import pandas
import numpy
import gradio
import matplotlib.pyplot
import matplotlib.collections

data = pandas.read_csv("1-s2.0-S2352340918302014-mmc2.csv")

def how_many_designs(team: int, participant: int):
    n = len(numpy.unique(data[(data['Team'] == team) & (data['Participant'] == participant)]['Design']))
    return gradio.Slider.update(1, n, step=1)

def print_design(team: int, participant: int, design: int):
    df = data[(data['Team'] == 1) & (data['Participant'] == 1) & (data['Design'] == design)]
    nodes = df[df['Component'] > 0]
    edges = df[df['Component'] < 0]
    e1 = [int(x) for x in edges['Var1'].values]
    e2 = [int(x) for x in edges['Var2'].values]
    all_info = [e1, e2, [0]*len(e1)]
    idx = numpy.array(all_info).transpose().flatten()
    x = [None if i == 0 else nodes[nodes['Component'] == i]['Var1'].values[0] for i in idx]
    y = [None if i == 0 else nodes[nodes['Component'] == i]['Var2'].values[0] for i in idx]
    fig = matplotlib.pyplot.figure()
    matplotlib.pyplot.plot(x, y)
    matplotlib.pyplot.plot(nodes['Var1'].values, nodes['Var2'].values, linestyle='none', marker='o', label="")

    matplotlib.pyplot.axis('equal')
    matplotlib.pyplot.xlim([-6.0, 6.0])
    matplotlib.pyplot.ylim([-3.0, 5.0])
    return fig

with gradio.Blocks() as demo:
  with gradio.Row():
    with gradio.Column():
      team = gradio.Dropdown(choices=[str(i) for i in range(1,17)], value="1")
      participant = gradio.Dropdown(choices=[str(i) for i in range(1,4)], value="1")
      design = gradio.Slider(1, 100, step=1, value=1)
    with gradio.Column():
      output = gradio.Plot()

    team.change(fn=how_many_designs, inputs=[team, participant], outputs=[design])
    participant.change(fn=how_many_designs, inputs=[team, participant], outputs=[design])

    participant.change(fn=print_design, inputs=[team, participant, design], outputs=[output])
    team.change(fn=print_design, inputs=[team, participant, design], outputs=[output])
    design.change(fn=print_design, inputs=[team, participant, design], outputs=[output])

demo.launch(debug=True)