Source code for pm4py.visualization.performance_spectrum.visualizer
'''
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see this software project's root or
visit <https://www.gnu.org/licenses/>.
Website: https://processintelligence.solutions
Contact: info@processintelligence.solutions
'''
import shutil
from enum import Enum
from typing import Optional, Dict, Any
from pm4py.util import exec_utils, vis_utils, constants
from pm4py.visualization.performance_spectrum.variants import neato
[docs]
class Variants(Enum):
NEATO = neato
[docs]
def apply(
perf_spectrum: Dict[str, Any],
variant=Variants.NEATO,
parameters: Optional[Dict[Any, Any]] = None,
) -> str:
"""
Construct the performance spectrum visualization
Parameters
----------------
perf_spectrum
Performance spectrum
variant
Variant of the visualization to use:
- NEATO: using the Graphviz Neato layouter
parameters
Variant-specific parameters
Returns
---------------
file_path
Path containing the visualization
"""
return exec_utils.get_variant(variant).apply(
perf_spectrum, parameters=parameters
)
[docs]
def view(figure: str):
"""
Views the performance spectrum
Parameters
---------------
figure
Path containing the visualization
"""
if constants.DEFAULT_ENABLE_VISUALIZATIONS_VIEW:
if constants.DEFAULT_GVIZ_VIEW == "matplotlib_view":
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
img = mpimg.imread(figure)
plt.axis("off")
plt.tight_layout(pad=0, w_pad=0, h_pad=0)
plt.imshow(img)
plt.show()
return
if vis_utils.check_visualization_inside_jupyter():
vis_utils.view_image_in_jupyter(figure)
else:
vis_utils.open_opsystem_image_viewer(figure)
[docs]
def save(figure: str, output_file_path: str):
"""
Saves the performance spectrum at the specified path
Parameters
---------------
figure
Path containing the visualization
output_file_path
Path into which the image should be saved
"""
shutil.copyfile(figure, output_file_path)
return ""
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def serialize(figure: str):
"""
Serializes the performance spectrum visualization
Parameters
---------------
figure
Path containing the visualization
"""
with open(figure, "rb") as f:
return f.read()
[docs]
def matplotlib_view(figure: str):
"""
Views the performance spectrum using Matplotlib
Parameters
---------------
figure
Path containing the visualization
"""
if constants.DEFAULT_ENABLE_VISUALIZATIONS_VIEW:
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
img = mpimg.imread(figure)
plt.imshow(img)
plt.show()