9938786759

Committed 15 Jul 2024 11:46AM UTC coverage: 79.516% (+8.6%) from 70.904%

Build # 9938786759

Build Type

push

github

Committed by

web-flow

Commit Message

Merge pull request #289 from WISDEM/develop

Release with improved installation

Run Details

163 of 521 new or added lines in 17 files covered. (31.29%)

707 existing lines in 19 files now uncovered.

21602 of 27167 relevant lines covered (79.52%)

0.8 hits per line

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0.0

/weis/visualization/opt_plotting.py

NEW 1	import glob	×
2
NEW 3	import glob	×
NEW 4	import json	×
NEW 5	import multiprocessing as mp	×
6
NEW 7	import pandas as pd	×
NEW 8	import numpy as np	×
NEW 9	import matplotlib.pyplot as plt	×
10
NEW 11	import openmdao.api as om	×
12
NEW 13	from weis.visualization.utils import *	×
14
15
NEW 16	def plot_conv(	×
17	keyset_in,
18	map_dataOM_vars,
19	use_casewise_feasibility=False,
20	feas_tol=1e-5,
21	figax=None,
22	alpha=None,
23	):
24	"""
25	plot a set of keys
26
27	args:
28	keyset_in: list[str]
29	list of keys to plot the convergence data for
30	map_dataOM_vars: dict[str -> dict]
31	map from a case of interest by name to an OM data dict to plot
32	use_casewise_feasibility: bool
33	if plotting a constraint should we plot feasibility w.r.t. that constraint (vs. all)
34
35	returns:
36	fig : plt.Figure
37	ax : plt.Axes
38	"""
39
NEW 40	if len(keyset_in) == 0:	×
NEW 41	return	×
42
NEW 43	markerstyle = "x"	×
NEW 44	markersize = 5	×
NEW 45	linestyle = "-"	×
46
NEW 47	fig, axes = plt.subplots(	×
48	len(keyset_in),
49	1,
50	sharex=True,
51	figsize=(6, 0.60 * 4 * len(keyset_in)),
52	squeeze=False,
53	dpi=150,
54	)
55
NEW 56	has_ref_vals = type(keyset_in) == dict	×
57
NEW 58	if has_ref_vals:	×
NEW 59	key_val_map = keyset_in	×
NEW 60	keyset = keyset_in.keys()	×
61	else:
NEW 62	keyset = keyset_in	×
63
NEW 64	pt_imethod = []	×
NEW 65	for imethod, method in enumerate(map_dataOM_vars.keys()):	×
NEW 66	if imethod == 0:	×
NEW 67	markerstyle = "o"	×
NEW 68	elif imethod == 1:	×
NEW 69	markerstyle = "p"	×
NEW 70	elif imethod == 2:	×
NEW 71	markerstyle = "s"	×
72	else:
NEW 73	markerstyle = "P"	×
74
NEW 75	pt0 = axes[0, 0].plot(	×
76	[],
77	[],
78	markerstyle + linestyle,
79	label=method,
80	markersize=markersize,
81	# color=(0.5,0.5,0.5),
82	alpha=alpha,
83	)
NEW 84	dataOM = map_dataOM_vars[method][0]	×
NEW 85	vars = map_dataOM_vars[method][1]	×
NEW 86	tfeas, varfeas = get_feasible_iterations(dataOM, vars, feas_tol=feas_tol)	×
87
NEW 88	for idx_ax, key in enumerate(keyset):	×
NEW 89	if key in ["rank", "iter",]: continue	×
NEW 90	if use_casewise_feasibility and key in varfeas.keys():	×
NEW 91	feas_val = varfeas[key]	×
92	else:
NEW 93	feas_val = tfeas # use total feasibility	×
94
NEW 95	axes[idx_ax, 0].plot(	×
96	np.squeeze(dataOM[key]),
97	linestyle,
98	label="".join(["_", method, "_"]),
99	color=pt0[-1].get_color(),
100	markersize=markersize,
101	alpha=alpha,
102	)
NEW 103	axes[idx_ax, 0].plot(	×
104	np.ma.array(
105	dataOM[key],
106	mask=~(
107	feas_val * np.ones(
108	(
109	1,
110	np.array(dataOM[key]).shape[1]
111	if len(np.array(dataOM[key]).shape) > 1
112	else 1
113	),
114	dtype=bool,
115	)
116	)
117	),
118	markerstyle,
119	label="".join(["_", method, "_"]),
120	color=pt0[-1].get_color(),
121	alpha=alpha,
122	fillstyle="full",
123	markersize=markersize,
124	)
NEW 125	axes[idx_ax, 0].plot(	×
126	np.ma.array(
127	dataOM[key],
128	mask=(
129	feas_val * np.ones(
130	(
131	1,
132	np.array(dataOM[key]).shape[1]
133	if len(np.array(dataOM[key]).shape) > 1
134	else 1
135	),
136	dtype=bool,
137	)
138	)
139	),
140	markerstyle,
141	label="".join(["_", method, "_"]),
142	color=pt0[-1].get_color(),
143	alpha=alpha,
144	fillstyle="none",
145	markersize=markersize,
146	)
NEW 147	if has_ref_vals:	×
NEW 148	cval = key_val_map[key]	×
NEW 149	if cval[0] is not None:	×
NEW 150	axes[idx_ax, 0].plot([0, len(dataOM[key])], [cval[0], cval[0]], "b:", label="_lower bound_")	×
NEW 151	if cval[1] is not None:	×
NEW 152	axes[idx_ax, 0].plot([0, len(dataOM[key])], [cval[1], cval[1]], "r:", label="_upper bound_")	×
NEW 153	axes[idx_ax, 0].set_title(key)	×
154
NEW 155	if has_ref_vals:	×
NEW 156	axes[0, 0].plot([], [], "b:", label="lower bound")	×
NEW 157	axes[0, 0].plot([], [], "r:", label="upper bound")	×
NEW 158	axes[0, 0].legend()	×
NEW 159	fig.tight_layout()	×
160
NEW 161	return fig, axes	×
162

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