我一直在研究一个问题（我是一名化学工程师，所以我需要永远理解如何编写代码）如何让多个选项卡在自己的流程中运行，但每个选项卡都有自己的数据显示在matplotlib情节中。我遇到了很多酸洗错误，我想知道是否有人有任何简单的解决方案。我相信酸洗错误的主要原因是由于我试图作为属性传递给选项卡对象的对象。该对象包含一些数据以及许多其他有助于拟合它所持有的数据的对象。我觉得这些对象非常好而且相当必要，但我也意识到它们导致了酸洗问题。这是我的代码的一个非常简化的版本：（如果你想复制/粘贴来测试它，它仍然可以编译。）
import multiprocessing as mp
from PyQt4 import QtGui, QtCore
import numpy as np
import matplotlib
matplotlib.use('QtAgg')
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib import figure
import sys
import lmfit
# This object will just hold certain objects which will help create data objects ato be shown in matplotlib plots
# this could be a type of species with properties that could be quantized to a location on an axis (like number of teeth)
#, which special_object would hold another quantization of that property (like length of teeth)
class object_within_special_object:
def __init__(self, n, m):
self.n = n
self.m = m
def location(self, i):
location = i*self.m/self.n
return location
def NM(self):
return str(self.n) + str(self.m)
# This is what will hold a number of species and all of their properties,
# as well as some data to try and fit using the species and their properties
class special_object:
def __init__(self, name, X, Y):
self.name = name
self.X = X
self.Y = Y
self.params = lmfit.Parameters()
self.things = self.make_a_whole_bunch_of_things()
for thing in self.things:
self.params.add('something' + str(thing.NM()) + 's', value = 3)
def make_a_whole_bunch_of_things(self):
things = []
for n in range(0,20):
m=1
things.append(object_within_special_object(n,m))
return things
# a special type of tab which holds a (or a couple of) matplotlib plots and a special_object ( which holds the data to display in those plots)
class Special_Tab(QtGui.QTabWidget):
def __init__(self, parent, special_object):
QtGui.QTabWidget.__init__(self, parent)
self.special_object = special_object
self.grid = QtGui.QGridLayout(self)
# matplotlib figure put into tab
self.fig = figure.Figure()
self.plot = self.fig.add_subplot(111)
self.line, = self.plot.plot(self.special_object.X, self.special_object.Y, 'r-')
self.canvas = FigureCanvas(self.fig)
self.grid.addWidget(self.canvas)
self.canvas.show()
self.canvas.draw()
self.canvas_BBox = self.plot.figure.canvas.copy_from_bbox(self.plot.bbox)
ax1 = self.plot.figure.axes[0]
def process_on_special_object(self):
# do a long fitting process involving the properties of the special_object
return
def update_GUI(self):
# change the GUI to reflect changes made to special_object
self.line.set_data(special_object.X, special_object.Y)
self.plot.draw_artist(self.line)
self.plot.figure.canvas.blit(self.plot.bbox)
return
# This window just has a button to make all of the tabs in separate processes
class MainWindow(QtGui.QMainWindow):
def __init__(self, parent = None):
# This GUI stuff shouldn't be too important
QtGui.QMainWindow.__init__(self)
self.resize(int(app.desktop().screenGeometry().width()*.6), int(app.desktop().screenGeometry().height()*.6))
self.tabs_list = []
central_widget = QtGui.QWidget(self)
self.main_tab_widget = QtGui.QTabWidget()
self.layout = QtGui.QHBoxLayout(central_widget)
button = QtGui.QPushButton('Open Tabs')
self.layout.addWidget(button)
self.layout.addWidget(self.main_tab_widget)
QtCore.QObject.connect(button, QtCore.SIGNAL("clicked()"), self.open_tabs)
self.setCentralWidget(central_widget)
central_widget.setLayout(self.layout)
# Here we open several tabs and put them in different processes
def open_tabs(self):
for i in range(0, 10):
# this is just some random data for the objects
X = np.arange(1240.0/1350.0, 1240./200., 0.01)
Y = np.array(np.e**.2*X + np.sin(10*X)+np.cos(4*X))
# Here the special tab is created
new_tab = Special_Tab(self.main_tab_widget, special_object(str(i), X, Y))
self.main_tab_widget.addTab(new_tab, str(i))
# this part works fine without the .start() function
self.tabs_list.append(mp.Process(target=new_tab))
# this is where pickling errors occur
self.tabs_list[-1].start()
return
if __name__ == "__main__":
app = QtGui.QApplication([])
win = MainWindow()
win.show()
sys.exit(app.exec_())
我注意到错误来自 matplotlib 轴（我不确定如何？）并给出错误pickle.PicklingError: Can't pickle <class 'matplotlib.axes.AxesSubplot'>: it's not found as matplotlib.axes.AxesSubplot。此外，我注意到注释掉 matplotlib 图也会产生酸洗错误pickle.PicklingError: Can't pickle <function <lambda> at 0x012A2B30>: it's not found as lmfit.parameter.<lambda>。我认为这是因为 lambda 函数不能被腌制，我猜 lmfit 在它的深处有一个 lambda ......但如果没有解决这些错误的方法，我真的不知道该怎么做。
奇怪的是，我从原始代码（不是此处显示的简化版本）中看到的错误略有不同，但在情感上仍然基本相同。我在其他代码中遇到的错误是pickle.PicklingError: Can't pickle 'BufferRegion' object: <BufferRegion object at 0x037EBA04>
有没有人可以通过移动对象来解决我通过它们的位置或任何其他想法来更好地解决这个问题？
我非常感谢您的时间和精力以及对此问题的任何帮助。
编辑：我以某种方式尝试了 unutbu 的想法，但对过程功能的位置进行了一些更改。所提出的解决方案的唯一问题是该do_long_fitting_process()函数调用另一个函数，该函数迭代地更新matplotlib图中的线。所以 do_long_fitting_process() 需要对Special_Tab属性进行一些访问才能更改它们并将更新显示到 GUI。
我已经尝试通过将do_long_fitting_process()函数推送到一个全局函数并调用它来做到这一点：
[代码] def open_tabs(self): for i in range(0, 10): ... self.tabs_list.append(new_tab)
consumer, producer = mp.Pipe()
process = mp.Process(target=process_on_special_object, args=(producer,))
process.start()
while(True):
message = consumer.recv()
if message == 'done':
break
tab.update_GUI(message[0], message[1])
process_list[-1].join()
[/code] 我update_GUI()通过 a传递数据的地方mp.Pipe()，但是一旦我启动进程，窗口就会转到“无响应”。