def score_plot(data, pipelines=None):
"""
In:
data: output of Results.to_dataframe()
pipelines: list of string|None, pipelines to include in this plot
Out:
ax: pyplot Axes reference
"""
data = collapse_session_scores(data)
data["dataset"] = data["dataset"].apply(_simplify_names)
if pipelines is not None:
data = data[data.pipeline.isin(pipelines)]
fig = plt.figure(figsize=(8.5, 11))
ax = fig.add_subplot(111)
# markers = ['o', '8', 's', 'p', '+', 'x', 'D', 'd', '>', '<', '^']
sea.stripplot(
data=data,
y="dataset",
x="score",
jitter=0.15,
palette=PIPELINE_PALETTE,
hue="pipeline",
dodge=True,
ax=ax,
alpha=0.7,
)
ax.set_xlim([0, 1])
ax.axvline(0.5, linestyle="--", color="k", linewidth=2)
ax.set_title("Scores per dataset and algorithm")
handles, labels = ax.get_legend_handles_labels()
color_dict = {lb: h.get_facecolor()[0] for lb, h in zip(labels, handles)}
plt.tight_layout()
return fig, color_dict
def score_plot(data, pipelines=None):
'''
In:
data: output of Results.to_dataframe()
pipelines: list of string|None, pipelines to include in this plot
Out:
ax: pyplot Axes reference
'''
data = collapse_session_scores(data)
data['dataset'] = data['dataset'].apply(_simplify_names)
if pipelines is not None:
data = data[data.pipeline.isin(pipelines)]
fig = plt.figure(figsize=(8.5, 11))
ax = fig.add_subplot(111)
sea.stripplot(data=data,
y="dataset",
x="score",
jitter=True,
dodge=True,
hue="pipeline",
zorder=1,
alpha=0.7,
ax=ax)
# sea.pointplot(data=data, y="score", x="dataset",
# hue="pipeline", zorder=1, ax=ax)
# sometimes the score is lower than 0.5 (...not sure how to deal with that)
ax.set_xlim([0, 1])
ax.set_title('Scores per dataset and algorithm')
handles, labels = ax.get_legend_handles_labels()
color_dict = {l: h.get_facecolor()[0] for l, h in zip(labels, handles)}
return fig, color_dict
def paired_plot(data, alg1, alg2):
"""Generate a figure with a paired plot
Parameters
----------
data: DataFrame
dataframe obtained from evaluation
alg1: str
Name of a member of column data.pipeline
alg2: str
Name of a member of column data.pipeline
Returns
-------
fig: Figure
Pyplot handle
"""
data = collapse_session_scores(data)
data = data[data.pipeline.isin([alg1, alg2])]
data = data.pivot_table(values="score",
columns="pipeline",
index=["subject", "dataset"])
data = data.reset_index()
fig = plt.figure(figsize=(11, 8.5))
ax = fig.add_subplot(111)
data.plot.scatter(alg1, alg2, ax=ax)
ax.plot([0, 1], [0, 1], ls="--", c="k")
ax.set_xlim([0.5, 1])
ax.set_ylim([0.5, 1])
return fig
def paired_plot(data, alg1, alg2):
"""
returns figure with an axis that has a paired plot on it
Data: dataframe from Results
alg1: name of a member of column data.pipeline
alg2: name of a member of column data.pipeline
"""
data = collapse_session_scores(data)
data = data[data.pipeline.isin([alg1, alg2])]
data = data.pivot_table(values="score",
columns="pipeline",
index=["subject", "dataset"])
data = data.reset_index()
fig = plt.figure(figsize=(11, 8.5))
ax = fig.add_subplot(111)
data.plot.scatter(alg1, alg2, ax=ax)
ax.plot([0, 1], [0, 1], ls="--", c="k")
ax.set_xlim([0.5, 1])
ax.set_ylim([0.5, 1])
return fig
def paired_plot(data, alg1, alg2, fig_ax=None, P=None, T=None, task=None):
'''
returns figure with an axis that has a paired plot on it
Data: dataframe from Results
alg1: name of a member of column data.pipeline
alg2: name of a member of column data.pipeline
'''
import pdb
if P is not None:
p_values = P.T['RE'].values[::-1][1:]
t_values = T.T['RE'].values[::-1][1:]
data = collapse_session_scores(data)
nr_feat = len(alg1)
if len(alg1) == 1:
data = data[data.pipeline.isin([alg1, alg2])]
data = data.pivot_table(values='score', columns='pipeline',
index=['subject', 'dataset'])
data = data.reset_index(level=['dataset'])
if fig_ax is None:
fig = plt.figure(figsize=(11, 8.5))
ax = fig.add_subplot(111)
else:
ax = fig_ax
# data.plot.scatter(alg1, alg2, ax=ax)
# sea.set(rc={'figure.figsize': (nr_feat * 4, 0.1)}, font="Times New Roman")
fig_ = sea.pairplot(data, x_vars=alg1, y_vars=alg2, hue='dataset', size=6,
palette=sea.color_palette("deep", 8),
plot_kws={"s": 180},
markers=["v", "^", "<", ">", "o", "+", "s", "D"])
for ind in range(nr_feat):
ax = fig_.axes[0, ind]
a_xl = ax.get_xlabel()
a_yl = ax.get_ylabel()
ax.set_xlabel(a_xl, fontsize=35)
ax.set_ylabel(a_yl, fontsize=35)
ax.set_xlim([0.5, 1])
ax.set_ylim([0.5, 1])
ax.set_xticklabels(labels=[0.5, 0.6, 0.7, 0.8, 0.9, 1], fontsize=30)
ax.set_yticklabels(labels=[0.5, 0.6, 0.7, 0.8, 0.9, 1], fontsize=30)
ax.plot([0, 1], [0, 1], ls='--', c='k')
if ind == 3:
ax.set_facecolor((0.9176470588235294, 0.9176470588235294,
0.9490196078431372, 1.0))
txt = 't={:.2f}\np={:1.0e}'.format(t_values[ind], p_values[ind])
if p_values[ind] < 0.05 and t_values[ind] >= 0:
ax.text(0.51, 0.9, txt, fontsize=35, fontweight='black', color='green')
elif p_values[ind] < 0.05 and t_values[ind] < 0:
ax.text(0.51, 0.9, txt, fontsize=35, fontweight='black', color='red')
else:
ax.text(0.51, 0.9, txt, fontsize=35)
mpl.rc('font', family='serif', serif='Times New Roman')
handles = fig_._legend_data.values()
labels = fig_._legend_data.keys()
fig_.fig.legend(handles=handles, labels=labels, loc='upper center', ncol=4,
fontsize=25)
fig_.fig.subplots_adjust(top=0.8, bottom=0.08)
mpl.rcParams['pdf.fonttype'] = 42
mpl.rcParams['ps.fonttype'] = 42
# fig_.savefig('Figure/color_pair_' + task + '.png')
fig_.savefig('Figure/color_pair_' + task + '.pdf')
if fig_ax is None:
return fig
else:
return ax