Page History

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For more examples, see How to access HDF5 data from Python and http://code.google.com/p/h5py/

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Plotting with

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The version available in our offline release system is
IPython 0.9.1 – An enhanced Interactive Python.
so this is the one I've been using in these examples.
Not a whole lot more than a python shell.

However, the latest IPython has loads of new and interesting features...

http://ipython.org/^{Image Removed}

[ofte@psana0106 xpptutorial]$ ipython
Python 2.4.3 (#1, Nov  3 2010, 12:52:40)
Type "copyright", "credits" or "license" for more information.

IPython 0.9.1 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object'. ?object also works, ?? prints more.

In [1]: from numpy import *

In [2]: from matplotlib.pyplot import *

In [3]: ipm3 = load('point_scan_delay.npy')

In [4]: ipm3.shape
Out[4]: (200, 3)

In [5]: ion()

In [6]: delay = ipm3[:,0]

In [7]: ipmraw = ipm3[:,1]

In [8]: ipmnorm = ipm3[:,2]

n [9]: plot(delay,ipmnorm,'ro')
Out[9]: [<matplotlib.lines.Line2D object at 0x59c4c10>]

In [10]: draw()

In [11]:

Plotting with MatPlotLib

Matplotlib:

• http://matplotlib.sourceforge.net/users/pyplot_tutorial.html^{Image Removed}

• The plotting can be done directly in the pyana module, but be aware that you need to disable plotting for the
  module to run successfully in a batch job.

  Code Block
  import matplotlib.pyplot as plt plt.plot(array) plt.show()

• Or you can load arrays from a file and interactively plot them in iPython. The same ('recommended') syntax as above can be used, or if you use 'import *' you don't need to prepend the commands with the package name, which is handy when plotting interactively:

  Code Block
  from matplotlib.pyplot import * ion() plot(array) draw()

Related useful tools and links

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MatPlotLib

Matplotlib:

• http://matplotlib.sourceforge.net/users/pyplot_tutorial.html^{Image Added}

• The plotting can be done directly in the pyana module, but be aware that you need to disable plotting for the
  module to run successfully in a batch job.

  Code Block
  import matplotlib.pyplot as plt plt.plot(array) plt.show()

• Or you can load arrays from a file and interactively plot them in iPython. The same ('recommended') syntax as above can be used, or if you use 'import *' you don't need to prepend the commands with the package name, which is handy when plotting interactively:

  Code Block
  from matplotlib.pyplot import * ion() plot(array) draw()

Related useful tools and links

• http://www.scipy.org/NumPy_for_Matlab_Users^{Image Added}
• http://www.scipy.org/^{Image Added}
• http://www.sagemath.org/^{Image Added}
• http://code.google.com/p/spyderlib/^{Image Added}

Interactive analysis with IPython

The version available in our offline release system is
IPython 0.9.1 – An enhanced Interactive Python.
so this is the one I've been using in these examples.
Not a whole lot more than a python shell.

However, the latest IPython has loads of new and interesting features...

http://ipython.org/^{Image Added}

[ofte@psana0106 xpptutorial]$ ipython
Python 2.4.3 (#1, Nov  3 2010, 12:52:40)
Type "copyright", "credits" or "license" for more information.

IPython 0.9.1 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object'. ?object also works, ?? prints more.

In [1]: from numpy import *

In [2]: from matplotlib.pyplot import *

In [3]: ipm3 = load('point_scan_delay.npy')

In [4]: ipm3.shape
Out[4]: (200, 3)

In [5]: ion()

In [6]: delay = ipm3[:,0]

In [7]: ipmraw = ipm3[:,1]

In [8]: ipmnorm = ipm3[:,2]

n [9]: plot(delay,ipmnorm,'ro')
Out[9]: [<matplotlib.lines.Line2D object at 0x59c4c10>]

In [10]: draw()

In [11]:

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Non-interactive batch analysis

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Image peak finding

Here are a collection of useful algorithms for image analysis: http://docs.scipy.org/doc/scipy/reference/ndimage.html

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