Data Extraction, Analysis and Formatting for Reports

Templex can be used to extract output data from results files to perform additional calculations or create text summary tables.

The Templex read statement is used to access a vector of data from a results file. The read statement automatically recognizes all result file types supported by import templates or external readers registered with your MotionView or HyperGraph installation. Import templates and external readers describe the file format, allowing Templex direct access to specific results vectors.

Tip: To use the two columns of data shown below, copy and paste them into a new file.
X Y 
0.0000000000e+00
1.0000000000e+00
2.0000000000e+00
3.0000000000e+00
4.0000000000e+00
5.0000000000e+00
6.0000000000e+00
7.0000000000e+00
8.0000000000e+00
9.0000000000e+00
1.0000000000e+01
 
0.0000000000e+00
-2.0452000000e-01
-2.0996000000e+02
1.3688000000e+02
-2.0412000000e+03
-4.5116000000e+03
-7.5309000000e+03
-9.4560000000e+03
-7.0598000000e+03
-4.3536000000e+03
-5.6833000000e+01
The following template reads the first column into a vector named "x" and the second column into a vector named "y." This template then uses the statement {max} to find the maximum negative value of the y-vector.
{x = read("curve.dat", 0, 0, 0) 'Read column 0 into }
{y = read("curve.dat", 0, 0, 1) 'Read column 1 into y vector}
{ny = -y}
{ymax = max(ny)}
The maximum negative value of {-ymax} occurs at x = {x[indexofmax(ny)]}

Any text outside the braces is treated as plain text. Plain text is copied to the output stream exactly as it appears in the template. Templex statements, expressions and variables are located within braces, {}. If the Templex statement generates output, the resulting value is sent to the output stream.

The above template yields the following output:
The maximum negative value of -9456 occurs at x = 7
In the following template, the same two vectors are read from one file. This template uses the math statement Polyfit to calculate the coefficients from a sixth-order least squares polynomial curve fit of the data.
{x = read("curve.dat", 0, 0, 0) 'Read column 0 into x vector}
{y = read("curve.dat", 0, 0, 1) 'Read column 1 into y vector}
{result = polyfit(x,y,6)}
{open "curvefit.out"}
    "X"          "Y"      Polyfit "Y"
-----------  -----------  -----------
{table(x, y, result, "%12.6f %12.6f %12.6f", 0, numpts(x)-1)}
{close}
There are two outputs from this template. First, the calculated coefficients are reported to the standard output stream, as shown:
Polynomial coefficients:
+4.61436e+01 * X^0
-1.23808e+03 * X^1
+1.30333e+03 * X^2
-3.38257e+02 * X^3
-3.88651e+00 * X^4
+6.09099e+00 * X^5
-3.50098e-01 * X^6
Mean deviation: 3.33713e+02
Correlation coefficient: 9.91274e-01
Second, a new dependent vector representing the polyfit data is assigned to the vector result, which is then written to the file along with the independent vector x. This is shown below:
X Y Polyfit"Y" 
0.000000
1.000000
2.000000
3.000000
4.000000
5.000000
6.000000
7.000000
8.000000
9.000000
10.000000
 
0.000000
-0.204520
-209.960000
136.880000
-2041.200000
-4511.600000
-7530.900000
-9456.000000
-7059.800000
-4353.600000
-56.833000
 
46.143579
-225.009132
187.561497
-161.006006
-1893.164101
-4708.213938
-7533.633874
-8928.478798
-7738.850272
-4005.437480
-123.128993

In the next example, the template reads in a file containing wheel center displacements and spindle alignment point displacements which result from stroking a suspension from jounce to rebound. This information is used to calculate camber and toe for each output position. The result is formatted and sent to the standard output stream.

The following input file is used:
Inc Whl_cntr_xdsp Whl_cntr_ydsp Whl_cntr_zdsp Spdl_aln_xdsp Spdl_aln_ydsp Spdl_aln_zdsp
1 1005.338500 -819.560700 420.000000 1004.721800 -769.611100 417.840800
2 1004.335100 -823.669400 400.000000 1003.815700 -773.695100 398.482200
3 1003.305400 -826.754700 380.000000 1002.889200 -776.766100 379.015600
4 1002.243700 -828.834400 360.000000 1001.943800 -778.838400 359.445100
5 1001.144100 -829.916700 340.000000 1000.980400 -779.917500 339.773200
6 1000.000000 -830.000000 320.000000 1000.000000 -780.000000 320.000000
7 998.804400 -829.072700 300.000000 999.002900 -779.073200 300.123900
8 997.548600 -827.111900 280.000000 997.989100 -777.114000 280.140400
9 996.222100 -824.081600 260.000000 996.958400 -774.087100 260.041900
10 994.811200 -819.929100 240.000000 995.910100 -769.941500 239.816500
11 993.296900 -814.579100 220.000000 994.842900 -764.606100 219.445900
The following template is created:
{increment = read("sdf.dat", 0, 0, 0)}
{wcx   = read("sdf.dat", 0, 0, 1)}
{wcy   = read("sdf.dat", 0, 0, 2)}
{wcz   = read("sdf.dat", 0, 0, 3)}
{spax  = read("sdf.dat", 0, 0, 4)}
{spay  = read("sdf.dat", 0, 0, 5)}
{spaz  = read("sdf.dat", 0, 0, 6)}
{n = numpts(increment)}
{camber = array(n)}
{toe    = array(n)}
Inc     wcx           wcy           wcz
--- ------------  ------------  ------------
{table(increment, wcx, wcy, wcz,"%2d  %12.6f  %12.6f  %12.6f", 0, n-1)}
Inc     spax          spay          spaz
--- ------------  ------------  ------------
{table(increment, spax, spay, spaz, "%2d  %12.6f  %12.6f  %12.6f", 0, n-1)}
{for(i=0; i<=10; i++)}
  {temp1 = spaz[i] - wcz[i]}
  {temp2 = sqrt((wcy[i]-spay[i])^2+(wcz[i]-spaz[i])^2)}
  {temp3 = wcx[i] - spax[i]}
  {temp4 = sqrt((wcx[i]-spax[i])^2+(wcy[i]-spay[i])^2)}
  {camber[i] = rtod(asin(temp1/temp2))}
  {toe[i]    = rtod(asin(temp3/temp4))}
{endloop}
Inc    camber         toe  
--- ------------  ------------
{table(increment, camber, toe, "%2d  %12.6f  %12.6f", 0, n-1)}
The template output is shown below:
Inc wcx wcy wcz
1 1005.338500 -819.560700 420.000000
2 1004.335100 -823.669400 400.000000
3 1003.305400 -826.754700 380.000000
4 1002.243700 -828.834400 360.000000
5 1001.144100 -829.916700 340.000000
6 1000.000000 -830.000000 320.000000
7 998.804400 -829.072700 300.000000
8 997.548600 -827.111900 280.000000
9 996.222100 -824.081600 260.000000
10 994.811200 -819.929100 240.000000
11 993.296900 -814.579100 220.000000
Inc spax spay spaz
1 1004.721800 -769.611100 417.840800
2 1003.815700 -773.695100 398.482200
3 1002.889200 -776.766100 379.015600
4 1001.943800 -778.838400 359.445100
5 1000.980400 -779.917500 339.773200
6 1000.000000 -780.000000 320.000000
7 999.002900 -779.073200 300.123900
8 997.989100 -777.114000 280.140400
9 996.958400 -774.087100 260.041900
10 995.910100 -769.941500 239.816500
11 994.842900 -764.606100 219.445900
Inc camber toe
1 -2.475217 0.707363
2 -1.739630 0.595473
3 -1.128151 0.477028
4 -0.635893 0.343683
5 -0.259896 0.187589
6 0.000000 0.000000
7 0.141980 -0.227465
8 0.160893 -0.504784
9 0.048019 -0.843769
10 -0.210327 -1.259356
11 -0.635269 -1.771978
Templex templates can also be incorporated into report definitions in MotionView and HyperGraph to produce text summaries as part of a standard report.