# ``parser.parse``
import fym.utils.parser as parser
from fym.core import BaseEnv, BaseSystem
json_dict = {
"env.kwargs": dict(dt=0.01, max_t=10),
"multicopter.nrotor": 6,
"multicopter.m": 3.,
"multicopter.LQRGain": {
"Q": [1, 1, 1, 1],
"R": [1, 1],
},
"actuator.tau": 1e-1,
}
cfg = parser.parse(json_dict)
# # ``parser.update``
# cfg = parser.parse()
# def load_config():
# parser.update(cfg, {
# "env.kwargs": dict(dt=0.01, max_t=10),
# "agent.memory_size": 1000,
# "agent.minibatch_size": 32,
# })
# load_config()
# cfg.env.kwargs.dt = 0.001
# # ``parser.decode``
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from matplotlib.patches import Circle
import mpl_toolkits.mplot3d.art3d as art3d
from fym.core import BaseEnv, BaseSystem
from fym.utils.linearization import jacob_analytic
from fym.agents import LQR
from fym.utils import parser
import fym.logging
from fym.models.quadrotor import Quadrotor
import agents
import logs
cfg = parser.parse()
def load_config():
fym.parser.update(cfg, {"path.base": Path("data", "exp7")})
fym.parser.update(
cfg, {
"path": {
"sample":
Path(cfg.path.base, "sampled_data"),
"train.sql":
Path(cfg.path.base, "train", "result-sql.h5"),
"train.klm":
Path(cfg.path.base, "train", "result-klm.h5"),
"train.sql_stable":
Path(cfg.path.base, "train", "result-sql-stable.h5"),
import fym.utils.parser as parser
cfg = parser.parse({
"env.kwargs": dict(dt=0.01, max_t=10),
"multicopter.nrotor": 6,
"multicopter.m": 3.,
"multicopter.LQRGain": {
"Q": [1, 1, 1, 1],
"R": [1, 1],
},
"actuator.tau": 1e-1,
})
class LQR:
def __init__(self):
self.Q = cfg.multicopter.LQRGain.Q
self.R = cfg.multicopter.LQRGain.R
return np.array([[2 * x1, 0], [x2, x1], [0, 2 * x2]])
np.random.seed(0)
# Parameter setup
cfg = parser.parse({
"env": {
"max_t": 20,
"dt": 0.0025,
},
"initial": {
"X": np.deg2rad(np.vstack((5, -5))),
"W1": 0.01 * np.random.rand(3, 1),
"W2": 0.01 * np.random.rand(3, 1),
},
"Q": np.diag([0.1, 0.1]),
"R": np.diag([0.1]),
"T": 1,
"agent": {
"F1": 1,
"F2": 1,
"alp1": 1e3,
"alp2": 1,
},
})
aerodata = scipy.io.loadmat("Data.mat", squeeze_me=True)
parser.update(
cfg, {
"A": np.array([[aerodata["Za"], 1], [aerodata["Ma"], aerodata["Mq"]]]),
"B": np.vstack([aerodata["Zdp"], aerodata["Mdp"]]),