J
jchambers13419
I need to create a 3D table from a multitude of data points, similar to the
2D histogram but in 3D. The data is engine data gathered from road testing
of a vehicle in the form of throttle position (TP), engine speed (RPM) and
engine load. Engine load is the value that I'm trying to develop a running
average/profile at the various TP and RPM points. RPM is the x-axis with the
first column being 500 rpm and then incremented to 6000 (see below). TP is
the y-axis starting at 0 and incrementing to full throttle being 750 counts.
Load is calculated by the engine PCM for the instananeous TP and RPM
conditions. I gather tens of thousands of the three point sets while driving
the car at various loads, speeds and acceleration rates. Data is collected
in .csv format. The resulting table is basically 10 rows x 10 columns in
size with:
x-axis (500, 800, 1100, 1400, 1700, 2000, 3000, 4000, 5000, 6000)
y-axis (0, 40, 80, 120, 160, 200, 250, 300, 500, 750)
My problem is how to process the data quickly and easily so that the load
data is sorted into the appropriate cells of the table (RPM, TP) and the
value of each load cell averaged and updated as load values are recorded for
each cell. For example, a small dataset might be
RPM, TP, LOAD
1338, 147, .235
2472, 220, .400
1190, 122, .210
4510, 540, .780
......
Data points 1 and 3 would be cast into the same cell (1100, 120) since the
RPM is between 1000 and 1499 and TP between 120 and 159. The resulting
average load for that cell would then be (.235+.210)/2 = 222.5. Data point 2
would fall into the (2000, 200) cell and point 4 would fall into the (4000,
500) cell.
I haven't been able to figure out a way to take tens of thousands of such
data points and construct the resulting table quickly and easily. This is
something that I have a need to do quite often so I'm desparately seeking
automation to make the task more efficient. Any help would be greatly
appreciated.
2D histogram but in 3D. The data is engine data gathered from road testing
of a vehicle in the form of throttle position (TP), engine speed (RPM) and
engine load. Engine load is the value that I'm trying to develop a running
average/profile at the various TP and RPM points. RPM is the x-axis with the
first column being 500 rpm and then incremented to 6000 (see below). TP is
the y-axis starting at 0 and incrementing to full throttle being 750 counts.
Load is calculated by the engine PCM for the instananeous TP and RPM
conditions. I gather tens of thousands of the three point sets while driving
the car at various loads, speeds and acceleration rates. Data is collected
in .csv format. The resulting table is basically 10 rows x 10 columns in
size with:
x-axis (500, 800, 1100, 1400, 1700, 2000, 3000, 4000, 5000, 6000)
y-axis (0, 40, 80, 120, 160, 200, 250, 300, 500, 750)
My problem is how to process the data quickly and easily so that the load
data is sorted into the appropriate cells of the table (RPM, TP) and the
value of each load cell averaged and updated as load values are recorded for
each cell. For example, a small dataset might be
RPM, TP, LOAD
1338, 147, .235
2472, 220, .400
1190, 122, .210
4510, 540, .780
......
Data points 1 and 3 would be cast into the same cell (1100, 120) since the
RPM is between 1000 and 1499 and TP between 120 and 159. The resulting
average load for that cell would then be (.235+.210)/2 = 222.5. Data point 2
would fall into the (2000, 200) cell and point 4 would fall into the (4000,
500) cell.
I haven't been able to figure out a way to take tens of thousands of such
data points and construct the resulting table quickly and easily. This is
something that I have a need to do quite often so I'm desparately seeking
automation to make the task more efficient. Any help would be greatly
appreciated.
1 enter 0, 40, 80, 120, 160, 200, 250, 300, 500, 750, 1000000 (or