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First the rendering.
# -*- coding: utf-8 -*-
import numpy as np
import tensorflow as tf
from import Path
from import PathPatch
import as plt
import matplotlib
from import FuncAnimation
import matplotlib as mpl
import datetime
import time
import re
import
np.set_printoptions(suppress=True)
['-serif'] = ['SimHei'] # Specify the default font, SimHei, to be bold
['axes.unicode_minus'] = False # Used to properly display negative
import requests
import re
import hashlib
#test data osm's point and line data
#test host 8G 4-core 1T mechanical disk
#mysql 5.7.23
#postgresql 12
#dameng 7
#oracle 19c 19.3
#Read Efficiency Point, Line, Plane
r = [ [24714, 21748, 19298], #Oracle
[44127, 45943, 42199], #GDB
#[0, 0, 0], #SQLITE
# [0, 0, 0], #MySQL
[352641, 352739, 304189], #SQLITE
[213550, 218095, 212749], #MySQL
[36556, 22172, 12741], #PostgreSQL
[52749, 46292, 20040], #dameng
[25111, 12000, 11000], #ArcGIS_GDB
[10102, 9003, 7003] #ArcGIS_ORACLE
]
# Write efficiency
w = [ [190, 675, 40], #Oracle
[15815, 9820, 11892], #GDB
[94547, 81847, 57235], #SQLITE
# [0, 0, 0], #SQLITE
[502, 662, 403], #MySQL
#[0, 0, 0], #MySQL
[1631, 1599, 1502], #PostgreSQL
[2004, 1849, 1524], #dameng
[10111, 8000, 5600] , #ArcGIS_GDB
[1100, 1000, 900] #ArcGIS_ORACLE
]
# This is the bar chart x-axis label
ysr = ['Oracle','GDB','SQLITE','MySQL','PostgreSQL','DAMENG','ArcGIS_GDB','ArcGIS_ORACLE']
def DrawGeoDtaabse(rcount, wcount, y):
#First row, first column, 2,1 for 2 rows and 1 column.
ax1 = (2,1,1)
# Second row, first column of graphics #
ax3 = (2,1,2)
# Default time format
(ax1)
("",color = 'r') #X-axis labels
("Article/s",color = 'r') #Y-axis labels
#(True) Show Grid
#().autofmt_xdate() display time
() # Show legend
("[Reading] efficiency") # Title
x1 = [1,5,9,13,17,21,25,29] # x-axis point efficiency position
x2 = [i + 1 for i in x1] # x-axis line efficiency position
x3 = [i + 2 for i in x1] # x-axis face efficiency position
y1 = [i[0] for i in rcount] # y-axis point efficiency position
y2 = [i[1] for i in rcount] # y-axis line efficiency position
y3 = [i[2] for i in rcount] # y-axis face efficiency position
#Placeholder to avoid loss of data source labels
y0 = ["","","","","","","",""]
(x1, y1, alpha=0.7, width=1, color='r',label="Point.", tick_label=y0)
(x3, y3, alpha=0.7, width=1, color='b',label="Face.", tick_label=y0)
(x2, y2, alpha=0.7, width=1, color='g',label="Line.", tick_label=y)
#The read efficiency of the first line is plotted, and the write efficiency of the second line is repeated.
(ax3)
("Data source",color = 'r') #X-axis labels
("Article/s",color = 'r') #Y-axis labels
#(True)
() # Show legend
("[Write] efficiency") # Figure Title
y1 = [i[0] for i in wcount]
y2 = [i[1] for i in wcount]
y3 = [i[2] for i in wcount]
y0 = ["","","","","","","",""]
(x1, y1, alpha=0.7, width=0.6, color='r',label="Point.", tick_label=y0)
(x3, y3, alpha=0.7, width=0.6, color='b',label="Face.", tick_label=y0)
(x2, y2, alpha=0.7, width=0.6, color='g',label="Line.", tick_label=y)
()
()
DrawGeoDtaabse(r,w,ysr)All of the above code was tested successfully on python 3.6.4
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