Dimensional Data

Its already late and time to modernize your Delphi/C++ Application with extensive Windows 10 support, as the support for Windows 7 ended on January 14, 2020. Rad Studio offers robust components and visually stunning styles to modernize your existing applications in Windows 10. This post will give overview some of the Windows 10 specific features introduced in RAD Studio. Features Overview: Quickly and Easily update VCL and FMX applications to Windows 10 with the Windows 10 Controls. Address common UI Paradigms on Windows 10. Range of UI controls specifically designed for windows 10. Built in windows 10 styles for both VCL and FireMonkey applications. Select custom styles for VCL and FireMonkey available for download in GetIt. VCL extensions for HI-DPI, 4k monitors Support. Rad Studio 10.3 includes PerMonitorV2, Multi Resolutions Image List support. Expanded WinRT API and Windows store support. Windows 10 uses Segoe as the Standard font. Some font guidelines which can make your application looks windows 10. Header – Segoe UI Light,46 pt. Sub Header – Segoe UI Light,34 pt. Title– Segoe UI Semi Light,24 pt. Subtitle – Segoe UI Normal,20 pt. Base – Segoe UI Semi Bold 15 pt. Body -Segoe UI Normal,15 pt. Caption -Segoe UI Normal,12 pt. Windows 10 VCL Controls : TSplitView : A container for other controls that can be opened and closed similar to the TMultiView in FireMonkey. When opened, TSplitView can be docked to the left or right edge of the form, or displayed on top of the client area of the form (overlayed). When closed, the TSplitView can be completely hidden (CloseStyle = svcCollapse), or a smaller portion of the split view can remain visible (CloseStyle = svcCompact). TRelativePanel : A container control that allows you to position child controls relative to the panel itself or relative to other child controls of this panel. For more information on how to use the relative panel, see Using the Relative Panel. TToggleSwitch : A clickable control that allows a user to toggle between an On state and an Off state. Flexible to change the caption of the state. TDatePicker and TTimePicker : Control to let users specify a date and time from a pop-up scrolling list of values. TCalenderView : Allows you to customize the look-and-feel of the control. It supports the selection of multiple dates and includes the Month, Year, Decade views. TCardpanel : Use the TCardPanel to manage a collection of cards. Each card is a container for other controls and only one card is active/visible at a time. TStackPanel : Use the TStackPanel to apply homogeneous alignment, margin, and padding settings to a series of controls inside a panel container. Windows 10 Styles For VCL and FireMonkey. You can apply styles to your application to have stunning look and feel. Some of the windows 10 specific styles were built in to the RAD studio. You can check by navigating to Project->Options->Application->Appearance->select some the styles and you can preview the styles as well. Alternatively you can get some VCL and FireMonkey Styles from Tools->Getit Package manger-> Under Styles category-> select the styles which you wish to apply to your application. You also have flexibility to create your own custom styles using the Tools-> BitMap Style Designer. Check the Video New UX Design Principles for RAD Studio Developers in Windows for Demonstration below. Check out the High DPI Styles and VCL Styling Per Control feature introduced in […]

Take your Delphi and C++Builder projects to the next level using the IBM Watson REST API, a collaborative environment with AI tools that you can use to deploy machine learning models and training data. In this webinar, you can learn how to use IBM Watson APIs to make AI applications with your Delphi or C++ Builder applications. Overview of this session: Delphi & C++ Builder Integration with Web and REST Services HTTP native client library SOAP clients REST clients BaaS clients Cloud API IBM Watson AI Services Visual Recognition Tone Analysis (Natural Language Classification) Watson Machine Learning What you can do with Watson APIs Speech to Text – Text to Speech NLP Knowledge Studio Visual Recognition Language Translator Language Classifier AI for IT Operations AI for Customer Service and more Infuse AI in your Delphi and C++ Builder applications to make more accurate predictions, automate processes, and decisions. Be sure to watch the whole session to learn the demos in action and learn best practices!

In this short tutorial, C++ Product Manager, David Millington, explains what event handlers are and how to use them in your C++ application development.  Overview The event is that something happens.  Event handler – a method that’s called when something happens or is attached to an event. Technical details: an object-method pointer, referring to both the method and object instance on which to call the method. And it can have any signature. Defining Event Handlers In an event receiver class, you define event handlers, which are methods with signatures for instance: return types, calling conventions, and arguments that match the event that they will handle. Firing Events To fire an event, simply call the method declared as an event in the event source class. If handlers have been hooked to the event, the handlers will be called. Be sure to check out other tutorials on C++ Builder here:

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Drawing graphics programmatically is a very popular task these days. You can easily solve it using Matplotlib library with Python4Delphi (P4D). P4D is a free set of instruments that allows you to work with Python scripts, modules and types in Delphi. In this post, we will look at how to run Matplotlib library using Python for Delphi. With Delphi and C++Builder and Python4Delphi, you can build Python GUI apps for Windows using various Python libraries. Open project Demo1 to run the Python script in Python for Delphi. Use Memo1 for Python script and Memo2 for results. Click Execute button for running the script. Download Demo1 source from GitHub. If you run into a floating point division error when executing the code run MaskFPUExceptions(True); before you call ExecStrings. procedure TForm1.Button1Click(Sender: TObject); begin PythonEngine1.ExecStrings( Memo1.Lines ); end; procedure TForm1.Button1Click(Sender: TObject); begin PythonEngine1.ExecStrings( Memo1.Lines ); end; Python Matplotlib library provides various tools for working with 2D graphics. With this library, you can create graphics, customize legends, style sheets, color schemes, and manipulate images. There are examples of code from the Matplotlib below. Draw a plot You can draw very simple plots with Mathplotlib. Or, if you want, you can change the shape and color of the points in the graphic in different ways. In the following example, we will draw the green triangular points using the argument ‘g^’  in function plot(). import matplotlib.pyplot as plt import numpy as np t = np.arange(0., 5., 0.2) plt.plot(t, ‘g^’) plt.show() import matplotlib.pyplot as plt import numpy as np t = np.arange(0., 5., 0.2) plt.plot(t, ‘g^’) plt.show() Stacked bar chart In this example, we show how to draw a stacked bar plot. We will use the function bar() twice. We need to pass to this function such parameters as labels, values of various categories that need to be displayed, names of labels. Finally, we will set such graphic parameters as title, y-label. import matplotlib.pyplot as plt labels = [1, 2, 3, 4, 5] cat1_means = [14, 39, 30, 19, 54] cat2_means = [43, 62, 52, 51, 29] width = 0.35 fig, ax = plt.subplots() ax.bar(labels, cat1_means, width, label=’Cat1′) ax.bar(labels, cat2_means, width, bottom=cat1_means, label=’Cat2′) ax.set_ylabel(‘Scores’) ax.set_title(‘Scores by product cutegories’) ax.legend() plt.show() import matplotlib.pyplot as plt labels = [1, 2, 3, 4, 5] cat1_means = [14, 39, 30, 19, 54] cat2_means = [43, 62, 52, 51, 29] width = 0.35 fig, ax = plt.subplots() ax.bar(labels, cat1_means, width, label=‘Cat1’) ax.bar(labels, cat2_means, width, bottom=cat1_means, label=‘Cat2’) ax.set_ylabel(‘Scores’) ax.set_title(‘Scores by product cutegories’) ax.legend() plt.show() Draw curves and fill the area In this example, we use the function plot() again to build a graphic of cos(x). Then we fill the area in green color between two curves using function fill_between(). Pass parameters x, y1 and y2 to determine the curve and exclude some horizontal regions from being filled using parameter where. import matplotlib.pyplot as plt import numpy as np fig, ax = plt.subplots() x = np.arange(0, 7 * np.pi, 0.1) y = np.cos(x) ax.plot(x, y, color=’black’) ax.fill_between(x, 0, 1, where=y > 0.75, color=’green’, alpha=0.5, transform=ax.get_xaxis_transform()) plt.show() import matplotlib.pyplot as plt import numpy as np fig, ax = plt.subplots() x = np.arange(0, 7 * np.pi, 0.1) y = np.cos(x) ax.plot(x, y, color=‘black’)   ax.fill_between(x, 0, 1, where=y > 0.75,                 color=‘green’, alpha=0.5, transform=ax.get_xaxis_transform()) plt.show() We got acquainted with some of the Matplotlib library’s features. Go here, […]