Update README.md

README.md

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-license: mit
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+---
+license: mit
+---
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+**Data Description:**
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+1. `gamma_5666_half.npy`: 5,666 heat sink design fields in [0,1] of shape (5666, 1, 256, 256). Please note these are the left sides of each design only, because there is symmetry about the vertical axis.
+Recommended loading technique in Python and NumPy: `X = np.load(args.dataset_path).reshape(-1, 1, 256, 256).astype(np.float32)`. This can easily be converted to a Tensor for training a machine learning model in PyTorch as well.
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+2. `inp_paras_5666.npy`: The corresponding 5,666 input parameter vectors, which are 3 scalars per design in the following order: (0) Inlet velocity in the range [-0.095, -0.025], (1) Maximum fluid power dissipation in the range [50J1, 75J1] where J1 = 1.58e-7, and (2) Volume Fraction in the range [0.25, 0.7].
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+3. `dissP_5666.npy`: The corresponding measured fluid power dissipation for each sample as a factor of J1.
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+4. `meanT_5666.npy`: The corresponding mean temperature across the domain in degrees C.