Note

Looking for a written, copy/paste friendly version? See PIVPy tutorial.

PIVPy graphics tutorial

import xarray as xr
import numpy as np
from pivpy import io, pivpy, graphics
import matplotlib.pyplot as plt

## Let's create a sample dataset

df = io.create_sample_Dataset()
df

<xarray.Dataset> Size: 5kB
Dimensions:  (y: 10, x: 11, t: 2)
Coordinates:
  * x        (x) float64 88B 0.0 20.0 40.0 60.0 80.0 ... 140.0 160.0 180.0 200.0
  * y        (y) float64 80B 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0
  * t        (t) float64 16B 0.0 1.0
Data variables:
    u        (y, x, t) float64 2kB 1.0 1.0 2.0 2.0 3.0 ... 10.0 10.0 11.0 11.0
    v        (y, x, t) float64 2kB 1.0 1.0 1.0 1.0 1.0 ... 10.0 10.0 10.0 10.0
    chc      (y, x, t) float64 2kB 1.0 1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0 1.0
Attributes: (2)

xarray.Dataset

• Dimensions:
  • y: 10
  • x: 11
  • t: 2
• Coordinates: (3)
  • x
    (x)
    float64
    0.0 20.0 40.0 ... 160.0 180.0 200.0

    units :

    pix

    array([  0.,  20.,  40.,  60.,  80., 100., 120., 140., 160., 180., 200.])

  • y
    (y)
    float64
    0.0 10.0 20.0 ... 70.0 80.0 90.0

    units :

    pix

    array([ 0., 10., 20., 30., 40., 50., 60., 70., 80., 90.])

  • t
    (t)
    float64
    0.0 1.0

    units :

    frame

    array([0., 1.])

• Data variables: (3)
  • u
    (y, x, t)
    float64
    1.0 1.0 2.0 2.0 ... 10.0 11.0 11.0

    units :

    pix

    array([[[ 1.,  1.],
            [ 2.,  2.],
            [ 3.,  3.],
            [ 4.,  4.],
            [ 5.,  5.],
            [ 6.,  6.],
            [ 7.,  7.],
            [ 8.,  8.],
            [ 9.,  9.],
            [10., 10.],
            [11., 11.]],
    
           [[ 1.,  1.],
            [ 2.,  2.],
            [ 3.,  3.],
            [ 4.,  4.],
            [ 5.,  5.],
            [ 6.,  6.],
            [ 7.,  7.],
            [ 8.,  8.],
    ...
            [ 4.,  4.],
            [ 5.,  5.],
            [ 6.,  6.],
            [ 7.,  7.],
            [ 8.,  8.],
            [ 9.,  9.],
            [10., 10.],
            [11., 11.]],
    
           [[ 1.,  1.],
            [ 2.,  2.],
            [ 3.,  3.],
            [ 4.,  4.],
            [ 5.,  5.],
            [ 6.,  6.],
            [ 7.,  7.],
            [ 8.,  8.],
            [ 9.,  9.],
            [10., 10.],
            [11., 11.]]])

  • v
    (y, x, t)
    float64
    1.0 1.0 1.0 1.0 ... 10.0 10.0 10.0

    units :

    pix

    array([[[ 1.,  1.],
            [ 1.,  1.],
            [ 1.,  1.],
            [ 1.,  1.],
            [ 1.,  1.],
            [ 1.,  1.],
            [ 1.,  1.],
            [ 1.,  1.],
            [ 1.,  1.],
            [ 1.,  1.],
            [ 1.,  1.]],
    
           [[ 2.,  2.],
            [ 2.,  2.],
            [ 2.,  2.],
            [ 2.,  2.],
            [ 2.,  2.],
            [ 2.,  2.],
            [ 2.,  2.],
            [ 2.,  2.],
    ...
            [ 9.,  9.],
            [ 9.,  9.],
            [ 9.,  9.],
            [ 9.,  9.],
            [ 9.,  9.],
            [ 9.,  9.],
            [ 9.,  9.],
            [ 9.,  9.]],
    
           [[10., 10.],
            [10., 10.],
            [10., 10.],
            [10., 10.],
            [10., 10.],
            [10., 10.],
            [10., 10.],
            [10., 10.],
            [10., 10.],
            [10., 10.],
            [10., 10.]]])

  • chc
    (y, x, t)
    float64
    1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0

    array([[[1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.]],
    
           [[1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
    ...
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.]],
    
           [[1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.],
            [1., 1.]]])

• Indexes: (3)
  • x
    PandasIndex

    PandasIndex(Index([0.0, 20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 140.0, 160.0, 180.0, 200.0], dtype='float64', name='x'))

  • y
    PandasIndex

    PandasIndex(Index([0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0], dtype='float64', name='y'))

  • t
    PandasIndex

    PandasIndex(Index([0.0, 1.0], dtype='float64', name='t'))

• Attributes: (2)

  delta_t :

  0.0

  files :

  []

plt.figure(figsize=(10,10))
graphics.quiver(df.piv.average,arrScale=3,streamlines=True);

<Figure size 1000x1000 with 0 Axes>

plt.figure(figsize=(10,10))
# plot quiver of the first frame (t[0]), selected by .isel and apply quiver()
df.isel(t=0).piv.quiver(arrScale=7,streamlines=True)

(<Figure size 640x480 with 1 Axes>, <Axes: xlabel='x [pix]', ylabel='y [pix]'>)

<Figure size 1000x1000 with 0 Axes>

fig,ax = graphics.contour_plot(df.isel(t=-1),colorbar='vertical')
fig.set_size_inches(6,6)
ax.set_xlabel('$x$ (pix)',fontsize=16);