Checks on the data sets array dimensions#82
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Added a few lines of code to the Sklearn.py and regression.py files both found within the task subfolder. I had noticed some weird and unexpected behavior while using the sklearn interface for the dso library when the function argument y for the fit function was not a one dimensional numpy array (See the recently closed issue made by myself tilted Different Learning Equations with Different Numpy Array shape). So fix this issue, within the sklearn.py file I have added a few lines of code to check that the function arguments (X,y) to the fit are first numpy ndarray class objects then if X and y have exactly 2 and 1 array dimensional respectively. A type error is through when the arguments are not numpy arrays and a value error is raised when the number of array dimensions for X or y is incorrect. Additionally, within the regression.py file of the dso library I have added similar error checking within the initialization method of the RegressionTask class but only for the y_train and y_test arrays of the RegressionTask (that they are single dimensional arrays) only after the have been created through either of 4 possible supported use cases.
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Added a few lines of code to the Sklearn.py and regression.py files both found within the task subfolder. I had noticed some weird and unexpected behavior while using the sklearn interface for the dso library when the function argument y for the fit function was not a one dimensional numpy array (See the recently closed issue made by myself tilted Different Learning Equations with Different Numpy Array shape). So fix this issue, within the sklearn.py file I have added a few lines of code to check that the function arguments (X,y) to the fit are first numpy ndarray class objects then if X and y have exactly 2 and 1 array dimensional respectively. A type error is through when the arguments are not numpy arrays and a value error is raised when the number of array dimensions for X or y is incorrect. Additionally, within the regression.py file of the dso library I have added similar error checking within the initialization method of the RegressionTask class but only for the y_train and y_test arrays of the RegressionTask (that they are single dimensional arrays) only after the have been created through either of 4 possible supported use cases.