[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:import scipy.ndimage as ndi\n%matplotlib inline\nimport matplotlib.pyplot as plt\nimport numpy\ndef plotImage(image):\nplt.figure(figsize=(20,10))\nimagePlotting = plt.imshow(image)\nimagePlotting.axes.get_xaxis().set_visible(False)\nimagePlotting.axes.get_yaxis().set_visible(False)\nplt.show()\ndef makeImageStripe(images):\nresult = numpy.zeros([width*3, height,3]);\ndef copyIntoArray(origin, target, fromX, toX):\ntarget[...,0][fromX:toX] = 255-origin.T[0,...]\ntarget[...,1][fromX:toX] = 255-origin.T[1,...]\ntarget[...,2][fromX:toX] = 255-origin.T[2,...]\ncopyIntoArray(images[0], result, 0, width)\ncopyIntoArray(images[1], result, width, width*2)\ncopyIntoArray(images[2], result, width*2, width*3)\nresult = result.transpose(1,0,2)\nreturn result\ndive1 = ndi.imread("images/dive1.jpg")\ndive2 = ndi.imread("images/dive2.jpg")\ndive3 = ndi.imread("images/dive3.jpg")\nwidth = len(dive1[0])\nheight = len(dive1)\nstripe = makeImageStripe([dive1, dive2, dive3])\nplotImage(stripe)'}, {'role': 'assistant', 'content': "['helper_functions', 'load_data', 'result_visualization']"}]