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What’s the advantages of using HDF5 for file saving and loading? I wrote something about pickle or JSON before, which are python packages for serialization. More specifically, pickle is a binary serialization format for python objects, saving objects to an unreadable file, can be loaded inside the same machine and is not sharable with other programming languages. And JSON is a text serialization which saves basically python dictionaries, text, list like object in a readable format....

Heatmap is great tool for visualizing two dimensional data magnitude using colors. This package provides almost complete features for building a heatmap under multiple conditions. Parameters that are used to customize a heatmap could be extremely complicated. This article try to archive part of the features that have been useful in my recently work. Note down their usage and syntax. Data The dataset used in this article comes from project Tycho, and is about recorded cases of measles in the United States....

Pyradiomics is an open-source python package for the extraction of radiomics data from medical images. Image loading and preprocessing (e.g. resampling and cropping) are first done using SimpleITK. Loaded data is then converted into numpy arrays for further calculation using multiple feature classes. Optional filters are also built-in. Ways to Deal with Medical Image Data The reasons that we choose pyradiomics could be its openness, widely recognized and reasonably good performance with a variety of features available....

The module pickle implements binary protocols for serializing and de-serializing a Python object structure. We can store almost any type of object of Python using pickle. Quick Example For example, we want to save a dictionary dict_obj to file. # Save file def saveFile(obj): out_file = open('obj.pickle','wb') pickle.dump(obj, out_file) out_file.close() # Read file def readFile(obj_file_name): file = open(obj_file_name, 'rb') obj = pickle.load(file) return obj >>> dict_obj = {'itemA': ['item', 'A'], 'itemB':[1, 3]} >>> saveFile(dict_obj) >>> obj_file_name = 'obj....