问题描述
我正在用Tkinter和ttk构建一个GUI，并使用matplotlib来创建交互式绘图-就像数百万其他人一样.即使到目前为止我所遇到的大多数问题都得到了充分的记录，但这种情况似乎很少见:
I'm building a GUI with Tkinter and ttk and using matplotlib in order to creat interactive plots - again, like millions other people do.Even though most problems I encountered so far are well documented, this one seems rare:
在3d中绘制并随后使用set_lim()命令调整轴比例时，绘制的线超出了看起来不太好的坐标系.另外，我对看起来有点小的框架也不满意.这是一个示例:
When plotting in 3d and adjusting the axis scale with set_lim() commands afterwards, the plotted line exceeds the coordinate-system which looks not good. Also, I'm not happy with the frame that seems to be a little to small. Here is an example:
# Missmatch.py
"""Graphical User Interface for plotting the results
calculated in the script in Octave"""
# importing libraries
import matplotlib, ttk, threading
matplotlib.use('TkAgg')
import numpy as nm
import scipy as sc
import pylab as pl
import decimal as dc
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2TkAgg
from matplotlib.figure import Figure
from mpl_toolkits.mplot3d import Axes3D
from oct2py import octave as oc
import Tkinter as tki
class CS:
"""CS - Controlset. This part creates the GUI with all important
Elements. Major changes and calculations will be executed
in the Calculation-Class in a seperate thread. This prevents the
GUI from hanging"""
def __init__(self,parent):
"""Building the main GUI"""
self.ThisParent=parent
### Entire Window
# Mainframe that contains everything.
self.main=tki.Frame(parent)
# Pack manager to expand the mainframe as the windowsize changes.
self.main.pack(fill=tki.BOTH, expand=tki.YES)
# Configure the grid of the mainframe so that only the top left
# cell grows if the users expands the window.
self.main.grid_rowconfigure(0, weight=1)
self.main.grid_rowconfigure(1, weight=1)
### Canvas for drawings
# Creating a figure of desired size
self.f = Figure(figsize=(6,6), dpi=100)
# Creating a canvas that lives inside the figure
self.Paper=FigureCanvasTkAgg(self.f, master=self.main)
# Making the canvas's drawings visible (updating)
self.Paper.show()
# positioning the canvas
self.Paper.get_tk_widget().grid(row=0,rowspan=3, column=0, sticky='NSWE')
# creating a toolbarframe for options regarding the plots
self.toolbarframe=tki.Frame(self.main)
self.toolbarframe.grid(row=3, column=0, sticky='NWE')
# Creating a toolbar for saving, zooming etc. (matplotlib standard)
self.toolbar = NavigationToolbar2TkAgg(self.Paper, self.toolbarframe)
self.toolbar.grid(row=0,column=0, sticky='NWE')
# setting the standard option on zoom
self.toolbar.zoom()
### Axis configuration toolbar
# A frame containing the axis config-menu
self.axisscaleframe=tki.Frame(self.main)
self.axisscaleframe.grid(row=5, column=0, sticky='SNEW')
# In that Frame, some Entry-boxes to specify scale
self.xaxisscalef=ttk.Entry(self.axisscaleframe, width=10)
self.xaxisscalef.insert(0,0)
self.xaxisscalet=ttk.Entry(self.axisscaleframe, width=10)
self.xaxisscalet.insert(0,15)
self.yaxisscalef=ttk.Entry(self.axisscaleframe, width=10)
self.yaxisscalef.insert(0,0)
self.yaxisscalet=ttk.Entry(self.axisscaleframe, width=10)
self.yaxisscalet.insert(0,15)
self.zaxisscalef=ttk.Entry(self.axisscaleframe, width=10)
self.zaxisscalef.insert(0,0)
self.zaxisscalet=ttk.Entry(self.axisscaleframe, width=10)
self.zaxisscalet.insert(0,15)
# And some Labels so we know what the boxes are for
self.xaxlab=ttk.Label(self.axisscaleframe, text='X-Axis', width=10)
self.yaxlab=ttk.Label(self.axisscaleframe, text='Y-Axis', width=10)
self.zaxlab=ttk.Label(self.axisscaleframe, text='Z-Axis', width=10)
self.axinfolab=ttk.Label(self.axisscaleframe, text='Adjust axis scale:')
# And a Button to validate the desired configuration
self.scaleset=ttk.Button(self.axisscaleframe, text='Set', command=self.SetAxis2)
self.scaleset.bind('<Return>', self.SetAxis)
# Let's organize all this in the axisscaleframe-grid
self.axinfolab.grid(row=0, column=0, sticky='W')
self.xaxlab.grid(row=1, column=0, sticky='W')
self.yaxlab.grid(row=2, column=0, sticky='W')
self.zaxlab.grid(row=3, column=0, sticky='W')
self.xaxisscalef.grid(row=1,column=1, sticky='W')
self.yaxisscalef.grid(row=2,column=1, sticky='W')
self.xaxisscalet.grid(row=1,column=2, sticky='W')
self.yaxisscalet.grid(row=2,column=2, sticky='W')
self.zaxisscalef.grid(row=3,column=1,sticky='W')
self.zaxisscalet.grid(row=3,column=2,sticky='W')
self.scaleset.grid(row=3,column=3,sticky='E')
def SetAxis(self,event):
self.SetAxis2()
def SetAxis2(self):
self.x1=float(self.xaxisscalef.get())
self.x2=float(self.xaxisscalet.get())
self.y1=float(self.yaxisscalef.get())
self.y2=float(self.yaxisscalet.get())
self.z1=float(self.zaxisscalef.get())
self.z2=float(self.zaxisscalet.get())
self.a.set_xlim(self.x1, self.x2)
self.a.set_ylim(self.y1, self.y2)
self.a.set_zlim(self.z1, self.z2)
self.Paper.show()
print "Set axis"
class Calculate3D(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
self.x=range(100)
self.y=range(100)
self.z=range(100)
print 'Done!'
controlset.a = controlset.f.add_subplot(111, projection='3d')
controlset.a.clear()
controlset.a.plot(self.x,self.y,self.z)
controlset.a.mouse_init()
controlset.a.set_xlabel('X')
controlset.a.set_ylabel('Y')
controlset.a.set_zlabel('Z')
controlset.a.set_title('Title')
controlset.Paper.show()
return
mainw=tki.Tk()
mainw.title("Example")
mainw.geometry('+10+10')
controlset=CS(mainw)
#for this example code, we run our Calculate3D class automatically
CL=Calculate3D()
CL.run()
mainw.mainloop()
只需运行代码，然后单击设置"按钮即可.这是我的问题.
Just run the code, and hit the "SET" Button. There is my problem.
编辑:添加了屏幕截图:
Edit: Added Screenshot:
推荐答案
这里的问题是mplot3d没有OpenGL后端.因此，用于显示数据的计算基于2d.我在此处找到了相同的问题，并在此处.即使在我看来，这种解决方法也不是最好的，因为它取决于您数据的分辨率.
The Problem here is, that mplot3d has no OpenGL backend. The calculations for displaying the data are thus based on 2d.I found the same issue here and a workaround here. Even though the workaround is not the best in my opinion because it depends on the resolution of your data.
无论如何，我都遵循了第二个链接.因此，我现在要做的是复制数组，并将所需缩放以上和之下的所有值都设置为NaN.在绘制这些图形时，将在数据点超出所需限制的地方切断线条.
I followed the second link anyway. So, what I'm doing now is copying the array and setting all the values above and under my desired scale to NaN. When plotting those, the lines will be cut off where the datapoints exceed the desired limit.
def SetAxis2(self):
self.dummyx=CL.x*1
self.dummyy=CL.y*1
self.dummyz=CL.z*1
#clipping manually
for i in nm.arange(len(self.dummyx)):
if self.dummyx[i] < self.x1:
self.dummyx[i] = nm.NaN
else:
pass
for i in nm.arange(len(self.dummyy)):
if self.dummyy[i] < self.y1:
self.dummyy[i] = nm.NaN
else:
pass
for i in nm.arange(len(self.dummyz)):
if self.dummyz[i] < self.z1:
self.dummyz[i] = nm.NaN
else:
pass
controlset.a.plot(self.dummyx,\
self.dummyy,\
self.dummyz)
self.a.set_xlim3d(self.x1, self.x2)
self.a.set_ylim3d(self.y1, self.y2)
self.a.set_zlim3d(self.z1, self.z2)
如果现在将比例尺设置为0到10，并且有六个数据点:[-1, 3 4 12 5 1]该行将从3变为4，从5变为1，因为-1和12将设置为NaN.关于该问题的改进将是不错的. Mayavi 可能更好，但是我没有尝试过，因为我想坚持与matplotlib.
If now your scale is set from 0 to 10 and you have six datapoints: [-1, 3 4 12 5 1] The line will go from 3 to 4 and 5 to 1 because -1 and 12 will be set to NaN. An improvement regarding that problem would be good.Mayavi might be better, but I haven't tried this as I wanted to stick with matplotlib.
这篇关于matplotlib中的set_xlim，set_ylim，set_zlim命令无法裁剪显示的数据的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！