def test_read_markers(
usecols,
shape_val,
first_last_val,
mean_val,
median_val,
sum_val,
nans_val,
extension,
):
if extension == "csv":
data = Markers.from_csv(**markers_csv_kwargs, usecols=usecols)
decimal = 0
elif extension == "c3d":
data = Markers.from_c3d(MARKERS_ANALOGS_C3D,
prefix_delimiter=":",
usecols=usecols)
decimal = 4
else:
raise ValueError("wrong extension provided")
if usecols and isinstance(usecols[0], str):
np.testing.assert_array_equal(x=data.channel, y=usecols)
is_expected_array(
data,
shape_val,
first_last_val,
mean_val,
median_val,
sum_val,
nans_val,
decimal=decimal,
)
DATA_FOLDER = Path("tests") / "data"
MARKERS_CSV = DATA_FOLDER / "markers.csv"
MARKERS_ANALOGS_C3D = DATA_FOLDER / "markers_analogs.c3d"
ANALOGS_CSV = DATA_FOLDER / "analogs.csv"
MARKERS_CSV_WITHOUT_HEADER = DATA_FOLDER / "markers_without_header.csv"
MARKERS_XLSX = DATA_FOLDER / "markers.xlsx"
MARKERS_TRC = DATA_FOLDER / "markers.trc"
ANALOGS_XLSX = DATA_FOLDER / "analogs.xlsx"
ANALOGS_STO = DATA_FOLDER / "inverse_dyn.sto"
ANALOGS_MOT = DATA_FOLDER / "inverse_kin.mot"
EXPECTED_VALUES_CSV = DATA_FOLDER / "is_expected_array_val.csv"
MARKERS_DATA = Markers.from_c3d(
MARKERS_ANALOGS_C3D,
usecols=["CLAV_post", "PSISl", "STERr", "CLAV_post"],
prefix_delimiter=":",
)
ANALOGS_DATA = Analogs.from_c3d(
MARKERS_ANALOGS_C3D,
usecols=["EMG1", "EMG10", "EMG11", "EMG12"],
prefix_delimiter=".",
)
EXPECTED_VALUES = pd.read_csv(
EXPECTED_VALUES_CSV,
index_col=[0],
converters={
"shape_val": eval,
"first_last_val": eval
},
# --- Markers --- #
markers_full_names = [
"XIPH", "STER", "STERback", "CLAV_SC", "CLAV_AC", "SCAP_CP", "SCAP_AA",
"SCAP_TS", "SCAP_IA", "DELT", "ARMl", "EPICl", "EPICm", "LARM_ant",
"LARM_post", "LARM_elb", "LARM_dist"
]
# markers_full_names = ["ASISr","PSISr", "PSISl","ASISl","XIPH","STER","STERlat","STERback","XIPHback","ThL",
# "CLAV_SC","CLAV_AC","SCAP_CP","SCAP_AA","SCAPspine","SCAP_TS","SCAP_IA","DELT","ARMl",
# "EPICl","EPICm","LARM_ant","LARM_post","LARM_elb","LARM_dist","STYLrad","STYLrad_up","STYLulna_up",
# "STYLulna","META2dist","META2prox","META5prox","META5dist","MAIN_opp"]
# markers_full_names = ["CLAV_SC","CLAV_AC","SCAP_CP","SCAP_AA","SCAP_TS","SCAP_IA","DELT","ARMl","EPICl",
# "EPICm","LARM_ant","LARM_post","LARM_elb","LARM_dist"]
markers_full = Markers.from_c3d(data_path, usecols=markers_full_names)
marker_rate = int(markers_full.rate)
marker_exp = markers_full[:, :, :].data * 1e-3
n_mark = marker_exp.shape[1]
# t = 0.24
n_frames = marker_exp.shape[2]
t = markers_full.time.data
marker_treat = np.ndarray(
(marker_exp.shape[0], marker_exp.shape[1], marker_exp.shape[2]))
for k in range(n_mark):
a = pd.DataFrame(marker_exp[:, k, :])
a = np.array(a.interpolate(method='polynomial', order=3, axis=1))
marker_treat[:, k, :] = a
marker_treat[3, :, :] = [1]
plt.figure("Markers")
# Rototrans_sym = RT(transX, transY, transZ, angleX, angleY, angleZ)
parent_dir_path = os.path.split(os.path.dirname(__file__))[0]
# biorbd_model = biorbd.Model(parent_dir_path +'/model_scaling/new_scal/Belaise_scaled_updated.bioMod')
biorbd_model = biorbd.Model(parent_dir_path +
'/models/arm_Belaise_real_v2.bioMod')
data = "flex"
data_path = f'./Sujet_5/{data}.c3d'
markers_names = [
"CLAV_SC", "CLAV_AC", "SCAP_CP", "SCAP_AA", "SCAP_TS", "SCAP_IA", "DELT",
"ARMl", "EPICl", "EPICm", "LARM_ant", "LARM_post", "LARM_elb", "LARM_dist"
]
# markers_names = ["XIPH", "STER", "CLAV_SC","CLAV_AC","SCAP_CP","SCAP_AA","SCAP_TS","SCAP_IA","DELT","ARMl","EPICl",
# "EPICm","LARM_ant","LARM_post","LARM_elb","LARM_dist","STYLrad", "STYLulna"]
markers = Markers.from_c3d(data_path, usecols=markers_names)
mat_contents = sio.loadmat(f"{data}.mat")
mat_contents = mat_contents["mov_reel"]
val = mat_contents[0, 0]
integ = val['integ']
q = integ['Q_reel'][0, 0]
marker_exp = markers[:, :, :q.shape[1]].data * 1e-3
n_mark = len(markers_names)
n_q = q.shape[0]
t = integ['temps'][0, 0] # 0.24s
n_frames = q.shape[1]
marker_model = np.ndarray((4, n_mark, n_frames))
symbolic_states = MX.sym("q", n_q, 1)
# markers_func = Function(
from pathlib import Path
import numpy as np
from pyomeca import Markers, Rototrans, Angles
from bioviz.biorbd_vtk import VtkModel, VtkWindow, Mesh
# Path to data
DATA_FOLDER = Path(
"/home/pariterre/Programmation/biorbd-viz") / "tests" / "data"
MARKERS_CSV = DATA_FOLDER / "markers.csv"
MARKERS_ANALOGS_C3D = DATA_FOLDER / "markers_analogs.c3d"
# Load data
d = Markers.from_c3d(MARKERS_ANALOGS_C3D,
usecols=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
prefix_delimiter=":")
d2 = Markers.from_c3d(MARKERS_ANALOGS_C3D,
usecols=["CLAV_post", "PSISl", "STERr", "CLAV_post"],
prefix_delimiter=":")
# mean of first 3 markers
d3 = Markers.from_c3d(MARKERS_ANALOGS_C3D,
usecols=[0, 1, 2],
prefix_delimiter=":").mean("channel", keepdims=True)
# Create a windows with a nice gray background
vtkWindow = VtkWindow(background_color=(0.5, 0.5, 0.5))
# Add marker holders to the window
vtkModelReal = VtkModel(vtkWindow,
markers_color=(1, 0, 0),