Read Me for Smooth wall PIV dataset supporting the publication " Effect of pressure gradient histories on turbulence characteristics of turbulent boundary layers over smooth and rough walls"’
Dataset DOI: 

Date that the file was created: 01/26
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GENERAL INFORMATION
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ReadMe Author: Thomas Preskett, University of Southampton
Date of data collection: 
06/22-01/24
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SHARING/ACCESS INFORMATION
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Licenses/restrictions placed on the data, or limitations of reuse: CC-BY
Recommended citation for the data: Please use the above DOI
This dataset supports the publication:
AUTHORS: T. Preskett
TITLE: Effect of pressure gradient histories on turbulence characteristics of turbulent boundary layers over smooth and rough walls 
Type: Thesis
Links to other publicly accessible locations of the data:
Links/relationships to ancillary or related data sets: 
DATA & FILE OVERVIEW
This file contains smooth-wall PIV data for five angles of attack at 20 m/s. It includes the instantaneous fields at each position as well as the mean flow fields and boundary layer properties. 
 Each angle of attack has its own folder and in each folder is the following -
There are four folders corresponding to each position in which PIV data was taken, see chapter 3 of “Effect of pressure gradient histories on turbulence characteristics of turbulent boundary layers over smooth and rough walls” for more detail. 
In the position folder is a Coords file which contains X and Y grids corresponding to the position of the velocity vectors. Also contained in the coords file are the mean viscosity and density grids, which can be used for calculations. Also  UInfinity (U0_mean) is given from the reference pitot tube when combined with other positions. 
Also in each position folder are approximately 2000 vector fields containing U and V corresponding to the X and Y coordinates, with a file name in the format XXXX.mat
Finally there is a Mean_Flow_Fields.mat which contains the U_mean, V_mean, X, Y, nu_mean, rho_mean, uu_mean, vv_mean and uv_mean along with U0_mean which are averaged across the 2000 images. 
In each AOA folder there is also a Mean_Flow_Fields_AOA_X.mat where X is the angle of attack. This contains U_mean, V_mean, X, Y, nu_mean, rho_mean, uu_mean, vv_mean and uv_mean which have been stitched together from the four positions. The data is normalised by the corresponding U0 value from a given position then converted back using the mean U0 value from all four positions given by U0_mean in Mean_Flow_Felds_AOA_X.mat.

In the main PIV folder is Summary_PIV_All_AOA_SW.pkl which contains a dictionary, the first layer is the string of the angle of attack, for each angle of attack the following keys are used. 
'X', 'Y', 'U_mean', 'V_mean', 'rho_mean', 'nu_mean', 'uu_mean', 'vv_mean', 'uv_mean', 'Uinf', 'utau_OFI_Raw', 'X_OFI_Raw', 'utau_OFI', 'U99', 'delta_array', 'deltastar_array', 'theta_array', 'H_array'
Of note, utau_OFI_raw is OFI as measured, while utau_OFI is the utau interpreted onto the X grid of the PIV. 

Note:
Pickle (.pkl) files can be read into python using the following command
with open(dir_pkl, 'rb') as f:
      data = pickle.load(f)
matlab data files can be read in python using:
data = mat73.loadmat('file.mat')