def heat_score(conf, dur, filename):
import numpy as np
length = config.str2dur(dur)
dirname = conf.get("changepoint", "temp_cp_data")
cpd = ChangePointData(dirname)
cpd.load()
cpd_top_dt, cpd_end_dt = cpd.term()
top_dt = cpd_end_dt - length
if top_dt < cpd.term()[0]:
top_dt = cpd.term()[0]
end_dt = cpd_end_dt
result = []
for evdef in cpd.iter_evdef():
l_label, l_data, l_score = zip(*cpd.get(evdef, top_dt, end_dt))
result.append(l_score)
else:
xlen = len(l_label)
ylen = cpd.len_evdef()
data = np.array(result)
#data = np.array([[np.log(float(score)) for score in l_score]
# for l_score in result])
length = len(l_label)
print xlen
print ylen
x, y = np.meshgrid(np.arange(xlen + 1), np.arange(ylen + 1))
print x
print y
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import explot
import matplotlib.colors
cm = explot.generate_cmap(["orangered", "white"])
#plt.pcolormesh(x, y, data, cmap = cm)
plt.pcolormesh(x,
y,
data,
norm=matplotlib.colors.LogNorm(vmin=max(data.min(), 1.0),
vmax=data.max()),
cmap=cm)
xt_v, xt_l = explot.dt_ticks((0, xlen), (top_dt, end_dt),
cpd.binsize(),
recent=True)
#import pdb; pdb.set_trace()
plt.xticks(xt_v, xt_l, rotation=336)
plt.xlim(xmax=xlen)
plt.ylim(ymax=ylen)
plt.colorbar()
plt.savefig(filename)
def heat_score(conf, dur, filename):
import numpy as np
length = config.str2dur(dur)
dirname = conf.get("changepoint", "temp_cp_data")
cpd = ChangePointData(dirname)
cpd.load()
cpd_top_dt, cpd_end_dt = cpd.term()
top_dt = cpd_end_dt - length
if top_dt < cpd.term()[0]:
top_dt = cpd.term()[0]
end_dt = cpd_end_dt
result = []
for evdef in cpd.iter_evdef():
l_label, l_data, l_score = zip(*cpd.get(evdef, top_dt, end_dt))
result.append(l_score)
else:
xlen = len(l_label)
ylen = cpd.len_evdef()
data = np.array(result)
#data = np.array([[np.log(float(score)) for score in l_score]
# for l_score in result])
length = len(l_label)
print xlen
print ylen
x, y = np.meshgrid(np.arange(xlen + 1), np.arange(ylen + 1))
print x
print y
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import explot
import matplotlib.colors
cm = explot.generate_cmap(["orangered", "white"])
#plt.pcolormesh(x, y, data, cmap = cm)
plt.pcolormesh(x, y, data, norm=matplotlib.colors.LogNorm(
vmin=max(data.min(), 1.0), vmax=data.max()), cmap = cm)
xt_v, xt_l = explot.dt_ticks((0, xlen), (top_dt, end_dt),
cpd.binsize(), recent = True)
#import pdb; pdb.set_trace()
plt.xticks(xt_v, xt_l, rotation = 336)
plt.xlim(xmax = xlen)
plt.ylim(ymax = ylen)
plt.colorbar()
plt.savefig(filename)
def heatmap(conf, method, area, fn):
def result2data(result, l_label):
d_temp = {}
for r, dist in result:
d_temp[r.get_fn()] = dist
return [d_temp[label] for label in l_label]
import cg_dag
if method is None:
method = conf.get("search", "method")
if area is None:
area = "all"
src_dir = conf.get("dag", "output_dir")
l_r = pcresult.results_in_area(conf, src_dir, area)
l_label = [r.get_fn() for r in l_r]
l_result = []
for r in l_r:
if method == "log":
result = similar_block_log(conf, r.top_dt, r.end_dt,
r.area, ignore_same = False)
elif method in ("dag_ed", "dag_mcs"):
result = cg_dag.similar_block_dag(conf,
r.top_dt, r.end_dt, r.area, method, ignore_same = False)
else:
raise NotImplementedError
l_result.append(result2data(result, l_label))
# replace None to max value of whole result
mval = max([max(result) for result in l_result])
data = np.array([[mval if i is None else i for i in result] for result
in l_result])
# data = np.array(l_result)
n = len(l_r)
assert data.shape == (n, n)
x, y = np.meshgrid(np.arange(n + 1), np.arange(n + 1))
explot.dump(fn + ".temp", (x, y, data))
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
cm = explot.generate_cmap(["orangered", "white"])
plt.pcolor(x, y, data, cmap = cm)
plt.colorbar()
plt.savefig(fn)
