MATLAB vs. PTC Mathcad

MATLAB really does best for solving computational problems in math and engineering. Especially when you have to use a lot of functions in your solving process, or if you have a nonlinear equation that must be iteratively solved. [MATLAB] can also perform things like integration and derivation on your equations that you put into it.

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It is great for any manual calculation. You can lay it out as you would on paper, but the math is calculated instantly, similar to how it is in excel. It is superior to either method for most engineering calculations. Being able to copy-and-paste is very helpful for considering multiple scenarios. In some situations where you need to do the same calculation on an array of numbers, Excel is still faster.

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• It has a very user friendly library which helps users learn this software fairly quickly in a short span of time.
• The graphical user interface provided by the software is really good.
• The code that a person writes allows options for debugging.
• One can visualize the flow of control of their code inside MATLAB.

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• Conversion of measurement units (Imperial and Metric)
• Easy to use for writing detailed engineering worksheets
• Formulas can be written in the expanded form which facilitates verification
• Spell Checker feature is life saver.

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• MatLab is pricier than most of its competitors and because of this reason, many organizations are moving towards cheaper alternatives - mostly Python.
• MatLab is inefficient when it comes to performing a large number of iterations. It gets laggy and often crashes. Python is better in this regard.
• There is a limited number of hardware options (mostly NI) that can be connected directly to the data acquisition toolbox.

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• Some of the math and text formatting aspects are a little cumbersome.
• Converting from older Matchcad versions to the newer Mathcad Prime platform could be made easier. It should be a direct import function.

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MATLAB is pretty easy to use. You can extend its capabilities using the programming interface. Very flexible capabilities when it comes to graphical presentation of your data (so many different kinds of options for your plotting needs). Anytime you are working with large data sets, or with matrices, MATLAB is likely to be very helpful.

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Higher-order math, despite symbolics, become tedious and variable nomenclature isn't as forgiving as other programs. Due to it's sheet-like nature, the greater the complexity the more bothersome the screen usage becomes. But it's a trade-off between a sketchpad-like interface or lines and lines of code. Pick your poison but MathCad was our choice.

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The built-in search engine is not as performing as I wish it would be. However, the YouTube channel has a vast library of informative video that can help understanding the software. Also, many other software have a nice bridge into MATLAB, which makes it very versatile. Overall, the support for MATLAB is good.

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How MATLAB compares to its competition or similar open access tools like R (programming language) or SciLab is that it's simply more powerful and capable. It embraces a wider spectrum of possibilities for far more fields than any other environment. R, for example, is intended primarily for the area of statistical computing. SciLab, on the other hand, is a similar open access tool that falls very short in its computing capabilities. It's much slower when running larger scripts and isn't documented or supported nearly as well as MATLAB.

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MathCAD is easier to learn and faster to start with. It has more user-friendly interface and conventional style toolbox and GUI. It is really good for the beginners and those who are afraid of complex math.

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• MATLAB helps us quickly sort through large sets of data because we keep the same script each time we run an analyzation, making it very efficient to run this whole process.
• The software makes it super easy for us to create plots that we can then show to investors or clients to display our data.
• We are also looking to create an app for our product, and we will not be able to do that on MATLAB, therefore creating a limiting issue and a new learning curve for a programming language.

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• Speeds up calculations (especially when corrections need to be made near the beginning).
• Ability to re-use old calculations as a template can save significant time.
• You can use consistent formatting for all calculations, allowing for more organized, clear calculations.

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