PIV computation in parallel with TopologyPIV

This minimal example presents how to carry out a simple PIV computation. See also the documentation of the class fluidimage.topologies.piv.TopologyPIV and the work defined in the subpackage fluidimage.works.piv.

from fluidimage import get_path_image_samples
from fluidimage.piv import Topology

params = Topology.create_default_params()

params.series.path = get_path_image_samples() / "Karman/Images"

params.mask.strcrop = "50:350, 0:380"

params.piv0.shape_crop_im0 = 32
params.piv0.displacement_max = 5
params.piv0.nb_peaks_to_search = 2

params.fix.correl_min = 0.4
params.fix.threshold_diff_neighbour = 2.0

params.multipass.number = 2
params.multipass.use_tps = "last"

# params.saving.how = 'complete'
params.saving.postfix = "piv_example"

topology = Topology(params, logging_level="info")

# To produce a graph of the topology
# topology.make_code_graphviz('topo.dot')

# Compute in parallel
topology.compute()
# topology.compute("multi_exec_subproc")

# Compute in sequential (for debugging)
# topology.compute(sequential=True)

We now show a similar example but with a simple preprocessing (using a function im2im):

from fluidimage import get_path_image_samples
from fluidimage.piv import Topology

params = Topology.create_default_params()

params.series.path = get_path_image_samples() / "Karman/Images"
params.series.ind_start = 1
params.series.ind_step = 2

params.piv0.shape_crop_im0 = 32
params.multipass.number = 2
params.multipass.use_tps = False

params.mask.strcrop = ":, 50:500"

params.saving.how = "recompute"
params.saving.postfix = "piv_im2im_func_example"

# we use the light versatile preprocessing feature:
params.preproc.im2im = "my_example_im2im.im2im"

# Here the "image to image" function will be imported with the statement
# `from my_example_im2im import im2im`

topology = Topology(params, logging_level="info")

# To produce a graph of the topology
topology.make_code_graphviz("topo.dot")

# Compute in parallel
topology.compute()

# Compute in sequential (for debugging)
# topology.compute(sequential=True)

assert len(topology.results) == 1

The file my_example_im2im.py should be importable (for example in the same directory than piv_parallel_im2im.py)

"""This is a very silly example of importable module where we define a
"filter" function im2im.

"""


def im2im(tuple_name_image):
    _, im = tuple_name_image
    print("in the function im2im...")
    return 2 * im

Same thing but the preprocessing is done with a class Im2Im

from fluidimage import get_path_image_samples
from fluidimage.piv import Topology

params = Topology.create_default_params()

params.series.path = get_path_image_samples() / "Karman/Images"
params.series.ind_start = 1
params.series.ind_step = 2

params.piv0.shape_crop_im0 = 32
params.multipass.number = 2
params.multipass.use_tps = False

params.mask.strcrop = ":, 50:500"

params.saving.how = "recompute"
params.saving.postfix = "piv_im2im_cls_example"

# we use the light versatile preprocessing feature:
params.preproc.im2im = "my_example_im2im_class.Im2Im"
params.preproc.args_init = ("arg0", "arg1")

# Here, the class will be imported with the statement
# `from my_example_im2im_class import Im2Im`

topology = Topology(params, logging_level="info")

# To produce a graph of the topology
topology.make_code_graphviz("topo.dot")

# Compute in parallel
topology.compute()

# Compute in sequential (for debugging)
# topology.compute(sequential=True)

assert len(topology.results) == 1

The file my_example_im2im_class.py should be importable (for example in the same directory than piv_parallel_im2im_class.py)

"""This is a very silly example of importable module where we define a
"filter" class Im2Im.

"""


class Im2Im:
    def __init__(self, arg0, arg1):
        self.arg0 = arg0
        self.arg1 = arg1

    def calcul(self, tuple_name_image):
        _, image = tuple_name_image
        print(f"in the function Im2Im.calcul (arg0={self.arg0})...")
        return 2 * image