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More typo and duplicate word fixes.

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commit 32a20f43753bcd8a6c7c04b3cca8557ca70ffd4e 1 parent ac9f504
Christian Brueffer cbrueffer authored peterjc committed

Showing 45 changed files with 75 additions and 75 deletions. Show diff stats Hide diff stats

  1. +1 1  Bio/Align/AlignInfo.py
  2. +1 1  Bio/Align/Applications/_Mafft.py
  3. +1 1  Bio/Align/__init__.py
  4. +1 1  Bio/Application/__init__.py
  5. +2 2 Bio/Blast/Applications.py
  6. +2 2 Bio/Blast/NCBIStandalone.py
  7. +1 1  Bio/Blast/NCBIXML.py
  8. +3 3 Bio/Emboss/Applications.py
  9. +1 1  Bio/GenBank/Scanner.py
  10. +1 1  Bio/Graphics/Comparative.py
  11. +2 2 Bio/HMM/Trainer.py
  12. +2 2 Bio/Motif/Applications/_AlignAce.py
  13. +2 2 Bio/Motif/_Motif.py
  14. +6 6 Bio/NeuralNetwork/BackPropagation/Layer.py
  15. +2 2 Bio/NeuralNetwork/BackPropagation/Network.py
  16. +1 1  Bio/NeuralNetwork/Gene/Motif.py
  17. +1 1  Bio/NeuralNetwork/Gene/Schema.py
  18. +3 3 Bio/Nexus/Trees.py
  19. +1 1  Bio/PDB/Atom.py
  20. +1 1  Bio/PDB/Entity.py
  21. +1 1  Bio/PDB/PDBParser.py
  22. +1 1  Bio/PDB/Polypeptide.py
  23. +1 1  Bio/Pathway/__init__.py
  24. +1 1  Bio/Phylo/Applications/_Raxml.py
  25. +2 2 Bio/Restriction/PrintFormat.py
  26. +2 2 Bio/Restriction/Restriction.py
  27. +4 4 Bio/Restriction/_Update/RestrictionCompiler.py
  28. +1 1  Bio/SCOP/Raf.py
  29. +1 1  Bio/SeqIO/PirIO.py
  30. +1 1  Bio/SeqIO/SffIO.py
  31. +1 1  Bio/SeqIO/__init__.py
  32. +1 1  Bio/SeqIO/_index.py
  33. +1 1  Bio/Sequencing/Phd.py
  34. +1 1  Bio/SubsMat/FreqTable.py
  35. +1 1  Bio/SubsMat/__init__.py
  36. +1 1  Bio/cpairwise2module.c
  37. +6 6 Doc/Tutorial.tex
  38. +3 3 Doc/biopdb_faq.lyx
  39. +3 3 Doc/biopdb_faq.tex
  40. +1 1  NEWS
  41. +1 1  Tests/common_BioSQL.py
  42. +1 1  Tests/test_NNGeneral.py
  43. +1 1  Tests/test_SeqIO_FastaIO.py
  44. +1 1  Tests/test_SeqIO_QualityIO.py
  45. +2 2 Tests/test_SeqIO_convert.py
2  Bio/Align/AlignInfo.py
@@ -322,7 +322,7 @@ def _get_all_letters(self):
322 322 return all_letters
323 323
324 324 def _get_base_replacements(self, skip_items = []):
325   - """Get a zeroed dictonary of all possible letter combinations.
  325 + """Get a zeroed dictionary of all possible letter combinations.
326 326
327 327 This looks at the type of alphabet and gets the letters for it.
328 328 It then creates a dictionary with all possible combinations of these
2  Bio/Align/Applications/_Mafft.py
@@ -327,7 +327,7 @@ def __init__(self, cmd="mafft", **kwargs):
327 327 equate=False),
328 328 #The old solution of also defining extra parameters with
329 329 #["--seed", "seed1"] etc worked, but clashes with the recent
330   - #code in the base class to look for duplicate paramters and raise
  330 + #code in the base class to look for duplicate parameters and raise
331 331 #an error. Perhaps that check should be ignored here, or maybe
332 332 #we can handle this more elegantly...
333 333 #TODO - Create an _OptionList parameter which allows a list to be
2  Bio/Align/__init__.py
@@ -15,7 +15,7 @@
15 15 from Bio.SeqRecord import SeqRecord
16 16 from Bio import Alphabet
17 17
18   -#We only import this and subclass it for some limited backward compatibilty.
  18 +#We only import this and subclass it for some limited backward compatibility.
19 19 from Bio.Align.Generic import Alignment as _Alignment
20 20
21 21
2  Bio/Application/__init__.py
@@ -385,7 +385,7 @@ def __call__(self, stdin=None, stdout=True, stderr=True,
385 385 by sending it to /dev/null to avoid wasting memory (False). In the
386 386 later case empty string(s) are returned.
387 387
388   - The optional cwd argument is a string giving the working directory to
  388 + The optional cwd argument is a string giving the working directory
389 389 to run the command from. See Python's subprocess module documentation
390 390 for more details.
391 391
4 Bio/Blast/Applications.py
@@ -1383,10 +1383,10 @@ def __init__(self, cmd="blast_formatter", **kwargs):
1383 1383 self.parameters = [
1384 1384 # Input options
1385 1385 _Option(["-rid", "rid"],
1386   - "BLAST Request ID (RID), not compatiable with archive arg",
  1386 + "BLAST Request ID (RID), not compatible with archive arg",
1387 1387 equate=False),
1388 1388 _Option(["-archive", "archive"],
1389   - "Archive file of results, not compatiable with rid arg.",
  1389 + "Archive file of results, not compatible with rid arg.",
1390 1390 filename=True,
1391 1391 equate=False),
1392 1392 # Restrict search or results
4 Bio/Blast/NCBIStandalone.py
@@ -17,7 +17,7 @@
17 17 NCBI BLAST, tools blastall, rpsblast and blastpgp via three helper functions of
18 18 the same name. These functions are very limited for dealing with the output as
19 19 files rather than handles, for which the wrappers in Bio.Blast.Applications are
20   -prefered. Furthermore, the NCBI themselves regard these command line tools as
  20 +preferred. Furthermore, the NCBI themselves regard these command line tools as
21 21 "legacy", and encourage using the new BLAST+ tools instead. Biopython has
22 22 wrappers for these under Bio.Blast.Applications (see the tutorial).
23 23
@@ -2217,6 +2217,6 @@ def _diagnose_error(self, handle, data_record):
2217 2217 # to indicate a failure to perform the BLAST due to
2218 2218 # low quality sequence
2219 2219 if line.startswith('Searchingdone'):
2220   - raise LowQualityBlastError("Blast failure occured on query: ",
  2220 + raise LowQualityBlastError("Blast failure occurred on query: ",
2221 2221 data_record.query)
2222 2222 line = handle.readline()
2  Bio/Blast/NCBIXML.py
@@ -437,7 +437,7 @@ def _end_Hsp_bit_score(self):
437 437 self._descr.bits = float(self._value)
438 438
439 439 def _end_Hsp_evalue(self):
440   - """expect value value of the HSP
  440 + """expect value of the HSP
441 441 """
442 442 self._hsp.expect = float(self._value)
443 443 if self._descr.e is None:
6 Bio/Emboss/Applications.py
@@ -640,7 +640,7 @@ def __init__(self, cmd = "fdnapars", **kwargs):
640 640 _Option(["-njumble", "njumble"],
641 641 "number of times to randomise input order (default is 0)"),
642 642 _Option(["-seed", "seed"],
643   - "provde random seed"),
  643 + "provide random seed"),
644 644 _Option(["-outgrno", "outgrno"],
645 645 "Specify outgroup"),
646 646 _Option(["-thresh", "thresh"],
@@ -684,7 +684,7 @@ def __init__(self, cmd = "fprotpars", **kwargs):
684 684 _Option(["-njumble", "njumble"],
685 685 "number of times to randomise input order (default is 0)"),
686 686 _Option(["-seed", "seed"],
687   - "provde random seed"),
  687 + "provide random seed"),
688 688 _Option(["-outgrno", "outgrno"],
689 689 "Specify outgroup"),
690 690 _Option(["-thresh", "thresh"],
@@ -735,7 +735,7 @@ def __init__(self, cmd = "fprotdist", **kwargs):
735 735 _Option(["-ttratio", "ttratio"],
736 736 "Transition/transversion ratio (0-1)"),
737 737 _Option(["-basefreq", "basefreq"],
738   - "DNA base frequencies (space seperated list)")]
  738 + "DNA base frequencies (space separated list)")]
739 739 _EmbossCommandLine.__init__(self, cmd, **kwargs)
740 740
741 741
2  Bio/GenBank/Scanner.py
@@ -1257,7 +1257,7 @@ def _feed_header_lines(self, consumer, lines):
1257 1257 #species names (as more and more strains and sub strains get
1258 1258 #sequenced) the oragnism name can now get wrapped onto multiple
1259 1259 #lines. The NCBI say we have to recognise the lineage line by
1260   - #the presense of semi-colon delimited entries. In the long term,
  1260 + #the presence of semi-colon delimited entries. In the long term,
1261 1261 #they are considering adding a new keyword (e.g. LINEAGE).
1262 1262 #See Bug 2591 for details.
1263 1263 organism_data = data
2  Bio/Graphics/Comparative.py
@@ -46,7 +46,7 @@ def __init__(self, output_format = 'pdf'):
46 46 # the information we'll be writing
47 47 self.display_info = []
48 48
49   - # inital colors and shapes used for drawing points
  49 + # initial colors and shapes used for drawing points
50 50 self.color_choices = [colors.red, colors.green, colors.blue,
51 51 colors.yellow, colors.orange, colors.black]
52 52 self.shape_choices = [makeFilledCircle, makeEmptySquare,
4 Bio/HMM/Trainer.py
@@ -2,7 +2,7 @@
2 2
3 3 These should be used to 'train' a Markov Model prior to actually using
4 4 it to decode state paths. When supplied training sequences and a model
5   -to work from, these classes will estimate paramters of the model.
  5 +to work from, these classes will estimate parameters of the model.
6 6
7 7 This aims to estimate two parameters:
8 8
@@ -53,7 +53,7 @@ def log_likelihood(self, probabilities):
53 53 Arguments:
54 54
55 55 o probabilities -- A list of the probabilities of each training
56   - sequence under the current paramters, calculated using the forward
  56 + sequence under the current parameters, calculated using the forward
57 57 algorithm.
58 58 """
59 59 total_likelihood = 0
4 Bio/Motif/Applications/_AlignAce.py
@@ -29,7 +29,7 @@
29 29 class AlignAceCommandline(AbstractCommandline):
30 30 """Create a commandline for the AlignAce program.
31 31
32   - XXX This could use more checking for valid paramters to the program.
  32 + XXX This could use more checking for valid parameters to the program.
33 33 """
34 34 def __init__(self, cmd="AlignACE", **kwargs):
35 35 self.parameters = \
@@ -64,7 +64,7 @@ def __init__(self, cmd="AlignACE", **kwargs):
64 64 class CompareAceCommandline(AbstractCommandline):
65 65 """Create a commandline for the CompareAce program.
66 66
67   - XXX This could use more checking for valid paramters to the program.
  67 + XXX This could use more checking for valid parameters to the program.
68 68 """
69 69 def __init__(self, cmd="CompareACE", **kwargs):
70 70 import os.path
4 Bio/Motif/_Motif.py
@@ -872,7 +872,7 @@ def dist_pearson_at(self,motif,offset):
872 872
873 873 def dist_product(self,other):
874 874 """
875   - A similarity measure taking into account a product probability of generating overlaping instances of two motifs
  875 + A similarity measure taking into account a product probability of generating overlapping instances of two motifs
876 876 """
877 877 warnings.warn("""\
878 878 This function is now obsolete, and will be deprecated and removed
@@ -1002,7 +1002,7 @@ def __str__(self,masked=False):
1002 1002 def __len__(self):
1003 1003 """return the length of a motif
1004 1004
1005   - Please use this method (i.e. invoke len(m)) instead of refering to the m.length directly.
  1005 + Please use this method (i.e. invoke len(m)) instead of referring to m.length directly.
1006 1006 """
1007 1007 if self.length is None:
1008 1008 return 0
12 Bio/NeuralNetwork/BackPropagation/Layer.py
@@ -111,7 +111,7 @@ def update(self, inputs):
111 111 for input_num in range(len(inputs)):
112 112 self.values[input_num + 1] = inputs[input_num]
113 113
114   - # propogate the update to the next layer
  114 + # propagate the update to the next layer
115 115 self._next_layer.update(self)
116 116
117 117 def backpropagate(self, outputs, learning_rate, momentum):
@@ -126,7 +126,7 @@ def backpropagate(self, outputs, learning_rate, momentum):
126 126
127 127 o outputs - The output info we are using to calculate error.
128 128 """
129   - # first backpropogate to the next layers
  129 + # first backpropagate to the next layers
130 130 next_errors = self._next_layer.backpropagate(outputs, learning_rate,
131 131 momentum)
132 132
@@ -203,7 +203,7 @@ def update(self, previous_layer):
203 203
204 204 self.values[update_node] = self._activation(sum)
205 205
206   - # propogate the update to the next layer
  206 + # propagate the update to the next layer
207 207 self._next_layer.update(self)
208 208
209 209 def backpropagate(self, outputs, learning_rate, momentum):
@@ -219,7 +219,7 @@ def backpropagate(self, outputs, learning_rate, momentum):
219 219 o outputs - The output values we are using to see how good our
220 220 network is at predicting things.
221 221 """
222   - # first backpropogate to the next layers
  222 + # first backpropagate to the next layers
223 223 next_errors = self._next_layer.backpropagate(outputs, learning_rate,
224 224 momentum)
225 225
@@ -241,7 +241,7 @@ def backpropagate(self, outputs, learning_rate, momentum):
241 241 # --- calculate error terms
242 242 errors = {}
243 243 for error_node in self.nodes:
244   - # get the error info propogated from the next layer
  244 + # get the error info propagated from the next layer
245 245 previous_error = 0.0
246 246 for next_node in self._next_layer.nodes:
247 247 previous_error += (next_errors[next_node] *
@@ -282,7 +282,7 @@ def update(self, previous_layer):
282 282
283 283 Arguments:
284 284
285   - o previous_layer -- The hidden layer preceeding this.
  285 + o previous_layer -- The hidden layer preceding this.
286 286 """
287 287 # update all of the nodes in this layer
288 288 for update_node in self.nodes:
4 Bio/NeuralNetwork/BackPropagation/Network.py
@@ -65,10 +65,10 @@ def train(self, training_examples, validation_examples,
65 65 for example in training_examples:
66 66 # update the predicted values for all of the nodes
67 67 # based on the current weights and the inputs
68   - # This propogates over the entire network from the input.
  68 + # This propagates over the entire network from the input.
69 69 self._input.update(example.inputs)
70 70
71   - # calculate the error via back propogation
  71 + # calculate the error via back propagation
72 72 self._input.backpropagate(example.outputs,
73 73 learning_rate, momentum)
74 74
2  Bio/NeuralNetwork/Gene/Motif.py
@@ -178,7 +178,7 @@ def representation(self, sequence):
178 178
179 179 This converts a sequence into a representation based on the motifs.
180 180 The representation is returned as a list of the relative amount of
181   - each motif (number of times a motif occured divided by the total
  181 + each motif (number of times a motif occurred divided by the total
182 182 number of motifs in the sequence). The values in the list correspond
183 183 to the input order of the motifs specified in the initializer.
184 184 """
2  Bio/NeuralNetwork/Gene/Schema.py
@@ -47,7 +47,7 @@ def __init__(self, ambiguity_info):
47 47
48 48 o ambiguity_info - A dictionary which maps letters in the motifs to
49 49 the ambiguous characters which they might represent. For example,
50   - {'R' : 'AG'} specifies that Rs in the motif can match a A or a G.
  50 + {'R' : 'AG'} specifies that Rs in the motif can match an A or a G.
51 51 All letters in the motif must be represented in the ambiguity_info
52 52 dictionary.
53 53 """
6 Bio/Nexus/Trees.py
@@ -527,7 +527,7 @@ def randomize(self,ntax=None,taxon_list=None,branchlength=1.0,branchlength_sd=No
527 527 def display(self):
528 528 """Quick and dirty lists of all nodes."""
529 529 table=[('#','taxon','prev','succ','brlen','blen (sum)','support','comment')]
530   - #Sort this to be consistent accross CPython, Jython, etc
  530 + #Sort this to be consistent across CPython, Jython, etc
531 531 for i in sorted(self.all_ids()):
532 532 n=self.node(i)
533 533 if not n.data:
@@ -754,9 +754,9 @@ def merge_with_support(self,bstrees=None,constree=None,threshold=0.5,outgroup=No
754 754 """
755 755
756 756 if bstrees and constree:
757   - raise TreeError('Specify either list of boostrap trees or consensus tree, not both')
  757 + raise TreeError('Specify either list of bootstrap trees or consensus tree, not both')
758 758 if not (bstrees or constree):
759   - raise TreeError('Specify either list of boostrap trees or consensus tree.')
  759 + raise TreeError('Specify either list of bootstrap trees or consensus tree.')
760 760 # no outgroup specified: use the smallest clade of the root
761 761 if outgroup is None:
762 762 try:
2  Bio/PDB/Atom.py
@@ -65,7 +65,7 @@ def __init__(self, name, coord, bfactor, occupancy, altloc, fullname, serial_num
65 65 self.siguij_array=None
66 66 self.sigatm_array=None
67 67 self.serial_number=serial_number
68   - # Dictionary that keeps addictional properties
  68 + # Dictionary that keeps additional properties
69 69 self.xtra={}
70 70 assert not element or element == element.upper(), element
71 71 self.element = self._assign_element(element)
2  Bio/PDB/Entity.py
@@ -24,7 +24,7 @@ def __init__(self, id):
24 24 self.parent=None
25 25 self.child_list=[]
26 26 self.child_dict={}
27   - # Dictionary that keeps addictional properties
  27 + # Dictionary that keeps additional properties
28 28 self.xtra={}
29 29
30 30 # Special methods
2  Bio/PDB/PDBParser.py
@@ -47,7 +47,7 @@ def __init__(self, PERMISSIVE=True, get_header=False,
47 47 o structure_builder - an optional user implemented StructureBuilder class.
48 48
49 49 o QUIET - Evaluated as a Boolean. If true, warnings issued in constructing
50   - the SMCRA data will be supressed. If false (DEFAULT), they will be shown.
  50 + the SMCRA data will be suppressed. If false (DEFAULT), they will be shown.
51 51 These warnings might be indicative of problems in the PDB file!
52 52 """
53 53 if structure_builder is not None:
2  Bio/PDB/Polypeptide.py
@@ -337,7 +337,7 @@ def build_peptides(self, entity, aa_only=1):
337 337 is_connected=self._is_connected
338 338 accept=self._accept
339 339 level=entity.get_level()
340   - # Decide wich entity we are dealing with
  340 + # Decide which entity we are dealing with
341 341 if level=="S":
342 342 model=entity[0]
343 343 chain_list=model.get_list()
2  Bio/Pathway/__init__.py
@@ -16,7 +16,7 @@
16 16 Network objects are used to represent the connectivity between species in pathways
17 17 and reaction networks.
18 18
19   -For applications where it is not neccessary to explicitly represent network connectivity,
  19 +For applications where it is not necessary to explicitly represent network connectivity,
20 20 the specialized classes Reaction and System should be used in place of Interacton and
21 21 Network.
22 22
2  Bio/Phylo/Applications/_Raxml.py
@@ -354,7 +354,7 @@ def __init__(self, cmd='raxmlHPC', **kwargs):
354 354 _Option(['-N', '-#', 'num_replicates'],
355 355 "Number of alternative runs on distinct starting trees. "
356 356 "In combination with the '-b' option, this will invoke a "
357   - "multiple boostrap analysis. "
  357 + "multiple bootstrap analysis. "
358 358 "DEFAULT: 1 single analysis."
359 359 "Note that '-N' has been added as an alternative since "
360 360 "'-#' sometimes caused problems with certain MPI job "
4 Bio/Restriction/PrintFormat.py
@@ -55,7 +55,7 @@
55 55 >>> new.print_that(dct)
56 56 ...
57 57
58   - Some of the methods of PrintFormat are meant to be overriden by derived
  58 + Some of the methods of PrintFormat are meant to be overridden by derived
59 59 class.
60 60 """
61 61
@@ -100,7 +100,7 @@ def print_that(self, dct, title='', s1=''):
100 100 dct is a dictionary as returned by a RestrictionBatch.search()
101 101
102 102 title is the title of the map.
103   - It must be a formated string, i.e. you must include the line break.
  103 + It must be a formatted string, i.e. you must include the line break.
104 104
105 105 s1 is the title separating the list of enzymes that have sites from
106 106 those without sites.
4 Bio/Restriction/Restriction.py
@@ -802,7 +802,7 @@ def is_methylable(self):
802 802
803 803
804 804 class Meth_Undep(AbstractCut):
805   - """Implement informations about methylation sensitibility.
  805 + """Implement information about methylation sensitibility.
806 806
807 807 Enzymes of this class are not sensible to methylation."""
808 808
@@ -2265,7 +2265,7 @@ def with_name(self, names, dct=None):
2265 2265 Limit the search to the enzymes named in list_of_names."""
2266 2266 for i, enzyme in enumerate(names):
2267 2267 if not enzyme in AllEnzymes:
2268   - print "no datas for the enzyme:", str(name)
  2268 + print "no data for the enzyme:", str(name)
2269 2269 del names[i]
2270 2270 if not dct:
2271 2271 return RestrictionBatch(names).search(self.sequence)
8 Bio/Restriction/_Update/RestrictionCompiler.py
@@ -30,9 +30,9 @@
30 30
31 31 The Rebase files are in the emboss format:
32 32
33   - emboss_e.### -> contains informations about the restriction sites.
34   - emboss_r.### -> contains general informations about the enzymes.
35   - emboss_s.### -> contains informations about the suppliers.
  33 + emboss_e.### -> contains information about the restriction sites.
  34 + emboss_r.### -> contains general information about the enzymes.
  35 + emboss_s.### -> contains information about the suppliers.
36 36
37 37 ### is a 3 digit number. The first digit is the year and the two last the month.
38 38 """
@@ -485,7 +485,7 @@ def build_dict(self):
485 485 results.write("rest_dict[%s] = _temp()\n" % repr(name))
486 486 results.write("\n")
487 487 print 'OK.\n'
488   - print 'Writing the dictionary containing the suppliers datas.\t\t',
  488 + print 'Writing the dictionary containing the suppliers data.\t\t',
489 489 results.write('suppliers = {}\n')
490 490 for name in sorted(suppliersdict) :
491 491 results.write("def _temp():\n")
2  Bio/SCOP/Raf.py
@@ -16,7 +16,7 @@
16 16 final arbiter in case of discrepancies.
17 17
18 18 Residues are referenced by residue ID. This consists of a the PDB residue
19   -sequence number (upto 4 digits) and an optional PDB insertion code (an
  19 +sequence number (up to 4 digits) and an optional PDB insertion code (an
20 20 ascii alphabetic character, a-z, A-Z). e.g. "1", "10A", "1010b", "-1"
21 21
22 22 See "ASTRAL RAF Sequence Maps":http://astral.stanford.edu/raf.html
2  Bio/SeqIO/PirIO.py
@@ -65,7 +65,7 @@
65 65 YNPVIYILMN KQFRNCMITT LCCGKNPLGD DE-SGASTSKT EVSSVSTSPV SPA*
66 66
67 67
68   -As with the FASTA format, each record starts with a line begining with ">"
  68 +As with the FASTA format, each record starts with a line beginning with ">"
69 69 character. There is then a two letter sequence type (P1, F1, DL, DC, RL,
70 70 RC, or XX), a semi colon, and the identification code. The second like is
71 71 free text description. The remaining lines contain the sequence itself,
2  Bio/SeqIO/SffIO.py
@@ -475,7 +475,7 @@ def ReadRocheXmlManifest(handle):
475 475 """Reads any Roche style XML manifest data in the SFF "index".
476 476
477 477 The SFF file format allows for multiple different index blocks, and Roche
478   - took advantage of this to define their own index block wich also embeds
  478 + took advantage of this to define their own index block which also embeds
479 479 an XML manifest string. This is not a publically documented extension to
480 480 the SFF file format, this was reverse engineered.
481 481
2  Bio/SeqIO/__init__.py
@@ -747,7 +747,7 @@ def index(filename, format, alphabet=None, key_function=None):
747 747
748 748 As with the to_dict() function, by default the id string of each record
749 749 is used as the key. You can specify a callback function to transform
750   - this (the record identifier string) into your prefered key. For example:
  750 + this (the record identifier string) into your preferred key. For example:
751 751
752 752 >>> from Bio import SeqIO
753 753 >>> def make_tuple(identifier):
2  Bio/SeqIO/_index.py
@@ -68,7 +68,7 @@ def _parse(handle):
68 68
69 69 def get(self, offset):
70 70 """Returns SeqRecord."""
71   - #Should be overriden for binary file formats etc:
  71 + #Should be overridden for binary file formats etc:
72 72 return self._parse(StringIO(_bytes_to_string(self.get_raw(offset))))
73 73
74 74
2  Bio/Sequencing/Phd.py
@@ -9,7 +9,7 @@
9 9 """
10 10 Parser for PHD files output by PHRED and used by PHRAP and CONSED.
11 11
12   -This module can be used used directly which will return Record objects
  12 +This module can be used directly which will return Record objects
13 13 which should contain all the original data in the file.
14 14
15 15 Alternatively, using Bio.SeqIO with the "phd" format will call this module
2  Bio/SubsMat/FreqTable.py
@@ -8,7 +8,7 @@
8 8 # Methods to read a letter frequency or a letter count file:
9 9 # Example files for a DNA alphabet:
10 10 #
11   -# A count file (whitespace seperated):
  11 +# A count file (whitespace separated):
12 12 #
13 13 # A 50
14 14 # C 37
2  Bio/SubsMat/__init__.py
@@ -24,7 +24,7 @@
24 24
25 25 Usage:
26 26 -----
27   -The following section is layed out in the order by which most people wish
  27 +The following section is laid out in the order by which most people wish
28 28 to generate a log-odds matrix. Of course, interim matrices can be
29 29 generated and investigated. Most people just want a log-odds matrix,
30 30 that's all.
2  Bio/cpairwise2module.c
@@ -323,7 +323,7 @@ static PyObject *cpairwise2__make_score_matrix_fast(
323 323 first_B_gap = calc_affine_penalty(1, open_B, extend_B,
324 324 penalize_extend_when_opening);
325 325
326   - /* Allocate matrices for storing the results and initalize them. */
  326 + /* Allocate matrices for storing the results and initialize them. */
327 327 lenA = PySequence_Length(py_sequenceA);
328 328 lenB = PySequence_Length(py_sequenceB);
329 329 score_matrix = malloc(lenA*lenB*sizeof(*score_matrix));
12 Doc/Tutorial.tex
@@ -4443,7 +4443,7 @@ \subsection{ClustalW}
4443 4443 ``r'' at the start for a raw string that isn't translated in this way.
4444 4444 This is generally good practice when specifying a Windows style file name.
4445 4445
4446   -The last line of the example requires Biopython 1.55 or later to run the
  4446 +The last line of the example requires Biopython 1.55 or later to run
4447 4447 the command line tool via our wrapper object. Internally this uses the
4448 4448 \verb|subprocess| module which is now the recommended way to run another
4449 4449 program in Python. This replaces older options like the \verb|os.system()|
@@ -5970,7 +5970,7 @@ \subsection{QueryResult}
5970 5970 \verb|QueryResult| objects, but you'll end up with regular Python lists and lose
5971 5971 the ability to do more interesting manipulations.
5972 5972
5973   -That's why, \verb|QueryResult| objects provide its own flavor of of
  5973 +That's why, \verb|QueryResult| objects provide its own flavor of
5974 5974 \verb|filter| and \verb|map| methods. Analogous to \verb|filter|, there are
5975 5975 \verb|hit_filter| and \verb|hsp_filter| methods. As their name implies, these
5976 5976 methods filter its \verb|QueryResult| object either on its \verb|Hit| objects
@@ -8966,7 +8966,7 @@ \subsection{Disordered atoms\label{disordered atoms}}
8966 8966 that represent the same physical atom are stored in a DisorderedAtom object.
8967 8967 Each Atom object in a DisorderedAtom object can be uniquely indexed using its
8968 8968 altloc specifier. The DisorderedAtom object forwards all uncaught method calls
8969   -to the selected Atom object, by default the one that represents the atom with
  8969 +to the selected Atom object, by default the one that represents the atom
8970 8970 with the highest occupancy. The user can of course change the selected Atom
8971 8971 object, making use of its altloc specifier. In this way atom disorder is represented
8972 8972 correctly without much additional complexity. In other words, if you are not
@@ -10890,7 +10890,7 @@ \subsection{Reading and writing}
10890 10890 motifs, but there's a couple of formats which are more used than
10891 10891 others. The most important distinction is whether the motif
10892 10892 representation is based on instances or on some version of PWM matrix.
10893   -On of the most popular motif databases \href{http://jaspar.genereg.net}{JASPAR}
  10893 +One of the most popular motif databases \href{http://jaspar.genereg.net}{JASPAR}
10894 10894 stores motifs in both formats, so
10895 10895 let's look at how we can import JASPAR motifs from instances:
10896 10896 %cont-doctest
@@ -15232,7 +15232,7 @@ \subsection{Information Content}
15232 15232 \begin{itemize}
15233 15233 \item $IC_{j}$ -- The information content for the $j$-th column in an alignment.
15234 15234 \item $N_{a}$ -- The number of letters in the alphabet.
15235   - \item $P_{ij}$ -- The frequency of a particular letter $i$ in the $j$-th column (i.~e.~if G occured 3 out of 6 times in an aligment column, this would be 0.5)
  15235 + \item $P_{ij}$ -- The frequency of a particular letter $i$ in the $j$-th column (i.~e.~if G occurred 3 out of 6 times in an aligment column, this would be 0.5)
15236 15236 \item $Q_{i}$ -- The expected frequency of a letter $i$. This is an
15237 15237 optional argument, usage of which is left at the user's
15238 15238 discretion. By default, it is automatically assigned to $0.05 = 1/20$ for a
@@ -15989,7 +15989,7 @@ \subsection{SubsMat}
15989 15989
15990 15990 \item Usage
15991 15991
15992   - The following section is layed out in the order by which most people wish to generate a log-odds matrix. Of course, interim matrices can be generated and
  15992 + The following section is laid out in the order by which most people wish to generate a log-odds matrix. Of course, interim matrices can be generated and
15993 15993 investigated. Most people just want a log-odds matrix, that's all.
15994 15994
15995 15995 \begin{enumerate}
6 Doc/biopdb_faq.lyx
@@ -1355,7 +1355,7 @@ Disordered\SpecialChar \-
1355 1355 Atom
1356 1356 \family default
1357 1357 object forwards all uncaught method calls to the selected Atom object,
1358   - by default the one that represents the atom with with the highest occupancy.
  1358 + by default the one that represents the atom with the highest occupancy.
1359 1359 The user can of course change the selected
1360 1360 \family typewriter
1361 1361 Atom
@@ -1922,7 +1922,7 @@ Residue
1922 1922
1923 1923 .
1924 1924 Note that DSSP (the program, and thus by consequence the class) cannot
1925   - handle mutiple models!
  1925 + handle multiple models!
1926 1926 \layout Standard
1927 1927
1928 1928
@@ -2249,7 +2249,7 @@ Residue depth is the average distance of a residue's atoms from the solvent
2249 2249 ResidueDepth
2250 2250 \family default
2251 2251 class.
2252   - This class behaves as a dictionary wich maps
  2252 + This class behaves as a dictionary which maps
2253 2253 \family typewriter
2254 2254 Residue
2255 2255 \family default
6 Doc/biopdb_faq.tex
@@ -730,7 +730,7 @@ \subsubsection*{How is disorder handled?}
730 730 Each \texttt{Atom} object in a \texttt{Disordered\-Atom} object can
731 731 be uniquely indexed using its altloc specifier. The \texttt{Disordered\-Atom}
732 732 object forwards all uncaught method calls to the selected Atom object,
733   -by default the one that represents the atom with with the highest
  733 +by default the one that represents the atom with the highest
734 734 occupancy. The user can of course change the selected \texttt{Atom}
735 735 object, making use of its altloc specifier. In this way atom disorder
736 736 is represented correctly without much additional complexity. In other
@@ -988,7 +988,7 @@ \subsubsection*{How do I determine secondary structure?}
988 988 Then use the \texttt{DSSP} class, which maps \texttt{Residue} objects
989 989 to their secondary structure (and accessible surface area). The DSSP
990 990 codes are listed in Table \ref{cap:DSSP-codes}. Note that DSSP (the
991   -program, and thus by consequence the class) cannot handle mutiple
  991 +program, and thus by consequence the class) cannot handle multiple
992 992 models!
993 993
994 994 %
@@ -1045,7 +1045,7 @@ \subsubsection*{How do I calculate residue depth?}
1045 1045 of solvent accessibility. For this functionality, you need to install
1046 1046 Michel Sanner's MSMS program (\url{http://www.scripps.edu/pub/olson-web/people/sanner/html/msms_home.html}).
1047 1047 Then use the \texttt{ResidueDepth} class. This class behaves as a
1048   -dictionary wich maps \texttt{Residue} objects to corresponding (residue
  1048 +dictionary which maps \texttt{Residue} objects to corresponding (residue
1049 1049 depth, C$\alpha$ depth) tuples. The C$\alpha$ depth is the distance
1050 1050 of a residue's C$\alpha$ atom to the solvent accessible surface.
1051 1051
2  NEWS
@@ -452,7 +452,7 @@ needed for our NCBI Entrez Utilities XML parser.
452 452
453 453 The parse, read and write functions in Bio.SeqIO and Bio.AlignIO will now
454 454 accept filenames as well as handles. This follows a general shift from
455   -from other Python libraries, and does make usage a little simpler. Also
  455 +other Python libraries, and does make usage a little simpler. Also
456 456 the write functions will now accept a single SeqRecord or alignment.
457 457
458 458 Bio.SeqIO now supports writing EMBL files (DNA and RNA sequences only).
2  Tests/common_BioSQL.py
@@ -694,7 +694,7 @@ def test_record_loading(self):
694 694 self.assertEqual(str(test_record.seq[:10]), 'ATTTGGCCTA')
695 695
696 696 def test_seq_feature(self):
697   - """Indepth check that SeqFeatures are transmitted through the db.
  697 + """In depth check that SeqFeatures are transmitted through the db.
698 698 """
699 699 test_record = self.db.lookup(accession = "AJ237582")
700 700 features = test_record.features
2  Tests/test_NNGeneral.py
@@ -80,7 +80,7 @@ def test_partioning_examples(self):
80 80 manager = ExampleManager(0, 0)
81 81 manager.add_examples(self.examples)
82 82 assert len(manager.test_examples) == self.num_examples, \
83   - "Did not partion correctly to test_examples."
  83 + "Did not partition correctly to test_examples."
84 84
85 85 manager = ExampleManager(1.0, 0)
86 86 manager.add_examples(self.examples)
2  Tests/test_SeqIO_FastaIO.py
@@ -15,7 +15,7 @@
15 15 def title_to_ids(title):
16 16 """Function to convert a title into the id, name, and description.
17 17
18   - This is just a quick-n-dirty implementation, and is definately not meant
  18 + This is just a quick-n-dirty implementation, and is definetely not meant
19 19 to handle every FASTA title line case.
20 20 """
21 21 # first split the id information from the description
2  Tests/test_SeqIO_QualityIO.py
@@ -56,7 +56,7 @@ def write_read(filename, in_format, out_format):
56 56
57 57
58 58 def compare_record(old, new, truncate=None):
59   - """Quality aware SeqRecord comparision.
  59 + """Quality aware SeqRecord comparison.
60 60
61 61 This will check the mapping between Solexa and PHRED scores.
62 62 It knows to ignore UnknownSeq objects for string matching (i.e. QUAL files).
4 Tests/test_SeqIO_convert.py
@@ -39,7 +39,7 @@ def check_convert(in_filename, in_format, out_format, alphabet=None):
39 39 #Now load it back and check it agrees,
40 40 records2 = list(SeqIO.parse(handle, out_format, alphabet))
41 41 compare_records(records, records2, qual_truncate)
42   - #Finally, use the convert fuction, and check that agrees:
  42 + #Finally, use the convert function, and check that agrees:
43 43 handle2 = StringIO()
44 44 if qual_truncate:
45 45 warnings.simplefilter('ignore', UserWarning)
@@ -84,7 +84,7 @@ def check_convert_fails(in_filename, in_format, out_format, alphabet=None):
84 84
85 85 #TODO - move this to a shared test module...
86 86 def compare_record(old, new, truncate=None):
87   - """Quality aware SeqRecord comparision.
  87 + """Quality aware SeqRecord comparison.
88 88
89 89 This will check the mapping between Solexa and PHRED scores.
90 90 It knows to ignore UnknownSeq objects for string matching (i.e. QUAL files).

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