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lauramurgatroyd
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lauramurgatroyd
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Hi @hrobarts
I noticed that the result after providing the arguments is the same as before.
It might be more beneficial to use a (probably synthetic) example dataset where we have some low and high outliers so that we can demonstrate a difference that has been made by using the parameters.
I also had an issue downloading the walnut dataset. Perhaps we need to open an issue in CIL? It needs further investigation
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| "from cil.utilities import dataexample\n", | ||
| "dataexample.WALNUT.download_data(data_dir='.', prompt=False)\n", | ||
| "data = dataexample.WALNUT.get('.')" |
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This only worked for me if I set prompt=True
With prompt=False:
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Create a `TransmissionAbsorptionConvertor` procesor to convert from x-ray transmission data to x-ray absorption data using the Beer-Lambert law " |
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| "Create a `TransmissionAbsorptionConvertor` procesor to convert from x-ray transmission data to x-ray absorption data using the Beer-Lambert law " | |
| "Create a `TransmissionAbsorptionConvertor` processor to convert from x-ray transmission data to x-ray absorption data using the Beer-Lambert law " |
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