Example of various pivpy methods

In [1]:

    

from pivpy import io, pivpy, graphics
import numpy as np
import xarray as xr
import os
import pkg_resources as pkg

import matplotlib.pyplot as plt
%matplotlib inline


    

In [2]:

    

f1 = 'Run000001.T000.D000.P000.H001.L.vec'
f2 = 'Run000002.T000.D000.P000.H001.L.vec'
path = pkg.resource_filename('pivpy','data')

a = io.load_vec(os.path.join(path,f1))
b = io.load_vec(os.path.join(path,f2))


    

In [3]:

    

# select where t = 1 (explicit time)
fig, ax = graphics.quiver(a.sel(t=1),arrScale=10)

#increase figure size
fig.set_size_inches(11,8)


    

In [4]:

    

# select just the first frame whatever t is .
b['t'] += 10
# define size before the plot
plt.figure(figsize=(11,8))

# show less vectors using nthArr 
fig, ax = graphics.quiver(b.isel(t=0),arrScale=10,nthArr=2)


    

In [5]:

    

c = a.piv.crop([5, 15,-5,-15])
a.u.shape, c.u.shape


    

    
Out[5]:





((63, 63, 1), (32, 32, 1))

In [6]:

    

# define size before the plot
plt.figure(figsize=(11,8))

# show less vectors using nthArr 
fig, ax = graphics.quiver(c.isel(t=0),arrScale=10,nthArr=2)


    

In [7]:

    

# want to play with some synthetic data? 
c = io.create_sample_dataset()
print(c)


    

    




<xarray.Dataset>
Dimensions:  (t: 5, x: 8, y: 5)
Coordinates:
  * x        (x) float64 32.0 45.71 59.43 73.14 86.86 100.6 114.3 128.0
  * y        (y) float64 16.0 44.0 72.0 100.0 128.0
  * t        (t) int64 0 1 2 3 4
Data variables:
    u        (x, y, t) float64 1.0 1.0 1.0 1.0 1.0 2.75 ... 8.0 8.0 8.0 8.0 8.0
    v        (x, y, t) float64 0.3062 -0.04227 -0.4652 ... 0.4233 0.3804 0.01454
    chc      (x, y, t) float64 1.0 1.0 1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0 1.0
Attributes:
    variables:  ['x', 'y', 'u', 'v']
    units:      ['pix', 'pix', 'pix/dt', 'pix/dt']
    dt:         1.0
    files:      

In [8]:

    

# want to slice it and not crop? 
d = c.sel(x = slice(35,70),y=slice(30,90))
print(d)


    

    




<xarray.Dataset>
Dimensions:  (t: 5, x: 2, y: 2)
Coordinates:
  * x        (x) float64 45.71 59.43
  * y        (y) float64 44.0 72.0
  * t        (t) int64 0 1 2 3 4
Data variables:
    u        (x, y, t) float64 2.75 2.75 2.75 2.75 2.75 ... 4.5 4.5 4.5 4.5 4.5
    v        (x, y, t) float64 -0.04766 -0.08423 0.2888 ... 0.248 0.09191 0.3806
    chc      (x, y, t) float64 1.0 1.0 1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0 1.0
Attributes:
    variables:  ['x', 'y', 'u', 'v']
    units:      ['pix', 'pix', 'pix/dt', 'pix/dt']
    dt:         1.0
    files:      

In [9]:

    

# want to show an ensemble average of 10 frames?
data = io.create_sample_dataset(10)

# want to change the size of arrows and figure aspectratio?
fig,_=graphics.quiver(data.piv.average,arrScale=8,aspectratio=0.5)
fig.set_size_inches(11,8)


    

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