Example ¨Correcting from pandas.DataFrame as Data¨ needs a data transpose not to fail with shape not aligned

[FinLouarn]

The first example ¨Correcting from Numpy Array as Data¨ works smoothly,
but the second example ¨Correcting from pandas.DataFrame as Data¨ fails with the following error of shape not aligned, unless you feed neuroCombat with data.T in stead of data.

python 3.7.7
pandas 0.25.3

---

ValueError Traceback (most recent call last)
in
15 batch_col=batch_col,
16 discrete_cols=discrete_cols,
---> 17 continuous_cols=continuous_cols)

/neuroCombat/neuroCombat/neuroCombat.py in neuroCombat(data, covars, batch_col, discrete_cols, continuous_cols)
97 # standardize data across features
98 print('Standardizing data across features..')
---> 99 s_data, s_mean, v_pool = standardize_across_features(data, design, info_dict)
100
101 # fit L/S models and find priors

/neuroCombat/neuroCombat/neuroCombat.py in standardize_across_features(X, design, info_dict)
159 sample_per_batch = info_dict['sample_per_batch']
160
--> 161 B_hat = np.dot(np.dot(la.inv(np.dot(design.T, design)), design.T), X.T)
162 grand_mean = np.dot((sample_per_batch/ float(n_sample)).T, B_hat[:n_batch,:])
163 var_pooled = np.dot(((X - np.dot(design, B_hat).T)**2), np.ones((n_sample, 1)) / float(n_sample))

<array_function internals> in dot(*args, **kwargs)

ValueError: shapes (8,57) and (22283,57) not aligned: 57 (dim 1) != 22283 (dim 0)