fix bug

soi/OrthoFinder.py

@@ -1851,7 +1851,7 @@ def get_paralogs(OFdir, outHomo, min_support=0.5):
 				print('\t'.join(line), file=outHomo)
 def gene_format_p(gene):
 	sp, g = gene.split('|')
-	sp = sp[:len(sp)/2]
+	sp = sp[:int(len(sp)/2)]
 	g = sp + '|' + g
 	return (sp, g)
 def gene_format_common(gene):

soi/colors.py

@@ -0,0 +1,56 @@
+#from reportlab.lib.units import cm
+#from reportlab.lib import colors
+import numpy as np
+from matplotlib import cm
+import matplotlib
+
+COLORS_HEX = ['#f9c00c', '#00b9f1', '#7200da', '#f9320c', '#00b8a9', "#F4A460", '#009999', '#00C02E',
+	'#980000','#00ffff','#0000ff','#ff0000','#4a86e8','#ff9900','#ffff00',
+	'#00ff00','#9900ff','#ff00ff','#20124d','#274e13','#000000','#cccccc',
+	'#7f6000','#a64d79','#6aa84f','#fff2cc','#47a952','#3ea6b6','#a5b805','#8f9276','#ca8d7c']
+#white = colors.white
+white = '#FFFFFF'
+
+class HexColors:
+	def __init__(self, colors_hex=None):
+		if colors_hex is None:
+			colors_hex = COLORS_HEX
+		elif isinstance(colors_hex, str):
+			colors_hex = colors_hex.split(',')
+		self.colors_hex = colors_hex
+	@property
+	def colors_rgb(self):
+		colors_lst = [colors.HexColor(v) for v in self.colors_hex]
+		return [','.join(map(str, v.bitmap_rgb())) for v in colors_lst]
+	@property 
+	def colors_r(self):
+		return 'c({})'.format(','.join(map(repr, self.colors_hex)))
+	def __str__(self):
+		return str(self.colors_hex)
+	def __repr__(self):
+		return str(self.colors_hex)
+
+class Colors:
+	def __init__(self, n):
+		self.n = n
+		self.colors = self.get_colors()
+
+	def get_colors(self):
+		if self.n <=10:
+			colors = cm.get_cmap('tab10')
+		elif self.n <= 20:
+			colors = cm.get_cmap('tab20')
+		else:
+			colors = cm.get_cmap('viridis', self.n)
+		colors = colors(np.linspace(0, 1, self.n))
+		return colors
+	def to_hex(self):
+		colors_hex = [matplotlib.colors.to_hex(c) for c in self.colors]
+		return colors_hex
+	def to_rgb(self):
+		colors_hex = self.to_hex()
+		colors_lst = [colors.HexColor(v) for v in colors_hex]
+		colors_rgb = [','.join(map(str, v.bitmap_rgb())) for v in colors_lst]
+		return colors_rgb
+
+

soi/evaluator.py

@@ -0,0 +1,155 @@
+import sys
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+from matplotlib.gridspec import GridSpec
+mpl.use("Agg")
+mpl.rcParams['pdf.fonttype'] = 42
+
+from lazy_property import LazyWritableProperty as lazyproperty
+
+from .mcscan import Collinearity, Gff, XCollinearity
+from .colors import Colors
+
+def eval(collinearities, gff, ref, pre=None):
+	d_rcs = {}
+	for rc in XCollinearity(collinearities, gff=gff):
+		rc.fr = rc.fractionation_rate(ref=ref)
+		if rc.fr is None:
+			continue
+		sp1, sp2 = rc.species1, rc.species2
+		if sp1 == sp2:
+			continue
+		if sp2 == ref:
+			sp1, sp2 = sp2, sp1
+		xrc = SynRec(rc)
+		try: d_rcs[sp2] += [xrc]
+		except KeyError: d_rcs[sp2] = [xrc]
+
+	for sp, rcs in d_rcs.items():
+		d_rcs[sp] = SynRecs(rcs)
+	outfig = 'test.png'
+	plot_eval(d_rcs, outfig)
+def main():
+	collinearities, gff, ref = sys.argv[1:4]
+	eval(collinearities, gff, ref)
+def plot_eval(d_rcs, outfig, legend_fontsize=9):
+	fig = plt.figure(figsize=(10,10))
+	gs = GridSpec(3, 7)
+
+	ax0 = fig.add_subplot(gs[:, 6]) # legend
+	ax1 = fig.add_subplot(gs[0, 0:3]) # accumulation N
+	ax2 = fig.add_subplot(gs[1, 0:3]) # decay N
+	ax3 = fig.add_subplot(gs[2, 0:3]) # histo of fr
+	ax4 = fig.add_subplot(gs[0, 3:6]) # dots
+	ax5 = fig.add_subplot(gs[1, 3:6]) # dots of 50
+	ax6 = fig.add_subplot(gs[2, 3:6]) # bar
+
+	n = len(d_rcs)
+	colors = Colors(n).colors
+	for i, (sp, rcs) in enumerate(sorted(d_rcs.items())):
+		_sp = convert_sp(sp)
+		i50, sn50, fn50 = rcs.xn50
+		fm, sm = np.median(rcs.extended_frs), np.median(rcs.extended_ns)
+		ns = rcs.ns
+		nb = len(ns)
+		kargs = dict(color=colors[i], alpha=0.9, label=_sp)
+		ax0.plot(-2, -2, linestyle='-', marker='o',  **kargs)
+#		ax0.barh(0, 0, height=0, left=0, align='center', label=_sp)
+
+		ax1.plot(range(1, nb+1), np.cumsum(ns), drawstyle="steps-post",  **kargs)
+
+		ax2.plot(range(1, nb+1), ns, drawstyle="steps-post", **kargs)
+#		ax2.scatter(i50, sn50, label=_sp)
+
+		ax3.scatter(len(rcs.ns), sum(rcs.ns), **kargs)
+		ax4.hist(rcs.extended_frs, bins=40, histtype='step', **kargs)
+#		ax4.scatter(rcs.frs, rcs.ns,  alpha=0.6, label=_sp)
+#		ax5.scatter(fn50, sn50, alpha=0.8, label=_sp)
+		ax5.scatter(fm, sn50, **kargs)
+
+#       ax5.hist(rcs.extended_ns, bins=30, histtype='step', label=_sp)
+#		ax5.scatter(np.mean(rcs.extended_frs), np.mean(rcs.extended_ns), label=_sp)
+		ax6.scatter(fm, sm, **kargs)
+#		print(sn50, sm)
+#	set_legends([ax1, ax2, ax3,ax4,ax5,ax6], fontsize=legend_fontsize)
+#	ax0.legend(loc='upper left',fancybox=False, frameon=False, ncols=ncols)
+	for ax, xlab, ylab in (
+		[ax1, '# of blocks', 'Cumulative number of genes'],
+		[ax2, '# of blocks', 'Number of genes'],
+		[ax3, 'Total number of blocks', 'Total number of genes'],
+		[ax4, 'Fractionation rate', 'Number of genes'],
+		[ax5, 'Fractionation rate', 'Block size'],
+		[ax6, 'Fractionation rate', 'Block size'],
+		):
+		set_labels(ax, xlab, ylab)
+
+	#legend
+	ncols = n // 30 + 1
+	ax0.set_xlim(0,1)
+	ax0.set_ylim(0,1)
+	ax0.legend(loc=(-1.5, 0),fancybox=False, frameon=False, ncols=ncols)
+	ax0.xaxis.set_tick_params(length=0)
+	ax0.spines['right'].set_color('none')
+	ax0.spines['top'].set_color('none')
+	ax0.spines['left'].set_color('none')
+	ax0.spines['bottom'].set_color('none')
+	ax0.xaxis.set_ticks([])
+	ax0.yaxis.set_ticks([])
+#	ax0.set_title('Species', loc='left')
+
+	plt.subplots_adjust(hspace=0.25, wspace=1.8)
+	plt.savefig(outfig, bbox_inches='tight')
+def set_labels(ax, xlab, ylab, **kargs):
+	ax.set_xlabel(xlab, **kargs)
+	ax.set_ylabel(ylab, **kargs)
+
+def set_legends(axs, **kargs):
+	for ax in axs:
+		ax.legend(**kargs)
+def convert_sp(sp):
+	return '$' + sp.replace('_', '~') + '$'
+class SynRec:
+	def __init__(self, rc):
+		self.N = rc.N
+		self.fr = rc.fr
+class SynRecs:
+	def __init__(self, rcs):
+		self.rcs = rcs
+	@lazyproperty
+	def matrix(self):
+		data = []
+		for rc in self.rcs:
+			data += [[rc.N, rc.fr]]
+		return np.array(sorted(data, key=lambda x:-x[0]))
+	@lazyproperty
+	def ns(self):
+		return self.matrix[:, 0]
+	@lazyproperty
+	def frs(self):
+		return self.matrix[:, 1]
+	def get_nx0(self, cutoff=50):
+		self.size = sum(self.ns)
+		accum = 0
+		for i, x in enumerate(self.ns):
+			accum += x
+			if 1e2 * accum / self.size >= cutoff:
+				return x, i+1
+	@lazyproperty
+	def xn50(self):
+		sn50,i50 = self.get_nx0()
+		fn50 = list(sorted(self.frs, reverse=1))[i50 -1]
+		return i50, sn50, fn50
+	@lazyproperty
+	def extended_frs(self):
+		frs = []
+		for n, fr in self.matrix:
+			frs += [fr]* int(n)
+		return frs
+	@lazyproperty
+	def extended_ns(self):
+		nrs = []
+		for n in self.ns:
+			nrs += [n] * int(n)
+		return nrs
+

soi/mcscan.py

@@ -623,7 +623,7 @@ def fractionation_rate(self, ref=None, both=False):
 		l1, l2 = ie1 - is1 + 1, ie2-is2+1
 		if both:
 			return 2.0*self.N / (l1+l2)
-		return 1.0*rc.N / l1
+		return 1.0*self.N / l1
 	@property
 	def good_ks(self):
 		return [ks for ks in self.ks if ks is not None]