EMAN::CccCmp Class Reference

Compute the cross-correlation coefficient between two images. More...

#include <cmp.h>

Inheritance diagram for EMAN::CccCmp:

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List of all members.

Public Member Functions

float cmp (EMData *image, EMData *with) const
 To compare 'image' with another image passed in through its parameters.
string get_name () const
 Get the Cmp's name.
string get_desc () const
TypeDict get_param_types () const
 Get Cmp parameter information in a dictionary.

Static Public Member Functions

static CmpNEW ()

Static Public Attributes

static const string NAME = "ccc"

Detailed Description

Compute the cross-correlation coefficient between two images.

The cross-correlation coefficient is defined as: <AB> - CCC = ------------- sig(A)sig(B)

where the angle brackets denote averages and "sig" is the standard deviation. In the case of a mask, only pixels under the mask are included in the calculation of averages.

For complex images, this routine currently bails.

Author:
Grant Goodyear (grant.goodyear@uth.tmc.edu)
Date:
2005-10-03
Parameters:
negative Returns -1 * ccc, default true

Definition at line 155 of file cmp.h.


Member Function Documentation

float CccCmp::cmp ( EMData image,
EMData with 
) const [virtual]

To compare 'image' with another image passed in through its parameters.

An optional transformation may be used to transform the 2 images.

Parameters:
image The first image to be compared.
with The second image to be comppared.
Returns:
The comparison result. Smaller better by default

Implements EMAN::Cmp.

Definition at line 90 of file cmp.cpp.

References dm, ENTERFUNC, EXITFUNC, EMAN::EMData::get_const_data(), EMAN::EMData::get_xsize(), EMAN::EMData::get_ysize(), EMAN::EMData::get_zsize(), EMAN::Dict::has_key(), ImageFormatException, EMAN::EMData::is_complex(), EMAN::Cmp::params, EMAN::Dict::set_default(), sqrt(), and EMAN::Cmp::validate_input_args().

00091 {
00092         ENTERFUNC;
00093         if (image->is_complex() || with->is_complex())
00094                 throw ImageFormatException( "Complex images not supported by CMP::CccCmp");
00095         validate_input_args(image, with);
00096 
00097         const float *const d1 = image->get_const_data();
00098         const float *const d2 = with->get_const_data();
00099 
00100         float negative = (float)params.set_default("negative", 1);
00101         if (negative) negative=-1.0; else negative=1.0;
00102 
00103         double avg1 = 0.0, var1 = 0.0, avg2 = 0.0, var2 = 0.0, ccc = 0.0;
00104         long n = 0;
00105         size_t totsize = image->get_xsize()*image->get_ysize()*image->get_zsize();
00106 
00107         bool has_mask = false;
00108         EMData* mask = 0;
00109         if (params.has_key("mask")) {
00110                 mask = params["mask"];
00111                 if(mask!=0) {has_mask=true;}
00112         }
00113 
00114         if (has_mask) {
00115                 const float *const dm = mask->get_const_data();
00116                 for (size_t i = 0; i < totsize; ++i) {
00117                         if (dm[i] > 0.5) {
00118                                 avg1 += double(d1[i]);
00119                                 var1 += d1[i]*double(d1[i]);
00120                                 avg2 += double(d2[i]);
00121                                 var2 += d2[i]*double(d2[i]);
00122                                 ccc += d1[i]*double(d2[i]);
00123                                 n++;
00124                         }
00125                 }
00126         } else {
00127                 for (size_t i = 0; i < totsize; ++i) {
00128                         avg1 += double(d1[i]);
00129                         var1 += d1[i]*double(d1[i]);
00130                         avg2 += double(d2[i]);
00131                         var2 += d2[i]*double(d2[i]);
00132                         ccc += d1[i]*double(d2[i]);
00133                 }
00134                 n = totsize;
00135         }
00136 
00137         avg1 /= double(n);
00138         var1 = var1/double(n) - avg1*avg1;
00139         avg2 /= double(n);
00140         var2 = var2/double(n) - avg2*avg2;
00141         ccc = ccc/double(n) - avg1*avg2;
00142         ccc /= sqrt(var1*var2);
00143         ccc *= negative;
00144         return static_cast<float>(ccc);
00145         EXITFUNC;
00146 }

string EMAN::CccCmp::get_desc (  )  const [inline, virtual]

Implements EMAN::Cmp.

Definition at line 165 of file cmp.h.

00166                 {
00167                         return "Cross-correlation coefficient (default -1 * ccc)";
00168                 }

string EMAN::CccCmp::get_name (  )  const [inline, virtual]

Get the Cmp's name.

Each Cmp is identified by a unique name.

Returns:
The Cmp's name.

Implements EMAN::Cmp.

Definition at line 160 of file cmp.h.

References NAME.

00161                 {
00162                         return NAME;
00163                 }

TypeDict EMAN::CccCmp::get_param_types (  )  const [inline, virtual]

Get Cmp parameter information in a dictionary.

Each parameter has one record in the dictionary. Each record contains its name, data-type, and description.

Returns:
A dictionary containing the parameter info.

Implements EMAN::Cmp.

Definition at line 176 of file cmp.h.

References EMAN::EMObject::EMDATA, EMAN::EMObject::INT, and EMAN::TypeDict::put().

00177                 {
00178                         TypeDict d;
00179                         d.put("negative", EMObject::INT, "If set, returns -1 * ccc product. Set by default so smaller is better");
00180                         d.put("mask", EMObject::EMDATA, "image mask");
00181                         return d;
00182                 }

static Cmp* EMAN::CccCmp::NEW (  )  [inline, static]

Definition at line 170 of file cmp.h.

00171                 {
00172                         return new CccCmp();
00173                 }


Member Data Documentation

const string CccCmp::NAME = "ccc" [static]

Definition at line 184 of file cmp.h.

Referenced by get_name().


The documentation for this class was generated from the following files:
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