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@@ -60,10 +60,10 @@ These notebooks double up as examples of how to use PythonicDISORT. The tests wh
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* Python 3.8+
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*`numpy >= 1.8.0`
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*`scipy >= 1.8.0`
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* (OPTIONAL) `autograd >= 1.5`
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* (OPTIONAL) `pytest >= 6.2.5` (Required to use the command `pytest`, see *PyTest and examples of how to use PythonicDISORT*)
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## (OPTIONAL) Additional requirements to run the Jupyter Notebook
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*`autograd >= 1.5`
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*`jupyter > 1.0.0`
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*`notebook > 6.5.2`
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*`matplotlib >= 3.6.0`
@@ -106,3 +106,4 @@ Science and Technology Center (STC) (Award #2019625) under which this package wa
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12) T. Nakajima and M. Tanaka. 1988. *Algorithms for radiative intensity calculations in moderately thick atmospheres using a truncation approximation.*https://www.sciencedirect.com/science/article/pii/0022407388900313.
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13) Connour, Kyle and Wolff, Michael. 2020. *pyRT_DISORT: A pre-processing front-end to help make DISORT simulations easier in Python.*https://github.com/kconnour/pyRT_DISORT.
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