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More typo and duplicate word fixes.

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1 parent ac9f504 commit 32a20f43753bcd8a6c7c04b3cca8557ca70ffd4e @cbrueffer cbrueffer committed with peterjc Dec 18, 2012
Showing with 75 additions and 75 deletions.
  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
View
2 Bio/Align/AlignInfo.py
@@ -322,7 +322,7 @@ def _get_all_letters(self):
return all_letters
def _get_base_replacements(self, skip_items = []):
- """Get a zeroed dictonary of all possible letter combinations.
+ """Get a zeroed dictionary of all possible letter combinations.
This looks at the type of alphabet and gets the letters for it.
It then creates a dictionary with all possible combinations of these
View
2 Bio/Align/Applications/_Mafft.py
@@ -327,7 +327,7 @@ def __init__(self, cmd="mafft", **kwargs):
equate=False),
#The old solution of also defining extra parameters with
#["--seed", "seed1"] etc worked, but clashes with the recent
- #code in the base class to look for duplicate paramters and raise
+ #code in the base class to look for duplicate parameters and raise
#an error. Perhaps that check should be ignored here, or maybe
#we can handle this more elegantly...
#TODO - Create an _OptionList parameter which allows a list to be
View
2 Bio/Align/__init__.py
@@ -15,7 +15,7 @@
from Bio.SeqRecord import SeqRecord
from Bio import Alphabet
-#We only import this and subclass it for some limited backward compatibilty.
+#We only import this and subclass it for some limited backward compatibility.
from Bio.Align.Generic import Alignment as _Alignment
View
2 Bio/Application/__init__.py
@@ -385,7 +385,7 @@ def __call__(self, stdin=None, stdout=True, stderr=True,
by sending it to /dev/null to avoid wasting memory (False). In the
later case empty string(s) are returned.
- The optional cwd argument is a string giving the working directory to
+ The optional cwd argument is a string giving the working directory
to run the command from. See Python's subprocess module documentation
for more details.
View
4 Bio/Blast/Applications.py
@@ -1383,10 +1383,10 @@ def __init__(self, cmd="blast_formatter", **kwargs):
self.parameters = [
# Input options
_Option(["-rid", "rid"],
- "BLAST Request ID (RID), not compatiable with archive arg",
+ "BLAST Request ID (RID), not compatible with archive arg",
equate=False),
_Option(["-archive", "archive"],
- "Archive file of results, not compatiable with rid arg.",
+ "Archive file of results, not compatible with rid arg.",
filename=True,
equate=False),
# Restrict search or results
View
4 Bio/Blast/NCBIStandalone.py
@@ -17,7 +17,7 @@
NCBI BLAST, tools blastall, rpsblast and blastpgp via three helper functions of
the same name. These functions are very limited for dealing with the output as
files rather than handles, for which the wrappers in Bio.Blast.Applications are
-prefered. Furthermore, the NCBI themselves regard these command line tools as
+preferred. Furthermore, the NCBI themselves regard these command line tools as
"legacy", and encourage using the new BLAST+ tools instead. Biopython has
wrappers for these under Bio.Blast.Applications (see the tutorial).
@@ -2217,6 +2217,6 @@ def _diagnose_error(self, handle, data_record):
# to indicate a failure to perform the BLAST due to
# low quality sequence
if line.startswith('Searchingdone'):
- raise LowQualityBlastError("Blast failure occured on query: ",
+ raise LowQualityBlastError("Blast failure occurred on query: ",
data_record.query)
line = handle.readline()
View
2 Bio/Blast/NCBIXML.py
@@ -437,7 +437,7 @@ def _end_Hsp_bit_score(self):
self._descr.bits = float(self._value)
def _end_Hsp_evalue(self):
- """expect value value of the HSP
+ """expect value of the HSP
"""
self._hsp.expect = float(self._value)
if self._descr.e is None:
View
6 Bio/Emboss/Applications.py
@@ -640,7 +640,7 @@ def __init__(self, cmd = "fdnapars", **kwargs):
_Option(["-njumble", "njumble"],
"number of times to randomise input order (default is 0)"),
_Option(["-seed", "seed"],
- "provde random seed"),
+ "provide random seed"),
_Option(["-outgrno", "outgrno"],
"Specify outgroup"),
_Option(["-thresh", "thresh"],
@@ -684,7 +684,7 @@ def __init__(self, cmd = "fprotpars", **kwargs):
_Option(["-njumble", "njumble"],
"number of times to randomise input order (default is 0)"),
_Option(["-seed", "seed"],
- "provde random seed"),
+ "provide random seed"),
_Option(["-outgrno", "outgrno"],
"Specify outgroup"),
_Option(["-thresh", "thresh"],
@@ -735,7 +735,7 @@ def __init__(self, cmd = "fprotdist", **kwargs):
_Option(["-ttratio", "ttratio"],
"Transition/transversion ratio (0-1)"),
_Option(["-basefreq", "basefreq"],
- "DNA base frequencies (space seperated list)")]
+ "DNA base frequencies (space separated list)")]
_EmbossCommandLine.__init__(self, cmd, **kwargs)
View
2 Bio/GenBank/Scanner.py
@@ -1257,7 +1257,7 @@ def _feed_header_lines(self, consumer, lines):
#species names (as more and more strains and sub strains get
#sequenced) the oragnism name can now get wrapped onto multiple
#lines. The NCBI say we have to recognise the lineage line by
- #the presense of semi-colon delimited entries. In the long term,
+ #the presence of semi-colon delimited entries. In the long term,
#they are considering adding a new keyword (e.g. LINEAGE).
#See Bug 2591 for details.
organism_data = data
View
2 Bio/Graphics/Comparative.py
@@ -46,7 +46,7 @@ def __init__(self, output_format = 'pdf'):
# the information we'll be writing
self.display_info = []
- # inital colors and shapes used for drawing points
+ # initial colors and shapes used for drawing points
self.color_choices = [colors.red, colors.green, colors.blue,
colors.yellow, colors.orange, colors.black]
self.shape_choices = [makeFilledCircle, makeEmptySquare,
View
4 Bio/HMM/Trainer.py
@@ -2,7 +2,7 @@
These should be used to 'train' a Markov Model prior to actually using
it to decode state paths. When supplied training sequences and a model
-to work from, these classes will estimate paramters of the model.
+to work from, these classes will estimate parameters of the model.
This aims to estimate two parameters:
@@ -53,7 +53,7 @@ def log_likelihood(self, probabilities):
Arguments:
o probabilities -- A list of the probabilities of each training
- sequence under the current paramters, calculated using the forward
+ sequence under the current parameters, calculated using the forward
algorithm.
"""
total_likelihood = 0
View
4 Bio/Motif/Applications/_AlignAce.py
@@ -29,7 +29,7 @@
class AlignAceCommandline(AbstractCommandline):
"""Create a commandline for the AlignAce program.
- XXX This could use more checking for valid paramters to the program.
+ XXX This could use more checking for valid parameters to the program.
"""
def __init__(self, cmd="AlignACE", **kwargs):
self.parameters = \
@@ -64,7 +64,7 @@ def __init__(self, cmd="AlignACE", **kwargs):
class CompareAceCommandline(AbstractCommandline):
"""Create a commandline for the CompareAce program.
- XXX This could use more checking for valid paramters to the program.
+ XXX This could use more checking for valid parameters to the program.
"""
def __init__(self, cmd="CompareACE", **kwargs):
import os.path
View
4 Bio/Motif/_Motif.py
@@ -872,7 +872,7 @@ def dist_pearson_at(self,motif,offset):
def dist_product(self,other):
"""
- A similarity measure taking into account a product probability of generating overlaping instances of two motifs
+ A similarity measure taking into account a product probability of generating overlapping instances of two motifs
"""
warnings.warn("""\
This function is now obsolete, and will be deprecated and removed
@@ -1002,7 +1002,7 @@ def __str__(self,masked=False):
def __len__(self):
"""return the length of a motif
- Please use this method (i.e. invoke len(m)) instead of refering to the m.length directly.
+ Please use this method (i.e. invoke len(m)) instead of referring to m.length directly.
"""
if self.length is None:
return 0
View
12 Bio/NeuralNetwork/BackPropagation/Layer.py
@@ -111,7 +111,7 @@ def update(self, inputs):
for input_num in range(len(inputs)):
self.values[input_num + 1] = inputs[input_num]
- # propogate the update to the next layer
+ # propagate the update to the next layer
self._next_layer.update(self)
def backpropagate(self, outputs, learning_rate, momentum):
@@ -126,7 +126,7 @@ def backpropagate(self, outputs, learning_rate, momentum):
o outputs - The output info we are using to calculate error.
"""
- # first backpropogate to the next layers
+ # first backpropagate to the next layers
next_errors = self._next_layer.backpropagate(outputs, learning_rate,
momentum)
@@ -203,7 +203,7 @@ def update(self, previous_layer):
self.values[update_node] = self._activation(sum)
- # propogate the update to the next layer
+ # propagate the update to the next layer
self._next_layer.update(self)
def backpropagate(self, outputs, learning_rate, momentum):
@@ -219,7 +219,7 @@ def backpropagate(self, outputs, learning_rate, momentum):
o outputs - The output values we are using to see how good our
network is at predicting things.
"""
- # first backpropogate to the next layers
+ # first backpropagate to the next layers
next_errors = self._next_layer.backpropagate(outputs, learning_rate,
momentum)
@@ -241,7 +241,7 @@ def backpropagate(self, outputs, learning_rate, momentum):
# --- calculate error terms
errors = {}
for error_node in self.nodes:
- # get the error info propogated from the next layer
+ # get the error info propagated from the next layer
previous_error = 0.0
for next_node in self._next_layer.nodes:
previous_error += (next_errors[next_node] *
@@ -282,7 +282,7 @@ def update(self, previous_layer):
Arguments:
- o previous_layer -- The hidden layer preceeding this.
+ o previous_layer -- The hidden layer preceding this.
"""
# update all of the nodes in this layer
for update_node in self.nodes:
View
4 Bio/NeuralNetwork/BackPropagation/Network.py
@@ -65,10 +65,10 @@ def train(self, training_examples, validation_examples,
for example in training_examples:
# update the predicted values for all of the nodes
# based on the current weights and the inputs
- # This propogates over the entire network from the input.
+ # This propagates over the entire network from the input.
self._input.update(example.inputs)
- # calculate the error via back propogation
+ # calculate the error via back propagation
self._input.backpropagate(example.outputs,
learning_rate, momentum)
View
2 Bio/NeuralNetwork/Gene/Motif.py
@@ -178,7 +178,7 @@ def representation(self, sequence):
This converts a sequence into a representation based on the motifs.
The representation is returned as a list of the relative amount of
- each motif (number of times a motif occured divided by the total
+ each motif (number of times a motif occurred divided by the total
number of motifs in the sequence). The values in the list correspond
to the input order of the motifs specified in the initializer.
"""
View
2 Bio/NeuralNetwork/Gene/Schema.py
@@ -47,7 +47,7 @@ def __init__(self, ambiguity_info):
o ambiguity_info - A dictionary which maps letters in the motifs to
the ambiguous characters which they might represent. For example,
- {'R' : 'AG'} specifies that Rs in the motif can match a A or a G.
+ {'R' : 'AG'} specifies that Rs in the motif can match an A or a G.
All letters in the motif must be represented in the ambiguity_info
dictionary.
"""
View
6 Bio/Nexus/Trees.py
@@ -527,7 +527,7 @@ def randomize(self,ntax=None,taxon_list=None,branchlength=1.0,branchlength_sd=No
def display(self):
"""Quick and dirty lists of all nodes."""
table=[('#','taxon','prev','succ','brlen','blen (sum)','support','comment')]
- #Sort this to be consistent accross CPython, Jython, etc
+ #Sort this to be consistent across CPython, Jython, etc
for i in sorted(self.all_ids()):
n=self.node(i)
if not n.data:
@@ -754,9 +754,9 @@ def merge_with_support(self,bstrees=None,constree=None,threshold=0.5,outgroup=No
"""
if bstrees and constree:
- raise TreeError('Specify either list of boostrap trees or consensus tree, not both')
+ raise TreeError('Specify either list of bootstrap trees or consensus tree, not both')
if not (bstrees or constree):
- raise TreeError('Specify either list of boostrap trees or consensus tree.')
+ raise TreeError('Specify either list of bootstrap trees or consensus tree.')
# no outgroup specified: use the smallest clade of the root
if outgroup is None:
try:
View
2 Bio/PDB/Atom.py
@@ -65,7 +65,7 @@ def __init__(self, name, coord, bfactor, occupancy, altloc, fullname, serial_num
self.siguij_array=None
self.sigatm_array=None
self.serial_number=serial_number
- # Dictionary that keeps addictional properties
+ # Dictionary that keeps additional properties
self.xtra={}
assert not element or element == element.upper(), element
self.element = self._assign_element(element)
View
2 Bio/PDB/Entity.py
@@ -24,7 +24,7 @@ def __init__(self, id):
self.parent=None
self.child_list=[]
self.child_dict={}
- # Dictionary that keeps addictional properties
+ # Dictionary that keeps additional properties
self.xtra={}
# Special methods
View
2 Bio/PDB/PDBParser.py
@@ -47,7 +47,7 @@ def __init__(self, PERMISSIVE=True, get_header=False,
o structure_builder - an optional user implemented StructureBuilder class.
o QUIET - Evaluated as a Boolean. If true, warnings issued in constructing
- the SMCRA data will be supressed. If false (DEFAULT), they will be shown.
+ the SMCRA data will be suppressed. If false (DEFAULT), they will be shown.
These warnings might be indicative of problems in the PDB file!
"""
if structure_builder is not None:
View
2 Bio/PDB/Polypeptide.py
@@ -337,7 +337,7 @@ def build_peptides(self, entity, aa_only=1):
is_connected=self._is_connected
accept=self._accept
level=entity.get_level()
- # Decide wich entity we are dealing with
+ # Decide which entity we are dealing with
if level=="S":
model=entity[0]
chain_list=model.get_list()
View
2 Bio/Pathway/__init__.py
@@ -16,7 +16,7 @@
Network objects are used to represent the connectivity between species in pathways
and reaction networks.
-For applications where it is not neccessary to explicitly represent network connectivity,
+For applications where it is not necessary to explicitly represent network connectivity,
the specialized classes Reaction and System should be used in place of Interacton and
Network.
View
2 Bio/Phylo/Applications/_Raxml.py
@@ -354,7 +354,7 @@ def __init__(self, cmd='raxmlHPC', **kwargs):
_Option(['-N', '-#', 'num_replicates'],
"Number of alternative runs on distinct starting trees. "
"In combination with the '-b' option, this will invoke a "
- "multiple boostrap analysis. "
+ "multiple bootstrap analysis. "
"DEFAULT: 1 single analysis."
"Note that '-N' has been added as an alternative since "
"'-#' sometimes caused problems with certain MPI job "
View
4 Bio/Restriction/PrintFormat.py
@@ -55,7 +55,7 @@
>>> new.print_that(dct)
...
- Some of the methods of PrintFormat are meant to be overriden by derived
+ Some of the methods of PrintFormat are meant to be overridden by derived
class.
"""
@@ -100,7 +100,7 @@ def print_that(self, dct, title='', s1=''):
dct is a dictionary as returned by a RestrictionBatch.search()
title is the title of the map.
- It must be a formated string, i.e. you must include the line break.
+ It must be a formatted string, i.e. you must include the line break.
s1 is the title separating the list of enzymes that have sites from
those without sites.
View
4 Bio/Restriction/Restriction.py
@@ -802,7 +802,7 @@ def is_methylable(self):
class Meth_Undep(AbstractCut):
- """Implement informations about methylation sensitibility.
+ """Implement information about methylation sensitibility.
Enzymes of this class are not sensible to methylation."""
@@ -2265,7 +2265,7 @@ def with_name(self, names, dct=None):
Limit the search to the enzymes named in list_of_names."""
for i, enzyme in enumerate(names):
if not enzyme in AllEnzymes:
- print "no datas for the enzyme:", str(name)
+ print "no data for the enzyme:", str(name)
del names[i]
if not dct:
return RestrictionBatch(names).search(self.sequence)
View
8 Bio/Restriction/_Update/RestrictionCompiler.py
@@ -30,9 +30,9 @@
The Rebase files are in the emboss format:
- emboss_e.### -> contains informations about the restriction sites.
- emboss_r.### -> contains general informations about the enzymes.
- emboss_s.### -> contains informations about the suppliers.
+ emboss_e.### -> contains information about the restriction sites.
+ emboss_r.### -> contains general information about the enzymes.
+ emboss_s.### -> contains information about the suppliers.
### is a 3 digit number. The first digit is the year and the two last the month.
"""
@@ -485,7 +485,7 @@ def build_dict(self):
results.write("rest_dict[%s] = _temp()\n" % repr(name))
results.write("\n")
print 'OK.\n'
- print 'Writing the dictionary containing the suppliers datas.\t\t',
+ print 'Writing the dictionary containing the suppliers data.\t\t',
results.write('suppliers = {}\n')
for name in sorted(suppliersdict) :
results.write("def _temp():\n")
View
2 Bio/SCOP/Raf.py
@@ -16,7 +16,7 @@
final arbiter in case of discrepancies.
Residues are referenced by residue ID. This consists of a the PDB residue
-sequence number (upto 4 digits) and an optional PDB insertion code (an
+sequence number (up to 4 digits) and an optional PDB insertion code (an
ascii alphabetic character, a-z, A-Z). e.g. "1", "10A", "1010b", "-1"
See "ASTRAL RAF Sequence Maps":http://astral.stanford.edu/raf.html
View
2 Bio/SeqIO/PirIO.py
@@ -65,7 +65,7 @@
YNPVIYILMN KQFRNCMITT LCCGKNPLGD DE-SGASTSKT EVSSVSTSPV SPA*
-As with the FASTA format, each record starts with a line begining with ">"
+As with the FASTA format, each record starts with a line beginning with ">"
character. There is then a two letter sequence type (P1, F1, DL, DC, RL,
RC, or XX), a semi colon, and the identification code. The second like is
free text description. The remaining lines contain the sequence itself,
View
2 Bio/SeqIO/SffIO.py
@@ -475,7 +475,7 @@ def ReadRocheXmlManifest(handle):
"""Reads any Roche style XML manifest data in the SFF "index".
The SFF file format allows for multiple different index blocks, and Roche
- took advantage of this to define their own index block wich also embeds
+ took advantage of this to define their own index block which also embeds
an XML manifest string. This is not a publically documented extension to
the SFF file format, this was reverse engineered.
View
2 Bio/SeqIO/__init__.py
@@ -747,7 +747,7 @@ def index(filename, format, alphabet=None, key_function=None):
As with the to_dict() function, by default the id string of each record
is used as the key. You can specify a callback function to transform
- this (the record identifier string) into your prefered key. For example:
+ this (the record identifier string) into your preferred key. For example:
>>> from Bio import SeqIO
>>> def make_tuple(identifier):
View
2 Bio/SeqIO/_index.py
@@ -68,7 +68,7 @@ def _parse(handle):
def get(self, offset):
"""Returns SeqRecord."""
- #Should be overriden for binary file formats etc:
+ #Should be overridden for binary file formats etc:
return self._parse(StringIO(_bytes_to_string(self.get_raw(offset))))
View
2 Bio/Sequencing/Phd.py
@@ -9,7 +9,7 @@
"""
Parser for PHD files output by PHRED and used by PHRAP and CONSED.
-This module can be used used directly which will return Record objects
+This module can be used directly which will return Record objects
which should contain all the original data in the file.
Alternatively, using Bio.SeqIO with the "phd" format will call this module
View
2 Bio/SubsMat/FreqTable.py
@@ -8,7 +8,7 @@
# Methods to read a letter frequency or a letter count file:
# Example files for a DNA alphabet:
#
-# A count file (whitespace seperated):
+# A count file (whitespace separated):
#
# A 50
# C 37
View
2 Bio/SubsMat/__init__.py
@@ -24,7 +24,7 @@
Usage:
-----
-The following section is layed out in the order by which most people wish
+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 investigated. Most people just want a log-odds matrix,
that's all.
View
2 Bio/cpairwise2module.c
@@ -323,7 +323,7 @@ static PyObject *cpairwise2__make_score_matrix_fast(
first_B_gap = calc_affine_penalty(1, open_B, extend_B,
penalize_extend_when_opening);
- /* Allocate matrices for storing the results and initalize them. */
+ /* Allocate matrices for storing the results and initialize them. */
lenA = PySequence_Length(py_sequenceA);
lenB = PySequence_Length(py_sequenceB);
score_matrix = malloc(lenA*lenB*sizeof(*score_matrix));
View
12 Doc/Tutorial.tex
@@ -4443,7 +4443,7 @@ \subsection{ClustalW}
``r'' at the start for a raw string that isn't translated in this way.
This is generally good practice when specifying a Windows style file name.
-The last line of the example requires Biopython 1.55 or later to run the
+The last line of the example requires Biopython 1.55 or later to run
the command line tool via our wrapper object. Internally this uses the
\verb|subprocess| module which is now the recommended way to run another
program in Python. This replaces older options like the \verb|os.system()|
@@ -5970,7 +5970,7 @@ \subsection{QueryResult}
\verb|QueryResult| objects, but you'll end up with regular Python lists and lose
the ability to do more interesting manipulations.
-That's why, \verb|QueryResult| objects provide its own flavor of of
+That's why, \verb|QueryResult| objects provide its own flavor of
\verb|filter| and \verb|map| methods. Analogous to \verb|filter|, there are
\verb|hit_filter| and \verb|hsp_filter| methods. As their name implies, these
methods filter its \verb|QueryResult| object either on its \verb|Hit| objects
@@ -8966,7 +8966,7 @@ \subsection{Disordered atoms\label{disordered atoms}}
that represent the same physical atom are stored in a DisorderedAtom object.
Each Atom object in a DisorderedAtom object can be uniquely indexed using its
altloc specifier. The DisorderedAtom object forwards all uncaught method calls
-to the selected Atom object, by default the one that represents the atom with
+to the selected Atom object, by default the one that represents the atom
with the highest occupancy. The user can of course change the selected Atom
object, making use of its altloc specifier. In this way atom disorder is represented
correctly without much additional complexity. In other words, if you are not
@@ -10890,7 +10890,7 @@ \subsection{Reading and writing}
motifs, but there's a couple of formats which are more used than
others. The most important distinction is whether the motif
representation is based on instances or on some version of PWM matrix.
-On of the most popular motif databases \href{http://jaspar.genereg.net}{JASPAR}
+One of the most popular motif databases \href{http://jaspar.genereg.net}{JASPAR}
stores motifs in both formats, so
let's look at how we can import JASPAR motifs from instances:
%cont-doctest
@@ -15232,7 +15232,7 @@ \subsection{Information Content}
\begin{itemize}
\item $IC_{j}$ -- The information content for the $j$-th column in an alignment.
\item $N_{a}$ -- The number of letters in the alphabet.
- \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)
+ \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)
\item $Q_{i}$ -- The expected frequency of a letter $i$. This is an
optional argument, usage of which is left at the user's
discretion. By default, it is automatically assigned to $0.05 = 1/20$ for a
@@ -15989,7 +15989,7 @@ \subsection{SubsMat}
\item Usage
- 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
+ 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
investigated. Most people just want a log-odds matrix, that's all.
\begin{enumerate}
View
6 Doc/biopdb_faq.lyx
@@ -1355,7 +1355,7 @@ Disordered\SpecialChar \-
Atom
\family default
object forwards all uncaught method calls to the selected Atom object,
- by default the one that represents the atom with with the highest occupancy.
+ by default the one that represents the atom with the highest occupancy.
The user can of course change the selected
\family typewriter
Atom
@@ -1922,7 +1922,7 @@ Residue
.
Note that DSSP (the program, and thus by consequence the class) cannot
- handle mutiple models!
+ handle multiple models!
\layout Standard
@@ -2249,7 +2249,7 @@ Residue depth is the average distance of a residue's atoms from the solvent
ResidueDepth
\family default
class.
- This class behaves as a dictionary wich maps
+ This class behaves as a dictionary which maps
\family typewriter
Residue
\family default
View
6 Doc/biopdb_faq.tex
@@ -730,7 +730,7 @@ \subsubsection*{How is disorder handled?}
Each \texttt{Atom} object in a \texttt{Disordered\-Atom} object can
be uniquely indexed using its altloc specifier. The \texttt{Disordered\-Atom}
object forwards all uncaught method calls to the selected Atom object,
-by default the one that represents the atom with with the highest
+by default the one that represents the atom with the highest
occupancy. The user can of course change the selected \texttt{Atom}
object, making use of its altloc specifier. In this way atom disorder
is represented correctly without much additional complexity. In other
@@ -988,7 +988,7 @@ \subsubsection*{How do I determine secondary structure?}
Then use the \texttt{DSSP} class, which maps \texttt{Residue} objects
to their secondary structure (and accessible surface area). The DSSP
codes are listed in Table \ref{cap:DSSP-codes}. Note that DSSP (the
-program, and thus by consequence the class) cannot handle mutiple
+program, and thus by consequence the class) cannot handle multiple
models!
%
@@ -1045,7 +1045,7 @@ \subsubsection*{How do I calculate residue depth?}
of solvent accessibility. For this functionality, you need to install
Michel Sanner's MSMS program (\url{http://www.scripps.edu/pub/olson-web/people/sanner/html/msms_home.html}).
Then use the \texttt{ResidueDepth} class. This class behaves as a
-dictionary wich maps \texttt{Residue} objects to corresponding (residue
+dictionary which maps \texttt{Residue} objects to corresponding (residue
depth, C$\alpha$ depth) tuples. The C$\alpha$ depth is the distance
of a residue's C$\alpha$ atom to the solvent accessible surface.
View
2 NEWS
@@ -452,7 +452,7 @@ needed for our NCBI Entrez Utilities XML parser.
The parse, read and write functions in Bio.SeqIO and Bio.AlignIO will now
accept filenames as well as handles. This follows a general shift from
-from other Python libraries, and does make usage a little simpler. Also
+other Python libraries, and does make usage a little simpler. Also
the write functions will now accept a single SeqRecord or alignment.
Bio.SeqIO now supports writing EMBL files (DNA and RNA sequences only).
View
2 Tests/common_BioSQL.py
@@ -694,7 +694,7 @@ def test_record_loading(self):
self.assertEqual(str(test_record.seq[:10]), 'ATTTGGCCTA')
def test_seq_feature(self):
- """Indepth check that SeqFeatures are transmitted through the db.
+ """In depth check that SeqFeatures are transmitted through the db.
"""
test_record = self.db.lookup(accession = "AJ237582")
features = test_record.features
View
2 Tests/test_NNGeneral.py
@@ -80,7 +80,7 @@ def test_partioning_examples(self):
manager = ExampleManager(0, 0)
manager.add_examples(self.examples)
assert len(manager.test_examples) == self.num_examples, \
- "Did not partion correctly to test_examples."
+ "Did not partition correctly to test_examples."
manager = ExampleManager(1.0, 0)
manager.add_examples(self.examples)
View
2 Tests/test_SeqIO_FastaIO.py
@@ -15,7 +15,7 @@
def title_to_ids(title):
"""Function to convert a title into the id, name, and description.
- This is just a quick-n-dirty implementation, and is definately not meant
+ This is just a quick-n-dirty implementation, and is definetely not meant
to handle every FASTA title line case.
"""
# first split the id information from the description
View
2 Tests/test_SeqIO_QualityIO.py
@@ -56,7 +56,7 @@ def write_read(filename, in_format, out_format):
def compare_record(old, new, truncate=None):
- """Quality aware SeqRecord comparision.
+ """Quality aware SeqRecord comparison.
This will check the mapping between Solexa and PHRED scores.
It knows to ignore UnknownSeq objects for string matching (i.e. QUAL files).
View
4 Tests/test_SeqIO_convert.py
@@ -39,7 +39,7 @@ def check_convert(in_filename, in_format, out_format, alphabet=None):
#Now load it back and check it agrees,
records2 = list(SeqIO.parse(handle, out_format, alphabet))
compare_records(records, records2, qual_truncate)
- #Finally, use the convert fuction, and check that agrees:
+ #Finally, use the convert function, and check that agrees:
handle2 = StringIO()
if qual_truncate:
warnings.simplefilter('ignore', UserWarning)
@@ -84,7 +84,7 @@ def check_convert_fails(in_filename, in_format, out_format, alphabet=None):
#TODO - move this to a shared test module...
def compare_record(old, new, truncate=None):
- """Quality aware SeqRecord comparision.
+ """Quality aware SeqRecord comparison.
This will check the mapping between Solexa and PHRED scores.
It knows to ignore UnknownSeq objects for string matching (i.e. QUAL files).

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