X_t = np.zeros(shape=(N_tag,df.shape,3)) # empty animation array (3D) T = np.linspace(0,data.Time,df.shape) # pseudo time-vector for first walking activity N_tag = df.shape/3 # nr of tags used (all) # Find max and min values for animation rangesĭf_minmax = pd.DataFrame(index=list('xyz'),columns=range(2))Ĭ_max = df.filter(regex='_'.format(i)).min().min()ĭf_minmax.ix = np.array()ĭf_minmax = 1.3*df_minmax # increase by 30% to make animation look betterĭf.columns = np.repeat(range(12),3) # store cols like this for simplicity e('TkAgg') # Need to use in order to run on macĭata = pd.read_csv('~/Smart-first_phase_NaN-zeros.csv') # only coordinate dataĭf = data.loc This is code adapted from .įull animation of a walking event (note: a lot of missing data) pairs of points - for example, how to add an animation line between the yellow and green tags), but I am not entirely sure how to do this. Now I would like the animation to also include the lines between pairs of tags (i.e. Each tag has a trajectory in time such that the movement path can be seen for each tag as it progresses (have a look at the image attached). Basically I have 12 tags which I am animating through time. I am currently having some trouble with my code which animates some time-series data, and I cannot quite figure it out.
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