from importlib_resources import files
from openpiv import windef



settings = windef.PIVSettings()
print(settings)

# 'Data related settings'
# Folder with the images to process
settings.filepath_images = files('openpiv') / "data" / "test1"
# Folder for the outputs
settings.save_path = settings.filepath_images.parent

# Root name of the output Folder for Result Files
settings.save_folder_suffix = 'Test_1'
# Format and Image Sequence
settings.frame_pattern_a = 'exp1_001_a.bmp'
settings.frame_pattern_b = 'exp1_001_b.bmp'

# 'Region of interest'
# (50,300,50,300) #Region of interest: (xmin,xmax,ymin,ymax) or 'full' for full image
settings.roi = 'full'

# 'Image preprocessing'
# 'None' for no masking, 'edges' for edges masking, 'intensity' for intensity masking
# WARNING: This part is under development so better not to use MASKS
settings.dynamic_masking_method = None
settings.dynamic_masking_threshold = 0.005
settings.dynamic_masking_filter_size = 7

# 'Processing Parameters'
settings.correlation_method = 'circular'  # 'circular' or 'linear'
settings.normalized_correlation = False
settings.num_iterations = 2  # select the number of PIV passes
# add the interroagtion window size for each pass.
# For the moment, it should be a power of 2
# if longer than n iteration the rest is ignored
settings.windowsizes = (64, 32, 16)
# The overlap of the interroagtion window for each pass.
settings.overlap = (32, 16, 8)  # This is 50% overlap
# Has to be a value with base two. In general window size/2 is a good choice.
# methode used for subpixel interpolation: 'gaussian','centroid','parabolic'
settings.subpixel_method = 'gaussian'
# 'symmetric' or 'second image', 'symmetric' splits the deformation on bot images
# while 'second image' does only deform the second image.
settings.deformation_method = 'symmetric'  # 'symmetric' or 'second image'
# order of the image interpolation for the window deformation
settings.interpolation_order = 3
settings.scaling_factor = 1  # scaling factor pixel/meter
settings.dt = 1  # time between to frames (in seconds)
# Signal to noise ratio options (only for the last pass)'
# It is possible to decide if the S/N should be computed (for the last
# pass) or not
# 'True' or 'False' (only for the last pass)
# settings.extract_sig2noise = False
# method used to calculate the signal to noise ratio 'peak2peak' or 'peak2mean'
settings.sig2noise_method = 'peak2peak'
# select the width of the masked to masked out pixels next to the main peak
settings.sig2noise_mask = 2
# If extract_sig2noise==False the values in the signal to noise ratio
# output column are set to NaN
# 'vector validation options'
# choose if you want to do validation of the first pass: True or False
settings.validation_first_pass = True
# only effecting the first pass of the interrogation the following passes
# in the multipass will be validated
# 'Validation Parameters'
# The validation is done at each iteration based on three filters.
# The first filter is based on the min/max ranges. Observe that these values are defined in
# terms of minimum and maximum displacement in pixel/frames.
settings.min_max_u_disp = (-30, 30)
settings.min_max_v_disp = (-30, 30)
# The second filter is based on the global STD threshold
settings.std_threshold = 7  # threshold of the std validation
# The third filter is the median test (not normalized at the moment)
settings.median_threshold = 3  # threshold of the median validation
# On the last iteration, an additional validation can be done based on the S/N.
settings.median_size = 1  # defines the size of the local median
# 'Validation based on the signal to noise ratio'
# Note: only available when extract_sig2noise==True and only for the last
# pass of the interrogation
# Enable the signal to noise ratio validation. Options: True or False
settings.sig2noise_validate = False  # This is time consuming
# minmum signal to noise ratio that is need for a valid vector
settings.sig2noise_threshold = 1.2
# 'Outlier replacement or Smoothing options'
# Replacment options for vectors which are masked as invalid by the validation
settings.replace_vectors = True  # Enable the replacment. Chosse: True or False
settings.smoothn = True  # Enables smoothing of the displacemenet field
settings.smoothn_p = 0.5  # This is a smoothing parameter
# select a method to replace the outliers: 'localmean', 'disk', 'distance'
settings.filter_method = 'localmean'
# maximum iterations performed to replace the outliers
settings.max_filter_iteration = 4
settings.filter_kernel_size = 2  # kernel size for the localmean method
# Output options'
# Select if you want to save the plotted vectorfield: True or False
settings.save_plot = False
# Choose wether you want to see the vectorfield or not :True or False
settings.show_plot = True
settings.scale_plot = 200  # select a value to scale the quiver plot of the vectorfield
# run the script with the given settings

windef.piv(settings)
