if file.endswith(".txt"):
predictions_fname = os.path.join("predictions/", file)
last_modified = os.path.getmtime(predictions_fname)
if latest_time <= last_modified:
self.predictions_fname = predictions_fname
latest_time = last_modified
fname = self.predictions_fname
with open(fname, 'r') as f:
self.predictions_strings = f.readlines()
self.days_out_prediction = len(self.predictions_strings)
def write_predictions_file(self, fname=None):
if fname is None:
fname = self.predictions_fname
with open(fname, 'w') as f:
for string, pred in zip(self.predictions_strings,
self.predictions):
string = string.strip('\n')
f.write(string + str(pred) + '\n')
if __name__ == '__main__':
mlpr = MLPRegressor()
mlpr.load()
mlpr.read_predictions_file()
for i in range(mlpr.days_out_prediction):
mlpr.load_feature_vector(fname='sd_feature_vec_' + str(i))
output = mlpr.predict(np.reshape(mlpr.feature_vector, (1, -1)))
print(output[0])
mlpr.write_predictions_file()
