import math
import os
import tempfile
import uuid
from datetime import datetime
from enum import Enum
from typing import Optional, Dict, Any, Union
import matplotlib as mpl
import matplotlib.cm as cm
from pm4py.util import exec_utils, constants
from pm4py.util.dt_parsing.variants import strpfromiso
from pm4py.util.colors import get_string_from_int_below_255
[docs]
class Parameters(Enum):
FORMAT = "format"
ACT_DIVIDER_SPACE = "act_divider_space"
DATE_DIVIDER_SPACE = "date_divider_space"
OVERALL_LENGTH_X = "overall_length_x"
N_DIV_DATES = "n_div_dates"
PERC_PATHS = "perc_paths"
LAYOUT_EXT_MULTIPLIER = "layout_ext_multiplier"
ENABLE_GRAPH_TITLE = "enable_graph_title"
GRAPH_TITLE = "graph_title"
[docs]
def give_color_to_line(dir: float) -> str:
"""
Gives a gradient color to the line
Parameters
----------------
dir
Intensity of the difference (number between 0 and 1; 0=min difference, 1=max difference)
Returns
----------------
color
Gradient color
"""
dir = 0.5 + 0.5 * dir
norm = mpl.colors.Normalize(vmin=0, vmax=1)
nodes = [0.0, 0.01, 0.25, 0.4, 0.45, 0.55, 0.75, 0.99, 1.0]
colors = [
"deepskyblue",
"skyblue",
"lightcyan",
"lightgray",
"gray",
"lightgray",
"mistyrose",
"salmon",
"tomato",
]
cmap = mpl.colors.LinearSegmentedColormap.from_list(
"mycmap2", list(zip(nodes, colors))
)
# cmap = cm.plasma
m = cm.ScalarMappable(norm=norm, cmap=cmap)
rgba = m.to_rgba(dir)
r = get_string_from_int_below_255(math.ceil(rgba[0] * 255.0))
g = get_string_from_int_below_255(math.ceil(rgba[1] * 255.0))
b = get_string_from_int_below_255(math.ceil(rgba[2] * 255.0))
return "#" + r + g + b
[docs]
def apply(
perf_spectrum: Dict[str, Any],
parameters: Optional[Dict[Union[str, Parameters], Any]] = None,
) -> str:
"""
Construct the performance spectrum visualization
Parameters
----------------
perf_spectrum
Performance spectrum
parameters
Parameters of the algorithm, including:
- Parameters.FORMAT => format of the output (svg, png, ...)
- Parameters.ACT_DIVIDER_SPACE => space between the activities in the spectrum
- Parameters.DATE_DIVIDER_SPACE => space between the lines and the dates
- Parmaeters.OVERALL_LENGTH_X => length of the X-line
- Parameters.N_DIV_DATES => specifies the number of intermediate dates reported
- Parameters.PERC_PATHS => (if provided) filter the (overall) most long paths
Returns
---------------
file_path
Path containing the visualization
"""
if parameters is None:
parameters = {}
format = exec_utils.get_param_value(Parameters.FORMAT, parameters, "png")
act_divider = exec_utils.get_param_value(
Parameters.ACT_DIVIDER_SPACE, parameters, 3.0
)
date_divider = exec_utils.get_param_value(
Parameters.DATE_DIVIDER_SPACE, parameters, 1.0
)
overall_length = exec_utils.get_param_value(
Parameters.OVERALL_LENGTH_X, parameters, 10.0
)
n_div = exec_utils.get_param_value(Parameters.N_DIV_DATES, parameters, 2)
perc_paths = exec_utils.get_param_value(
Parameters.PERC_PATHS, parameters, 1.0
)
layout_ext_multiplier = exec_utils.get_param_value(
Parameters.LAYOUT_EXT_MULTIPLIER, parameters, 100
)
enable_graph_title = exec_utils.get_param_value(
Parameters.ENABLE_GRAPH_TITLE,
parameters,
constants.DEFAULT_ENABLE_GRAPH_TITLES,
)
graph_title = exec_utils.get_param_value(
Parameters.GRAPH_TITLE, parameters, "Performance Spectrum"
)
output_file_gv = tempfile.NamedTemporaryFile(suffix=".gv")
output_file_gv.close()
output_file_img = tempfile.NamedTemporaryFile(suffix="." + format)
output_file_img.close()
lines = []
lines.append("graph G {")
if enable_graph_title:
lines.append(
'label=<<FONT POINT-SIZE="20">'
+ graph_title
+ '</FONT>>;\nlabelloc="top";\n'
)
min_x = min(x[0] for x in perf_spectrum["points"])
max_x = max(x[-1] for x in perf_spectrum["points"])
all_diffs = [
x[i + 1] - x[i]
for x in perf_spectrum["points"]
for i in range(len(x) - 1)
]
min_diff = min(all_diffs)
max_diff = max(all_diffs)
points = sorted(
perf_spectrum["points"], key=lambda x: x[-1] - x[0], reverse=True
)
points = points[: math.ceil(perc_paths * len(points))]
for polyline in points:
this_pts = []
for i, p in enumerate(polyline):
p_id = "n" + str(uuid.uuid4()).replace("-", "") + "e"
first_coord = (p - min_x) / (max_x - min_x) * overall_length
second_coord = act_divider * (
len(perf_spectrum["list_activities"]) - i - 1
)
lines.append(
'%s [label="", pos="%.10f,%.10f!", shape=none, width="0px", height="0px"];' %
(p_id,
first_coord *
layout_ext_multiplier,
second_coord *
layout_ext_multiplier,
))
this_pts.append(p_id)
for i in range(len(this_pts) - 1):
diff = polyline[i + 1] - polyline[i]
color = give_color_to_line(
(diff - min_diff) / (max_diff - min_diff)
)
lines.append(
'%s -- %s [ color="%s" ];'
% (this_pts[i], this_pts[i + 1], color)
)
for i, act in enumerate(perf_spectrum["list_activities"]):
second_coord = act_divider * (
len(perf_spectrum["list_activities"]) - i - 1
)
a_id = "n" + str(uuid.uuid4()).replace("-", "") + "e"
lines.append(
'%s [label="%s", pos="%.10f,%.10f!", shape=none, width="0px", height="0px"];' %
(a_id,
act,
overall_length *
layout_ext_multiplier,
second_coord *
layout_ext_multiplier,
))
s_id = "n" + str(uuid.uuid4()).replace("-", "") + "e"
lines.append(
'%s [label="", pos="0,%.10f!", shape=none, width="0px", height="0px"];' %
(s_id, second_coord * layout_ext_multiplier))
lines.append('%s -- %s [ color="black" ];' % (s_id, a_id))
if i == len(perf_spectrum["list_activities"]) - 1:
for j in range(n_div + 1):
pos = float(j * overall_length) / float(n_div)
tst = min_x + float(j) / float(n_div) * (max_x - min_x)
dt = strpfromiso.fix_naivety(datetime.fromtimestamp(tst))
n_id = "n" + str(uuid.uuid4()).replace("-", "") + "e"
lines.append(
'%s [label="%s", pos="%.10f,%.10f!", shape=none, width="0px", height="0px"];' %
(n_id,
str(dt),
pos *
layout_ext_multiplier,
(second_coord -
date_divider) *
layout_ext_multiplier,
))
lines.append("}")
lines = "\n".join(lines)
F = open(output_file_gv.name, "w")
F.write(lines)
F.close()
os.system(
"neato -n1 -T"
+ format
+ " "
+ output_file_gv.name
+ " > "
+ output_file_img.name
)
return output_file_img.name
