tools: Fix typos in imagery tools (#5345)

imagery: fix typos
Found via codespell

Author: luzpaz

imagery/i.atcorr/6s.cpp

@@ -251,7 +251,7 @@ void printOutput()
 TransformInput compute()
 {
     const double accu3 = 1e-07;
-    /* ---- initilialization         very liberal :) */
+    /* ---- initialization         very liberal :) */
     int i, j;
 
     double fr = 0;

imagery/i.atcorr/aerosolmodel.cpp

@@ -190,7 +190,7 @@ void AerosolModel::mie(double (&ex)[4][10], double (&sc)[4][10],
             sc[0][j] += (double)(mie_in.cij[i] * sca2[j][i]);
         }
 
-    /* computation of the phase function and the asymetry coefficient
+    /* computation of the phase function and the asymmetry coefficient
        of the mixture of particles */
 
     for (j = 0; j < 10; j++) {
@@ -492,7 +492,7 @@ void AerosolModel::save()
   oceanic component (O.C., SUBROUTINE OCEA)
   water-soluble component (W.S., SUBROUTINE WATE)
   soot component (S.O., SUBROUTINE SOOT)
-  (2) pre-computed caracteristics, now available are the desertic aerosol model
+  (2) pre-computed characteristics, now available are the desertic aerosol model
   corresponding to background conditions, as described in Shettle(1984), a
   stratospheric aerosol model as measured Mona Loa (Hawaii) during El Chichon
   eruption and as described by King et al. (1984), and a biomass burning aerosol

imagery/i.atcorr/interp.h

@@ -25,7 +25,7 @@ struct InterpStruct {
 
 /*
    To estimate the different atmospheric functions r(mS,mv,fS,fv), T(q) and S at
-   any wavelength from the 10 discret computations (subroutine DISCOM).
+   any wavelength from the 10 discrete computations (subroutine DISCOM).
  */
 void interp(const int iaer, const int idatmp, const double wl,
             const double taer55, const double taer55p, const double xmud,

imagery/i.gensig/i.gensig.html

@@ -78,7 +78,7 @@ <h3>Parameters</h3>
 This is the resultant signature file (containing the means
 and covariance matrices) for each class in the training map
 that is associated with the band files in the subgroup
-select (see <a href="#subgroup">above</a>). Resultant singature file
+select (see <a href="#subgroup">above</a>). Resultant signature file
 can be used with any other imagery group as long as semantic labels
 match.
 </dl>

imagery/i.gensig/i.gensig.md

@@ -43,7 +43,7 @@ select a subset of all the band files that form an image.
 Input **signaturefile** is the resultant signature file (containing the means and
 covariance matrices) for each class in the training map that is
 associated with the band files in the subgroup select.
-Resultant singature file can be used with any other
+Resultant signature file can be used with any other
 imagery group as long as semantic labels match.
 
 ## NOTES

imagery/i.gensigset/i.gensigset.html

@@ -121,7 +121,7 @@ <h3>Parameters</h3>
 The spectral signatures which are produced by this program
 are "mixed" signatures (see <a href="#notes">NOTES</a>).
 Each signature contains one or more subsignatures
-(represeting subclasses).  The algorithm in this program
+(representing subclasses).  The algorithm in this program
 starts with a maximum number of subclasses and reduces this
 number to a minimal number of subclasses which are
 spectrally distinct.  The user has the option to set this

imagery/i.gensigset/i.gensigset.md

@@ -61,7 +61,7 @@ Option **maxsig** is the maximum number of sub-signatures in any class
 
 The spectral signatures which are produced by this program are "mixed"
 signatures (see [NOTES](#notes)). Each signature contains one or more
-subsignatures (represeting subclasses). The algorithm in this program
+subsignatures (representing subclasses). The algorithm in this program
 starts with a maximum number of subclasses and reduces this number to a
 minimal number of subclasses which are spectrally distinct. The user has
 the option to set this starting value with this option.

imagery/i.group/main.c

@@ -97,7 +97,7 @@ int main(int argc, char *argv[])
     if (G_parser(argc, argv))
         exit(EXIT_FAILURE);
 
-    /* backward comaptibility -> simple list implied l flag list, if there was
+    /* backward compatibility -> simple list implied l flag list, if there was
        only l flag (with s flag added it is not clear, simple_flag is linked to
        both) */
     if ((simple_flag->answer && !s->answer) && !l->answer)

imagery/i.landsat.toar/landsat_met.c

@@ -165,7 +165,7 @@ void lsat_metadata(char *metafile, lsat_data *lsat)
         chrncpy(lsat->date, value, 10);
     }
     else
-        G_warning("Using adquisition date from the command line 'date'");
+        G_warning("Using acquisition date from the command line 'date'");
 
     get_mtldata(mtldata, "FILE_DATE", value);
     if (value[0] == '\0') {

imagery/i.landsat.toar/landsat_set.c

@@ -120,7 +120,7 @@ void sensor_OLI(lsat_data *lsat)
 /** **********************************************
  ** Before access to these functions ...
  ** store previously
- ** >>> adquisition date,
+ ** >>> acquisition date,
  ** >>> creation date, and
  ** >>> sun_elev
  ** **********************************************/

imagery/i.modis.qc/mod09A1a.c

@@ -1,6 +1,6 @@
 /* MODLAND QA Bits 500m long int bits[0-1]
  * 00 -> class 0: Corrected product produced at ideal quality -- all bands
- * 01 -> class 1: Corrected product produced at less than idel quality -- some
+ * 01 -> class 1: Corrected product produced at less than ideal quality -- some
  * or all bands 10 -> class 2: Corrected product NOT produced due to cloud
  * effect -- all bands 11 -> class 3: Corrected product NOT produced due to
  * other reasons -- some or all bands mayb be fill value (Note that a value of

imagery/i.modis.qc/mod09GAa.c

@@ -1,6 +1,6 @@
 /* MODLAND QA Bits 500m long int bits[0-1]
  * 00 -> class 0: Corrected product produced at ideal quality -- all bands
- * 01 -> class 1: Corrected product produced at less than idel quality -- some
+ * 01 -> class 1: Corrected product produced at less than ideal quality -- some
  * or all bands 10 -> class 2: Corrected product NOT produced due to cloud
  * effect -- all bands 11 -> class 3: Corrected product NOT produced due to
  * other reasons -- some or all bands mayb be fill value (Note that a value of

imagery/i.modis.qc/mod09Q1a.c

@@ -1,6 +1,6 @@
 /* MODLAND QA Bits 250m Unsigned Int bits[0-1]
  * 00 -> class 0: Corrected product produced at ideal quality -- all bands
- * 01 -> class 1: Corrected product produced at less than idel quality -- some
+ * 01 -> class 1: Corrected product produced at less than ideal quality -- some
  * or all bands 10 -> class 2: Corrected product NOT produced due to cloud
  * effect -- all bands 11 -> class 3: Corrected product NOT produced due to
  * other reasons -- some or all bands mayb be fill value (Note that a value of

imagery/i.ortho.photo/i.ortho.photo/i.ortho.photo.html

@@ -46,7 +46,7 @@ <h2>DESCRIPTION</h2>
 image in pixels (<em>image coordinate system</em>) and the coordinate
 system of the camera sensor in millimetres (<em>photo coordinate system</em>)
 for the interior orientation of the image, and further to the georeferenced
-coordinate system defined by projection parametres
+coordinate system defined by projection parameters
 (<em>target coordinate system</em>) for exterior orientation.
 
 <h2>EXAMPLE</h2>
@@ -96,7 +96,7 @@ <h2>EXAMPLE</h2>
 group for the ortho-rectification. After choosing this option you will
 be prompted for the name of a new or existing imagery group. As a result,
 a new file <em>mapset/group/name_of_group/<b>REF</b></em>
-is created that contatins the names of all images in a group.
+is created that contains the names of all images in a group.
 
 <div class="code"><pre>
 IMG_0020 source_mapset
@@ -116,7 +116,7 @@ <h2>EXAMPLE</h2>
 project is also the project from which the elevation model (raster
 map) will be selected (see Step 3). In Step 2, a new file
 <em>mapset/group/name_of_group/<b>TARGET</b></em>
-is created contatining the names of target project and mapset.
+is created containing the names of target project and mapset.
 
 <div class="code"><pre>
 ETRS_33N
@@ -139,7 +139,7 @@ <h2>EXAMPLE</h2>
 In Step 3 you will be prompted for the name of the raster map in the
 target project that you want to use as the elevation model. As a result
 of this step, a new file <em>mapset/group/name_of_group/<b>ELEVATION</b></em>
-is created contatining the name and mapset of the chosen DEM.
+is created containing the name and mapset of the chosen DEM.
 
 <div class="code"><pre>
 elevation layer :ELEVATION
@@ -163,9 +163,9 @@ <h2>EXAMPLE</h2>
 characteristic of the camera is its focal length. Fiducial or reseau marks
 locations are required to compute the scanned image to photo coordinate
 transformation parameter (Step 5). Two new files are created in this step:
-a file <em>mapset/group/name_of_group/<b>CAMERA</b></em>, contatining
+a file <em>mapset/group/name_of_group/<b>CAMERA</b></em>, containing
 the name of the reference camera and a file
-<em>mapset/camera/<b>name_of_reference</b></em>, contatining the
+<em>mapset/camera/<b>name_of_reference</b></em>, containing the
 camera parameters.
 
 <div class="code"><pre>
@@ -192,7 +192,7 @@ <h2>EXAMPLE</h2>
 associate the scanned reference points (fiducials, reseau marks, etc.)
 with their known photo coordinates from the camera reference file. A new
 file <em>mapset/group/name_of_group/<b>REF_POINTS</b></em>
-is created, contatining a list of pairs of coordinates in image and photo
+is created, containing a list of pairs of coordinates in image and photo
 coordinate systems.
 
 <div class="code"><pre>
@@ -245,7 +245,7 @@ <h2>EXAMPLE</h2>
 </div>
 
 <p>In Step 6, a new file <em>mapset/group/name_of_group/<b>INIT_EXP</b></em>
-is created, contatining camera parameters.
+is created, containing camera parameters.
 
 <div class="code"><pre>
 INITIAL XC    215258.345387

imagery/i.ortho.photo/i.ortho.photo/i.ortho.photo.md

@@ -31,7 +31,7 @@ on the surface of the earth by matching the coordinate system of the
 aerial image in pixels (*image coordinate system*) and the coordinate
 system of the camera sensor in millimetres (*photo coordinate system*)
 for the interior orientation of the image, and further to the
-georeferenced coordinate system defined by projection parametres
+georeferenced coordinate system defined by projection parameters
 (*target coordinate system*) for exterior orientation.
 
 ## EXAMPLE
@@ -75,7 +75,7 @@ The steps to follow are described below:
     existing imagery group for the ortho-rectification. After choosing
     this option you will be prompted for the name of a new or existing
     imagery group. As a result, a new file
-    *mapset/group/name_of_group/**REF*** is created that contatins the
+    *mapset/group/name_of_group/**REF*** is created that contains the
     names of all images in a group.
 
     ```sh
@@ -94,7 +94,7 @@ The steps to follow are described below:
     and mapset where the ortho-rectified raster maps will reside. The
     target project is also the project from which the elevation model
     (raster map) will be selected (see Step 3). In Step 2, a new file
-    *mapset/group/name_of_group/**TARGET*** is created contatining the
+    *mapset/group/name_of_group/**TARGET*** is created containing the
     names of target project and mapset.
 
     ```sh
@@ -117,7 +117,7 @@ The steps to follow are described below:
     program. In Step 3 you will be prompted for the name of the raster
     map in the target project that you want to use as the elevation
     model. As a result of this step, a new file
-    *mapset/group/name_of_group/**ELEVATION*** is created contatining
+    *mapset/group/name_of_group/**ELEVATION*** is created containing
     the name and mapset of the chosen DEM.
 
     ```sh
@@ -142,9 +142,9 @@ The steps to follow are described below:
     Fiducial or reseau marks locations are required to compute the
     scanned image to photo coordinate transformation parameter (Step 5).
     Two new files are created in this step: a file
-    *mapset/group/name_of_group/**CAMERA***, contatining the name of the
+    *mapset/group/name_of_group/**CAMERA***, containing the name of the
     reference camera and a file *mapset/camera/**name_of_reference***,
-    contatining the camera parameters.
+    containing the camera parameters.
 
     ```sh
     CAMERA NAME   sony
@@ -169,7 +169,7 @@ The steps to follow are described below:
     interactive step you associate the scanned reference points
     (fiducials, reseau marks, etc.) with their known photo coordinates
     from the camera reference file. A new file
-    *mapset/group/name_of_group/**REF_POINTS*** is created, contatining
+    *mapset/group/name_of_group/**REF_POINTS*** is created, containing
     a list of pairs of coordinates in image and photo coordinate
     systems.
 
@@ -212,7 +212,7 @@ The steps to follow are described below:
     *Principle of pitch and yaw*
 
     In Step 6, a new file *mapset/group/name_of_group/**INIT_EXP*** is
-    created, contatining camera parameters.
+    created, containing camera parameters.
 
     ```sh
     INITIAL XC    215258.345387

imagery/i.ortho.photo/i.ortho.transform/main.c

@@ -423,7 +423,7 @@ static void do_pt_xforms(void)
         /* ? sscanf(buf, "%s %s", &east_str, &north_str)
            ? G_scan_easting(,,-1)
            ? G_scan_northing(,,-1) */
-        /* ? muliple delims with sscanf(buf, "%[ ,|\t]", &dummy) ? */
+        /* ? multiple delims with sscanf(buf, "%[ ,|\t]", &dummy) ? */
 
         ret = sscanf(buf, "%lf %lf %lf", &easting, &northing, &height);
         if (ret != 3)

imagery/i.ortho.photo/lib/orthoref.c

@@ -87,7 +87,7 @@ int I_compute_ortho_equations(struct Ortho_Control_Points *cpz,
 #ifdef DEBUG
     debug = fopen("ortho_compute.rst", "w");
     if (debug == NULL) {
-        sprintf(msg, "Cant open debug file ortho_compute.rst\n");
+        sprintf(msg, "Cannot open debug file ortho_compute.rst\n");
         G_fatal_error(msg);
     }
 #endif

imagery/i.segment/i.segment.html

@@ -90,7 +90,7 @@ <h4>Maximum number of segments</h4>
 unprocessed pixel is merged with another segment. Integer overflow can
 happen for computational regions with more than 2 billion cells and
 very low threshold values, resulting in many segments. If integer
-overflow occurs durin region growing, starting segments can be used
+overflow occurs during region growing, starting segments can be used
 (created by initial classification or other methods).
 
 <h4>Goodness of Fit</h4>

imagery/i.segment/i.segment.md

@@ -89,7 +89,7 @@ starting segment IDs. Segment IDs are assigned whenever a yet
 unprocessed pixel is merged with another segment. Integer overflow can
 happen for computational regions with more than 2 billion cells and very
 low threshold values, resulting in many segments. If integer overflow
-occurs durin region growing, starting segments can be used (created by
+occurs during region growing, starting segments can be used (created by
 initial classification or other methods).
 
 #### Goodness of Fit

imagery/i.segment/main.c

@@ -2,7 +2,7 @@
  *
  * MODULE:       i.segment
  * AUTHOR(S):    Markus Metz
- *               based on the the GSoC project by
+ *               based on the GSoC project by
  *               Eric Momsen <eric.momsen at gmail com>
  * PURPOSE:      Object recognition, segments an image group.
  * COPYRIGHT:    (C) 2012 by Eric Momsen, and the GRASS Development Team

imagery/i.segment/outline

@@ -109,7 +109,7 @@ I think this will apply to vector lines only, initially it was framed as being f
 
 /*ML: vector to raster conversion is probably necessary. Pixels crosses by a line (polygon boundary or not) have to become part of a segment boundary.*/
 /*EM: hmm, OK, something else for discussion: These pixels that are on a vector line, should they eventually be included in one of the adjacent segments?  Is "segment boundary" just the edge pixels of the segment, or are the not included in any segment?*/
-/*ML: Here is where a difference comes into play between lines that are boundary polgons and lines as linear features. In my eyes pixels that are on boundarylines of polygons should be part of the segments that are internal to that boundary. Linear features would have to be treated differently. During discussions with colleagues we did have some difficulties finding actual use cases for linear features. Maybe we can start with only polygon features and if the use case of a linear features comes up try to integrate that then ?*/
+/*ML: Here is where a difference comes into play between lines that are boundary polygons and lines as linear features. In my eyes pixels that are on boundarylines of polygons should be part of the segments that are internal to that boundary. Linear features would have to be treated differently. During discussions with colleagues we did have some difficulties finding actual use cases for linear features. Maybe we can start with only polygon features and if the use case of a linear features comes up try to integrate that then ?*/
 /*EM: But for polygons covering the entire map, there is a segment on either side of the polygon line.  If the line crosses the pixel, what should be done... It looks like this will not be a problem for multi-scalar segmentation, the polygons generated in a high level segmentation will be exactly between pixels.  This will only be an issue for polygons generated elsewhere, smoothed, at different resolution, etc.*/
 /* MM: You can not know where the polygons are coming from, therefore you have consider all cases or, better, come up with a general solution. You will need to clone (substantial) parts of the t.to.vect module if you want to rasterize polygons/boundaries. If you do not rasterize, you will need to check for a boundary/line whenever you evaluate a neighbor. This could be sped up a bit by selecting all boundaries/lines crossing the current 3x3 neighborhood. The spatial selection of vector features is fast, but doing that for every cell/3x3 neighborhood can substantially slow down the module. You will also need to check if the boundary is actually part of an area (not an invalid boundary). Then you will need to check if the focus cell is inside the area, if not, if the neighbor is inside the area. Even though some spatial information gets lost by rasterization, I tend to recommend rasterization. In any case, taking into account boundaries/lines can easily become the bulk of the code, the most complex part of the code, and the most time-consuming component of the module. */
 /* EM: left the above discussion... unresolved.  One thought: instead of storing the output as a raster, maybe it should be first converted to a map, edges representing the neighbor relationship.  After we have a map, we could use the vector map to delete edges crossing the borders.  This is done once, afterwards we never calculate neighbors, only check for edges.  It seems this will be a very large memory structure to start with, but as the segmentation continues it will get smaller.
@@ -271,7 +271,7 @@ will use function pointer based on input, to select 4 or 8 neighbors
 
 
 /*****************************************/
-/******Function: calculate simularity ****/
+/******Function: calculate similarity ****/
 /*****************************************/
 
 Initially only Euclidean Distance

imagery/i.segment/region_growing.c

@@ -886,7 +886,7 @@ double calculate_shape(struct reg_stats *rsi, struct reg_stats *rsk,
 
     /* here we calculate a shape index for the new object to be created
      * the radiometric index ranges from 0 to 1, 0 = identical
-     * with the shape index we want to favour compact and smooth opjects
+     * with the shape index we want to favour compact and smooth objects
      * thus the shape index should range from 0 to 1,
      * 0 = maximum compactness and smoothness */
 

imagery/i.smap/interp.c

@@ -211,7 +211,7 @@ static void interp(
     double cost, mincost;  /* cost of class selection; minimum cost */
     int best = 0;          /* class of minimum cost selection */
     double Constant, tmp;
-    double *pdf; /* propability density function of class selections */
+    double *pdf; /* probability density function of class selections */
     double Z;    /* normalizing constant for pdf */
     double alpha0, alpha1, alpha2; /* transition probabilities */
     double log_tbl[2][3][2];       /* log of transition probability */
@@ -314,7 +314,7 @@ void MLE(                       /* computes maximum likelihood classification */
 }
 
 static int up_char(
-    /* Computes list of pointers to nieghbors at next coarser resolution. *
+    /* Computes list of pointers to neighbors at next coarser resolution. *
      * Returns flag when on boundary.                                     */
     int i, int j,          /* fine resolution pixel location */
     struct Region *region, /* fine resolution image region */

imagery/i.svm.train/testsuite/test_i_svm_train.py

@@ -177,7 +177,7 @@ def test_wrong_sigfile_mapset(self):
 
     @unittest.skipIf(shutil.which("i.svm.train") is None, "i.svm.train not found.")
     def test_wrong_svm_param(self):
-        """Attempt to use invalid SVM parametres"""
+        """Attempt to use invalid SVM parameters"""
         sigfile = grass.tempname(10)
         isvm = SimpleModule(
             "i.svm.train",