Data Management for MathCAD

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Getting Organized: Data Management for MathCAD

Bradley CarmanJune 2012

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Introduction

MathCAD is the ideal tool for data analysis

Not ideal for data storage and management

A tool is needed for Data Management

Started with Excel Add-in, Evolved to full application (SciData)

Data Management

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Applied Example: Drag Coefficient Measurement for Parachute

Parachutes A-D dropped from 100m elevation

Velocity measured every 0.5s for 5s

100kg mass attached to each parachute

Goal is to determine the Drag Coefficient: Cv

Ac=1.5m2

A B

C D

Ac=1.75m2

Ac=1.4m2

Ac=2m2

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Data Analysis – The Current Way

MathCAD easily provides the Data Analysis for this problemPlotting, Curve Fitting, etc.

But, current data import is “Hard Coded”

1. Hard Coded Data Input and Characteristic Values

2. Analysis & Results

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Data Analysis – The Current Way

Problems:

Slow to change out data sets

No link between characteristic values and data sets

Changing data sets often leads to separate MathCAD files = tendency for errors

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Data Analysis – The New Way

Replace hard coded data and characteristic values with variables

Feed the variables data from database using the MathCAD API

Analysis & Results remain exactly the same!

1. Variable Data Input/Characteristic Values

2. Analysis & Results

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Data Analysis – The New Way

Result:

Single MathCAD document and analysis

Quickly change out data sets

Data and characteristic values can be linked

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Separating Data from Analysis - Implemented

Real benefit now comes from a Data Management System as the driver of inputs and outputs of the analysis

Now it is possible to Batch Process all data sets!

Retrieved Results

Send to MathCAD

Data Management System

Data

Characteristic Values

Results

Data

Characteristic Values

Results

Data

Characteristic Values

Results

Data

Characteristic Values

Results

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Demonstration: Using SciData as the Data Management System

Data is organized in a table

Each row contains a data set, characteristic values, and results

Data

Characteristic Values

Results

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Step 1: Importing Data

Data files use SDS Standard

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Step 2: Categorize the Data Set

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Step 3: Add Characteristic Values to the Data Set

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Step 4: Link to MathCAD Analysis File

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Step 5: Execute the Link

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Step 6: Setup Inputs and Outputs

# = Result tag

Note: Results are retrieved by file due to bugs with MathCAD API. WRITEPRN is much faster.

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Step 6: Setup Outputs Continued…

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Step 7: Batch Processing

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Step 8: Compile Results

All results are now compiled together and ready to be presented

Since everything came from the same MathCAD analysis, there are no discrepancies among results

Fast, organized, and error free!

Parachute Ax CvA 1.5 1.48B 1.75 2.34C 2 2.59D 1.4 1.84

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Conclusion

Data and Analysis are now separate:

-Now have a good place to store and organize data and information

-Enabling batch processing

-Improving efficiency and accuracy!

sourceforge.net/projects/scidata/

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Additional Examples

Design Table

Full Table Analysis

Table Filter

Data Extraction

High Speed Video Analysis

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Parachute Design Table

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Full Table Analysis

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Table Filter

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Data Extraction

When SciData cannot interpret a data file, only the file name is added

Use MathCAD to interpret and filter more complex data files, then export to SciData

First challenge: Building a path to the file using the name

Building a relative path Best practice

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Data Extraction

Handling different data formats

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Data Extraction

Use READFILE or READPRN

Don’t Use Import>Data>…

Problem: - Can’t use variable path

Problem: - Can’t use relative path ‘..\..\Data\’- Has bugs (problems updating)

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Data Extraction

READPRN can filter out all non-numeric information automatically.

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Data Extraction

1. Data Extraction File

2. Extract to SciData

3. Add Clean Analysis File

4. Start with a Clean Slate

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High Speed Video Drop Analysis

1. In DOS run: ren *.bmp *.bmp.dat

2. Scan Data folder

3. Batch Process, get dropPositionX

4. Full Table Analysis

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Review

Data Management for MathCAD SciData can be downloaded at:

– sourceforge.net/projects/scidata/

Data Management benefits:– Organization and error avoidance– All data types stored conveniently together in a standardized form (metadata and arrays)– Batch Processing– Row by Row and Full Table Analysis from the same root source

Contact Info– Brad Carman– bradcarman@users.sourceforge.net

Questions?– Remember your evaluations