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from pypet import Trajectory


    

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traj = Trajectory(filename='./pypet/FanSimulation_2016_02_22_14h46m09s.hdf5')


    

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traj.f_load(index=-1, load_parameters=2, load_results=2)


    

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traj.f_get_parameters()


    

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traj.f_get_explored_parameters()


    

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traj.f_get_run_names()


    

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def my_filter_function(location,dt):
    result = location =='mars' and dt=1e-2
    return result


    

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set(traj.f_get('incline').f_get_range())


    

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def filter_function(loc,dt,vmax,vent_radius,incline):
    result = loc=='mars' and dt==1e-2 and vmax==50\
        and vent_radius==0.5 and incline==1.0
    return result


    

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def standard_filter(loc, dt, jitter, incline):
    result = loc=='mars' and dt==1e-2 and jitter==0.1 and incline!=10.0
    return result


    

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idx_iter = traj.f_find_idx(['parameters.location','parameters.dt',
                            'parameters.jitter', 'parameters.incline'], standard_filter)


    

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indexes = list(idx_iter)


    

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indexes


    

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%matplotlib nbagg


    

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def plot_data(i):

    traj.v_idx = indexes[i]
    data = traj.res.crun.positions
    title = ''
    for k,v in traj.f_get_parameters(fast_access=True).items():
        key = k.split('.')[1]
        if key=='location' or key=='dt' or key=='N' or key=='jitter':
            continue
        t = "{}:{} | ".format(key, v)
        title += t
    fig, axes = plt.subplots(nrows=2, squeeze=False)
    axes = axes.ravel()
    for ax in axes:
        ax.scatter(data[:, 0], data[:, 1])
    axes[1].set_xlim(-15, 70)
    axes[1].set_ylim(-20, 20)
    fig.suptitle(title[:-2], fontsize=13)


    

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%matplotlib inline
import seaborn as sns
sns.set_context('notebook')


    

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from ipywidgets import interact


    

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interact(plot_data, i=(0, len(indexes)-1));


    

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