def make_edge_comparisons(cgraphs, bgraphs):
cgsets = dict([(k, set(v.edges())) for k, v in cgraphs.iteritems()])
for bname, bg in bgraphs.iteritems():
#if bname != 'kn': continue
f = myplots.fignum(3,(8,8))
f.clear()
axes = [f.add_subplot(311),
f.add_subplot(312),
f.add_subplot(313)]
ccolors = dict(zip(cgraphs.keys(), mycolors.getct(len(cgraphs))))
bgset = set(bg.edges())
yvals = {'jaccard':[], 'spec':[], 'sens':[]}
xofs = 0
heights, xvals ,colors ,names= [], [], [], []
for cname, cg in sorted(cgraphs.iteritems(),
key = lambda x: x[0]):
cgset = set(cg)
#SIMILARITIES MATCHING THE ORDER OF SIMNAMES
yvals['jaccard'].append(float(len(bgset.intersection(cgsets[cname])))/\
len(bgset.union(cgsets[cname])))
yvals['spec'].append(
float(len(bgset.intersection(cgsets[cname])))/\
len(cgsets[cname]))
yvals['sens'].append(
float(len(bgset.intersection(cgsets[cname])))/\
len(bgset))
#colors.extend([ccolors[cname]] * len(sims))
#heights.extend(sims)
names.append(cname )
#xvals.extend(xofs +arange(len(sims)))
#xofs = max(xvals) + 2
#if cname == 'unsup': raise Exception()
for j, elt in enumerate(yvals.iteritems()):
metric_name = elt[0]
heights = elt[1]
print heights
ax = axes[j]
xvals = argsort(argsort(heights))
ax.bar(xvals, heights, color = [ccolors[n] for n in names])
ax.set_title('edge similarity vs {0}, metric: {1}'.\
format(bname, metric_name))
myplots.color_legend(f, ccolors.values(), ccolors.keys())
#for i , n in enumerate(names):
# ax.annotate(n, [xvals[i], .001],
# xycoords = 'data',
# xytext = [2,0],
# textcoords = 'offset points',
# rotation = 90, va = 'bottom', ha = 'left')
f.savefig(figtemplate.format('edges_vs_{0}'.format(bname)))
def plot_ts(fig,params,
do_grid_resources = True):
fname = params['fname']
window = params.get('window',20)
cols, data = au.parse_printed( fname)
data_dict_unfiltered = {}
widths_dict = {}
for i in range(len(cols)):
c = cols[i]
data_dict_unfiltered[c] = array(map(lambda x: x[i], data),float)
widths_dict[c] = i +1
if 'Update' in cols:
cols.remove('Update')
data_dict = {}
for c in cols:
data_dict[c] = data_dict_unfiltered[c]
name = params['name']
if name in ['tasks','fitness','all','cdata','res']:
pass
else:
raise Exception('unhandled graph type: '+name)
nplots = len(cols)
fig.clear()
widths = params.get('widths',1)
last_y = zeros(window)
ct =mycolors.getct(len(cols))
do_fold = False
if fold_ts and nplots > 9:
do_fold = True
if do_fold:
all_cols = [cols[0:nplots/2],cols[nplots/2:]]
else: all_cols = [cols]
j = 0
colors = ct[(nplots/len(all_cols)*j):(nplots/len(all_cols)*(j+1))]
yvals = zeros( (len(all_cols[j]) ,window ) )
for i in range(len(all_cols[j])):
c = all_cols[j][i]
n = min(window, len(data_dict[c]))
y_sm = data_dict[c][-n:]
yvals[i,-n:] = y_sm
seismic(fig, yvals, colors, cols)
up.color_legend(fig, colors, cols,pos = 3)
print 'Current level: ', cols[0], data_dict[cols[0]][-1]
plt.draw()
if name == 'res' and do_grid_resources == True:
grid_resources(cols)
return
xs,ys,rs,cs = [[] for i in range(4)]
c_lambda = lambda x: x>=0 and ct[x] or [0,0,0]
arr = zeros((x,y,3))
for i in range(nc):
arr[nonzero(equal(grid, i))] = ct[i]
fig.clear()
sxs = False
scatter_GEO = True
if scatter_GEO:
sxs = scatter_array(arr,params)
if not sxs:
plt.imshow(arr,interpolation = 'nearest')
up.color_legend(fig,ct,cols)
plt.draw()
return True
def scatter_array(arr, params):
geo = params['computed']['geometry']
if geo['name'] == 'square': return False
name = geo['name']
sxs = True
if name == 'star':
f = plt.gcf()
ax = f.add_subplot(111)
star_k = geo['k']
d = geo['dim']