### Updated README.md with basic tutorial

parent b7809eb1
 ... @@ -51,9 +51,9 @@ my_project = my_project.run(verbose=True) ... @@ -51,9 +51,9 @@ my_project = my_project.run(verbose=True) Once you have this, you can do several things! But let's first explore how the results of those computations I mentioned Once you have this, you can do several things! But let's first explore how the results of those computations I mentioned are stored. To extract trajectories, distances and/or angles, you can respectively type: are stored. To extract trajectories, distances and/or angles, you can respectively type: ``` ``` deepof_coords = deepof_main.get_coords(center=True, polar=False, speed=0, align="Nose", align_inplace=True) my_project_coords = my_project.get_coords(center=True, polar=False, speed=0, align="Nose", align_inplace=True) deepof_dists = deepof_main.get_distances(speed=0) my_project_dists = my_project.get_distances(speed=0) deepof_angles = deepof_main.get_angles(speed=0) my_project_angles = my_project.get_angles(speed=0) ``` ``` Here, the data are stored as ```deepof.data.table_dict``` instances. These are very similar to python dictionaries Here, the data are stored as ```deepof.data.table_dict``` instances. These are very similar to python dictionaries with experiment IDs as keys and pandas.DataFrame objects as values, with a few extra methods for convinience. Peeping with experiment IDs as keys and pandas.DataFrame objects as values, with a few extra methods for convinience. Peeping ... ...
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