def plot2(df): p = pyggplot.Plot(df).add_scatter("Y", "X") p.width = 5 p.height = 2 return p
def plot(df): return pyggplot.Plot(df).add_scatter("X", "Y")
def plot(df): append("out/plot", "B") return pyggplot.Plot(df).add_scatter("X", "Y")
def plot(df): p = pyggplot.Plot(df["A"]).add_scatter("X", "Y") p.width = 5 p.height = 1 return p
fwd['A'].append(forward_samples.count('A') / nSamples) fwd['B'].append(forward_samples.count('B') / nSamples) fwd['C'].append(forward_samples.count('C') / nSamples) if __name__ == '__main__': nSimulations = 10000 rand = RandomState(1122) cftp = {'A': [], 'B': [], 'C': []} fwd = {'A': [], 'B': [], 'C': []} # couple_from_the_past parameters nSamples = 1000 for simulation in range(nSimulations): couple_engine(rand, cftp, fwd, nSamples) cftp_data = pd.DataFrame.from_dict(cftp) cftp_long = pd.melt(cftp_data, var_name="State", value_name="Proportion") p = pyggplot.Plot(cftp_long) p.add_boxplot(x='State', y='Proportion') p.render("../../figures/cftp_simple_comparison.pdf") fwd_data = pd.DataFrame.from_dict(fwd) fwd_long = pd.melt(fwd_data, var_name="State", value_name="Proportion") p = pyggplot.Plot(fwd_long) p.add_boxplot(x='State', y='Proportion') p.render("../../figures/fwd_simple_comparison.pdf")
def plot(df): append('out/plot', 'B') return pyggplot.Plot(df).add_scatter('X', 'Y')
def plot(df): return pyggplot.Plot(df).add_scatter('X', 'Y')