AX2009配置AIF WCF服务教程

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"本文档详细介绍了如何在AX2009中配置并使用AIF (Application Integration Framework) 来生成和部署WCF服务。" 在Microsoft Dynamics AX 2009中，AIF是一个关键组件，它允许系统与其他应用程序进行集成和数据交换。通过AIF，你可以创建Web服务，使得外部系统能够访问和操作AX2009中的业务数据。以下是配置AIF以生成WCF服务的详细步骤： 1. **安装AIF组件** 要安装AIF，首先需要重新运行`setup.exe`安装程序，并选择“添加或修改组件”选项。确保.NET Business Connector已经安装，因为AIF Web服务的安装需要这个前提。 2. **配置虚拟目录** 安装过程中，会提示你为虚拟目录提供默认名称，记住这个名字以备后续使用。虚拟目录用于存放AIF Web服务的相关文件。 3. **创建AIF网站** 在AX2009中，进入“基本设置”->“设置”->“应用程序框架”->“网站”。在这里创建一个新的网站记录，指定名称和虚拟目录的共享路径。此路径应指向安装AIF后在C:\Program Files\Microsoft Dynamics AX\50下生成的AifWebServices共享文件夹。 4. **创建服务** - 新增一个类，并设置其`RunOn`属性为`Server`。这将确保服务在服务器端运行。 - 创建新的Service，定义其命名空间为`http://schemas.microsoft.com/dynamics/2008/01/services`，并关联新创建的类。随后，添加Operations以定义服务的行为。 5. **启用和生成服务** 在“基本设置”->“设置”->“应用程序框架”->“服务”中，刷新列表，找到刚刚创建的服务，勾选“已启用”，然后点击“生成”按钮。这将创建WCF服务的元数据，并使其可供外部调用。 6. **测试WCF服务** 使用IIS管理器，找到Default Website下的Microsoft Dynamics AX Aif50站点，可以查看生成的WCF服务。通过发送请求到这些服务，你可以测试它们是否正常工作。 配置完成后，外部系统可以通过WCF服务与AX2009进行交互，例如，进行数据导入导出、业务流程自动化等。AIF提供了丰富的接口和工具，使得集成过程更加灵活和高效。注意，为了确保安全，你可能还需要配置身份验证和权限，以限制对AX2009数据的访问。 在实际操作中，可能还会遇到其他问题，如IIS配置、防火墙设置、错误调试等。因此，熟悉AX2009的错误日志和调试工具至关重要，它们能帮助你快速定位并解决问题。同时，遵循最佳实践，定期更新和维护AIF配置，以确保系统的稳定性和安全性。

Microsoft Dynamics AX2009

2014-11-24 上传
Microsoft Dynamics AX2009开发笔记

AX2009 LICENSE

2010-05-15 上传
AX2009 LICENSE en_dynamics_ax_2009_msdn_license_file_x86

BURNINTEST--硬件检测工具

2015-05-12 上传
- Corrected a problem where the loopback sound test could run out of memory if run for several days. Release 5.3 build 1013 WIN32 release 31 December 2007 - Improved the reporting of ...

mu = [14, 23, 22] sigma = [2, 3, 4] tips = ['design', 'build', 'test'] figureIndex = 0 fig = plt.figure(figureIndex, figsize=(10, 8)) color = ['r', 'g', 'b'] ax = fig.add_subplot(111) for i in range(3): x = np.linspace(mu[i] - 3*sigma[i], mu[i] + 3*sigma[i], 100) y_sig = np.exp(-(x - mu[i])**2/(2*sigma[i]**2))/(math.sqrt(2*math.pi)) ax.plot(x, y_sig, color[i], label=tips[i]) ax.legend(loc='best', frameon=False) ax.set_xlabel('# of days') ax.set_ylabel('probability') plt.grid(True) plt.show() size = 100000 samples = [np.random.normal(mu[i], sigma[i], size) for i in range(3)] data = np.zeros(len(samples[1])) for i in range(len(samples[1])): for j in range(3): data[i] += samples[j][i] data[i] = int(data[i]) a, b = count(data) pdf = [x/size for x in b] cdf = np.zeros(len(a)) for i in range(len(a)): if i > 0: cdf[i] += cdf[i - 1] cdf = cdf/size figureIndex += 1 fig = plt.figure(figureIndex, figsize=(10, 8)) ax = fig.add_subplot(211) ax.bar(a, height=pdf, color='blue', edgecolor='white', label='MC PDF') ax.plot(a, pdf) ax.legend(loc='best', frameon=False) ax.set_xlabel('# of days for project') ax.set_ylabel('probability') ax.set_title('Monte Carlo Simulation') ax = fig.add_subplot(212) ax.plot(a, cdf) ax.legend(loc='best', frameon=False) ax.set_xlabel('# of days for project') ax.set_ylabel('probability') ax.grid(True) plt.show()

2023-05-18 上传
这段代码实现了蒙特卡罗模拟的概率分布和累积分布函数的绘制。具体来说，代码首先定义了三个平均值 mu 和标准差 sigma，以及对应的项目阶段 tips。然后通过 np.linspace 函数生成一组数据 x，计算出正态分布的概率...

画出下列盒式图D loop while a if b>0 then C1 else end if case d of case d1 :D1 case d2 :D2 default :D3 end case end loop E

2024-10-11 上传
if d == 'd1': data = data_D1 elif d == 'd2': data = data_D2 else: # 当d等于'default' data = data_D3 ``` 3. **计算并绘制盒式图**： 可以使用Python中的matplotlib库来绘制： ```python import ...

1. 简答题 The time stamp of a MS-DOS file directory entry uses bits 0 through 4 for the number of 2-second increments, bits 5 through 10 for the minutes, and bits 11 through 15 for the hours (24-hour clock). For example, the following binary value indicates a time of 02:16:14, in hh:mm:ss format: 00010 010000 00111 Write a procedure named ShowFileTime that receives a binary file time value in the AX register and displays the time in hh:mm:ss format. Test the procedure in a simple program. Submit your code and the screenshot of the input/output of your test program in the consoler.

2023-05-22 上传
Receives a binary file time value in the AX register and displays the time in hh:mm:ss format. ShowFileTime PROC PUSH AX PUSH BX PUSH CX PUSH DX ; Extracting time values from AX register MOV...

. The User Info field is addressed to a non-AP STA if the AID12 subfield is equal to the 12 LSBs of the AID of the STA and the MU-RTS Trigger frame is sent by the AP with which the non-AP STA is associated or by the AP corresponding to the transmitted BSSID if the non-AP STA is associated with an AP corresponding to a nontransmitted BSSID and has indicated support for receiving Control frames with TA field set to the transmitted BSSID by setting the Rx Control Frame To MultiBSS subfield to 1 in the HE Capabilities element that the non-AP STA transmits.这段802.11ax协议是什么意思

2023-06-03 上传
这段802.11ax协议描述了MU-RTS触发帧中的User Info字段的寻址方式。如果AID12子字段等于STA的AID的12个最低有效位，并且MU-RTS触发帧由非-AP STA关联的AP或与传输BSSID对应的AP发送，而该非-AP STA已经表明支持接收...

function [mag,ax,ay, or] = Canny(im, sigma) % Magic numbers GaussianDieOff = .0001; % Design the filters - a gaussian and its derivative pw = 1:30; % possible widths ssq = sigma^2; width = find(exp(-(pw.*pw)/(2*ssq))>GaussianDieOff,1,'last'); if isempty(width) width = 1; % the user entered a really small sigma end gau=fspecial('gaussian',2*width+1,1); % Find the directional derivative of 2D Gaussian (along X-axis) % Since the result is symmetric along X, we can get the derivative along % Y-axis simply by transposing the result for X direction. [x,y]=meshgrid(-width:width,-width:width); dgau2D=-x.*exp(-(x.*x+y.*y)/(2*ssq))/(pi*ssq); % Convolve the filters with the image in each direction % The canny edge detector first requires convolution with % 2D gaussian, and then with the derivitave of a gaussian. % Since gaussian filter is separable, for smoothing, we can use % two 1D convolutions in order to achieve the effect of convolving % with 2D Gaussian. We convolve along rows and then columns. %smooth the image out aSmooth=imfilter(im,gau,'conv','replicate'); % run the filter across rows aSmooth=imfilter(aSmooth,gau','conv','replicate'); % and then across columns %apply directional derivatives ax = imfilter(aSmooth, dgau2D, 'conv','replicate'); ay = imfilter(aSmooth, dgau2D', 'conv','replicate'); mag = sqrt((ax.*ax) + (ay.*ay)); magmax = max(mag(:)); if magmax>0 mag = mag / magmax; % normalize end or = atan2(-ay, ax); % Angles -pi to + pi. neg = or<0; % Map angles to 0-pi. or = or.*~neg + (or+pi).*neg; or = or*180/pi; % Convert to degrees. end

2023-05-22 上传
这是一个实现Canny边缘检测算法的Matlab函数。函数接受一个图像和一个高斯滤波器的标准差作为输入，并输出图像的边缘强度、x和y方向的梯度以及每个像素的梯度方向。首先，函数设计高斯滤波器和它的一阶导数。...

Matplotlib created a temporary config/cache directory at C:\Users\Elegent\AppData\Local\Temp\matplotlib-pyrb807h because the default path (C:\Users\Elegent\.matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing. Traceback (most recent call last): File "D:\pythonProject\AppleStock\ananly2.py", line 24, in <module> candlestick_ochl(ax, df[["Open", "Close", "Volume", "High", "Low"]].values, width=0.5, colorup="green", colordown="red") File "D:\pythonProject\venv\lib\site-packages\mplfinance\original_flavor.py", line 195, in candlestick_ochl return _candlestick(ax, quotes, width=width, colorup=colorup, File "D:\pythonProject\venv\lib\site-packages\mplfinance\original_flavor.py", line 286, in _candlestick if close >= open: TypeError: '>=' not supported between instances of 'int' and 'str'

2023-06-02 上传
这个错误可能是由于您的数据类型不匹配所导致的。您可以尝试将 Close、Open、High 和 Low 这些列的数据类型转换为 float 或者 int 类型。您可以使用以下代码进行转换： ```python df['Close'] = df['Close'].astype...

# Look through unique values in each categorical column categorical_cols = train_df.select_dtypes(include="object").columns.tolist() for col in categorical_cols: print(f"{col}", f"Number of unique entries: {len(train_df[col].unique().tolist())},") print(train_df[col].unique().tolist()) def plot_bar_chart(df, columns, grid_rows, grid_cols, x_label='', y_label='', title='', whole_numbers_only=False, count_labels=True, as_percentage=True): num_plots = len(columns) grid_size = grid_rows * grid_cols num_rows = math.ceil(num_plots / grid_cols) if num_plots == 1: fig, axes = plt.subplots(1, 1, figsize=(12, 8)) axes = [axes] # Wrap the single axes in a list for consistent handling else: fig, axes = plt.subplots(num_rows, grid_cols, figsize=(12, 8)) axes = axes.ravel() # Flatten the axes array to iterate over it for i, column in enumerate(columns): df_column = df[column] if whole_numbers_only: df_column = df_column[df_column % 1 == 0] ax = axes[i] y = [num for (s, num) in df_column.value_counts().items()] x = [s for (s, num) in df_column.value_counts().items()] ax.bar(x, y, color='blue', alpha=0.5) try: ax.set_xticks(range(x[-1], x[0] + 1)) except: pass ax.set_xlabel(x_label) ax.set_ylabel(y_label) ax.set_title(title + ' - ' + column) if count_labels: df_col = df_column.value_counts(normalize=True).mul(100).round(1).astype(str) + '%' for idx, (year, value) in enumerate(df_column.value_counts().items()): if as_percentage == False: ax.annotate(f'{value}\n', xy=(year, value), ha='center', va='center') else: ax.annotate(f'{df_col[year]}\n', xy=(year, value), ha='center', va='center', size=8) if num_plots < grid_size: for j in range(num_plots, grid_size): fig.delaxes(axes[j]) # Remove empty subplots if present plt.tight_layout() plt.show()

2023-06-11 上传
这段代码定义了一个名为plot_bar_chart的函数，它可以绘制柱状图。函数的输入包括一个数据框（df）、一个列名的列表（columns）、网格的行数和列数（grid_rows和grid_cols）、x轴和y轴标签（x_label和y_label）、...
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