Rebin Functions - Revision history

Dean Whittaker at 14:59, 18 March 2008

2008-03-18T14:59:10Z

Dean Whittaker at 10:00, 18 March 2008

2008-03-18T10:00:46Z

Dean Whittaker at 10:00, 18 March 2008

2008-03-18T10:00:16Z

Dean Whittaker at 09:53, 18 March 2008

2008-03-18T09:53:51Z

Dean Whittaker at 08:52, 18 March 2008

2008-03-18T08:52:36Z

Dean Whittaker at 17:06, 17 March 2008

2008-03-17T17:06:06Z

Dean Whittaker at 16:35, 17 March 2008

2008-03-17T16:35:34Z

New page

Rebin functions change the way in which the data is binned, but should not effect the data itself. For instance, one might rebin data from a low resolution run into wider bins.

These functions are

<pre>>> wout = rebin(w,[xlo, dx, xhi])
>> wwout = rebin_x(ww,[xlo, dx, xhi])
>> wwout = rebin_y(ww,[ylo, dy, yhi])
>> wwout = rebin_xy(ww,[xlo, dx, xhi], [ylo, dy, yhi])
>> wout = rebunch(w, nbins)
>> wwout = rebunch_x(w, nbins)
>> wwout = rebunch_y(w, nbins)
>> wwout = rebunch_xy(w, xbins, ybins)
>> wout = regroup(w, [xlo, dx, xhi])
>> wwout = regroup_x(ww, [xlo, dx, xhi])
>> wwout = regroup_y(ww, [ylo, dy, yhi])
>> wwout = regroup_xy(ww, [xlo, dx, xhi], [ylo, dy, yhi])</pre>

== Rebin Functions ==

== Rebunch Functions ==

== Regroup Functions ==

← Older revision		Revision as of 14:59, 18 March 2008
Line 1:		Line 1:
	Rebin functions change the way in which the data is binned, but should not effect the data itself. For instance, one might rebin data from a low resolution run into wider bins.		Rebin functions change the way in which the data is binned, but should not effect the data itself. For instance, one might rebin data from a low resolution run into wider bins.

−	~~These functions are~~
−
−	~~<pre>>> wout = rebin(w,[xlo, dx, xhi])~~
−	~~>> wwout = rebin_x(ww,[xlo, dx, xhi])~~
−	~~>> wwout = rebin_y(ww,[ylo, dy, yhi])~~
−	~~>> wwout = rebin_xy(ww,[xlo, dx, xhi], [ylo, dy, yhi])~~
−	~~>> wout = rebunch(w, nbins)~~
−	~~>> wwout = rebunch_x(w, nbins)~~
−	~~>> wwout = rebunch_y(w, nbins)~~
−	~~>> wwout = rebunch_xy(w, xbins, ybins)~~
−	~~>> wout = regroup(w, [xlo, dx, xhi])~~
−	~~>> wwout = regroup_x(ww, [xlo, dx, xhi])~~
−	~~>> wwout = regroup_y(ww, [ylo, dy, yhi])~~
−	~~>> wwout = regroup_xy(ww, [xlo, dx, xhi], [ylo, dy, yhi])</pre>~~

	== Rebin Functions ==		== Rebin Functions ==

@@ Line 32: / Line 32: @@
 * Re-evaluates signal data to coincide with the new bins
-<pre>>>rebin(w, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...])</pre>
+<pre>>> wout = rebin(w, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...])</pre>
 * Input is an [[IXTdataset_1d]] object
@@ Line 45: / Line 45: @@
 This bunches a number of bins together. For instance if there are 400 bins in the original dataset and the number of bins given is 4, then there will be 100 bins in the new dataset.
-<pre>>> rebunch_x(ww, xbins)
+<pre>>> wwout = rebunch_x(ww, xbins)
 >> wwout = rebunch_y(ww, ybins)
 >> wwout = rebunch_xy(ww, xbins, ybins)</pre>

@@ Line 46: / Line 46: @@
 <pre>>> rebunch_x(ww, xbins)
->> rebunch_y(ww, ybins)
+>> wwout = rebunch_y(ww, ybins)
->> rebunch_xy(ww, xbins, ybins)</pre>
+>> wwout = rebunch_xy(ww, xbins, ybins)</pre>
 * Input is an [[IXTdataset_2d]] object
@@ Line 54: / Line 54: @@
 * Signal and Error data is re-evaluated to coincide with the new bins
-<pre>>> rebunch(w, xbins)</pre>
+<pre>>> wout = rebunch(w, xbins)</pre>
 * Input is an [[IXTdataset_1d]] object
@@ Line 65: / Line 65: @@
 These functions act very similarly to the rebin functions, except new bins are ''always'' coincident with original bins. For instance if the bin widths are 10 and a new width of 28 is given, then the bin widths of the new dataset will be 30 since this is now coincident with the original bins.
-<pre>>> regroup_x(ww, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...])
+<pre>>> wwout = regroup_x(ww, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...])
->> regroup_y(ww, [ylo1, dy1, yhi1, ylo2, dy2, yhi2, ...])
+>> wwout = regroup_y(ww, [ylo1, dy1, yhi1, ylo2, dy2, yhi2, ...])
->> regroup_xy(ww, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...], [ylo1, dy1, yhi1, ylo2, dy2, yhi2, ...])</pre>
+>> wwout = regroup_xy(ww, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...], [ylo1, dy1, yhi1, ylo2, dy2, yhi2, ...])</pre>
 * Input is an [[IXTdataset_2d]] object
@@ Line 77: / Line 77: @@
 * Re-evaluates signal data to coincide with the new bins
-<pre>>>regroup(w, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...])</pre>
+<pre>>> wout = regroup(w, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...])</pre>
 * Input is an [[IXTdataset_1d]] object

@@ Line 20: / Line 20: @@
-<pre>>> rebin_x(ww, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...])
+<pre>>> wwout = rebin_x(ww, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...])
->> rebin_y(ww, [ylo1, dy1, yhi1, ylo2, dy2, yhi2, ...])
+>> wwout = rebin_y(ww, [ylo1, dy1, yhi1, ylo2, dy2, yhi2, ...])
->> rebin_xy(ww, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...], [ylo1, dy1, yhi1, ylo2, dy2, yhi2, ...])</pre>
+>> wwout = rebin_xy(ww, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...], [ylo1, dy1, yhi1, ylo2, dy2, yhi2, ...])</pre>
 * Input is an [[IXTdataset_2d]] object

← Older revision		Revision as of 08:52, 18 March 2008
Line 43:		Line 43:
	== Rebunch Functions ==		== Rebunch Functions ==

		+	This bunches a number of bins together. For instance if there are 400 bins in the original dataset and the number of bins given is 4, then there will be 100 bins in the new dataset.
		+
		+	<pre>>> rebunch_x(ww, xbins)
		+	>> rebunch_y(ww, ybins)
		+	>> rebunch_xy(ww, xbins, ybins)</pre>
		+
		+	* Input is an [[IXTdataset_2d]] object
		+	* Output is an [[IXTdataset_2d]] object
		+	* xbins number of bins in x are bunched together, ybins number of bins in y are bunched together
		+	* Signal and Error data is re-evaluated to coincide with the new bins
		+
		+	<pre>>> rebunch(w, xbins)</pre>
		+
		+	* Input is an [[IXTdataset_1d]] object
		+	* Output is an [[IXTdataset_1d]] object
		+	* xbins number of bins in x are bunched together
		+	* Signal and Error data is re-evaluated to coincide with the new bins
		+
	== Regroup Functions ==		== Regroup Functions ==
		+
		+	These functions act very similarly to the rebin functions, except new bins are ''always'' coincident with original bins. For instance if the bin widths are 10 and a new width of 28 is given, then the bin widths of the new dataset will be 30 since this is now coincident with the original bins.
		+
		+	<pre>>> regroup_x(ww, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...])
		+	>> regroup_y(ww, [ylo1, dy1, yhi1, ylo2, dy2, yhi2, ...])
		+	>> regroup_xy(ww, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...], [ylo1, dy1, yhi1, ylo2, dy2, yhi2, ...])</pre>
		+
		+	* Input is an [[IXTdataset_2d]] object
		+	* Output is an [[IXTdataset_2d]] object
		+	* Requires dataset to contain histogram data
		+	* Changes x bins so that the minimum bin size between xlo1 and xhi1 are dx1, between xlo2 and xhi2 are dx2 etc.
		+	* Changes y bins so that the minimum bin size between ylo1 and yhi1 are dy1, between ylo2 and yhi2 are dy2 etc.
		+	* Only keeps data between the ranges of xlo and xhi
		+	* Re-evaluates signal data to coincide with the new bins
		+
		+	<pre>>>regroup(w, [xlo1, dx1, xhi1, xlo2, dx2, xhi2, ...])</pre>
		+
		+	* Input is an [[IXTdataset_1d]] object
		+	* Output is an [[IXTdataset_1d]] object
		+	* Requires dataset to contain histogram data
		+	* Changes x bins so that the minimum bin size between xlo1 and xhi1 are dx1, between xlo2 and xhi2 are dx2 etc.
		+	* Only keeps data between the ranges of xlo and xhi
		+	* Re-evaluates signal data to coincide with the new bins

@@ Line 17: / Line 17: @@
 == Rebin Functions ==
 == Rebunch Functions ==
 == Regroup Functions ==