diffsol 0.11.0

A library for solving ordinary differential equations (ODEs) in Rust.
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127

import json
import glob
import matplotlib.pyplot as plt
import numpy as np
from pprint import pprint

bench_dirs = glob.glob('target/criterion/*')
sundials_reference = {}
problems = [
    {
        "name": "robertson", 
        "reference_name": "roberts_dns",
        "arg": None,
        "solvers": ["nalgebra_esdirk34", "nalgebra_tr_bdf2", "nalgebra_bdf", "nalgebra_bdf_diffsl"]
    },
    {
        "name": "robertson_ode",
        "reference_name": "robertson_ode_klu",
        "arg": [25, 100, 400, 900],
        #"solvers": ["faer_sparse_bdf_klu"],
        "solvers": ["faer_sparse_bdf"],
    },
    {
        "name": "heat2d",
        "reference_name": "heat2d_klu",
        "arg": [5, 10, 20, 30],
        "solvers": ["faer_sparse_esdirk", "faer_sparse_tr_bdf2", "faer_sparse_bdf", "faer_sparse_bdf_diffsl"]
        #"solvers": ["faer_sparse_esdirk_klu", "faer_sparse_tr_bdf2_klu", "faer_sparse_bdf_klu", "faer_sparse_bdf_klu_diffsl"]
    },
    {
        "name": "foodweb",
        "reference_name": "foodweb_bnd",
        "arg": [5, 10, 20, 30],
        "solvers": ["faer_sparse_esdirk", "faer_sparse_tr_bdf2", "faer_sparse_bdf", "faer_sparse_bdf_diffsl"]
        #"solvers": ["faer_sparse_esdirk_klu", "faer_sparse_tr_bdf2_klu", "faer_sparse_bdf_klu", "faer_sparse_bdf_klu_diffsl"]
    },
]
estimates = {}
for problem in problems:
    estimates[problem['name']] = {}
    estimates[problem['name']]['reference'] = []
    if problem['arg'] is None:
        reference_dirs = [f"target/criterion/sundials_{problem['reference_name']}"]
    else:
        reference_dirs = [f"target/criterion/sundials_{problem['reference_name']}_{arg}" for arg in problem['arg']]
    for reference_dir in reference_dirs:
        with open(f"{reference_dir}/new/estimates.json") as f:
            bench = json.load(f)
            estimates[problem['name']]['reference'].append(bench["mean"]["point_estimate"])
    for solver in problem['solvers']:
        estimates[problem['name']][solver] = {}
        estimates[problem['name']][solver]['diffsol'] = []
        estimates[problem['name']][solver]['args'] = []
        if problem['arg'] is None:
            diffsol_dirs = [f"target/criterion/{solver}_{problem['name']}"]
        else:
            diffsol_dirs = [f"target/criterion/{solver}_{problem['name']}_{arg}" for arg in problem['arg']]

        for diffsol_dir in diffsol_dirs:
            with open(f"{diffsol_dir}/new/estimates.json") as f:
                bench = json.load(f)
                estimates[problem['name']][solver]['diffsol'].append(bench["mean"]["point_estimate"])

fig1 = plt.figure(figsize=(12, 4))
(ax1, ax2) = fig1.subplots(1, 2, sharex=True, sharey=True)
fig2 = plt.figure(figsize=(6, 4))
ax3 = fig2.subplots(1, 1)
fig3 = plt.figure(figsize=(6, 4))
ax4 = fig3.subplots(1, 1)
for problem in problems:
    for solver in problem['solvers']:
        reference = np.array(estimates[problem['name']]['reference'])
        #if 'diffsl' in solver:
        #    reference = np.array(estimates[problem['name']][solver.replace("_diffsl", "")]['diffsol'])
        y = np.array(estimates[problem['name']][solver]['diffsol']) / reference
        label = f"{problem['name']}_{solver}"
        if 'tr_bdf2' in solver:
            axs = (ax1,)
        elif 'esdirk' in solver:
            axs = (ax2,)
        elif 'diffsl' in solver:
            axs = (ax4,)
        #elif 'nalgebra_bdf' in solver or 'faer_sparse_bdf' in solver and 'klu' not in solver and 'robertson_ode' not in problem['name']:
        #    axs = (ax3, ax4)
        else:
            axs = (ax3,)
        if 'foodweb' in problem['name']:
            color = 'red'
        elif 'heat2d' in problem['name']:
            color = 'blue'
        elif 'robertson_ode' in problem['name']:
            color = 'green'
        else:
            color = 'orange'

        if problem['arg'] is None:
            # plot a horizontal line
            for ax in axs: 
                ax.plot([5, 30], [y, y], label=label, color=color)
        elif 'robertson_ode' in problem['name']:
            for ax in axs: 
                ax.plot(np.sqrt(problem['arg']), y, label=label, color=color)
        else:
            for ax in axs: 
                ax.plot(problem['arg'], y, label=label, color=color)
for ax in [ax1, ax2, ax3, ax4]:
    ax.set_yscale('log')
    ax.set_yticks([0.1, 1, 10])
    ax.tick_params(axis='y', which='minor')
    ax.set_ylabel("Time relative to sundials")
    ax.set_xlabel("Problem size (grid size if applicable)")
    ax.legend()
ax1.set_title("TR-BDF2 solver")
ax2.set_title("ESDIRK solver")
ax3.set_title("BDF solver")
ax4.set_title("BDF solver + DiffSL")

basedir = "book/src/benchmarks/images"
fig1.savefig(f"{basedir}/bench_tr_bdf2_esdirk.svg")
fig2.savefig(f"{basedir}/bench_bdf.svg")
fig3.savefig(f"{basedir}/bench_bdf_diffsl.svg")
basedir = "."
fig1.savefig(f"{basedir}/bench_tr_bdf2_esdirk.png")
fig2.savefig(f"{basedir}/bench_bdf.png")
fig3.savefig(f"{basedir}/bench_bdf_diffsl.png")