cluster_ids = list(cluster_ids)
cluster_ids.sort()
for cluster_id in cluster_ids:
print("{},{}".format(
cluster_id,
o_data.df.loc[o_data.df['cluster_id'] == cluster_id].shape[0]))
from matplotlib import cm
n_clusters = len(cluster_ids)
o_ref_data = PyposmatDataFile()
o_ref_data.read(filename=ref_data_fn)
n_reference_potentials = o_ref_data.df.shape[0]
cm_subsection = np.linspace(0.0, 1.0, n_clusters + n_reference_potentials)
colors = [cm.jet(i) for i in cm_subsection]
o_plot = PyposmatParallelCoordinatesPlot()
for i, cluster_id in enumerate(cluster_ids):
df = o_data.df.loc[o_data.df['cluster_id'] == cluster_id]
o_plot.plot(config=o_config,
data=o_data,
label=cluster_id,
nsmallest=20,
linewidth=1,
alpha=0.7,
color=colors[i],
cluster_id=cluster_id)
# plot the reference potentials for comparison
o_plot.plot_reference_potentials(config=ref_config_fn,
data=ref_data_fn,
linewidth=5)
if qoi_type == 'by_qoi_target':
o_data.create_normalized_errors(normalize_type='by_qoi_target',
qoi_targets=o_config.qoi_targets)
df = o_data.df[o_data.normalized_error_names]
if __name__ == "__main__":
# reset the plot directory
plot_dir = 'parallel_plots'
if os.path.isdir(plot_dir):
shutil.rmtree(plot_dir)
os.mkdir(plot_dir)
figure_fn = os.path.join(plot_dir, 'parallel_plot.jpg')
o_plot = PyposmatParallelCoordinatesPlot()
o_plot.create_subplots()
for k, v in parallel_plot_config.items():
print(v)
o_plot.plot(config=v['config_fn'],
data=v['data_fn'],
label=v['label'],
color=v['color'],
nsmallest=20,
alpha=0.7)
ref_config_fn = os.path.join(
pypospack.utils.get_pypospack_root_directory(), 'data', 'Si__sw__data',
'reference_potentials', 'pyposmat.config.in')
ref_data_fn = os.path.join(pypospack.utils.get_pypospack_root_directory(),
'data', 'Si__sw__data', 'reference_potentials',