def plot_p12_p3_contour(x_bin,
y_bin,
data,
xy_data,
graph_name='p12_p3_contour.png',
prob_axes=True,
**kwargs):
"""Outputs a P12 versus P3 contour graph
and the mean equation of the plot
takes: x_bin, y_bin, data (data matrix)
label (default 'Unknown Species')
num_genes (default 0 will not print, other numbers will)
size: of graph in inches (default = 8.0)
graph_name: default 'p12_p3_contourlines.png'
"""
plot_data = [(x_bin, y_bin, data)]
plot_filled_contour(plot_data, graph_grid='/', x_label="$P_3$", \
y_label="$P_{12}$", prob_axes=prob_axes,**kwargs)
set_axis_to_probs()
if graph_name is not None:
savefig(graph_name)
def plot_cai_p3_contour(x_bin,
y_bin,
data,
xy_data,
graph_name='cai_contour.png',
prob_axes=True,
**kwargs):
"""Output a contour plot of cai vs p3 with colorbar on side
takes: x_bin, y_bin, data (data matrix)
label (default 'Unknown Species')
num_genes (default 0 will not print, other numbers will)
size: of graph in inches (default = 8.0)
graph_name: default 'cai_contour.png'
"""
plot_data = [(x_bin, y_bin, data)]
plot_filled_contour(plot_data, graph_grid='/',x_label="$P_3$", \
y_label="CAI", prob_axes=prob_axes, **kwargs)
set_axis_to_probs()
if graph_name is not None:
savefig(graph_name)
def plot_p12_p3_contourlines(x_bin,y_bin,data,xy_data, prob_axes=True,\
graph_name='p12_p3_contourlines.png', **kwargs):
"""Outputs a P12 versus P3 contourline graph
and the mean equation of the plot
takes: x_bin, y_bin, data (data matrix)
label (default 'Unknown Species')
num_genes (default 0 will not print, other numbers will)
size: of graph in inches (default = 8.0)
graph_name: default 'p12_p3_contourlines.png
"""
plot_data =[(x_bin,y_bin,data)]
plot_contour_lines(plot_data, graph_grid='/', x_label="$P_3$",\
y_label="$P_{12}$", prob_axes=prob_axes, **kwargs)
set_axis_to_probs()
if graph_name is not None:
savefig(graph_name)
def plot_cai_p3_contour(x_bin,y_bin,data,xy_data,
graph_name='cai_contour.png',
prob_axes=True, **kwargs):
"""Output a contour plot of cai vs p3 with colorbar on side
takes: x_bin, y_bin, data (data matrix)
label (default 'Unknown Species')
num_genes (default 0 will not print, other numbers will)
size: of graph in inches (default = 8.0)
graph_name: default 'cai_contour.png'
"""
plot_data =[(x_bin,y_bin,data)]
plot_filled_contour(plot_data, graph_grid='/',x_label="$P_3$", \
y_label="CAI", prob_axes=prob_axes, **kwargs)
set_axis_to_probs()
if graph_name is not None:
savefig(graph_name)
def plot_fingerprint(data, alpha=0.7, \
show_legend=True, graph_name='fingerprint.png', has_mean=True,
which_blocks='quartets', multiple=False, graph_grid='t', prob_axes=True, \
edge_colors='k', **kwargs):
"""Outputs a bubble plot of four-codon amino acid blocks
labeled with the colors from Sueoka 2002.
takes: data: array-elements in the col order x, y, r of
each of the four codon Amino Acids in the row order:
ALA, ARG4, GLY, LEU4, PRO, SER, THR, VAL
(for traditional fingerprint), or:
UU -> GG (for 16-block fingerprint).
last row is the mean (if has_mean is set True)
**kwargs passed on to init_graph_display (these include
graph_shape, graph_grid, x_label, y_label, dark, with_parens).
title: will be printed on graph (default: 'Unknown Species')
num_genes (number of genes contributing to graph: default None)
NOTE: will not print if None.)
size: of graph in inches (default = 8.0)
alpha: transparency of bubbles
(ranges from 0, transparent, to 1, opaque; default 0.7)
show_legend: bool, default True, whether to print legend
graph_name: name of file to write (default 'fingerprint.png')
has_mean: whether the data contain the mean (default: True)
which_blocks: which codon blocks to print (default is 'quartets'
for the 4-codon amino acid blocks, but can also use 'all' for all
quartets or 'split' for just the split quartets.)
multiple: if False (the default), assumes it got a single block
of data. Otherwise, assumes multiple blocks of data in a list or
array.
edge_colors: if multiple is True (ignored otherwise), uses this
sequence of edge color strings to hand out edge colors to successive
series. Will iterate over this, so can be a string of 1-letter
color codes or a list of color names.
note: that the data are always expected to be in the range (0,1)
since we're plotting frequencies. axes, gid, etc. are hard-coded
to these values.
"""
#figure out which type of fingerprint plot we're doing, and get the
#right colors
if which_blocks == 'quartets':
blocks = CodonUsage.SingleAABlocks
elif which_blocks == 'split':
blocks = CodonUsage.SplitBlocks
else:
blocks = CodonUsage.Blocks
colors = [doublets_to_colors[i] for i in blocks]
#formatting the labels in latex
x_label="$G_3/(G_3+C_3)$"
y_label="$A_3/(A_3+T_3)$"
#initializing components of the graph
font,label_font_size=init_graph_display(graph_shape='sqr', \
graph_grid=graph_grid, x_label=x_label, \
y_label=y_label, prob_axes=prob_axes, **kwargs)
if not multiple:
data = [data]
alpha = broadcast(alpha, len(data))
edge_colors = broadcast(edge_colors, len(data))
for al, d, edge_color in zip(alpha, data, edge_colors):
#skip this series if no data
if d is None or not d.any():
continue
for i, color in enumerate(colors):
j = i+1
#note: doing these as slices because scatter_classic needs the
#extra level of nesting
patches = scatter_classic(d[i:j,0], d[i:j,1],
s=(d[i:j,2]/2), c=color)
#set alpha for the patches manually
for p in patches:
p.set_alpha(al)
p.set_edgecolor(edge_color)
#plot mean as its own point -- can't do cross with scatter
if has_mean:
mean_index = len(blocks) #next index after the blocks
plot([d[mean_index,0]], [d[mean_index,1]],
'-k+',markersize=label_font_size, alpha=al)
abbrev = CodonUsage.BlockAbbreviations
a = gca()
#if show_legend is True prints a legend in the right center area
if show_legend:
legend_key = [abbrev[b] for b in blocks]
#copy legend font properties from the x axis tick labels
legend_font_props = \
a.xaxis.get_label().get_fontproperties().copy()
legend_font_scale_factor = 0.7
curr_size = legend_font_props.get_size()
legend_font_props.set_size(curr_size*legend_font_scale_factor)
l = figlegend(a.patches[:len(blocks)],
legend_key,
prop=legend_font_props,
loc='center right',borderpad=0.1,labelspacing=0.5,
handlelength=1.0,handletextpad=0.5, borderaxespad=0.0)
#fix transparency of patches
for p in l.get_patches():
p.set_alpha(1)
#initialize the ticks
set_axis_to_probs()
init_ticks(a, label_font_size)
a.set_xticks([0, 0.5, 1])
a.set_yticks([0,0.5,1])
#output the figure
if graph_name is not None:
savefig(graph_name)
def plot_pr2_bias(data, title='ALANINE', graph_name='pr2_bias.png', \
num_genes='ignored', **kwargs):
"""Outputs a PR2-Bias plot of:
-isotypic transversions (base swapping)
with G3/(G3+C3) and A3/(A3+T3)
-Transitions (deaminations)
with G3/(G3+A3) and C3/(C3+T3)
-Allotypic transversions (G- oxidations)
with G3/(G3+T3) and C3/(C3+A3)
takes: an array in the order: x,G3/(G3+C3),A3/(A3+T3),
G3/(G3/A3),C3/(C3+T3),G3/(G3+T3),C3/(C3+A3)
label: default 'ALANINE'
one amino acid written out in caps:
ALANINE, ARGININE4, GLYCINE, LEUCINE4,
PROLINE, SERINE4, THREONINE, VALINE
from one of the amino acids program will add acronym
C2 type: ala(GCN), pro(CCN), ser4(TCN), thr(ACN)
G2 type: arg4 (CGN), an gly(GGN)
T2 type: leu4(CTN), val (GTN)
size: of graph in inches (default = 8.0)
graph_name: default 'pr2_bias.png'
num_genes: number of genes contributing to graph, currently ignored.
"""
#we can't put anything in the top right, so print num_genes after the title
#if it was supplied
#initializes the graph display and font
font,label_font_size=init_graph_display(graph_shape='sqr', \
graph_grid='/', x_label="$P_3$", y_label="Y axis", prob_axes=True, \
title=title, **kwargs)
#sets the marker_size relative to the font and thus the graph size
marker_size = (label_font_size-1)
#plots the pr2bias in order G3/(G3+C3),A3/(A3+T3),
# G3/(G3/A3),C3/(C3+T3),
# G3/(G3+T3),C3/(C3+A3)
#colors and symbols coded from Sueoka 2002
plot(data[:,0], data[:,1], '-ko', c='k',
markersize=marker_size)
plot(data[:,0], data[:,2], '-kv', c='k',
markersize=marker_size)
plot(data[:,0], data[:,3], '-ro', c='r',
markersize=marker_size)
plot(data[:,0], data[:,4], '-rv', c='r',
markersize=marker_size)
plot(data[:,0], data[:,5], '-wo', c='k', mfc='w',
markersize=marker_size)
plot(data[:,0], data[:,6], '-wv', c='k', mfc='w',
markersize=marker_size)
#aaLabel based on the amino acid that is graphed
#C2 type: ala(GCN), pro(CCN), ser4(TCN), thr(ACN)
#G2 type: arg4 (CGN), an gly(GGN)
#T2 type: leu4(CTN), val (GTN) (Sueoka 2002)
text(.95, .05, aa_labels[title], font, verticalalignment='bottom',
horizontalalignment='right')
#output the figure
set_axis_to_probs()
if graph_name is not None:
savefig(graph_name)
def plot_fingerprint(data, alpha=0.7, \
show_legend=True, graph_name='fingerprint.png', has_mean=True,
which_blocks='quartets', multiple=False, graph_grid='t', prob_axes=True, \
edge_colors='k', **kwargs):
"""Outputs a bubble plot of four-codon amino acid blocks
labeled with the colors from Sueoka 2002.
takes: data: array-elements in the col order x, y, r of
each of the four codon Amino Acids in the row order:
ALA, ARG4, GLY, LEU4, PRO, SER, THR, VAL
(for traditional fingerprint), or:
UU -> GG (for 16-block fingerprint).
last row is the mean (if has_mean is set True)
**kwargs passed on to init_graph_display (these include
graph_shape, graph_grid, x_label, y_label, dark, with_parens).
title: will be printed on graph (default: 'Unknown Species')
num_genes (number of genes contributing to graph: default None)
NOTE: will not print if None.)
size: of graph in inches (default = 8.0)
alpha: transparency of bubbles
(ranges from 0, transparent, to 1, opaque; default 0.7)
show_legend: bool, default True, whether to print legend
graph_name: name of file to write (default 'fingerprint.png')
has_mean: whether the data contain the mean (default: True)
which_blocks: which codon blocks to print (default is 'quartets'
for the 4-codon amino acid blocks, but can also use 'all' for all
quartets or 'split' for just the split quartets.)
multiple: if False (the default), assumes it got a single block
of data. Otherwise, assumes multiple blocks of data in a list or
array.
edge_colors: if multiple is True (ignored otherwise), uses this
sequence of edge color strings to hand out edge colors to successive
series. Will iterate over this, so can be a string of 1-letter
color codes or a list of color names.
note: that the data are always expected to be in the range (0,1)
since we're plotting frequencies. axes, gid, etc. are hard-coded
to these values.
"""
#figure out which type of fingerprint plot we're doing, and get the
#right colors
if which_blocks == 'quartets':
blocks = CodonUsage.SingleAABlocks
elif which_blocks == 'split':
blocks = CodonUsage.SplitBlocks
else:
blocks = CodonUsage.Blocks
colors = [doublets_to_colors[i] for i in blocks]
#formatting the labels in latex
x_label="$G_3/(G_3+C_3)$"
y_label="$A_3/(A_3+T_3)$"
#initializing components of the graph
font,label_font_size=init_graph_display(graph_shape='sqr', \
graph_grid=graph_grid, x_label=x_label, \
y_label=y_label, prob_axes=prob_axes, **kwargs)
if not multiple:
data = [data]
alpha = broadcast(alpha, len(data))
edge_colors = broadcast(edge_colors, len(data))
for al, d, edge_color in zip(alpha, data, edge_colors):
#skip this series if no data
if d is None or not d.any():
continue
for i, color in enumerate(colors):
j = i+1
#note: doing these as slices because scatter_classic needs the
#extra level of nesting
patches = scatter_classic(d[i:j,0], d[i:j,1],
s=(d[i:j,2]/2), c=color)
#set alpha for the patches manually
for p in patches:
p.set_alpha(al)
p.set_edgecolor(edge_color)
#plot mean as its own point -- can't do cross with scatter
if has_mean:
mean_index = len(blocks) #next index after the blocks
plot([d[mean_index,0]], [d[mean_index,1]],
'-k+',markersize=label_font_size, alpha=al)
abbrev = CodonUsage.BlockAbbreviations
a = gca()
#if show_legend is True prints a legend in the right center area
if show_legend:
legend_key = [abbrev[b] for b in blocks]
#copy legend font properties from the x axis tick labels
legend_font_props = \
a.xaxis.get_label().get_fontproperties().copy()
legend_font_scale_factor = 0.7
curr_size = legend_font_props.get_size()
legend_font_props.set_size(curr_size*legend_font_scale_factor)
l = figlegend(a.patches[:len(blocks)],
legend_key,
prop=legend_font_props,
loc='center right',borderpad=0.1,labelspacing=0.5,
handlelength=1.0,handletextpad=0.5, borderaxespad=0.0)
#fix transparency of patches
for p in l.get_patches():
p.set_alpha(1)
#initialize the ticks
set_axis_to_probs()
init_ticks(a, label_font_size)
a.set_xticks([0, 0.5, 1])
a.set_yticks([0,0.5,1])
#output the figure
if graph_name is not None:
savefig(graph_name)
def plot_pr2_bias(data, title='ALANINE', graph_name='pr2_bias.png', \
num_genes='ignored', **kwargs):
"""Outputs a PR2-Bias plot of:
-isotypic transversions (base swapping)
with G3/(G3+C3) and A3/(A3+T3)
-Transitions (deaminations)
with G3/(G3+A3) and C3/(C3+T3)
-Allotypic transversions (G- oxidations)
with G3/(G3+T3) and C3/(C3+A3)
takes: an array in the order: x,G3/(G3+C3),A3/(A3+T3),
G3/(G3/A3),C3/(C3+T3),G3/(G3+T3),C3/(C3+A3)
label: default 'ALANINE'
one amino acid written out in caps:
ALANINE, ARGININE4, GLYCINE, LEUCINE4,
PROLINE, SERINE4, THREONINE, VALINE
from one of the amino acids program will add acronym
C2 type: ala(GCN), pro(CCN), ser4(TCN), thr(ACN)
G2 type: arg4 (CGN), an gly(GGN)
T2 type: leu4(CTN), val (GTN)
size: of graph in inches (default = 8.0)
graph_name: default 'pr2_bias.png'
num_genes: number of genes contributing to graph, currently ignored.
"""
#we can't put anything in the top right, so print num_genes after the title
#if it was supplied
#initializes the graph display and font
font,label_font_size=init_graph_display(graph_shape='sqr', \
graph_grid='/', x_label="$P_3$", y_label="Y axis", prob_axes=True, \
title=title, **kwargs)
#sets the marker_size relative to the font and thus the graph size
marker_size = (label_font_size-1)
#plots the pr2bias in order G3/(G3+C3),A3/(A3+T3),
# G3/(G3/A3),C3/(C3+T3),
# G3/(G3+T3),C3/(C3+A3)
#colors and symbols coded from Sueoka 2002
plot(data[:,0], data[:,1], '-ko', c='k',
markersize=marker_size)
plot(data[:,0], data[:,2], '-kv', c='k',
markersize=marker_size)
plot(data[:,0], data[:,3], '-ro', c='r',
markersize=marker_size)
plot(data[:,0], data[:,4], '-rv', c='r',
markersize=marker_size)
plot(data[:,0], data[:,5], '-wo', c='k', mfc='w',
markersize=marker_size)
plot(data[:,0], data[:,6], '-wv', c='k', mfc='w',
markersize=marker_size)
#aaLabel based on the amino acid that is graphed
#C2 type: ala(GCN), pro(CCN), ser4(TCN), thr(ACN)
#G2 type: arg4 (CGN), an gly(GGN)
#T2 type: leu4(CTN), val (GTN) (Sueoka 2002)
text(.95, .05, aa_labels[title], font, verticalalignment='bottom',
horizontalalignment='right')
#output the figure
set_axis_to_probs()
if graph_name is not None:
savefig(graph_name)