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New regression in python #69
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#write_file.write(json.dumps(numpyData, cls=NumpyArrayEncoder, indent=4)) | ||
#res = json.dumps(numpyData, cls=NumpyArrayEncoder, indent=4) | ||
#print(res) | ||
#json.dump(numpyData, zipfile, cls=NumpyArrayEncoder) |
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tools/RegressionSceneData.py
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for step in range(0, self.steps + 1): | ||
# export rest position, final position + modulo steps: | ||
if (step == 0 or counterStep >= moduloStep or step == self.steps): | ||
#print("step: " + str(step) + " | counterStep: " + str(counterStep) + " | moduloStep: " + str(moduloStep) + " | dt: " + str(self.rootNode.dt.value*(step))) |
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This is a new version of Regression using SofaPython3. Feel free to improve it.
TODO:
Style based on .regression-test file but the last argument is the number of keyframe to test:
for example:
demos/mydemo.py 4000 1e-3 1 100
100 step will be tested with a threshold of 1e-3.
key frame will be: [0 40 80 ... 4000]*dt so 101 values.
Right now, at each key frame, full distance between the ref dofs and simulated dofs is computer.
totalError = sum(fullDist) accumulated over all key frames.
errorByDos = sum(fullDist)/nbrDofs accumulated over all key frames.
Computation is done using numpy array. Maybe better metrics could be used.
example of output: