def compare_regions(dirs, labels, o):
"""Output onto *o* an HTML fragment for the comparison of the three
regions: Global, Northern Hemisphere, Southern Hemisphere.
"""
anomaly_file = '%s.Ts.ho2.GHCN.CL.PA.txt'
for region, code in [
('global', 'GLB'),
('northern hemisphere', 'NH'),
('southern hemisphere', 'SH'),
]:
# Annual series
fs = map(lambda d: open(os.path.join(d, anomaly_file % code), 'r'),
dirs)
anns = map(list, map(vischeck.annual_anomalies, fs))
url = vischeck.asgooglechartURL(anns)
print >> o, '<h2>%s annual temperature anomaly</h2>' % region.capitalize(
)
print >> o, '<p>%s in red, %s in black.</p>' % tuple(labels)
print >> o, '<img src="%s">' % escape(url)
print >> o, ('<h3>%s annual residues (%s - %s)</h3>' %
(region.capitalize(), labels[0], labels[1]))
print >> o, '<img src="%s">' % escape(differences_url(anns))
diffs = list(difference(anns, 0.01))
d = map(lambda a: a[1], diffs)
print >> o, '<h3>%s annual residue distribution</h3>' % region.capitalize(
)
print >> o, '<img src="%s">' % escape(distribution_url(d))
print >> o, '<h3>%s annual residue summary</h3>' % region.capitalize()
print >> o, '<ul>'
print >> o, '<li>Min = %g<li>Max = %g' % (min(d), max(d))
print >> o, '<li>Zeroes: %d/%d<li>Mean = %g<li>Standard deviation = %g' % stats(
d)
print >> o, '</ul>'
top(diffs, 10, o, 'Largest %s annual residues' % region,
lambda k, v: "%04d: %g" % (k, v))
# Monthly series
fs = map(lambda d: open(os.path.join(d, anomaly_file % code), 'r'),
dirs)
mons = map(asmon, fs)
diffs = list(difference(mons, 0.01))
d = map(lambda a: a[1], diffs)
print >> o, '<h3>%s monthly residue distribution</h3>' % region.capitalize(
)
print >> o, '<img src="%s">' % escape(distribution_url(d))
print >> o, '<h3>%s monthly residue summary</h3>' % region.capitalize()
print >> o, '<ul>'
print >> o, '<li>Min = %g<li>Max = %g' % (min(d), max(d))
print >> o, '<li>Zeroes: %d/%d<li>Mean = %g<li>Standard deviation = %g' % stats(
d)
print >> o, '</ul>'
top(diffs, 10, o, 'Largest %s monthly residues' % region,
lambda k, v: "%04d-%02d: %g" % (k[0], k[1] + 1, v))
def compare_regions(dirs, labels, o):
"""Output onto *o* an HTML fragment for the comparison of the three
regions: Global, Northern Hemisphere, Southern Hemisphere.
"""
surface = 'land'
anomaly_file = '%s%s.Ts.GHCN.CL.PA.txt'
for region, code in [
('global', 'GLB'),
('northern hemisphere', 'NH'),
('southern hemisphere', 'SH'),
]:
# Annual series
fs = map(lambda d:
open(os.path.join(d, anomaly_file % (surface, code)), 'r'), dirs)
anns = map(list, map(vischeck.annual_anomalies, fs))
url = vischeck.asgooglechartURL(anns)
print >>o, '<h2>%s annual temperature anomaly</h2>' % region.capitalize()
print >>o, '<p>%s in red, %s in black.</p>' % tuple(labels)
print >>o, '<img src="%s">' % escape(url)
print >>o, ('<h3>%s annual residues (%s - %s)</h3>'
% (region.capitalize(), labels[0], labels[1]))
print >>o, '<img src="%s">' % escape(differences_url(anns))
diffs = list(difference(anns, 0.01))
d = map(lambda a: a[1], diffs)
print >>o, '<h3>%s annual residue distribution</h3>' % region.capitalize()
print >>o, '<img src="%s">' % escape(distribution_url(d))
print >>o, '<h3>%s annual residue summary</h3>' % region.capitalize()
print >>o, '<ul>'
print >>o, '<li>Min = %g<li>Max = %g' % (min(d), max(d))
print >>o, '<li>Zeroes: %d/%d<li>Mean = %g<li>Standard deviation = %g' % stats(d)
print >>o, '</ul>'
top(diffs, 10, o, 'Largest %s annual residues' % region,
lambda k, v: "%04d: %g" % (k, v))
# Monthly series
fs = map(lambda d:
open(os.path.join(d, anomaly_file % (surface, code)), 'r'), dirs)
mons = map(asmon, fs)
diffs = list(difference(mons, 0.01))
d = map(lambda a: a[1], diffs)
print >>o, '<h3>%s monthly residue distribution</h3>' % region.capitalize()
print >>o, '<img src="%s">' % escape(distribution_url(d))
print >>o, '<h3>%s monthly residue summary</h3>' % region.capitalize()
print >>o, '<ul>'
print >>o, '<li>Min = %g<li>Max = %g' % (min(d), max(d))
print >>o, '<li>Zeroes: %d/%d<li>Mean = %g<li>Standard deviation = %g' % stats(d)
print >>o, '</ul>'
top(diffs, 10, o, 'Largest %s monthly residues' % region,
lambda k, v: "%04d-%02d: %g" % (k[0], k[1] + 1, v))
def compare(dirs, labels, o):
"""Compare results from the two directories in the sequence *dirs*,
which are labelled by the two strings in the sequence *labels*. Write a
comparison document in HTML to the stream *o*."""
assert len(dirs) == 2
assert len(labels) == 2
# XML-encode meta-characters &,<,>
escape = xml.sax.saxutils.escape
labels = map(escape, labels)
# Version of ``asmon`` that avoids yielding ``None``.
asmon_values_only = lambda f: asmon(f, values_only=True)
title = "Comparison of %s and %s" % tuple(dirs)
print >>o, """<!doctype HTML>
<html>
<head>
<title>%s</title>
</head>
<body>
<h1>%s</h1>
<p>Generated: %s</p>
""" % (title, title, datetime.datetime.now())
anomaly_file = '%s.Ts.ho2.GHCN.CL.PA.txt'
box_file = 'BX.Ts.ho2.GHCN.CL.PA.1200'
for region, code in [
('global', 'GLB'),
('northern hemisphere', 'NH'),
('southern hemisphere', 'SH'),
]:
# Annual series
fs = map(lambda d: open(os.path.join(d, anomaly_file % code), 'r'), dirs)
anns = map(list, map(asann_values_only, fs))
url = vischeck.asgooglechartURL(anns)
print >>o, '<h2>%s annual temperature anomaly</h2>' % region.capitalize()
print >>o, '<p>%s in red, %s in black.</p>' % tuple(labels)
print >>o, '<img src="%s">' % escape(url)
print >>o, ('<h3>%s annual residues (%s - %s)</h3>'
% (region.capitalize(), labels[0], labels[1]))
print >>o, '<img src="%s">' % escape(differences_url(anns))
diffs = list(difference(anns, 0.01))
d = map(lambda a: a[1], diffs)
print >>o, '<h3>%s annual residue distribution</h3>' % region.capitalize()
print >>o, '<img src="%s">' % escape(distribution_url(d))
print >>o, '<h3>%s annual residue summary</h3>' % region.capitalize()
print >>o, '<ul>'
print >>o, '<li>Min = %g<li>Max = %g' % (min(d), max(d))
print >>o, '<li>Zeroes: %d/%d<li>Mean = %g<li>Standard deviation = %g' % stats(d)
print >>o, '</ul>'
top(diffs, 10, o, 'Largest %s annual residues' % region,
lambda k, v: "%04d: %g" % (k, v))
# Monthly series
fs = map(lambda d: open(os.path.join(d, anomaly_file % code), 'r'), dirs)
mons = map(asmon_values_only, fs)
diffs = list(difference(mons, 0.01))
d = map(lambda a: a[1], diffs)
print >>o, '<h3>%s monthly residue distribution</h3>' % region.capitalize()
print >>o, '<img src="%s">' % escape(distribution_url(d))
print >>o, '<h3>%s monthly residue summary</h3>' % region.capitalize()
print >>o, '<ul>'
print >>o, '<li>Min = %g<li>Max = %g' % (min(d), max(d))
print >>o, '<li>Zeroes: %d/%d<li>Mean = %g<li>Standard deviation = %g' % stats(d)
print >>o, '</ul>'
top(diffs, 10, o, 'Largest %s monthly residues' % region,
lambda k, v: "%04d-%02d: %g" % (k[0], k[1] + 1, v))
# Box series
fs = map(lambda d: open(os.path.join(d, box_file), 'r'), dirs)
boxes = map(list, map(box_series, fs))
diffs = list(difference(boxes))
box_table = {}
for d in diffs:
box = d[0][0]
box_table[box] = box_table.get(box,[])
box_table[box].append(d[1])
box_std_devs = []
max_std_dev = 0.0
for (box, box_diffs) in box_table.items():
box_table[box] = stats(box_diffs)
std_dev = box_table[box][3]
max_std_dev = max(max_std_dev, std_dev)
box_std_devs.append((box, std_dev))
d = map(lambda a: a[1], diffs)
print >>o, '<h3>Per-box monthly residue distribution</h3>'
print >>o, '<img src="%s">' % escape(distribution_url(d))
print >>o, '<h3>Per-box monthly residue summary</h3>'
print >>o, '<ul>'
print >>o, '<li>Min = %g<li>Max = %g' % (min(d), max(d))
print >>o, '<li>Zeroes: %d/%d<li>Mean = %g<li>Standard deviation = %g' % stats(d)
print >>o, '</ul>'
top(diffs, 10, o,'Largest per-box monthly residues',
lambda k, v: "Box %02d, %04d-%02d: %g" % (k[0], k[1], k[2] + 1, v))
top(box_std_devs, 10, o,'Largest per-box standard deviations',
lambda k, v: "Box %02d: %g" % (k, v))
print >>o, '<h3>Geographic distribution of per-box monthly residue statistics</h3>'
print >>o, '<table border=1 style="border-collapse:collapse; border-width:1px; border-color:#cccccc; border-style:solid; font-size:small">'
box = 0
for band in range(8):
print >>o, '<tr>'
boxes_in_band = 18 - 2 * (abs(7 - 2*band)) # silly hack to get 4,8,12,16,16,12,8,4
box_span = 48 / boxes_in_band
for i in range(boxes_in_band):
std_dev = box_table[box][3]
if std_dev == 0 or max_std_dev == 0:
gb_level = 0xff
else:
gb_level = 0xff - int(0x80 * std_dev / max_std_dev)
color = "#ff%02x%02x" % (gb_level, gb_level)
print >>o, '<td align="center" colspan="%d" bgcolor = "%s">' % (box_span, color)
print >>o, '%d%%<br/>%.2g</td>' % (100 * box_table[box][0]/box_table[box][1], box_table[box][3])
box += 1
print >>o, '</tr>'
print >>o, '</table>'
print >>o, "</body>"
print >>o, "</html>"
o.close()
