如何在matplotlib表中设置列的背景色 [英] How to set background color of a column in a matplotlib table

问题描述

我在一个目录中有多个 .txt 文件，例如 d:\memdump\0.txt,1.txt,...10.txt 示例文本文件如下:

 应用程序内存使用率(kB):正常运行时间:7857410实时时间:7857410** pid 23875 [com.example.twolibs] 中的 MEMINFO **共享私有堆 堆 堆Pss 脏脏大小分配免费------ ------ ------ ------ ------ ------ ------本机 0 0 0 13504 10836 459达尔维克6806 7740 6580 24076 18523 5553堆栈 80 0 80光标0 0 0阿什姆 0 0 0其他开发人员 14741 836 1028.so mmap 1367 448 1028.jar mmap 0 0 0.apk mmap 225 0 0.ttf mmap 0 0 0.dex mmap 1225 340 16其他mmap 5 8 4未知3473 564 3432总计 27922 9936 12168 37580 29359 6012对象浏览次数:62 ViewRootImpl:2AppContexts:5活动:2资产:3 资产管理器:3本地绑定器:9 代理绑定器:18死亡收件人:0OpenSSL套接字:0的SQLMEMORY_USED:0PAGECACHE_OVERFLOW: 0 MALLOC_SIZE: 0

我必须解析这些文件以获取PID值，本机堆大小，本机堆Alloc大小，Dalvik堆大小，Dalvik堆Alloc大小，并绘制具有以下堆大小的图形

我正在使用以下代码来实现这一目标:

  import glob导入操作系统汇入将numpy导入为np导入matplotlib.pyplot作为pltos.chdir("D:\ Python_Trainings \ MemInfo \ Data")pid_arr = []native_heapsize_arr = []dalvik_heapsize_arr = []native_heapalloc_arr = []dalvik_heapalloc_arr = []pkg_name_arr = []#解析内存转储文件的方法def parse_dumpFiles():对于glob.glob("*.txt")中的data_file:尝试:fo = 打开(数据文件，r")对于线在 fo:pid_match = re.search('pid\s+(\d+)',line)pkg_name_match = re.search("\[(\w+\.+\w+\.+\w+)\]",line)native_heapsize_match = re.search('(Native+\s+\d+\s+\d+\s+\d+\s+)+(\d+)',line)dalvik_heapsize_match = re.search('(Dalvik+\s+\d+\s+\d+\s+\d+\s+)+(\d+)',line)native_heapalloc_match = re.search('(本机+ \ s + \ d + \ s + \ d + \ s + \ d + \ s + \ d + \ s +)+(\ d +)'，行)dalvik_heapalloc_match = re.search('(Dalvik+\s+\d+\s+\d+\s+\d+\s+\d+\s+)+(\d+)',line)如果pid_match:pid_arr.append(int(pid_match.group(1)))如果 native_heapsize_match:native_heapsize_arr.append(native_heapsize_match.group(2))如果dalvik_heapsize_match:dalvik_heapsize_arr.append(dalvik_heapsize_match.group(2))如果 native_heapalloc_match:native_heapalloc_arr.append(native_heapalloc_match.group(2))如果 dalvik_heapalloc_match:dalvik_heapalloc_arr.append(dalvik_heapalloc_match.group(2))如果 pkg_name_match:如果 pkg_name_match.group(1) 不在 pkg_name_arr 中:pkg_name_arr.append(pkg_name_match.group(1))除了 IOError:打印错误:找不到文件或读取数据"最后:关闭()#end of parse_dumpFiles()方法#从内存转储绘图的方法def plt_MemDump(pid_arr, native_heapsize_arr, dalvik_heapsize_arr, native_heapalloc_arr, dalvik_heapalloc_arr, pkg_name_arr):#创建一个图形和带有表空间的轴无花果= plt.figure()ax = plt.axes([0.2, 0.2, 0.7, 0.7])#将行和列的标签创建为元组colLabels = ('0','10', '20', '30', '40', '50', '60', '70', '80', '90', '100')rowLabels = ('Native Heap Size','Native Heap Allocated','Dalvik Heap Size','Dalvik Heap Allocated','PID')#将表格数据作为numpy数组tableData = np.asarray([native_heapsize_arr，dalvik_heapsize_arr，native_heapalloc_arr，dalvik_heapalloc_arr，pid_arr]，dtype = int)#将当前颜色周期作为列表获取，然后将颜色周期重置为开始颜色 = []为真:colors.append(ax._get_lines.color_cycle.next())如果colors [0] == colors [-1]并且len(colors)> 1:颜色.pop(-1)休息对于我在xrange(len(colors)-1)中:ax._get_lines.color_cycle.next()#显示表格the_table = plt.table(cellText = tableData，rowLabels = rowLabels，rowColours = colors，colLabels = colLabels，loc ='bottom')#制作一些线图xAxis_val = [0,10,20,30,40,50,60,70,80,90,100]ax.plot(xAxis_val,native_heapsize_arr, linewidth=2.5, marker="o", label="Native Heap Size")ax.plot(xAxis_val，dalvik_heapsize_arr，linewidth = 2.5，marker ="D"，label ="Dalvik堆大小")ax.plot(xAxis_val，native_heapalloc_arr，linewidth = 2.5，marker ="^"，label =已分配本地堆")ax.plot(xAxis_val，dalvik_heapalloc_arr，linewidth = 2.5，marker ="h"，label ="Dalvik堆已分配")#显示图例plt.legend(loc='右上角', fontsize=10)#设置PID与第一个PID不同的列颜色c = the_table.get_celld()[(5,3)]c.set_color('r')i = 0当 i<=10 时:c=the_table.get_celld()[(5,i)]if(c.get_text().get_text()!=((the_table.get_celld()[(5,0)]).get_text().get_text())):c.set_color('r')(the_table.get_celld()[(4，i)]).set_color('r')(the_table.get_celld()[(3,i)]).set_color('r')(the_table.get_celld()[(2，i)]).set_color('r')(the_table.get_celld()[(1，i)]).set_color('r')我+=1#关闭x轴刻度线并显示绘图plt.xticks([])#配置Y轴ylim(0,60000)plt.yticks([10000,20000,30000,40000,50000,60000])plt.grid(真)#设置绘图窗口标题的名称fig.canvas.set_window_title(pkg_name_arr [0] +-内存转储图")#设置图的标题plt.title(pkg_name_arr[0],color='r',fontsize=20)#设置Y标签plt.ylabel('堆大小', fontsize=14, color='r')#显示情节plt.show()#plt_MemDump() 方法结束parse_dumpFiles()plt_MemDump(pid_arr, native_heapsize_arr, dalvik_heapsize_arr, native_heapalloc_arr, dalvik_heapalloc_arr, pkg_name_arr)

现在，我想用一些颜色标记表的列，其中PID值与第一个PID值不同(例如，列30,60& 100).

有人能帮我实现这个目标吗?

解决方案

matplotlib.pyplot.table 已经为您提供了执行所需功能的工具:

• cellColours(与cellText形状相同):让你为每个单元格选择颜色
• colColours:用作 rowColours，但用于列标题

如果您希望一列中的所有单元格都具有特定颜色，您可以执行以下操作

cellcolours = np.empty_like(tableData, dtype='object')对于我来说，cl在enumerate(colLabels)中:如果 cl >50:cellcolors[:,i] = 'r'

，然后调用 cellColours = cellcolours 来调用 plt.table (尽管我建议您更改为 ax.table )./p>

如果您还想要彩色列标题，只需执行上述操作

<小时>

如果您希望能够在创建表格后更改单元格，table.get_celld() 返回一个单元格字典，其键是每个单元格位置的元组，例如:

{(0, 0): , # 这些是列标题(0, 1): ,(0，2):< matplotlib.table.Cell at 0x5d75450> ;,(0，3):< matplotlib.table.Cell at 0x5d75610> ;,[...](1, -1): , # 这是一个行标题(1, 0): , # 这是一个单元格(1，1):< matxlotlib.table.Cell at 0x5d74150> ;,(1，2):< matplotlib.table.Cell at 0x5d74290> ;,(1，3):< matplotlib.table.Cell at 0x5d743d0> ;,[...](2, -1): , # 这是一个行标题[...] }

您可以使用元组访问每个单元格，例如

c=table.get_celld()[(1,1)]

您可以使用 c.set_color()设置单元格颜色，并使用 c.get_text().get_text()检查单元格中的文本(第一个get_text 返回一个 Text 实例，第二个是其中的字符串)

I have multile .txt files in a directory, say, d:\memdump\0.txt,1.txt,...10.txt sample text file is given below:

 Applications Memory Usage (kB):
 Uptime: 7857410 Realtime: 7857410
** MEMINFO in pid 23875 [com.example.twolibs] **
                 Shared  Private     Heap     Heap     Heap
               Pss    Dirty     Dirty     Size    Alloc     Free
              ------   ------   ------   ------   ------   ------
  Native        0        0        0       13504    10836      459
  Dalvik     6806     7740     6580       24076    18523     5553
  Stack       80        0       80                           
  Cursor        0        0        0                           
  Ashmem        0        0        0                           
  Other dev    14741      836     1028                           
 .so mmap     1367      448     1028                           
 .jar mmap        0        0        0                           
 .apk mmap      225        0        0                           
 .ttf mmap        0        0        0                           
 .dex mmap     1225      340       16                           
  Other mmap        5        8        4                           
  Unknown     3473      564     3432                           
  TOTAL    27922     9936    12168    37580    29359     6012
  Objects
       Views:       62         ViewRootImpl:        2
  AppContexts:        5           Activities:        2
      Assets:        3        AssetManagers:        3
  Local Binders:        9        Proxy Binders:       18
  Death Recipients:        0
  OpenSSL Sockets:        0
  SQL
    MEMORY_USED:        0
   PAGECACHE_OVERFLOW:        0          MALLOC_SIZE:        0

I have to parse these files to get values of PID, Native Heap Size, Native Heap Alloc size, Dalvik Heap Size, Dalvik Heap Alloc size and plot a graph with these heap sizes as below

I am using the following code to achieve this:

import glob
import os
import re
import numpy as np
import matplotlib.pyplot as plt

os.chdir("D:\Python_Trainings\MemInfo\Data")
pid_arr = []
native_heapsize_arr = []
dalvik_heapsize_arr = []
native_heapalloc_arr = []
dalvik_heapalloc_arr = []
pkg_name_arr = []

#Method to parse the memory dump files
def parse_dumpFiles():
  for data_file in glob.glob("*.txt"):
    try:
      fo = open(data_file,"r")
      for line in fo:
        pid_match = re.search('pid\s+(\d+)',line)
        pkg_name_match = re.search("\[(\w+\.+\w+\.+\w+)\]",line)
        native_heapsize_match = re.search('(Native+\s+\d+\s+\d+\s+\d+\s+)+(\d+)',line)
        dalvik_heapsize_match = re.search('(Dalvik+\s+\d+\s+\d+\s+\d+\s+)+(\d+)',line)
        native_heapalloc_match = re.search('(Native+\s+\d+\s+\d+\s+\d+\s+\d+\s+)+(\d+)',line)
        dalvik_heapalloc_match = re.search('(Dalvik+\s+\d+\s+\d+\s+\d+\s+\d+\s+)+(\d+)',line)
        if pid_match:
          pid_arr.append(int(pid_match.group(1)))
        if native_heapsize_match:
          native_heapsize_arr.append(native_heapsize_match.group(2))
        if dalvik_heapsize_match:
          dalvik_heapsize_arr.append(dalvik_heapsize_match.group(2))
        if native_heapalloc_match:
          native_heapalloc_arr.append(native_heapalloc_match.group(2))
        if dalvik_heapalloc_match:
          dalvik_heapalloc_arr.append(dalvik_heapalloc_match.group(2))
        if pkg_name_match:
          if pkg_name_match.group(1) not in pkg_name_arr:
            pkg_name_arr.append(pkg_name_match.group(1))

    except IOError:
      print "Error: can\'t find file or read data"
    finally:
      fo.close()
#end of parse_dumpFiles() Method

#Method to plot from Memory Dumps
def plt_MemDump(pid_arr, native_heapsize_arr, dalvik_heapsize_arr,   native_heapalloc_arr, dalvik_heapalloc_arr, pkg_name_arr):

#Create a figure and axes with room for the table
  fig = plt.figure()
  ax = plt.axes([0.2, 0.2, 0.7, 0.7])

#Create labels for the rows and columns as tuples
  colLabels = ('0','10', '20', '30', '40', '50', '60', '70', '80', '90', '100')
  rowLabels = ('Native Heap Size','Native Heap Allocated','Dalvik Heap Size','Dalvik Heap Allocated','PID')

#Table data as a numpy array
  tableData = np.asarray([native_heapsize_arr,dalvik_heapsize_arr,native_heapalloc_arr,dalvik_heapalloc_arr,pid_arr],dtype=int)

#Get the current color cycle as a list, then reset the cycle to be at the beginning
  colors = []     
  while True:
    colors.append(ax._get_lines.color_cycle.next())
    if colors[0] == colors[-1] and len(colors)>1:
      colors.pop(-1)
      break

  for i in xrange(len(colors)-1):
    ax._get_lines.color_cycle.next()

#Show the table
  the_table = plt.table(cellText=tableData, rowLabels=rowLabels, rowColours=colors,    colLabels=colLabels, loc='bottom')

#Make some line plots
  xAxis_val = [0,10,20,30,40,50,60,70,80,90,100]
  ax.plot(xAxis_val,native_heapsize_arr, linewidth=2.5, marker="o", label="Native Heap Size")
  ax.plot(xAxis_val,dalvik_heapsize_arr, linewidth=2.5, marker="D", label="Dalvik Heap Size")
  ax.plot(xAxis_val,native_heapalloc_arr, linewidth=2.5, marker="^",label="Native Heap Allocated")
  ax.plot(xAxis_val,dalvik_heapalloc_arr, linewidth=2.5, marker="h", label="Dalvik Heap Allocated")

#show legend
  plt.legend(loc='upper right', fontsize=10)

#set the column color where PID is different from 1st PID 
  c=the_table.get_celld()[(5,3)]
  c.set_color('r')
  i=0
  while i<=10:
    c=the_table.get_celld()[(5,i)]
if(c.get_text().get_text()!=((the_table.get_celld()[(5,0)]).get_text().get_text())):
  c.set_color('r')
  (the_table.get_celld()[(4,i)]).set_color('r')
  (the_table.get_celld()[(3,i)]).set_color('r')
  (the_table.get_celld()[(2,i)]).set_color('r')
  (the_table.get_celld()[(1,i)]).set_color('r')
  i+=1

#Turn off x-axis ticks and show the plot              
  plt.xticks([])

#Configure Y axis
  plt.ylim(0,60000)
  plt.yticks([10000,20000,30000,40000,50000,60000])
  plt.grid(True)

#Setting the name of the window title of the plot  
  fig.canvas.set_window_title(pkg_name_arr[0] + "- Memory Dump Plot")

#Setting the Title of the plot
  plt.title(pkg_name_arr[0],color='r',fontsize=20)

#Setting Y Label 
  plt.ylabel('Heap Size', fontsize=14, color='r')

#show plot
  plt.show()
#end of plt_MemDump() Method

parse_dumpFiles()
plt_MemDump(pid_arr, native_heapsize_arr, dalvik_heapsize_arr, native_heapalloc_arr, dalvik_heapalloc_arr, pkg_name_arr)

Now I want to mark the columns of the table with some color where PID value differ with 1st PID value.(eg,column 30,60 & 100).

Can anybody help me to achieve this?

解决方案

matplotlib.pyplot.table gives you already the tool to do what you need:

• cellColours (of the same shape of cellText): let you chose the colour for each cell
• colColours: works as rowColours, but for the column headers

If you want all the cells in a column to have a specific colour you can do something like this

cellcolours = np.empty_like(tableData, dtype='object')
for i, cl in enumerate(colLabels):
    if cl > 50:
        cellcolours[:,i] = 'r'

and then call plt.table (although I suggest you to change to ax.table) adding the cellColours=cellcolours keyword.

If you want also the column headers coloured, just do something like above

---

If you want to be able to change the cells after you create the table, table.get_celld() returns a dictionary of cells, whose keys are tuples of the position of each cell, eg:

{(0, 0): <matplotlib.table.Cell at 0x5d750d0>,  # these are column headers
 (0, 1): <matplotlib.table.Cell at 0x5d75290>,
 (0, 2): <matplotlib.table.Cell at 0x5d75450>,
 (0, 3): <matplotlib.table.Cell at 0x5d75610>,
 [...]
 (1, -1): <matplotlib.table.Cell at 0x5d757d0>, # this is a row header
 (1, 0): <matplotlib.table.Cell at 0x5a58110>,  # this is a cell
 (1, 1): <matplotlib.table.Cell at 0x5d74150>,
 (1, 2): <matplotlib.table.Cell at 0x5d74290>,
 (1, 3): <matplotlib.table.Cell at 0x5d743d0>,
 [...]
 (2, -1): <matplotlib.table.Cell at 0x5d75990>, # this is a row header
 [...] }

You can access each cell using the tuple, e.g.

c=table.get_celld()[(1,1)]

You can set the cell color with c.set_color() and inspect the text in the cell with c.get_text().get_text() (the first get_text returns a Text instance, the second the string in it)

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