# 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.
"""
## all exported names
__all__ = [
'data', 'plots', 'labels', 'live', 'liveInterval', 'setLiveForceAlwaysUpdate', '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
import _thread
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
from cycler import cycler
# 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 yade.minieigenHP import *
#matplotlib.use('TkAgg')
#matplotlib.use('GTKAgg')
##matplotlib.use('Qt5Agg')
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."
plotSyncLock = _thread.allocate_lock()
"A lock (mutex) used for synchronizing live drawing (happens every ``liveInterval`` seconds) and adding more plot data. Also see https://gitlab.com/yade-dev/trunk/-/issues/110"
liveForceAlwaysUpdate = False
"See :yref:`yade.plot.setLiveForceAlwaysUpdate`."
live = True if yade.runtime.hasDisplay else False
"Enable/disable live plot updating."
liveInterval = 1
"Interval for the live plot updating, in seconds."
autozoom = True
"Enable/disable automatic plot rezooming after data update. Sometimes rezooming must be skipped unless a call to :yref:`yade.plot.setLiveForceAlwaysUpdate` forces it to work."
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(marker=[(0., 0.), (-30., 10.), (-25, 0), (-30., -10.)])
"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()
[docs]
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 (live and liveForceAlwaysUpdate):
plotSyncLock.acquire()
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)
if (
live and liveForceAlwaysUpdate and plotSyncLock.locked()
): # check if locked() in case when liveForceAlwaysUpdate was changed during addData(…) call.
plotSyncLock.release()
[docs]
def setLiveForceAlwaysUpdate(forceLiveUpdate):
"The :yref:`yade.plot.liveInterval` and :yref:`yade.plot.live` control live refreshing of the plot during calculations. The refreshing is done in a separate thread, so that it does not interfere with calculations. Drawing the data will not work when at exactly the same time it is being updated in other thread. Use ``yade.plot.setLiveForceAlwaysUpdate(True)`` if you want calculations to **PAUSE** during the plot updates. This function returns current ``bool`` value of forced updates if the call was a success, otherwise it returns a ``str`` with explanation why it failed. It is guaranteed to work if simulation was paused with :yref:`O.pause()<Omega.pause>` call."
if (plotSyncLock.acquire(blocking=False)):
global liveForceAlwaysUpdate
liveForceAlwaysUpdate = forceLiveUpdate
plotSyncLock.release()
return forceLiveUpdate
else:
return "setLiveForceAlwaysUpdate(" + str(
forceLiveUpdate
) + "); failed. Try again after pausing the simulation with :yref:`O.pause()<Omega.pause>`."
[docs]
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
[docs]
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]), '')
[docs]
def tuplifyYAxis(pp):
"""convert one variable to a 1-tuple"""
if type(pp) in [tuple, list]:
return pp
else:
return (pp,)
[docs]
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
[docs]
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
[docs]
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')
[docs]
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.prop_cycle' in pylab.rcParams:
pylab.rcParams['axes.prop_cycle'] = cycler('color', ['b', 'g', 'r', 'c', 'm', 'y', 'k'
]) if not isY1 else cycler('color', ['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], 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'])
[docs]
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:
if (liveForceAlwaysUpdate):
plotSyncLock.acquire()
for ax in axes:
try:
## Note about https://gitlab.com/yade-dev/trunk/-/issues/110 , we can see that the data (x,y) to plot has correct sizes:
#print("1st line sizes: ", len(ax.lines[0]._x), len(ax.lines[0]._y)) # ← e.g. the first line: ax.lines[0]
## But before ax.relim() finishes running the other thread will add data to _y, but not yet to _x
## We can confirm this by printing these sizes inside function _broadcast_shape in file stride_tricks.py from package python3-numpy
ax.relim() # recompute axes limits
ax.autoscale_view()
except Exception:
## This happens if data are being updated and have not the same dimension at the very moment.
## So the solution is to ignore this exception and hope that next time plot refresh will happen at more favorable time.
## Alternatively one might call setLiveForceAlwaysUpdate(True) which will pause addData during the plot redraw
#print(e)
pass # happens if data are being updated and have not the same dimension at the very moment
if (liveForceAlwaysUpdate and plotSyncLock.locked()):
plotSyncLock.release()
for fig in figs:
try:
fig.canvas.draw()
except Exception:
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
[docs]
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:
_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])
>>> import os # cleanup
>>> os.remove('/tmp/dataFile.txt.tar.gz')
: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()
[docs]
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'
