{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport os\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"# load a spectrogram\nimport gzip\n\nSAMPLE =  '../input/fma_small_spectrograms/fma_small_spectrograms/Blues/1042.fused.full.npy.gz'\n\nwith gzip.GzipFile(SAMPLE, 'r') as f:\n    s = np.load(f)\n\nmel = s[0:128]\nchroma = s[128:]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"e9cee518d6fcedb25db28b87a7a80314fa6c42d0"},"cell_type":"code","source":"print('Mel Spectrogram shape')\n\nprint('(n_features, timesteps)')\nprint(mel.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"ce765b10707f344c41015aaab1bc924ce1f56772"},"cell_type":"code","source":"print('Chromagram shape')\n\nprint('(n_features, timesteps)')\nprint(chroma.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"86759660649605f951426c5758c19956f7777ece"},"cell_type":"code","source":"# Visualize with librosa.display.spec... Leaving for exercise","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}