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investigation and check setFind and UnionCode var iJK: Longint; Father:Array[1..50000]of Longint; Used:Array[1..50000]OfBoolean; NM: Longint; XY: Longint; Ans: Longint; C: Longint;functionFind(x: Longint): Longint;BeginIf X=father[x]ThenExit(x)ElseBegin Father[x]:=Find(Father[x]);Exit(Father[x]);End;End;ProcedureUnion(xY: Longint);Begin Father[Find(x)]:=Find(Father[Y]);End;Begin C:=0;Readln(nM);While(n0)and(M0)DoBeginInc(c);For I:=1to nDo father[I]:=i;For I:=1to MDoBeginReadln(xY);IfFin
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The morning to attend the daughter Kindergarten Christmas ball, every year, now is the third game. Watching her dance when in fact not excited, but is to see a bunch of ignorant baby in the stage at a loss of the lovely appearance, tears suddenly flow down. I think it's going to be too fast.One girl said that 2015 was the year I had harvested. But I think carefully, in fact, there is nothing, most of the time is mixed and selves here. Think about doing something seriously, but once you walk in y
, but what use? I always like to talk about this sentence, what is the use? But I just like to kill time.Recall more, people say the environment affects people, but some people do not know how to the whole.Anyway, the weekend is my time, want to how the whole, to say how the work, how to improve, or do not want to go to the song, because do not come.Do you really need to be a professional programmer to write good code?I do not think so, anyway should do, the work of some arrangements can be done
New Year's Eve was originally just a common day of the year. On this day, you can reunite with your family and get together with your lover. On this day, when the lights were on, the streets were full of pedestrians, regardless of the city or rural areas. They were warm and sweet. People who have been busy for a year feel happy, happy, and warm at this moment ...... On the occasion of the New Year, I wish you all, your parents, colleagues, and leader
concerned about those indicators (including SQL Server and Windows), how to develop performance baselines, which monitoring software you have used;26. Database migration steps; rebuild a larger set of test systems (minimum of 10 db instances), if the original DB data volume is not large, but DB is more, the new system data are not needed, how to quickly achieve;27. Create cluster brief steps, require a minimum number of IP, what services need to be installed, what fixed disks are required, how
, etc.) migrating to another new server all possible methods and steps to describe the pros and cons of each; 24. What basic maintenance work do you do for the database, and what do you do with that? 25. If you have 10 times times the number and traffic of existing SQL Server servers, what are your countermeasures? 26. When maintaining a database, what tools do you use most often, what do they do, and what actions do you think that tools can greatly improve your productivity, you work for the da
, and requires as little data as possible loss, you may adopt whatMethod25. If you want to do database monitoring, you will be concerned about those indicators (including SQL Server and Windows), how to develop performance baselines, which monitoring software you have used;26. Database migration steps; rebuild a larger set of test systems (minimum of 10 db instances), if the original database volume is not large, but DB is more, the newly built system dataDo not need, how to quickly achieve;27.
the view to the underlying base table. If the SELECT statement in the view definition specifies a GROUP by clause, the key for a unique clustered index can only refer to the column specified in the GROUP by clause. The SELECT statement in the view cannot contain the following Transact-SQL syntax elements:The select list cannot specify columns using the * or table_name.* syntax. You must explicitly give the dequeue name 在创建索引视图的select语句中，不能存在重复的列名 A view cannot contain an external link or a self
Fityk is a non-linear fitting and data analysis tool. It is usually used for experimental data analysis and supports common peak functions. The interface is intuitive and supports user-defined operations, which can be optimized and automatically processed. . It can run on Linux, windows, and MacOS X. The latest version is 0.9.2. Home: http://www.unipress.waw.pl/fityk/ The important achievements made in Curve Fit
1. Polynomial-fitting function:Y= A0 + a1x + a2x^2 + ... + akx^k (where k is fit times)When the k=1 is linear fit, the k=2 is a two-time polynomial ... Three-time polynomial.2. Least squares principle matrix algorithm principle:X*a=yA= ((X ' *x)-1) *x ' *y|-X1 x1^2 ... x1^k| |y0||-X2 x2^2 ... x2^k| |a0| |y1||... | |a1| |. ||... | |. | = |. ||... | |ak| |. ||-Xn xn^2 ... xn^k| |yn|where x is the initial Vandermonde matrix, A
to make a fitting line in the WPS table: First, input the data that needs to fit straight line; Select the table data from the bottom right to the left, select the table in the Insert, and select the XY (scatter) chart with the smooth curve in the table. As shown in figure: Click the table that appears, click the first box on the right, select the trendline in the pop-up menu, and then select Linear. As shown in figure:
Linear function fitting (Y=A+BX) 1. R Run Instance The R language runs the code as follows: Green for the data to be provided, the yellow identification information is required to be saved. X Y Data1=data.frame (x=x,y=y) #数据存入数据框 #拟合线性函数 LM.DATA1 Summary (LM.DATA1) #输出拟合后信息 Call: LM (formula = data1$y ~ data1$x) Residuals: #残差分位数 (all residual values are shown here when the number of residuals is low) Min 1Q Median 3Q Max -2.0431-0.7056 0.1694 0.66
Reprinted please indicate Source Address: http://www.cnblogs.com/xbinworld/archive/2013/04/21/3034300.html Pattern Recognition and machine learning (PRML) book learning, Chapter 1.1, introduces polynomial curve fitting) The doctor is almost finished. He will graduate next year and start preparing for graduation this year. He feels that he has done a lot of research on machine learning, and his thesis has been published, but he is not systematic
Original writing. For more information, see http://blog.csdn.net/xbinworld,bincolumns. Pattern Recognition and machine learning (PRML) book learning, Chapter 1.1, introduces polynomial curve fitting) The doctor is almost finished. He will graduate next year and start preparing for graduation this year. He feels that he has done a lot of research on machine learning, and his thesis has been published, but he is not systematic. I am determined to make u
Suppose there is such a group of data, X = [4 5 6 7 8 4 8 10] '; Y = [56 56 56 56 60 60 60] ';Z = [6 6 6 9 6 19 6 6] '; The plane equation z = C + ax + by is required. You can use MATLAB's regress for plane fitting: X = [ones (SIZE (x, 1), 1) x Y];B = regress (z, X ); Solution: B = [-63.488372093023390;-1.406976744186046; 1.402325581395351]; Corresponding to the preceding C A B Draw a plane in MATLAB: Scatter3 (X, Y, Z, 'filened ')Hold onXf
(3600,'angle:'+ Angle1 +'°,'+ Angle2 +'°,'+ Angle3 +'°','Image', -, -,'Red','true')Results:Step Analysis:① image triangle is mainly composed of 3 straight lines;② threshold, skeleton extract skeleton, the skeleton (region) to Xld, the xld break split, filter XLD get 3 main xld, the 3 xld to be synthesized 3 straight lines .Effect Analysis:Although the procedure is simple, the robustness is not good. The main risk in the " screening xld get 3 main xld" This step, sometimes, it can not be accurat
Linear Fitting Using the least square method # Coding: utf-8import numpy as npimport matplotlib. pyplot as pltdots = NP. array ([[], [], [], [], []) PLT. plot ([I [0] For I in DOTS], [I [1] For I in DOTS], 'ro') PLT. axis ([0, 6, 0, 12]) def nihezhixian (K, X, B ): return K * x + bsumxy = sum ([A [0] * A [1] For a in DOTS]) # print sumxysumxx = sum ([A [0] ** 2 for a in DOTS]) print sumxxsumx = sum ([A [0] For a in DOTS]) print sumxsumy = sum ([A [1]
to fit function y = Alpha * POW (x, Beta)Input: x array, y arrayOutput: Alpha,beta, correlation coefficient R2From scipy.optimize import leastsqfrom pylab import *import numpy as Npxdata = Np.array ([4.79616, 11.63, 37.5534, 105.414] ) Ydata = Np.array ([1.33921, 0.755319, 0.34085, 0.0554339]) # Define function for calculating a power Lawpowerlaw = lambda x , Alpha, Beta:alpha * (x * * Beta) LOGX = log10 (xdata) logy = log10 (ydata) # define our (line) fitti
1. Polynomial-fittingImport Matplotlib.pyplot as PltImport NumPy as NP#潘海东, 2014/1/13x = Np.arange (1, 17, 1)y = Np.array ([4.00, 6.40, 8.00, 8.80, 9.22, 9.50, 9.70, 9.86, 10.00, 10.20, 10.32, 10.42, 10.50, 10.55, 10.58, 10.60])Z1 = Np.polyfit (x, Y, 3) #用3次多项式拟合P1 = np.poly1d (z1)Print (p1) #在屏幕上打印拟合多项式YVALS=P1 (x) #也可以使用yvals =np.polyval (z1,x)Plot1=plt.plot (x, y, ' * ', label= ' original values ')Plot2=plt.plot (x, Yvals, ' R ', label= ' polyfit values ')Plt.xlabel (' x axis ')Plt.ylabel ('
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