doc: fix spelling mistakes

Signed-off-by: Eric Engestrom <eric@engestrom.ch>
Signed-off-by: Rémi Denis-Courmont <remi@remlab.net>

doc/Doxyfile.skins2

@@ -138,7 +138,7 @@ STRIP_CODE_COMMENTS    = NO
 # file names in lower case letters. If set to YES upper case letters are also 
 # allowed. This is useful if you have classes or files whose names only differ 
 # in case and if your file system supports case sensitive file names. Windows 
-# users are adviced to set this option to NO.
+# users are advised to set this option to NO.
 
 CASE_SENSE_NAMES       = YES
 

doc/browsing.txt

@@ -27,11 +27,11 @@ A call to pf_readdir has 3 possible results:
   input_item_t possible depending on system state and module options. In this
   case, pf_readdir MUST return VLC_SUCCESS and info.b_eof MUST be set to true.
   This callback must NOT be called again.
-* An unrecoverable error has occured and no input_item_t was added to the node.
+* An unrecoverable error has occurred and no input_item_t was added to the node.
   The callback returns a VLC_ENOITEM error code, and sets info.b_eof to true.
   This error SHOULD be propagated by the calling code (stream/demux/...)
   This callback must NOT be called again.
-* A recoverable error has occured. The callback MUST return an error code
+* A recoverable error has occurred. The callback MUST return an error code
   that is not VLC_SUCCESS or VLC_ENOITEM (e.g. VLC_EGENERIC, VLC_ENOMEM, ...).
   Some input_item_t objects might have been added to the node; they are
   owned by the node which is owned by the access. This callback CAN be

doc/release-howto.txt

@@ -57,7 +57,7 @@ Release HOWTO
   - edit the /index.php /vlc/*.php, include/os-specific.php files
   - create a /vlc/release/X.X.X page
   - add a news item to news.msg
-  - update the front page OS dependant screenshots if the interface changed.
+  - update the front page OS dependent screenshots if the interface changed.
   - update the md5
 
  * "Check for updates" functionality

doc/skins/events-howto.txt

@@ -17,7 +17,7 @@ How to create an event ?
 
 An event describes a simple action as seen above.
 All attributes are explained in the 'skins-howto.txt' file except the 'event'
-attribute wich is a bit special.
+attribute which is a bit special.
 In the 'event' attribute you will enter a simple script with the following
 syntax :
   "EVENT(parameter1,parameter2,...)"
@@ -180,12 +180,12 @@ When creating your event, you must assign an ID to each of them.
 Now you have to associate events with controls.
 Some attributes of some controls are supposed to be filled with those IDs. That
 is to say that when the action corresponding to the attribute will be done,
-the event associated will be executed. The best exemple is assigning an event
+the event associated will be executed. The best example is assigning an event
 to the 'onclick' attribute of a button control. The event will be executed when
 clicking on the button.
 You can execute several events. To do this you just have to separate them with
 semicolon.
-Exemple:
+Example:
   <ButtonControl [...] onclick="event1;event2;event3"/>
 
 

doc/transforms.py

@@ -77,7 +77,7 @@ def unscaled_DFT_radix2_time (N, input, output):
 # reversible, so we can calculate the IDFT with the same complexity.
 
 
-# A varient of this is the radix-2 decimation-in-frequency algorithm :
+# A variant of this is the radix-2 decimation-in-frequency algorithm :
 
 def unscaled_DFT_radix2_freq (N, input, output):
     even_input = vector(N/2)
@@ -103,7 +103,7 @@ def unscaled_DFT_radix2_freq (N, input, output):
 # have exactly the same complexity, they only do the operations in a different
 # order.
 
-# Actually, if you look at the decimation-in-time varient of the DFT, and
+# Actually, if you look at the decimation-in-time variant of the DFT, and
 # reverse it to calculate an IDFT, you get something that is extremely close
 # to the decimation-in-frequency DFT algorithm...
 
@@ -275,7 +275,7 @@ def unscaled_DFT_radix4_freq (N, input, output):
 #	output[i+N/2] = tmp_0[i] - tmp_2[i]
 #	output[i+3*N/4] = tmp_1[i] + 1j * tmp_3[i]
 
-# We didnt do anything here, only reorder the operations. But now, look at the
+# We didn't do anything here, only reorder the operations. But now, look at the
 # first part of this function, up to the calculations of tmp0 and tmp1 : this
 # is extremely similar to the radix-2 decimation-in-time algorithm ! or more
 # precisely, it IS the radix-2 decimation-in-time algorithm, with size N/2,
@@ -368,7 +368,7 @@ def unscaled_DFT_split_radix_freq (N, input, output):
 	output[4*i+1] = output_1[i]
 	output[4*i+3] = output_3[i]
 
-# The complexity is again the same as for the decimation-in-time varient.
+# The complexity is again the same as for the decimation-in-time variant.
 
 
 # Now let us now summarize our various algorithms for DFT decomposition :
@@ -862,7 +862,7 @@ def unscaled_DCT_Lee (N, input, output):
 # Some of the multiplication coefficients 0.5/cos(...) can get quite large.
 # This means that a small error in the input will give a large error on the
 # output... For a DCT of size N the biggest coefficient will be at i=N/2-1
-# and it will be slighly more than N/pi which can be large for large N's.
+# and it will be slightly more than N/pi which can be large for large N's.
 
 # In the IDCT however, the multiplication coefficients for the reverse
 # transformation are of the form 2*cos(...) so they can not get big and there
@@ -958,15 +958,15 @@ def unscaled_DCT_AAN (N, input, output):
 # but that one does not save operations actually, because the other
 # coefficients are the conjugates of the ones we look anyway.
 
-# One useful way to use the symetry of the input is to use the radix-2
+# One useful way to use the symmetry of the input is to use the radix-2
 # decimation-in-frequency algorithm. We can write a version of
-# unscaled_DFT_radix2_freq for the case where the input is symetrical :
+# unscaled_DFT_radix2_freq for the case where the input is symmetrical :
 # we have removed a few additions in the first stages because even_input
-# is symetrical and odd_input is antisymetrical. Also, we have modified the
+# is symmetrical and odd_input is antisymetrical. Also, we have modified the
 # odd_input vector so that the second half of it is set to zero and the real
 # part of the DFT output is not modified. After that modification, the second
 # part of the odd_input was null so we used the radix-2 decimation-in-frequency
-# again on the odd DFT. Also odd_output is symetrical because input is real...
+# again on the odd DFT. Also odd_output is symmetrical because input is real...
 
 def symetrical_unscaled_DFT (N, input, output):
     even_input = vector(N/2)
@@ -986,7 +986,7 @@ def symetrical_unscaled_DFT (N, input, output):
 	odd_input[i] = (odd_tmp[i] + odd_tmp[i-1]) * W (i, N)
 
     unscaled_DFT (N/2, even_input, even_output)
-    # symetrical real inputs, real outputs
+    # symmetrical real inputs, real outputs
 
     unscaled_DFT (N/4, odd_input, odd_output)
     # complex inputs, real outputs
@@ -998,7 +998,7 @@ def symetrical_unscaled_DFT (N, input, output):
 	output[N-1-4*i] = output[4*i+1] = odd_output[i]
 
 # This procedure takes 3*N/4-1 real additions and N/2-3 real multiplies,
-# followed by another symetrical real DFT of size N/2 and a "complex to real"
+# followed by another symmetrical real DFT of size N/2 and a "complex to real"
 # DFT of size N/4.
 
 # We thus get the following performance results :