fluidimage.topologies.piv¶
Topology for PIV computation (fluidimage.topologies.piv
)¶

class
fluidimage.topologies.piv.
TopologyPIV
(params, logging_level='info', nb_max_workers=None)[source]¶ Bases:
fluidimage.topologies.base.TopologyBase
Topology for PIV computation.
The most useful methods for the user (in particular
compute()
) are defined in the base classfluidimage.topologies.base.TopologyBase
. Parameters
 paramsNone
A ParamContainer (created with the class method
create_default_params()
) containing the parameters for the computation. logging_levelstr, {‘warning’, ‘info’, ‘debug’, …}
Logging level.
 nb_max_workersNone, int
Maximum numbers of “workers”. If None, a number is estimated from the number of cores detected. If there are memory errors, you can try to decrease the number of workers.

WorkVelocimetry
¶
Documentation for params¶
Documentation for params.series¶
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/explainpythonsslicenotation.
Another possibility is to follow simple examples:
For singleframe 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 doubleframe 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
Documentation for params.saving¶
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.
Documentation for params.piv0¶
Parameters describing one PIV step.
 shape_crop_im0int (48)
Shape of the cropped images 0 from which are computed the correlation.
 shape_crop_im1int or None
Shape of the cropped images 0 (has to be None for correl based on fft).
 displacement_maxNone
Displacement maximum used in correlation classes. The exact effect depends on the correlation method. For fft based correlation, it can also be of the form ‘50%’ and then the maximum displacement is computed for each pass as a pourcentage of max(shape_crop_im0).
 displacement_meanNone
Displacement averaged over space (NotImplemented).
method_correl : str, default ‘fftw’
Can be in [‘pythran’, ‘pycuda’, ‘scipy.signal’, ‘scipy.ndimage’, ‘theano’, ‘np.fft’, ‘fftw’, ‘cufft’, ‘skcufft’]
method_subpix : str, default ‘2d_gaussian2’
Can be in [‘2d_gaussian’, ‘2d_gaussian2’, ‘centroid’, ‘no_subpix’]
 nsubpixNone
Integer used in the subpix finder. It is related to the typical size of the particles. It has to be increased in case of peak locking (plot the histograms of the displacements).
 coef_correl_no_displNone, number
If this coefficient is not None, the correlation of the point corresponding to no displacement is multiplied by this coefficient (for the first pass).
 nb_peaks_to_search1, int
Number of peaks to search. Secondary peaks can be used during the fix step.
 particle_radius3, int
Typical radius of a particle (or more preciselly of a correlation peak). Used only if nb_peaks_to_search is larger than one.
Documentation for params.piv0.grid¶
Parameters describing the grid.
 overlapfloat (0.5)
Number smaller than 1 defining the overlap between interrogation windows.
 fromstr {‘overlap’}
Keyword for the method from which is computed the grid.
Documentation for params.mask¶
Parameters describing how images are masked.
strcrop : None, str
Twodimensional slice (for example ‘100:600, :’). If None, the whole image is used.
Documentation for params.fix¶
Parameters indicating how are detected and processed false vectors.
correl_min : 0.2
Vectors associated with correlation smaller than correl_min are considered as false vectors.
threshold_diff_neighbour : 10
Vectors for which the difference with the average vectors is larger than threshold_diff_neighbour are considered as false vectors.
displacement_max : None
Vectors larger than displacement_max are considered as false vectors.
Documentation for params.multipass¶
Multipass PIV parameters:
 numberint (default 1)
Number of PIV passes.
coeff_zoom : integer or iterable of size number  1.
Reduction coefficient defining the size of the interrogation windows for the passes 1 (second pass) to number  1 (last pass) (always defined comparing the passes i1).
use_tps : bool or ‘last’
If it is True, the interpolation is done using the Thin Plate Spline method (computationnally heavy but sometimes interesting). If it is ‘last’, the TPS method is used only for the last pass.
subdom_size : int
Number of vectors in the subdomains used for the TPS method.
smoothing_coef : float
Coefficient used for the TPS method. The result is smoother for larger smoothing_coef.
threshold_tps : float
Allowed difference of displacement (in pixels) between smoothed and input field for TPS filter.
Documentation for params.preproc¶
im2im : str {None}
Function or class to be used to process the images.
args_init : object {None}
An argument given to the init function of the class used to process the images.
Functions

Check if a name is in a queue of series 
Classes



Topology for PIV computation. 