in plots: pStrip=p.strip().split('=',1)[0] if plots[p]==None: continue ## this plot is image plot, which is not applicable to gnuplot plots_p=[addPointTypeSpecifier(o) for o in tuplifyYAxis(plots[p])] if term in ['wxt','x11']: fPlot.write("set term %s %d persist\n"%(term,i)) else: fPlot.write("set term %s; set output '%s.%d.%s'\n"%(term,baseNameNoPath,i,extension)) fPlot.write("set xlabel '%s'\n"%xlateLabel(p)) fPlot.write("set grid\n") fPlot.write("set datafile missing 'nan'\n") if title: fPlot.write("set title '%s'\n"%title) y1=True; plots_y1,plots_y2=[],[] # replace callable/dict-like data specifiers by the results, it that particular data exists plots_p2=[] for pp in plots_p: if callable(pp[0]): plots_p2+=[(ppp,'') for ppp in pp[0]() if ppp in list(data.keys())] elif hasattr(pp[0],'keys'): plots_p2+=[(name,val) for name,val in list(pp[0].items()) if name in list(data.keys())] else: plots_p2.append((pp[0],pp[1])) plots_p=plots_p2 #plots_p=sum([([(pp,'') for pp in p[0]() if pp in data.keys()] if callable(p[0]) else [(p[0],p[1])] ) for p in plots_p],[]) for d in plots_p: if d[0]==None: y1=False; continue if y1: plots_y1.append(d) else: plots_y2.append(d) fPlot.write("set ylabel '%s'\n"%(','.join([xlateLabel(_p[0]) for _p in plots_y1]))) if len(plots_y2)>0: fPlot.write("set y2label '%s'\n"%(','.join([xlateLabel(_p[0]) for _p in plots_y2]))) fPlot.write("set y2tics\n") ppp=[] for pp in plots_y1: ppp.append(" %s using %d:%d title '← %s(%s)' with lines"%(dataFile,vars.index(pStrip)+1,vars.index(pp[0])+1,xlateLabel(pp[0]),xlateLabel(pStrip),)) for pp in plots_y2: ppp.append(" %s using %d:%d title '%s(%s) →' with lines axes x1y2"%(dataFile,vars.index(pStrip)+1,vars.index(pp[0])+1,xlateLabel(pp[0]),xlateLabel(pStrip),)) fPlot.write("plot "+",".join(ppp)+"\n") i+=1 fPlot.close() return baseName+'.gnuplot'