Mercurial > repos > davidmurphy > codonlogo
diff weblogolib/__init__.py @ 0:c55bdc2fb9fa
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| author | davidmurphy |
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| date | Thu, 27 Oct 2011 12:09:09 -0400 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/weblogolib/__init__.py Thu Oct 27 12:09:09 2011 -0400 @@ -0,0 +1,2078 @@ +#!/usr/bin/env python + +# -------------------------------- WebLogo -------------------------------- + +# Copyright (c) 2003-2004 The Regents of the University of California. +# Copyright (c) 2005 Gavin E. Crooks +# Copyright (c) 2006, The Regents of the University of California, through print +# Lawrence Berkeley National Laboratory (subject to receipt of any required +# approvals from the U.S. Dept. of Energy). All rights reserved. + +# This software is distributed under the new BSD Open Source License. +# <http://www.opensource.org/licenses/bsd-license.html> +# +# Redistribution and use in source and binary forms, with or without +# modification, are permitted provided that the following conditions are met: +# +# (1) Redistributions of source code must retain the above copyright notice, +# this list of conditions and the following disclaimer. +# +# (2) Redistributions in binary form must reproduce the above copyright +# notice, this list of conditions and the following disclaimer in the +# documentation and or other materials provided with the distribution. +# +# (3) Neither the name of the University of California, Lawrence Berkeley +# National Laboratory, U.S. Dept. of Energy nor the names of its contributors +# may be used to endorse or promote products derived from this software +# without specific prior written permission. +# +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE +# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +# POSSIBILITY OF SUCH DAMAGE. + +# Replicates README.txt + +""" +WebLogo (http://code.google.com/p/weblogo/) is a tool for creating sequence +logos from biological sequence alignments. It can be run on the command line, +as a standalone webserver, as a CGI webapp, or as a python library. + +The main WebLogo webserver is located at http://bespoke.lbl.gov/weblogo/ + + +Codonlogo is based on Weblogo. + +Please consult the manual for installation instructions and more information: +(Also located in the weblogolib/htdocs subdirectory.) + +For help on the command line interface run + ./codonlogo --help + +To build a simple logo run + ./codonlogo < cap.fa > logo0.eps + +To run as a standalone webserver at localhost:8080 + ./codonlogo --server + +To create a logo in python code: + >>> from weblogolib import * + >>> fin = open('cap.fa') + >>> seqs = read_seq_data(fin) + >>> data = LogoData.from_seqs(seqs) + >>> options = LogoOptions() + >>> options.title = "A Logo Title" + >>> format = LogoFormat(data, options) + >>> fout = open('cap.eps', 'w') + >>> eps_formatter( data, format, fout) + + +-- Distribution and Modification -- +This package is distributed under the new BSD Open Source License. +Please see the LICENSE.txt file for details on copyright and licensing. +The WebLogo source code can be downloaded from http://code.google.com/p/weblogo/ +WebLogo requires Python 2.3, 2.4 or 2.5, the corebio python toolkit for computational +biology (http://code.google.com/p/corebio), and the python array package +'numpy' (http://www.scipy.org/Download) + +# -------------------------------- CodonLogo -------------------------------- + + +""" + +from math import * +import random +from itertools import izip, count +import sys +import copy +import os +from itertools import product +from datetime import datetime +from StringIO import StringIO + + + +from corebio.data import rna_letters, dna_letters, amino_acid_letters +import random + +# python2.3 compatability +from corebio._future import Template +from corebio._future.subprocess import * +from corebio._future import resource_string, resource_filename + + +from math import log, sqrt + +# Avoid 'from numpy import *' since numpy has lots of names defined +from numpy import array, asarray, float64, ones, zeros, int32,all,any, shape +import numpy as na + +from corebio.utils.deoptparse import DeOptionParser +from optparse import OptionGroup + +from color import * +from colorscheme import * +from corebio.seq import Alphabet, Seq, SeqList +from corebio import seq_io +from corebio.utils import isfloat, find_command, ArgumentError +from corebio.moremath import * +from corebio.data import amino_acid_composition +from corebio.seq import unambiguous_rna_alphabet, unambiguous_dna_alphabet, unambiguous_protein_alphabet + +codon_alphabetU=['AAA', 'AAC', 'AAG', 'AAU', 'ACA', 'ACC', 'ACG', 'ACU', 'AGA', 'AGC', 'AGG', 'AGU', 'AUA', 'AUC', 'AUG', 'AUU', 'CAA', 'CAC', 'CAG', 'CAU', 'CCA', 'CCC', 'CCG', 'CCU', 'CGA', 'CGC', 'CGG', 'CGU', 'CUA', 'CUC', 'CUG', 'CUU', 'GAA', 'GAC', 'GAG', 'GAU', 'GCA', 'GCC', 'GCG', 'GCU', 'GGA', 'GGC', 'GGG', 'GGU', 'GUA', 'GUC', 'GUG', 'GUU', 'UAA', 'UAC', 'UAG', 'UAU', 'UCA', 'UCC', 'UCG', 'UCU', 'UGA', 'UGC', 'UGG', 'UGU', 'UUA', 'UUC', 'UUG', 'UUU'] +codon_alphabetT=['AAA', 'AAC', 'AAG', 'AAT', 'ACA', 'ACC', 'ACG', 'ACT', 'AGA', 'AGC', 'AGG', 'AGT', 'ATA', 'ATC', 'ATG', 'ATT', 'CAA', 'CAC', 'CAG', 'CAT', 'CCA', 'CCC', 'CCG', 'CCT', 'CGA', 'CGC', 'CGG', 'CGT', 'CTA', 'CTC', 'CTG', 'CTT', 'GAA', 'GAC', 'GAG', 'GAT', 'GCA', 'GCC', 'GCG', 'GCT', 'GGA', 'GGC', 'GGG', 'GGT', 'GTA', 'GTC', 'GTG', 'GTT', 'TAA', 'TAC', 'TAG', 'TAT', 'TCA', 'TCC', 'TCG', 'TCT', 'TGA', 'TGC', 'TGG', 'TGT', 'TTA', 'TTC', 'TTG', 'TTT'] + +altype="codonsT" +offset=0 +col=[] + + + +__all__ = ['LogoSize', + 'LogoOptions', + 'description', + '__version__', + 'LogoFormat', + 'LogoData', + 'Dirichlet', + 'GhostscriptAPI', + 'std_color_schemes', + 'default_color_schemes', + 'classic', + 'std_units', + 'std_sizes', + 'std_alphabets', + 'std_percentCG', + 'pdf_formatter', + 'jpeg_formatter', + 'png_formatter', + 'png_print_formatter', + 'txt_formatter', + 'eps_formatter', + 'formatters', + 'default_formatter', + 'base_distribution', + 'equiprobable_distribution', + 'read_seq_data', + 'which_alphabet', + 'color', + 'colorscheme', + ] + +description = "Create sequence logos from biological sequence alignments." + +__version__ = "1.0" + +# These keywords are subsituted by subversion. +# The date and revision will only tell the truth after a branch or tag, +# since different files in trunk will have been changed at different times +release_date ="$Date: 2011-09-17 16:30:00 -0700 (Tue, 14 Oct 2008) $".split()[1] +release_build = "$Revision: 53 $".split()[1] +release_description = "CodonLogo %s (%s)" % (__version__, release_date) + + + +def cgi(htdocs_directory) : + import weblogolib._cgi + weblogolib._cgi.main(htdocs_directory) + +class GhostscriptAPI(object) : + """Interface to the command line program Ghostscript ('gs')""" + + formats = ('png', 'pdf', 'jpeg') + + def __init__(self, path=None) : + try: + command = find_command('gs', path=path) + except EnvironmentError: + try: + command = find_command('gswin32c.exe', path=path) + except EnvironmentError: + raise EnvironmentError("Could not find Ghostscript on path." + " There should be either a gs executable or a gswin32c.exe on your system's path") + + self.command = command + + def version(self) : + args = [self.command, '--version'] + try : + p = Popen(args, stdout=PIPE) + (out,err) = p.communicate() + except OSError : + raise RuntimeError("Cannot communicate with ghostscript.") + return out.strip() + + def convert(self, format, fin, fout, width, height, resolution=300) : + device_map = { 'png':'png16m', 'pdf':'pdfwrite', 'jpeg':'jpeg'} + + try : + device = device_map[format] + except KeyError: + raise ValueError("Unsupported format.") + + args = [self.command, + "-sDEVICE=%s" % device, + "-dPDFSETTINGS=/printer", + #"-q", # Quite: Do not dump messages to stdout. + "-sstdout=%stderr", # Redirect messages and errors to stderr + "-sOutputFile=-", # Stdout + "-dDEVICEWIDTHPOINTS=%s" % str(width), + "-dDEVICEHEIGHTPOINTS=%s" % str(height), + "-dSAFER", # For added security + "-dNOPAUSE",] + + if device != 'pdf' : + args.append("-r%s" % str(resolution) ) + if resolution < 300 : # Antialias if resolution is Less than 300 DPI + args.append("-dGraphicsAlphaBits=4") + args.append("-dTextAlphaBits=4") + args.append("-dAlignToPixels=0") + + args.append("-") # Read from stdin. Must be last argument. + + error_msg = "Unrecoverable error : Ghostscript conversion failed " \ + "(Invalid postscript?). %s" % " ".join(args) + + source = fin.read() + + try : + p = Popen(args, stdin=PIPE, stdout = PIPE, stderr= PIPE) + (out,err) = p.communicate(source) + except OSError : + raise RuntimeError(error_msg) + + if p.returncode != 0 : + error_msg += '\nReturn code: %i\n' % p.returncode + if err is not None : error_msg += err + raise RuntimeError(error_msg) + + print >>fout, out +# end class Ghostscript + + +aa_composition = [ amino_acid_composition[_k] for _k in + unambiguous_protein_alphabet] + + + +# ------ DATA ------ + +classic = ColorScheme([ + ColorGroup("G", "orange" ), + ColorGroup("TU", "red"), + ColorGroup("C", "blue"), + ColorGroup("A", "green") + ] ) + +std_color_schemes = {"auto": None, # Depends on sequence type + "monochrome": monochrome, + "base pairing": base_pairing, + "classic": classic, + "hydrophobicity" : hydrophobicity, + "chemistry" : chemistry, + "charge" : charge, + }# + +default_color_schemes = { + unambiguous_protein_alphabet: hydrophobicity, + unambiguous_rna_alphabet: base_pairing, + unambiguous_dna_alphabet: base_pairing + #codon_alphabet:codonsU + } + + +std_units = { + "bits" : 1./log(2), + "nats" : 1., + "digits" : 1./log(10), + "kT" : 1., + "kJ/mol" : 8.314472 *298.15 /1000., + "kcal/mol": 1.987 *298.15 /1000., + "probability" : None, +} + +class LogoSize(object) : + def __init__(self, stack_width, stack_height) : + self.stack_width = stack_width + self.stack_height = stack_height + + def __repr__(self): + return stdrepr(self) + +# The base stack width is set equal to 9pt Courier. +# (Courier has a width equal to 3/5 of the point size.) +# Check that can get 80 characters in journal page @small +# 40 chacaters in a journal column +std_sizes = { + "small" : LogoSize( stack_width = 10, stack_height = 10*1*5), + "medium" : LogoSize( stack_width = 10*2, stack_height = 10*2*5), + "large" : LogoSize( stack_width = 10*3, stack_height = 10*3*5), +} + + +std_alphabets = { + 'protein': unambiguous_protein_alphabet, + 'rna': unambiguous_rna_alphabet, + 'dna': unambiguous_dna_alphabet, + 'codonsU':codon_alphabetU, + 'codonsT':codon_alphabetT +} + +std_percentCG = { + 'H. sapiens' : 40., + 'E. coli' : 50.5, + 'S. cerevisiae' : 38., + 'C. elegans' : 36., + 'D. melanogaster': 43., + 'M. musculus' : 42., + 'T. thermophilus' : 69.4, +} + +# Thermus thermophilus: Henne A, Bruggemann H, Raasch C, Wiezer A, Hartsch T, +# Liesegang H, Johann A, Lienard T, Gohl O, Martinez-Arias R, Jacobi C, +# Starkuviene V, Schlenczeck S, Dencker S, Huber R, Klenk HP, Kramer W, +# Merkl R, Gottschalk G, Fritz HJ: The genome sequence of the extreme +# thermophile Thermus thermophilus. +# Nat Biotechnol 2004, 22:547-53 + +def stdrepr(obj) : + attr = vars(obj).items() + + + attr.sort() + args = [] + for a in attr : + if a[0][0]=='_' : continue + args.append( '%s=%s' % ( a[0], repr(a[1])) ) + args = ',\n'.join(args).replace('\n', '\n ') + return '%s(\n %s\n)' % (obj.__class__.__name__, args) + + +class LogoOptions(object) : + """ A container for all logo formating options. Not all of these + are directly accessible through the CLI or web interfaces. + + To display LogoOption defaults: + >>> from weblogolib import * + >>> LogoOptions() + + + Attributes: + o alphabet + o creator_text -- Embedded as comment in figures. + o logo_title + o logo_label + o stacks_per_line + o unit_name + o show_yaxis + o yaxis_label -- Default depends on other settings. + o yaxis_tic_interval + o yaxis_minor_tic_ratio + o yaxis_scale + o show_xaxis + o xaxis_label + o xaxis_tic_interval + o rotate_numbers + o number_interval + o show_ends + o show_fineprint + o fineprint + o show_boxes + o shrink_fraction + o show_errorbars + o errorbar_fraction + o errorbar_width_fraction + o errorbar_gray + o resolution -- Dots per inch + o default_color + o color_scheme + o debug + o logo_margin + o stroke_width + o tic_length + o size + o stack_margin + o pad_right + o small_fontsize + o fontsize + o title_fontsize + o number_fontsize + o text_font + o logo_font + o title_font + o first_index + o logo_start + o logo_end + o scale_width + """ + + def __init__(self, **kwargs) : + """ Create a new LogoOptions instance. + + >>> L = LogoOptions(logo_title = "Some Title String") + >>> L.show_yaxis = False + >>> repr(L) + """ + + self.creator_text = release_description, + self.alphabet = None + + self.logo_title = "" + self.logo_label = "" + self.stacks_per_line = 20 + + self.unit_name = "bits" + + self.show_yaxis = True + # yaxis_lable default depends on other settings. See LogoFormat + self.yaxis_label = None + self.yaxis_tic_interval = 1. + self.yaxis_minor_tic_ratio = 5 + self.yaxis_scale = None + + self.show_xaxis = True + self.xaxis_label = "" + self.xaxis_tic_interval =1 + self.rotate_numbers = False + self.number_interval = 5 + self.show_ends = False + + self.show_fineprint = True + self.fineprint = "CodonLogo "+__version__ + + self.show_boxes = False + self.shrink_fraction = 0.5 + + self.show_errorbars = True + self.altype = True + + self.errorbar_fraction = 0.90 + self.errorbar_width_fraction = 0.25 + self.errorbar_gray = 0.75 + + self.resolution = 96. # Dots per inch + + self.default_color = Color.by_name("black") + self.color_scheme = None + #self.show_color_key = False # NOT yet implemented + + self.debug = False + + self.logo_margin = 2 + self.stroke_width = 0.5 + self.tic_length = 5 + + self.size = std_sizes["medium"] + + self.stack_margin = 0.5 + self.pad_right = False + + self.small_fontsize = 6 + self.fontsize = 10 + self.title_fontsize = 12 + self.number_fontsize = 8 + + self.text_font = "ArialMT" + self.logo_font = "Arial-BoldMT" + self.title_font = "ArialMT" + + self.first_index = 1 + self.logo_start = None + self.logo_end=None + + # Scale width of characters proportional to gaps + self.scale_width = True + + from corebio.utils import update + update(self, **kwargs) + + def __repr__(self) : + attr = vars(self).items() + attr.sort() + args = [] + for a in attr : + if a[0][0]=='_' : continue + args.append( '%s=%s' % ( a[0], repr(a[1])) ) + args = ',\n'.join(args).replace('\n', '\n ') + return '%s(\n %s\n)' % (self.__class__.__name__, args) +# End class LogoOptions + + + + +class LogoFormat(LogoOptions) : + """ Specifies the format of the logo. Requires a LogoData and LogoOptions + objects. + + >>> data = LogoData.from_seqs(seqs ) + >>> options = LogoOptions() + >>> options.title = "A Logo Title" + >>> format = LogoFormat(data, options) + """ + # TODO: Raise ArgumentErrors instead of ValueError and document + def __init__(self, data, options= None) : + + LogoOptions.__init__(self) + #global offset + if options is not None : + self.__dict__.update(options.__dict__) + + #offset=options.frame + + self.alphabet = data.alphabet + self.seqlen = data.length + self.altype = True + self.show_title = False + self.show_xaxis_label = False + self.yaxis_minor_tic_interval = None + self.lines_per_logo = None + self.char_width = None + self.line_margin_left = None + self.line_margin_right = None + self.line_margin_bottom = None + self.line_margin_top = None + self.title_height = None + self.xaxis_label_height = None + self.line_height = None + self.line_width = None + self.logo_height = None + self.logo_width = None + self.creation_date = None + self.end_type = None + + if self.stacks_per_line< 1 : + raise ArgumentError("Stacks per line should be greater than zero.", + "stacks_per_line" ) + + if self.size.stack_height<=0.0 : + raise ArgumentError( + "Stack height must be greater than zero.", "stack_height") + if (self.small_fontsize <= 0 or self.fontsize <=0 or + self.title_fontsize<=0 ): + raise ValueError("Font sizes must be positive.") + + if self.errorbar_fraction<0.0 or self.errorbar_fraction>1.0 : + raise ValueError( + "The visible fraction of the error bar must be between zero and one.") + + if self.yaxis_tic_interval<=0.0 : + raise ArgumentError( "The yaxis tic interval cannot be negative.", + 'yaxis_tic_interval') + + if self.size.stack_width <= 0.0 : + raise ValueError( + "The width of a stack should be a positive number.") + + if self.yaxis_minor_tic_interval and \ + self.yaxis_minor_tic_interval<=0.0 : + raise ValueError("Distances cannot be negative.") + + if self.xaxis_tic_interval<=0 : + raise ValueError("Tic interval must be greater than zero.") + + if self.number_interval<=0 : + raise ValueError("Invalid interval between numbers.") + + if self.shrink_fraction<0.0 or self.shrink_fraction>1.0 : + raise ValueError("Invalid shrink fraction.") + + if self.stack_margin<=0.0 : + raise ValueError("Invalid stack margin." ) + + if self.logo_margin<=0.0 : + raise ValueError("Invalid logo margin." ) + + if self.stroke_width<=0.0 : + raise ValueError("Invalid stroke width.") + + if self.tic_length<=0.0 : + raise ValueError("Invalid tic length.") + + # FIXME: More validation + + # Inclusive upper and lower bounds + # FIXME: Validate here. Move from eps_formatter + if self.logo_start is None: self.logo_start = self.first_index + + if self.logo_end is None : + self.logo_end = self.seqlen + self.first_index -1 + + self.total_stacks = self.logo_end - self.logo_start +1 + + if self.logo_start - self.first_index <0 : + raise ArgumentError( + "Logo range extends before start of available sequence.", + 'logo_range') + + if self.logo_end - self.first_index >= self.seqlen : + raise ArgumentError( + "Logo range extends beyond end of available sequence.", + 'logo_range') + + if self.logo_title : self.show_title = True + if not self.fineprint : self.show_fineprint = False + if self.xaxis_label : self.show_xaxis_label = True + + if self.yaxis_label is None : + self.yaxis_label = self.unit_name + + if self.yaxis_label : + self.show_yaxis_label = True + else : + self.show_yaxis_label = False + self.show_ends = False + + if not self.yaxis_scale : + conversion_factor = std_units[self.unit_name] + if conversion_factor : + self.yaxis_scale=log(len(self.alphabet))*conversion_factor + #self.yaxis_scale=max(data.entropy)*conversion_factor + #marker# this is where I handle the max height. needs revision. + else : + self.yaxis_scale=1.0 # probability units + + if self.yaxis_scale<=0.0 : + raise ValueError(('yaxis_scale', "Invalid yaxis scale")) + if self.yaxis_tic_interval >= self.yaxis_scale: + self.yaxis_tic_interval /= 2. + + self.yaxis_minor_tic_interval \ + = float(self.yaxis_tic_interval)/self.yaxis_minor_tic_ratio + + if self.color_scheme is None : + #if self.alphabet in default_color_schemes : + #self.color_scheme = default_color_schemes[self.alphabet] + #else : + self.color_scheme = codonsT + #else: + #for color, symbols, desc in options.colors: + #try : + #self.color_scheme.append( ColorGroup(symbols, color, desc) ) + #print >>sys.stderr, color_scheme.groups[2] + #except ValueError : + #raise ValueError( + #"error: option --color: invalid value: '%s'" % color ) + + + self.lines_per_logo = 1+ ( (self.total_stacks-1) / self.stacks_per_line) + + if self.lines_per_logo==1 and not self.pad_right: + self.stacks_per_line = min(self.stacks_per_line, self.total_stacks) + + self.char_width = self.size.stack_width - 2* self.stack_margin + + + if self.show_yaxis : + self.line_margin_left = self.fontsize * 3.0 + else : + self.line_margin_left = 0 + + if self.show_ends : + self.line_margin_right = self.fontsize *1.5 + else : + self.line_margin_right = self.fontsize + + if self.show_xaxis : + if self.rotate_numbers : + self.line_margin_bottom = self.number_fontsize *2.5 + else: + self.line_margin_bottom = self.number_fontsize *1.5 + else : + self.line_margin_bottom = 4 + + self.line_margin_top = 4 + + if self.show_title : + self.title_height = self.title_fontsize + else : + self.title_height = 0 + + self.xaxis_label_height =0. + if self.show_xaxis_label : + self.xaxis_label_height += self.fontsize + if self.show_fineprint : + self.xaxis_label_height += self.small_fontsize + + self.line_height = (self.size.stack_height + self.line_margin_top + + self.line_margin_bottom ) + self.line_width = (self.size.stack_width*self.stacks_per_line + + self.line_margin_left + self.line_margin_right ) + + self.logo_height = int(2*self.logo_margin + self.title_height \ + + self.xaxis_label_height + self.line_height*self.lines_per_logo) + self.logo_width = int(2*self.logo_margin + self.line_width ) + + + self.creation_date = datetime.now().isoformat(' ') + + end_type = '-' + end_types = { + unambiguous_protein_alphabet: 'p', + unambiguous_rna_alphabet: '-', + unambiguous_dna_alphabet: 'd' + } + if self.show_ends and self.alphabet in end_types: + end_type = end_types[self.alphabet] + self.end_type = end_type + # End __init__ +# End class LogoFormat + + + +# ------ Logo Formaters ------ +# Each formatter is a function f(LogoData, LogoFormat, output file). +# that draws a represntation of the logo into the given file. +# The main graphical formatter is eps_formatter. A mapping 'formatters' +# containing all available formatters is located after the formatter +# definitions. + +def pdf_formatter(data, format, fout) : + """ Generate a logo in PDF format.""" + + feps = StringIO() + eps_formatter(data, format, feps) + feps.seek(0) + + gs = GhostscriptAPI() + gs.convert('pdf', feps, fout, format.logo_width, format.logo_height) + + +def _bitmap_formatter(data, format, fout, device) : + feps = StringIO() + eps_formatter(data, format, feps) + feps.seek(0) + + gs = GhostscriptAPI() + gs.convert(device, feps, fout, + format.logo_width, format.logo_height, format.resolution) + + +def jpeg_formatter(data, format, fout) : + """ Generate a logo in JPEG format.""" + _bitmap_formatter(data, format, fout, device="jpeg") + + +def png_formatter(data, format, fout) : + """ Generate a logo in PNG format.""" + + _bitmap_formatter(data, format, fout, device="png") + + +def png_print_formatter(data, format, fout) : + """ Generate a logo in PNG format with print quality (600 DPI) resolution.""" + format.resolution = 600 + _bitmap_formatter(data, format, fout, device="png") + + +def txt_formatter( logodata, format, fout) : + """ Create a text representation of the logo data. + """ + print >>fout, str(logodata) + + + + +def eps_formatter( logodata, format, fout) : + """ Generate a logo in Encapsulated Postscript (EPS)""" + + subsitutions = {} + from_format =[ + "creation_date", "logo_width", "logo_height", + "lines_per_logo", "line_width", "line_height", + "line_margin_right","line_margin_left", "line_margin_bottom", + "line_margin_top", "title_height", "xaxis_label_height", + "creator_text", "logo_title", "logo_margin", + "stroke_width", "tic_length", + "stacks_per_line", "stack_margin", + "yaxis_label", "yaxis_tic_interval", "yaxis_minor_tic_interval", + "xaxis_label", "xaxis_tic_interval", "number_interval", + "fineprint", "shrink_fraction", "errorbar_fraction", + "errorbar_width_fraction", + "errorbar_gray", "small_fontsize", "fontsize", + "title_fontsize", "number_fontsize", "text_font", + "logo_font", "title_font", + "logo_label", "yaxis_scale", "end_type", + "debug", "show_title", "show_xaxis", + "show_xaxis_label", "show_yaxis", "show_yaxis_label", + "show_boxes", "show_errorbars", "show_fineprint", + "rotate_numbers", "show_ends", "altype", + + ] + + for s in from_format : + subsitutions[s] = getattr(format,s) + + + from_format_size = ["stack_height", "stack_width"] + for s in from_format_size : + subsitutions[s] = getattr(format.size,s) + + subsitutions["shrink"] = str(format.show_boxes).lower() + + + # --------- COLORS -------------- + def format_color(color): + return " ".join( ("[",str(color.red) , str(color.green), + str(color.blue), "]")) + + subsitutions["default_color"] = format_color(format.default_color) + global col + colors = [] + + if altype=="codonsT" or altype=="codonsU": + for group in col: + cf = format_color(group.color) + colors.append( " ("+group.symbols+") " + cf ) + for group in format.color_scheme.groups : + cf = format_color(group.color) + + colors.append( " ("+group.symbols+") " + cf ) + #print >>sys.stderr,opts.colors + #print >>sys.stderr,logodata.options + #print >>sys.stderr, group.symbols + #print >>sys.stderr, cf + + + + else: + for group in format.color_scheme.groups : + cf = format_color(group.color) + for s in group.symbols : + colors.append( " ("+s+") " + cf ) + + subsitutions["color_dict"] = "\n".join(colors) + data = [] + + # Unit conversion. 'None' for probability units + conv_factor = std_units[format.unit_name] + + data.append("StartLine") + + + seq_from = format.logo_start- format.first_index + seq_to = format.logo_end - format.first_index +1 + + # seq_index : zero based index into sequence data + # logo_index : User visible coordinate, first_index based + # stack_index : zero based index of visible stacks + for seq_index in range(seq_from, seq_to) : + logo_index = seq_index + format.first_index + stack_index = seq_index - seq_from + + if stack_index!=0 and (stack_index % format.stacks_per_line) ==0 : + data.append("") + data.append("EndLine") + data.append("StartLine") + data.append("") + + if logo_index % format.number_interval == 0 : + data.append("(%d) StartStack" % logo_index) + else : + data.append("() StartStack" ) + + if conv_factor: + stack_height = logodata.entropy[seq_index] * std_units[format.unit_name] + else : + stack_height = 1.0 # Probability + + # if logodata.entropy_interval is not None and conv_factor: + # Draw Error bars + # low, high = logodata.entropy_interval[seq_index] + # center = logodata.entropy[seq_index] + + + # down = (center - low) * conv_factor + # up = (high - center) * conv_factor + # data.append(" %f %f %f DrawErrorbarFirst" % (down, up, stack_height) ) + + s = zip(logodata.counts[seq_index], logodata.alphabet) + def mycmp( c1, c2 ) : + # Sort by frequency. If equal frequency then reverse alphabetic + if c1[0] == c2[0] : return cmp(c2[1], c1[1]) + return cmp(c1[0], c2[0]) + + s.sort(mycmp) + + C = float(sum(logodata.counts[seq_index])) + if C > 0.0 : + fraction_width = 1.0 + if format.scale_width : + fraction_width = logodata.weight[seq_index] + for c in s: + data.append(" %f %f (%s) ShowSymbol" % (fraction_width, c[0]*stack_height/C, c[1]) ) + + # Draw error bar on top of logo. Replaced by DrawErrorbarFirst above. + if logodata.entropy_interval is not None and conv_factor: + low, high = logodata.entropy_interval[seq_index] + center = logodata.entropy[seq_index] + + down = (center - low) * conv_factor + up = (high - center) * conv_factor + data.append(" %f %f DrawErrorbar" % (down, up) ) + + data.append("EndStack") + data.append("") + + data.append("EndLine") + subsitutions["logo_data"] = "\n".join(data) + + + # Create and output logo + template = resource_string( __name__, 'template.eps', __file__) + logo = Template(template).substitute(subsitutions) + print >>fout, logo + + +# map between output format names and logo +formatters = { + 'eps': eps_formatter, + 'pdf': pdf_formatter, + 'png': png_formatter, + 'png_print' : png_print_formatter, + 'jpeg' : jpeg_formatter, + 'txt' : txt_formatter, + } + +default_formatter = eps_formatter + + + + + +def parse_prior(composition, alphabet, weight=None) : + """ Parse a description of the expected monomer distribution of a sequence. + + Valid compositions: + + - None or 'none' : No composition sepecified + - 'auto' or 'automatic': Use the typical average distribution + for proteins and an equiprobable distribution for + everything else. + - 'equiprobable' : All monomers have the same probability. + - a percentage, e.g. '45%' or a fraction '0.45': + The fraction of CG bases for nucleotide alphabets + - a species name, e.g. 'E. coli', 'H. sapiens' : + Use the average CG percentage for the specie's + genome. + - An explicit distribution, e.g. {'A':10, 'C':40, 'G':40, 'T':10} + """ + + + if composition is None: return None + comp = composition.strip() + + if comp.lower() == 'none': return None + + if weight is None and alphabet is not None: weight = float(len(alphabet)) + + if comp.lower() == 'equiprobable' : + prior = weight * equiprobable_distribution(len(alphabet)) + elif comp.lower() == 'auto' or comp.lower() == 'automatic': + if alphabet == unambiguous_protein_alphabet : + prior = weight * asarray(aa_composition, float64) + else : + prior = weight * equiprobable_distribution(len(alphabet)) + elif comp in std_percentCG : + prior = weight * base_distribution(std_percentCG[comp]) + + elif comp[-1] == '%' : + prior = weight * base_distribution( float(comp[:-1])) + + elif isfloat(comp) : + prior = weight * base_distribution( float(comp)*100. ) + + elif composition[0] == '{' and composition[-1] == '}' : + explicit = composition[1: -1] + explicit = explicit.replace(',',' ').replace("'", ' ').replace('"',' ').replace(':', ' ').split() + + if len(explicit) != len(alphabet)*2 : + #print explicit + raise ValueError("Explicit prior does not match length of alphabet") + prior = - ones(len(alphabet), float64) + try : + for r in range(len(explicit)/2) : + letter = explicit[r*2] + index = alphabet.index(letter) + value = float(explicit[r*2 +1]) + prior[index] = value + except ValueError : + raise ValueError("Cannot parse explicit composition") + + if any(prior==-1.) : + raise ValueError("Explicit prior does not match alphabet") + prior/= sum(prior) + prior *= weight + + + else : + raise ValueError("Unknown or malformed composition: %s"%composition) + if len(prior) != len(alphabet) : + raise ValueError( + "The sequence alphabet and composition are incompatible.") + + return prior + + +def base_distribution(percentCG) : + A = (1. - (percentCG/100.))/2. + C = (percentCG/100.)/2. + G = (percentCG/100.)/2. + T = (1. - (percentCG/100))/2. + return asarray((A,C,G,T), float64) + +def equiprobable_distribution( length) : + return ones( (length), float64) /length + + + + +def read_seq_data(fin, input_parser=seq_io.read,alphabet=None, ignore_lower_case=False, max_file_size=0): + # TODO: Document this method and enviroment variable + max_file_size =int(os.environ.get("WEBLOGO_MAX_FILE_SIZE", max_file_size)) + + # If max_file_size is set, or if fin==stdin (which is non-seekable), we + # read the data and replace fin with a StringIO object. + + if(max_file_size>0) : + data = fin.read(max_file_size) + + more_data = fin.read(2) + if more_data != "" : + raise IOError("File exceeds maximum allowed size: %d bytes" % max_file_size) + + fin = StringIO(data) + elif fin == sys.stdin: + fin = StringIO(fin.read()) + + seqs = input_parser(fin) + + if seqs is None or len(seqs) ==0 : + raise ValueError("Please provide a multiple sequence alignment") + + if ignore_lower_case : + # Case is significant. Do not count lower case letters. + for i,s in enumerate(seqs) : + seqs[i] = s.mask() + + global altype + if(altype=="codonsT" or altype=="codonsU"): + if 'T' in seqs[0] or 't' in seqs[0]: + altype="codonsT" + if 'U' in seqs[0] or 'u' in seqs[0]: + altype="codonsU" + global offset + seq2=[""]*len(seqs) + seq2 = [] + for i in xrange(len(seqs)): + seq2.append([]) + if(offset%6>2): + for x in range(0,len(seqs)): + backs=seqs[x][::-1] + for y in range(0,len(backs)): + seq2[x].append(str(backs[y])) + + if(altype=="codonsU"): + for x in range(0,len(seq2)): + for y in range(0,len(seq2[x])): + if(cmp(seq2[x][y],'G')==0): + seq2[x][y]="C" + elif(cmp(seq2[x][y],'A')==0): + seq2[x][y]='U' + elif(cmp(seq2[x][y],'U')==0): + seq2[x][y]='A' + elif(cmp(seq2[x][y],'C')==0): + seq2[x][y]='G' + if(altype=="codonsT"): + for x in range(0,len(seq2)): + for y in range(0,len(seq2[x])): + if(cmp(seq2[x][y],'G')==0): + seq2[x][y]='C' + elif(cmp(seq2[x][y],'A')==0): + seq2[x][y]='T' + elif(cmp(seq2[x][y],'T')==0): + seq2[x][y]='A' + elif(cmp(seq2[x][y],'C')==0): + seq2[x][y]='G' + offset=offset%3 + for x in range(0,len(seqs)): + seqs[x]=Seq("".join(seq2[x])) + + + # Add alphabet to seqs. + if alphabet : + seqs.alphabet = alphabet + else : + seqs.alphabet = which_alphabet(seqs) + + return seqs + + + +#TODO: Move to seq_io? +# Would have to check that no symbol outside of full alphabet? +def which_alphabet(seqs) : + """ Returns the most appropriate unambiguous protien, rna or dna alphabet + for a Seq or SeqList. + """ + alphabets = (unambiguous_protein_alphabet, + unambiguous_rna_alphabet, + unambiguous_dna_alphabet + ) + # Heuristic + # Count occurances of each letter. Downweight longer alphabet. + #for x in seqs: + + + if( altype=="codonsU"): + return codon_alphabetU + if( altype=="codonsT"): + return codon_alphabetT + else: + score = [1.0*asarray(seqs.tally(a)).sum()/sqrt(len(a)) for a in alphabets] + #print score + best = argmax(score) # Ties go to last in list. + a = alphabets[best] + return a + + + +class LogoData(object) : + """The data needed to generate a sequence logo. + + - alphabet + - length + - counts -- An array of character counts + - entropy -- The relative entropy of each column + - entropy_interval -- entropy confidence interval + """ + + def __init__(self, length=None, alphabet = None, counts =None, + entropy =None, entropy_interval = None, weight=None) : + """Creates a new LogoData object""" + self.length = length + self.alphabet = alphabet + self.counts = counts + self.entropy = entropy + self.entropy_interval = entropy_interval + self.weight = weight + + + + #@classmethod + def from_counts(cls, alphabet, counts, prior= None): + + """Build a logodata object from counts.""" + seq_length, A = counts.shape + + if prior is not None: prior = array(prior, float64) + if prior is None : + R = log(A) + ent = zeros( seq_length, float64) + entropy_interval = None + for i in range (0, seq_length) : + C = sum(counts[i]) + #FIXME: fixup corebio.moremath.entropy()? + if C == 0 : + ent[i] = 0.0 + else : + ent[i] = R - entropy(counts[i]) + else : + ent = zeros( seq_length, float64) + entropy_interval = zeros( (seq_length,2) , float64) + + R = log(A) + + for i in range (0, seq_length) : + alpha = array(counts[i] , float64) + alpha += prior + + posterior = Dirichlet(alpha) + ent[i] = posterior.mean_relative_entropy(prior/sum(prior)) + entropy_interval[i][0], entropy_interval[i][1] = \ + posterior.interval_relative_entropy(prior/sum(prior), 0.95) + weight = array( na.sum(counts,axis=1) , float) + + weight /= max(weight) + + return cls(seq_length, alphabet, counts, ent, entropy_interval, weight) + from_counts = classmethod(from_counts) + + + #@classmethod + def from_seqs(cls, seqs, prior= None): + + + alphabet=seqs.alphabet + + #get the offset and if it's greater than 2 flip the sequences to the negative strand and reverse. + for x in range(0,len(seqs)): + seqs[x]=seqs[x].upper() + counter=0 + + + """Build a 2D array from a SeqList, a list of sequences.""" + # --- VALIDATE DATA --- + # check that there is at least one sequence of length 1 + if len(seqs)==0 or len(seqs[0]) ==0: + raise ValueError("No sequence data found.") + sys.exit(0) + # Check sequence lengths + seq_length = len(seqs[0]) + for i,s in enumerate(seqs) : + #print i,s, len(s) + if seq_length != len(s) : + raise ArgumentError( + "Sequence number %d differs in length from the previous sequences" % (i+1) ,'sequences') + sys.exit(0) + + if(altype=="codonsT" or altype=="codonsU"): + x = [[0]*64 for x in xrange(seq_length/3)] + counter=offset + + while counter+offset<seq_length: + for i in range(0,len(seqs)): + if len(str(seqs[i][(counter):(counter+3)]))==3 and len(seqs[i][(counter):(counter+3)].strip("GATUC"))==0 : + if(str(seqs[i][(counter):(counter+3)]) in alphabet): + x[counter/3][ (alphabet.index(str(seqs[i][(counter):(counter+3)]))) ]+=1 + counter=counter+3 + counts=asarray(x) + else: + counts = asarray(seqs.tally()) + + return cls.from_counts(alphabet, counts, prior) + from_seqs = classmethod(from_seqs) + + + + def __str__(self) : + out = StringIO() + print >>out, '## LogoData' + print >>out, '# First column is position number, couting from zero' + print >>out, '# Subsequent columns are raw symbol counts' + print >>out, '# Entropy is mean entropy measured in nats.' + print >>out, '# Low and High are the 95% confidence limits.' + print >>out, '# Weight is the fraction of non-gap symbols in the column.' + print >>out, '#\t' + print >>out, '#\t', + for a in self.alphabet : + print >>out, a, '\t', + print >>out, 'Entropy\tLow\tHigh\tWeight' + + for i in range(self.length) : + print >>out, i, '\t', + for c in self.counts[i] : print >>out, c, '\t', + print >>out, self.entropy[i], '\t', + if self.entropy_interval is not None: + print >>out, self.entropy_interval[i][0], '\t', + print >>out, self.entropy_interval[i][1], '\t', + else : + print >>out, '\t','\t', + if self.weight is not None : + print >>out, self.weight[i], + print >>out, '' + print >>out, '# End LogoData' + + return out.getvalue() + +# ====================== Main: Parse Command line ============================= +def main(): + """CodonLogo command line interface """ + + # ------ Parse Command line ------ + parser = _build_option_parser() + (opts, args) = parser.parse_args(sys.argv[1:]) + if args : parser.error("Unparsable arguments: %s " % args) + + if opts.serve: + httpd_serve_forever(opts.port) # Never returns? + sys.exit(0) + + + # ------ Create Logo ------ + try: + data = _build_logodata(opts) + + + format = _build_logoformat(data, opts) + + + formatter = opts.formatter + formatter(data, format, opts.fout) + + except ValueError, err : + print >>sys.stderr, 'Error:', err + sys.exit(2) + except KeyboardInterrupt, err: + sys.exit(0) +# End main() + + +def httpd_serve_forever(port=8080) : + """ Start a webserver on a local port.""" + import BaseHTTPServer + import CGIHTTPServer + + class __HTTPRequestHandler(CGIHTTPServer.CGIHTTPRequestHandler): + def is_cgi(self) : + if self.path == "/create.cgi": + self.cgi_info = '', 'create.cgi' + return True + return False + + # Add current directory to PYTHONPATH. This is + # so that we can run the standalone server + # without having to run the install script. + pythonpath = os.getenv("PYTHONPATH", '') + pythonpath += ":" + os.path.abspath(sys.path[0]).split()[0] + os.environ["PYTHONPATH"] = pythonpath + + htdocs = resource_filename(__name__, 'htdocs', __file__) + os.chdir(htdocs) + + HandlerClass = __HTTPRequestHandler + ServerClass = BaseHTTPServer.HTTPServer + httpd = ServerClass(('', port), HandlerClass) + print "Serving HTTP on localhost:%d ..." % port + + try : + httpd.serve_forever() + except KeyboardInterrupt: + sys.exit(0) +# end httpd_serve_forever() + +def read_priors(finp, alphabet ,max_file_size=0): + + max_file_size =int(os.environ.get("WEBLOGO_MAX_FILE_SIZE", max_file_size)) + if(max_file_size>0) : + data = finp.read(max_file_size) + more_data = finp.read(2) + if more_data != "" : + raise IOError("File exceeds maximum allowed size: %d bytes" % max_file_size) + finp = StringIO(data) + priordict={} + while 1: + line = finp.readline() + if not line: + break + line = line.split() + priordict[line[0]]=line[1] + return priordict + +def _build_logodata(options) : + global offset + offset=options.frame + options.alphabet = None + options.ignore_lower_case = False + #options.default_color = Color.by_name("black") + options.color_scheme=None + #options.colors=[] + options.show_ends=False + seqs = read_seq_data(options.fin, + options.input_parser.read, + alphabet=options.alphabet, + ignore_lower_case = options.ignore_lower_case) + if(options.priorfile!=None): + if(altype=="CodonsT"): + options.composition= str(read_priors(options.priorfile,codon_alphabetT)) + options.alphabet = codon_alphabetT + else: + options.composition= str(read_priors(options.priorfile,codon_alphabetU)) + options.alphabet = codon_alphabetU + + prior = parse_prior( options.composition,seqs.alphabet, options.weight) + data = LogoData.from_seqs(seqs, prior) + return data + + +def _build_logoformat( logodata, opts) : + """ Extract and process relevant option values and return a + LogoFormat object.""" + + args = {} + direct_from_opts = [ + "stacks_per_line", + "logo_title", + "yaxis_label", + "show_xaxis", + "show_yaxis", + "xaxis_label", + "show_ends", + "fineprint", + "show_errorbars", + "altype", + "show_boxes", + "yaxis_tic_interval", + "resolution", + "alphabet", + "debug", + "show_ends", + "default_color", + #"show_color_key", + "color_scheme", + "unit_name", + "logo_label", + "yaxis_scale", + "first_index", + "logo_start", + "logo_end", + "scale_width", + "frame", + ] + + for k in direct_from_opts: + args[k] = opts.__dict__[k] + logo_size = copy.copy(opts.__dict__['logo_size']) + size_from_opts = ["stack_width", "stack_height"] + for k in size_from_opts : + length = getattr(opts, k) + if length : setattr( logo_size, k, length ) + args["size"] = logo_size + + global col + + if opts.colors: + color_scheme = ColorScheme() + for color, symbols, desc in opts.colors: + try : + #c = Color.from_string(color) + color_scheme.groups.append( ColorGroup(symbols, color, desc) ) + #print >> sys.stderr, color + + col.append( ColorGroup(symbols, color, desc) ) + + except ValueError : + raise ValueError( + "error: option --color: invalid value: '%s'" % color ) + if(altype!="codonsU" and altype!="codonsT") : + args["color_scheme"] = color_scheme + + #cf = colorscheme.format_color(col[0]) + #col.append( " ("+group.symbols+") " + cf ) + + logooptions = LogoOptions() + for a, v in args.iteritems() : + setattr(logooptions,a,v) + + + + theformat = LogoFormat(logodata, logooptions ) + + return theformat + + + + + + +# ========================== OPTIONS ========================== +def _build_option_parser() : + defaults = LogoOptions() + parser = DeOptionParser(usage="%prog [options] < sequence_data.fa > sequence_logo.eps", + description = description, + version = __version__ , + add_verbose_options = False + ) + + io_grp = OptionGroup(parser, "Input/Output Options",) + data_grp = OptionGroup(parser, "Logo Data Options",) + format_grp = OptionGroup(parser, "Logo Format Options", + "These options control the format and display of the logo.") + color_grp = OptionGroup(parser, "Color Options", + "Colors can be specified using CSS2 syntax. e.g. 'red', '#FF0000', etc.") + advanced_grp = OptionGroup(parser, "Advanced Format Options", + "These options provide fine control over the display of the logo. ") + server_grp = OptionGroup(parser, "CodonLogo Server", + "Run a standalone webserver on a local port.") + + + parser.add_option_group(io_grp) + parser.add_option_group(data_grp) + parser.add_option_group(format_grp) + parser.add_option_group(color_grp) + parser.add_option_group(advanced_grp) + parser.add_option_group(server_grp) + + # ========================== IO OPTIONS ========================== + + + + io_grp.add_option( "-f", "--fin", + dest="fin", + action="store", + type="file_in", + default=sys.stdin, + help="Sequence input file (default: stdin)", + metavar="FILENAME") + + io_grp.add_option( "-R", "--prior", + dest="priorfile", + action="store", + type="file_in", + help="A file with 64 codons and their prior probabilities, one per line, each codon followed by a space and it's probability.", + metavar="FILENAME") + + io_grp.add_option("", "--fin-format", + dest="input_parser", + action="store", type ="dict", + default = seq_io, + choices = seq_io.format_names(), + help="Multiple sequence alignment format: (%s)" % + ', '.join([ f.names[0] for f in seq_io.formats]), + metavar="FORMAT") + + io_grp.add_option("-o", "--fout", dest="fout", + type="file_out", + default=sys.stdout, + help="Output file (default: stdout)", + metavar="FILENAME") + + + + io_grp.add_option( "-F", "--format", + dest="formatter", + action="store", + type="dict", + choices = formatters, + metavar= "FORMAT", + help="Format of output: eps (default), png, png_print, pdf, jpeg, txt", + default = default_formatter) + + + # ========================== Data OPTIONS ========================== + + data_grp.add_option("-m", "--frame", + dest="frame", + action="store", + type="int", + default=0, + help="Offset of the reading frame you wish to look in (default: 0)", + metavar="COUNT") + + data_grp.add_option("-T", "--type", + dest="altype", + action="store", + type="boolean", + default=True, + help="Generate a codon logo rather than a sequence logo (default: True)", + metavar="YES/NO") + + + + #data_grp.add_option( "-A", "--sequence-type", + #dest="alphabet", + #action="store", + #type="dict", + #choices = std_alphabets, + #help="The type of sequence data: 'protein', 'rna' or 'dna'.", + #metavar="TYPE") + + #data_grp.add_option( "-a", "--alphabet", + #dest="alphabet", + #action="store", + #help="The set of symbols to count, e.g. 'AGTC'. " + #"All characters not in the alphabet are ignored. " + #"If neither the alphabet nor sequence-type are specified then codonlogo will examine the input data and make an educated guess. " + #"See also --sequence-type, --ignore-lower-case" ) + + # FIXME Add test? + #data_grp.add_option( "", "--ignore-lower-case", + #dest="ignore_lower_case", + #action="store", + #type = "boolean", + #default=False, + #metavar = "YES/NO", + #help="Disregard lower case letters and only count upper case letters in sequences? (Default: No)" + #) + + data_grp.add_option( "-U", "--units", + dest="unit_name", + action="store", + choices = std_units.keys(), + type="choice", + default = defaults.unit_name, + help="A unit of entropy ('bits' (default), 'nats', 'digits'), or a unit of free energy ('kT', 'kJ/mol', 'kcal/mol'), or 'probability' for probabilities", + metavar = "NUMBER") + + + data_grp.add_option( "", "--composition", + dest="composition", + action="store", + type="string", + default = "auto", + help="The expected composition of the sequences: 'auto' (default), 'equiprobable', 'none' (Do not perform any compositional adjustment), a CG percentage, a species name (e.g. 'E. coli', 'H. sapiens'), or an explicit distribution (e.g. {'A':10, 'C':40, 'G':40, 'T':10}). The automatic option uses a typical distribution for proteins and equiprobable distribution for everything else. ", + metavar="COMP.") + + data_grp.add_option( "", "--weight", + dest="weight", + action="store", + type="float", + default = None, + help="The weight of prior data. Default: total pseudocounts equal to the number of monomer types.", + metavar="NUMBER") + + data_grp.add_option( "-i", "--first-index", + dest="first_index", + action="store", + type="int", + default = 1, + help="Index of first position in sequence data (default: 1)", + metavar="INDEX") + + data_grp.add_option( "-l", "--lower", + dest="logo_start", + action="store", + type="int", + help="Lower bound of sequence to display", + metavar="INDEX") + + data_grp.add_option( "-u", "--upper", + dest="logo_end", + action="store", + type="int", + help="Upper bound of sequence to display", + metavar="INDEX") + + # ========================== FORMAT OPTIONS ========================== + + format_grp.add_option( "-s", "--size", + dest="logo_size", + action="store", + type ="dict", + choices = std_sizes, + metavar = "LOGOSIZE", + default = defaults.size, + help="Specify a standard logo size (small, medium (default), large)" ) + + + + format_grp.add_option( "-n", "--stacks-per-line", + dest="stacks_per_line", + action="store", + type="int", + help="Maximum number of logo stacks per logo line. (default: %default)", + default = defaults.stacks_per_line, + metavar="COUNT") + + format_grp.add_option( "-t", "--title", + dest="logo_title", + action="store", + type="string", + help="Logo title text.", + default = defaults.logo_title, + metavar="TEXT") + + format_grp.add_option( "", "--label", + dest="logo_label", + action="store", + type="string", + help="A figure label, e.g. '2a'", + default = defaults.logo_label, + metavar="TEXT") + + format_grp.add_option( "-X", "--show-xaxis", + action="store", + type = "boolean", + default= defaults.show_xaxis, + metavar = "YES/NO", + help="Display sequence numbers along x-axis? (default: %default)") + + format_grp.add_option( "-x", "--xlabel", + dest="xaxis_label", + action="store", + type="string", + default = defaults.xaxis_label, + help="X-axis label", + metavar="TEXT") + + format_grp.add_option( "-S", "--yaxis", + dest="yaxis_scale", + action="store", + type="float", + help="Height of yaxis in units. (Default: Maximum value with uninformative prior.)", + metavar = "UNIT") + + format_grp.add_option( "-Y", "--show-yaxis", + action="store", + type = "boolean", + dest = "show_yaxis", + default= defaults.show_yaxis, + metavar = "YES/NO", + help="Display entropy scale along y-axis? (default: %default)") + + format_grp.add_option( "-y", "--ylabel", + dest="yaxis_label", + action="store", + type="string", + help="Y-axis label (default depends on plot type and units)", + metavar="TEXT") + + #format_grp.add_option( "-E", "--show-ends", + #action="store", + #type = "boolean", + #default= defaults.show_ends, + #metavar = "YES/NO", + #help="Label the ends of the sequence? (default: %default)") + + format_grp.add_option( "-P", "--fineprint", + dest="fineprint", + action="store", + type="string", + default= defaults.fineprint, + help="The fine print (default: Codonlogo version)", + metavar="TEXT") + + format_grp.add_option( "", "--ticmarks", + dest="yaxis_tic_interval", + action="store", + type="float", + default= defaults.yaxis_tic_interval, + help="Distance between ticmarks (default: %default)", + metavar = "NUMBER") + + + format_grp.add_option( "", "--errorbars", + dest = "show_errorbars", + action="store", + type = "boolean", + default= defaults.show_errorbars, + metavar = "YES/NO", + help="Display error bars? (default: %default)") + + + + # ========================== Color OPTIONS ========================== + # TODO: Future Feature + # color_grp.add_option( "-K", "--color-key", + # dest= "show_color_key", + # action="store", + # type = "boolean", + # default= defaults.show_color_key, + # metavar = "YES/NO", + # help="Display a color key (default: %default)") + + + #color_scheme_choices = std_color_schemes.keys() + #color_scheme_choices.sort() + #color_grp.add_option( "-c", "--color-scheme", + #dest="color_scheme", + #action="store", + #type ="dict", + #choices = std_color_schemes, + #metavar = "SCHEME", + #default = None, # Auto + #help="Specify a standard color scheme (%s)" % \ + #", ".join(color_scheme_choices) ) + + color_grp.add_option( "-C", "--color", + dest="colors", + action="append", + metavar="COLOR SYMBOLS DESCRIPTION ", + nargs = 3, + default=[], + help="Specify symbol colors, e.g. --color black AG 'Purine' --color red TC 'Pyrimidine' ") + + color_grp.add_option( "", "--default-color", + dest="default_color", + action="store", + metavar="COLOR", + default= defaults.default_color, + help="Symbol color if not otherwise specified.") + + # ========================== Advanced options ========================= + + advanced_grp.add_option( "-W", "--stack-width", + dest="stack_width", + action="store", + type="float", + default= None, + help="Width of a logo stack (default: %s)"% defaults.size.stack_width, + metavar="POINTS" ) + + advanced_grp.add_option( "-H", "--stack-height", + dest="stack_height", + action="store", + type="float", + default= None, + help="Height of a logo stack (default: %s)"%defaults.size.stack_height, + metavar="POINTS" ) + + advanced_grp.add_option( "", "--box", + dest="show_boxes", + action="store", + type = "boolean", + default=False, + metavar = "YES/NO", + help="Draw boxes around symbols? (default: no)") + + advanced_grp.add_option( "", "--resolution", + dest="resolution", + action="store", + type="float", + default=96, + help="Bitmap resolution in dots per inch (DPI). (default: 96 DPI, except png_print, 600 DPI) Low resolution bitmaps (DPI<300) are antialiased.", + metavar="DPI") + + advanced_grp.add_option( "", "--scale-width", + dest="scale_width", + action="store", + type = "boolean", + default= True, + metavar = "YES/NO", + help="Scale the visible stack width by the fraction of symbols in the column? (i.e. columns with many gaps of unknowns are narrow.) (default: yes)") + + advanced_grp.add_option( "", "--debug", + action="store", + type = "boolean", + default= defaults.debug, + metavar = "YES/NO", + help="Output additional diagnostic information. (default: %default)") + + + # ========================== Server options ========================= + server_grp.add_option( "", "--serve", + dest="serve", + action="store_true", + default= False, + help="Start a standalone CodonLogo server for creating sequence logos.") + + server_grp.add_option( "", "--port", + dest="port", + action="store", + type="int", + default= 8080, + help="Listen to this local port. (Default: %default)", + metavar="PORT") + + return parser + + # END _build_option_parser + + +############################################################## + +class Dirichlet(object) : + """The Dirichlet probability distribution. The Dirichlet is a continuous + multivariate probability distribution across non-negative unit length + vectors. In other words, the Dirichlet is a probability distribution of + probability distributions. It is conjugate to the multinomial + distribution and is widely used in Bayesian statistics. + + The Dirichlet probability distribution of order K-1 is + + p(theta_1,...,theta_K) d theta_1 ... d theta_K = + (1/Z) prod_i=1,K theta_i^{alpha_i - 1} delta(1 -sum_i=1,K theta_i) + + The normalization factor Z can be expressed in terms of gamma functions: + + Z = {prod_i=1,K Gamma(alpha_i)} / {Gamma( sum_i=1,K alpha_i)} + + The K constants, alpha_1,...,alpha_K, must be positive. The K parameters, + theta_1,...,theta_K are nonnegative and sum to 1. + + Status: + Alpha + """ + __slots__ = 'alpha', '_total', '_mean', + + + + + def __init__(self, alpha) : + """ + Args: + - alpha -- The parameters of the Dirichlet prior distribution. + A vector of non-negative real numbers. + """ + # TODO: Check that alphas are positive + #TODO : what if alpha's not one dimensional? + self.alpha = asarray(alpha, float64) + + self._total = sum(alpha) + self._mean = None + + + def sample(self) : + """Return a randomly generated probability vector. + + Random samples are generated by sampling K values from gamma + distributions with parameters a=\alpha_i, b=1, and renormalizing. + + Ref: + A.M. Law, W.D. Kelton, Simulation Modeling and Analysis (1991). + Authors: + Gavin E. Crooks <gec@compbio.berkeley.edu> (2002) + """ + alpha = self.alpha + K = len(alpha) + theta = zeros( (K,), float64) + + for k in range(K): + theta[k] = random.gammavariate(alpha[k], 1.0) + theta /= sum(theta) + + return theta + + def mean(self) : + if self._mean ==None: + self._mean = self.alpha / self._total + return self._mean + + def covariance(self) : + alpha = self.alpha + A = sum(alpha) + #A2 = A * A + K = len(alpha) + cv = zeros( (K,K), float64) + + for i in range(K) : + cv[i,i] = alpha[i] * (1. - alpha[i]/A) / (A * (A+1.) ) + + for i in range(K) : + for j in range(i+1,K) : + v = - alpha[i] * alpha[j] / (A * A * (A+1.) ) + cv[i,j] = v + cv[j,i] = v + return cv + + def mean_x(self, x) : + x = asarray(x, float64) + if shape(x) != shape(self.alpha) : + raise ValueError("Argument must be same dimension as Dirichlet") + return sum( x * self.mean()) + + def variance_x(self, x) : + x = asarray(x, float64) + if shape(x) != shape(self.alpha) : + raise ValueError("Argument must be same dimension as Dirichlet") + + cv = self.covariance() + var = na.dot(na.dot(na.transpose( x), cv), x) + return var + + + def mean_entropy(self) : + """Calculate the average entropy of probabilities sampled + from this Dirichlet distribution. + + Returns: + The average entropy. + + Ref: + Wolpert & Wolf, PRE 53:6841-6854 (1996) Theorem 7 + (Warning: this paper contains typos.) + Status: + Alpha + Authors: + GEC 2005 + + """ + # TODO: Optimize + alpha = self.alpha + A = float(sum(alpha)) + ent = 0.0 + for a in alpha: + if a>0 : ent += - 1.0 * a * digamma( 1.0+a) # FIXME: Check + ent /= A + ent += digamma(A+1.0) + return ent + + + + def variance_entropy(self): + """Calculate the variance of the Dirichlet entropy. + + Ref: + Wolpert & Wolf, PRE 53:6841-6854 (1996) Theorem 8 + (Warning: this paper contains typos.) + """ + alpha = self.alpha + A = float(sum(alpha)) + A2 = A * (A+1) + L = len(alpha) + + dg1 = zeros( (L) , float64) + dg2 = zeros( (L) , float64) + tg2 = zeros( (L) , float64) + + for i in range(L) : + dg1[i] = digamma(alpha[i] + 1.0) + dg2[i] = digamma(alpha[i] + 2.0) + tg2[i] = trigamma(alpha[i] + 2.0) + + dg_Ap2 = digamma( A+2. ) + tg_Ap2 = trigamma( A+2. ) + + mean = self.mean_entropy() + var = 0.0 + + for i in range(L) : + for j in range(L) : + if i != j : + var += ( + ( dg1[i] - dg_Ap2 ) * (dg1[j] - dg_Ap2 ) - tg_Ap2 + ) * (alpha[i] * alpha[j] ) / A2 + else : + var += ( + ( dg2[i] - dg_Ap2 ) **2 + ( tg2[i] - tg_Ap2 ) + ) * ( alpha[i] * (alpha[i]+1.) ) / A2 + + var -= mean**2 + return var + + + + def mean_relative_entropy(self, pvec) : + ln_p = na.log(pvec) + return - self.mean_x(ln_p) - self.mean_entropy() + + + def variance_relative_entropy(self, pvec) : + ln_p = na.log(pvec) + return self.variance_x(ln_p) + self.variance_entropy() + + + def interval_relative_entropy(self, pvec, frac) : + mean = self.mean_relative_entropy(pvec) + variance = self.variance_relative_entropy(pvec) + # If the variance is small, use the standard 95% + # confidence interval: mean +/- 1.96 * sd + if variance< 0.1 : + sd = sqrt(variance) + return max(0.0, mean - sd*1.96), mean + sd*1.96 + sd = sqrt(variance) + return max(0.0, mean - sd*1.96), mean + sd*1.96 + + g = gamma.from_mean_variance(mean, variance) + low_limit = g.inverse_cdf( (1.-frac)/2.) + high_limit = g.inverse_cdf( 1. - (1.-frac)/2. ) + + return low_limit, high_limit + + +# Standard python voodoo for CLI +if __name__ == "__main__": + ## Code Profiling. Uncomment these lines + #import hotshot, hotshot.stats + #prof = hotshot.Profile("stones.prof") + #prof.runcall(main) + #prof.close() + #stats = hotshot.stats.load("stones.prof") + #stats.strip_dirs() + #stats.sort_stats('cumulative', 'calls') + #stats.print_stats(40) + #sys.exit() + + main() + + + + + +