Recent changes to Python, filtering

Python, filtering modified by Gert Wollny

Gert Wollny — Fri, 09 Jan 2015 17:34:21 -0000

--- v4
+++ v5
@@ -4,24 +4,24 @@

 ### Filtering 

-The *mia.filter* function transparently distinguishes between 2D and 3D images. Filters are specified as strings like they are given on the [mia-2dimagefilter](http://mia.sourceforge.net/userref/Secmia2dimagefilter.html) and [mia-3dimagefilter](http://mia.sourceforge.net/userref/Secmia3dimagefilter.html) command line.
+The *pymia.filter* function transparently distinguishes between 2D and 3D images. Filters are specified as strings like they are given on the [mia-2dimagefilter](http://mia.sourceforge.net/userref/Secmia2dimagefilter.html) and [mia-3dimagefilter](http://mia.sourceforge.net/userref/Secmia3dimagefilter.html) command line.

 Filters can be run one at a time, or as a pipeline. To run a single filter, e.g. a *median* filter of *half filter width* 3 on an image *input* run 

     :::python 
-    filtered = mia.filter(input, "median:w=3")
+    filtered = pymia.filter(input, "median:w=3")

 To run a filter chain, e.g. the above median, followed by a *mean-least-variance* filter with a filter width parameter 5, provide the filters as a list: 

     :::python 
-    filtered = mia.filter(input, ["median:w=3", "mlv:w=5"])
+    filtered = pymia.filter(input, ["median:w=3", "mlv:w=5"])

 Note that the filters function converts the *input* to the internal MIA image format, creates and runs the filters, and then converts the images back to *numpy* arrays. Therefore, for performance reasons, it is best to run the filter chains instead of one filter at a time. 

 In order to avoid re-creating filters one can enable the filter cache by calling 

     :::python 
-    mia.set_filter_plugin_cache(True)
+    pymia.set_filter_plugin_cache(True)

-Then, filters with the same description are re-used  in subsequent calls to the *mia.filter* function. The filters in MIA normally work like functions, i.e. no state changes when it is called. *However, in some rare cases, when external data is loaded by means of a filter parameter, this may actually not work like expected (cf. [tickets:#134]).*
+Then, filters with the same description are re-used  in subsequent calls to the *pymia.filter* function. The filters in MIA normally work like functions, i.e. no state changes when it is called. *However, in some rare cases, when external data is loaded by means of a filter parameter, this may actually not work like expected (cf. [tickets:#134]).*

Python, filtering modified by Gert Wollny

Gert Wollny — Thu, 12 Dec 2013 15:16:57 -0000

--- v3
+++ v4
@@ -1,6 +1,5 @@
 Navigation | | 
 -----------|-|-----------------
-
 [loading images](Python, loading images) | [Contents](Using mia from Python) | [image registration](Python, image registration)

 ### Filtering

Python, filtering modified by Gert Wollny

Gert Wollny — Thu, 12 Dec 2013 15:16:46 -0000

--- v2
+++ v3
@@ -1,3 +1,8 @@
+Navigation | | 
+-----------|-|-----------------
+
+[loading images](Python, loading images) | [Contents](Using mia from Python) | [image registration](Python, image registration)
+
 ### Filtering

 The *mia.filter* function transparently distinguishes between 2D and 3D images. Filters are specified as strings like they are given on the [mia-2dimagefilter](http://mia.sourceforge.net/userref/Secmia2dimagefilter.html) and [mia-3dimagefilter](http://mia.sourceforge.net/userref/Secmia3dimagefilter.html) command line.
@@ -21,6 +26,3 @@

 Then, filters with the same description are re-used  in subsequent calls to the *mia.filter* function. The filters in MIA normally work like functions, i.e. no state changes when it is called. *However, in some rare cases, when external data is loaded by means of a filter parameter, this may actually not work like expected (cf. [tickets:#134]).*

------
-
-[loading images](Python, loading images) [top](Using mia from Python)  [image registration](Python, image registration)

Python, filtering modified by Gert Wollny

Gert Wollny — Thu, 12 Dec 2013 15:02:59 -0000

--- v1
+++ v2
@@ -23,4 +23,4 @@

 -----

-[back](Python, loading images) [top](Using mia from Python)  [forward](Python, image registration)
+[loading images](Python, loading images) [top](Using mia from Python)  [image registration](Python, image registration)

Python, filtering modified by Gert Wollny

Gert Wollny — Thu, 12 Dec 2013 14:46:46 -0000

Filtering

The mia.filter function transparently distinguishes between 2D and 3D images. Filters are specified as strings like they are given on the mia-2dimagefilter and mia-3dimagefilter command line.

Filters can be run one at a time, or as a pipeline. To run a single filter, e.g. a median filter of half filter width 3 on an image input run

filtered = mia.filter(input, "median:w=3")

To run a filter chain, e.g. the above median, followed by a mean-least-variance filter with a filter width parameter 5, provide the filters as a list:

filtered = mia.filter(input, ["median:w=3", "mlv:w=5"])

Note that the filters function converts the input to the internal MIA image format, creates and runs the filters, and then converts the images back to numpy arrays. Therefore, for performance reasons, it is best to run the filter chains instead of one filter at a time.

In order to avoid re-creating filters one can enable the filter cache by calling

mia.set_filter_plugin_cache(True)

Then, filters with the same description are re-used in subsequent calls to the mia.filter function. The filters in MIA normally work like functions, i.e. no state changes when it is called. However, in some rare cases, when external data is loaded by means of a filter parameter, this may actually not work like expected (cf. [tickets:#134]).

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