def get_points(points_file):
"""Get grid points extracted from calibration images
"""
imgpts = ParamContainer(path_file=points_file)
tidy_container(imgpts)
imgpts = imgpts.geometry_calib.source_calib.__dict__
points = [x for x in imgpts.keys() if "point_" in x or "Point" in x]
points.sort()
# [X, Y, Z, x, y]
results = [[], [], [], [], []]
# X, Y and Z are coordinate in real space (physical unit)
# x and y are the indices of the pixel in the image
for point in points:
numbers = get_number_from_string2(imgpts[point])
for i, result in enumerate(results):
result.append(numbers[i])
results = [np.array(result) for result in results]
# particularity for Z
results[2] = results[2][0]
# particularity for X, Y, Z
for i in range(3):
results[i] /= 100.0
return results
def create_oper(type_fft=None, coef_dealiasing=2.0 / 3):
params = ParamContainer(tag="params")
params._set_attrib("ONLY_COARSE_OPER", False)
params._set_attrib("f", 0)
params._set_attrib("c2", 100)
params._set_attrib("kd2", 0)
OperatorsPseudoSpectralSW1L._complete_params_with_default(params)
if mpi.nb_proc == 1:
nh = 9
else:
nh = 8
params.oper.nx = nh
params.oper.ny = nh
Lh = 6.0
params.oper.Lx = Lh
params.oper.Ly = Lh
if type_fft is not None:
params.oper.type_fft = type_fft
params.oper.coef_dealiasing = coef_dealiasing
oper = OperatorsPseudoSpectralSW1L(params=params)
return oper
def create_default_params(cls):
"""Class method returning the default parameters."""
params = ParamContainer(tag='params')
params._set_child('preproc')
params.preproc._set_child('series', attribs={'path': ''})
PreprocTools._complete_class_with_tools(params)
return params
def create_default_params(cls):
"""Class method returning the default parameters."""
params = ParamContainer(tag='params')
params._set_child('preproc')
params.preproc._set_child('series', attribs={'path': ''})
PreprocTools._complete_class_with_tools(params)
return params
def get_grid_pixel_from_piv_file(path, index_pass=-1):
"""Recompute 1d arrays containing the approximate positions of the vectors
Useful to compute a grid on which we can interpolate the displacement fields.
Parameters
----------
path: str
Path of a PIV file.
index_pass: int
Index of the pass
Returns
-------
xs1d: np.ndarray
Indices (2nd, direction "x") of the pixel in the image
ys1d: np.ndarray
Indices (1st, direction "y") of the pixel in the image
"""
with h5py.File(path) as f:
params = ParamContainer(hdf5_object=f["params"])
shape_images = f["couple/shape_images"].value
return get_grid_pixel(params, shape_images, index_pass)
def open_file(self):
path_file = QtWidgets.QFileDialog.getOpenFileName(
self.centralwidget, "OpenFile")
params = ParamContainer(path_file=path_file)
print(params)
raise NotImplementedError
def pandas_from_path(p, key, as_df=False):
init_field, c, nh, Bu, init_field_const = keyparams_from_path(p)
params_xml_path = os.path.join(p, "params_simul.xml")
params = ParamContainer(path_file=params_xml_path)
# sim = fls.load_sim_for_plot(p, merge_missing_params=True)
c = int(c)
kf = _k_f(params)
Lf = np.pi / kf
kd_kf = _k_diss(params) / kf
# ts = _t_stationary(path=p)
# eps = _eps(t_start=ts, path=p)
eps, E, ts, tmax = epsetstmax(p)
efr = params.preprocess.init_field_const
if params.nu_2 > 0:
Re = eps**(1 / 3) * Lf**(4 / 3) / params.nu_2
else:
Re = np.nan # defined differently
Fr = (eps * Lf)**(1.0 / 3) / c
try:
Ro = (eps / Lf**2)**(1.0 / 3) / params.f
except ZeroDivisionError:
Ro = np.inf
minh = 0
maxuc = 0
# del sim
gc.collect()
data = [
nh,
c,
params.nu_8,
params.nu_2,
params.f,
eps,
kd_kf,
Fr,
Ro,
Re,
Re * Fr**(2 / 3),
Bu,
# minh, maxuc,
efr,
E,
ts,
tmax,
key,
]
if as_df:
return pd.DataFrame(data, columns=pd_columns)
else:
return pd.Series(data, index=pd_columns)
def save(self, zs, ret, mtx, dist, rvecs, tvecs):
self.params = params = ParamContainer(tag="CalibCV")
params._set_attribs({
"class": self.__class__.__name__,
"module": self.__module__,
"f": np.diag(mtx)[:2],
"C": mtx[0:2, 2],
"cam_mtx": mtx,
"kc": dist.T[0],
"rotation": np.array(rvecs),
"translate": tvecs,
"zs": np.array(zs),
})
path_dir = os.path.dirname(self.path_file)
os.makedirs(path_dir, exist_ok=True)
if os.path.exists(self.path_file):
print(f"WARNING: {self.path_file} already exists. Skipping save.")
else:
params._save_as_hdf5(self.path_file)
def create_default_params(cls):
"Create an object containing the default parameters (class method)."
params = ParamContainer(tag="params")
cls._complete_params_with_default(params)
return params
def create_default_params(cls):
params = ParamContainer(tag="params")
cls._complete_params_with_default(params)
return params
def params_from_path(p):
params_xml_path = os.path.join(p, "params_simul.xml")
params = ParamContainer(path_file=params_xml_path)
return params
def create_default_params():
"""Class method returning the default parameters.
For developers: cf. fluidsim.base.params
"""
params = ParamContainer(tag="params")
params._set_child(
"series",
attribs={
"path": "",
"strcouple": "i:i+2",
"ind_start": 0,
"ind_stop": None,
"ind_step": 1,
},
)
params.series._set_doc(
"""
Parameters indicating the input series of images.
path : str, {''}
String indicating the input images (can be a full path towards an image
file or a string given to `glob`).
strcouple : 'i:i+2'
String indicating as a Python slicing how couples of images are formed.
There is one couple per value of `i`. The values of `i` are set with the
other parameters `ind_start`, `ind_step` and `ind_stop` approximately with
the function range (`range(ind_start, ind_stop, ind_step)`).
Python slicing is a very powerful notation to define subset from a
(possibly multidimensional) set of images. For a user, an alternative is to
understand how Python slicing works. See for example this page:
http://stackoverflow.com/questions/509211/explain-pythons-slice-notation.
Another possibility is to follow simple examples:
For single-frame images (im0, im1, im2, im3, ...), we keep the default
value 'i:i+2' to form the couples (im0, im1), (im1, im2), ...
To see what it gives, one can use ipython and range:
>>> i = 0
>>> list(range(10))[i:i+2]
[0, 1]
>>> list(range(10))[i:i+4:2]
[0, 2]
We see that we can also use the value 'i:i+4:2' to form the couples (im0,
im2), (im1, im3), ...
For double-frame images (im1a, im1b, im2a, im2b, ...) you can write
>>> params.series.strcouple = 'i, 0:2'
In this case, the first couple will be (im1a, im1b).
To get the first couple (im1a, im1a), we would have to write
>>> params.series.strcouple = 'i:i+2, 0'
ind_start : int, {0}
ind_step : int, {1}
int_stop : None
"""
)
params._set_child(
"saving", attribs={"path": None, "how": "ask", "postfix": "piv"}
)
params.saving._set_doc(
"""Saving of the results.
path : None or str
Path of the directory where the data will be saved. If None, the path is
obtained from the input path and the parameter `postfix`.
how : str {'ask'}
'ask', 'new_dir', 'complete' or 'recompute'.
postfix : str
Postfix from which the output file is computed.
"""
)
WorkPIV._complete_params_with_default(params)
params._set_internal_attr(
"_value_text",
json.dumps(
{
"program": "fluidimage",
"module": "fluidimage.topologies.piv",
"class": "TopologyPIV",
}
),
)
params._set_child("preproc")
image2image.complete_im2im_params_with_default(params.preproc)
return params
def __init__(self, path_file="cam.h5"):
self.path_file = str(path_file)
if os.path.exists(path_file):
print(f"Loading {path_file}.")
self.params = ParamContainer(path_file=self.path_file)
def create_info_simul(info_solver, params):
"""Create a ParamContainer instance gathering info_solver and params."""
info = ParamContainer(tag="info_simul")
info._set_as_child(info_solver)
info._set_as_child(params)
return info
def make_params_calibration(path_file):
"""Make a tidy parameter container from a UVmat file.
"""
params = ParamContainer(tag="calib")
calib_uvmat = ParamContainer(path_file=str(path_file))
tidy_container(calib_uvmat)
calib_uvmat = calib_uvmat["geometry_calib"]
f = [float(n) for n in np.array(get_number_from_string(calib_uvmat.fx_fy))]
C = np.array(get_number_from_string(calib_uvmat.cx__cy))
kc = np.array(calib_uvmat.kc)
T = np.array(get_number_from_string(calib_uvmat.tx__ty__tz))
R = []
for i in range(3):
R = np.hstack(
[R, get_number_from_string(calib_uvmat["r_{}".format(i + 1)])]
)
omc = np.array(get_number_from_string(calib_uvmat["omc"]))
params._set_attribs({"f": f, "C": C, "kc": kc, "T": T, "R": R, "omc": omc})
if calib_uvmat.nb_slice is not None:
nb_slice = np.array(calib_uvmat["nb_slice"])
zslice_coord = np.zeros([nb_slice, 3])
if calib_uvmat.nb_slice == 1:
zslice_coord[:] = get_number_from_string(calib_uvmat["slice_coord"])
if (
hasattr(calib_uvmat, "slice_angle")
and calib_uvmat["slice_angle"] is not None
):
slice_angle = np.zeros([nb_slice, 3])
slice_angle[:] = get_number_from_string(
calib_uvmat["slice_angle"]
)
else:
slice_angle = [0, 0, 0]
else:
for i in range(nb_slice):
zslice_coord[i][:] = get_number_from_string(
calib_uvmat["slice_coord_{}".format(i + 1)]
)
if (
hasattr(calib_uvmat, "slice_angle_1")
and calib_uvmat["slice_angle_1"] is not None
):
slice_angle = np.zeros([nb_slice, 3])
for i in range(nb_slice):
slice_angle[i][:] = get_number_from_string(
calib_uvmat["slice_angle_{}".format(i + 1)]
)
else:
slice_angle = [0, 0, 0]
params._set_child(
"slices",
attribs={
"nb_slice": nb_slice,
"zslice_coord": zslice_coord,
"slice_angle": slice_angle,
},
)
if hasattr(calib_uvmat, "refraction_index"):
params._set_attrib("refraction_index", calib_uvmat.refraction_index)
if hasattr(calib_uvmat, "interface_coord"):
params._set_attrib(
"interface_coord",
get_number_from_string(calib_uvmat["interface_coord"]),
)
return params
def load_params(path):
if os.path.isdir(path):
path = os.path.join(path, "params_simul.xml")
return ParamContainer(path_file=path)
