def _draw_probs(fatmodel, fatdict, ecomodel, ecodict, version_folder):
fatG = fatmodel.getCombinedG(fatdict)
fat_probs = fatmodel.getProbabilities(fatdict, fatG)
fat_figure = drawImpactScale(fatdict, fat_probs, "fatality")
ecoG = ecomodel.getCombinedG(ecodict)
eco_probs = ecomodel.getProbabilities(ecodict, ecoG)
eco_figure = drawImpactScale(ecodict, eco_probs, "economic")
fat_probs_file = os.path.join(version_folder, "alertfatal.pdf")
fat_probs_file_png = os.path.join(version_folder, "alertfatal.png")
fat_probs_file_small = os.path.join(version_folder, "alertfatal_small.png")
fat_probs_file_smaller = os.path.join(version_folder, "alertfatal_smaller.png")
eco_probs_file = os.path.join(version_folder, "alertecon.pdf")
eco_probs_file_png = os.path.join(version_folder, "alertecon.png")
eco_probs_file_small = os.path.join(version_folder, "alertecon_small.png")
eco_probs_file_smaller = os.path.join(version_folder, "alertecon_smaller.png")
fat_figure.savefig(fat_probs_file, bbox_inches="tight")
fat_figure.savefig(fat_probs_file_png, bbox_inches="tight")
fat_figure.savefig(fat_probs_file_small, bbox_inches="tight", dpi=57)
fat_figure.savefig(fat_probs_file_smaller, bbox_inches="tight", dpi=35)
eco_figure.savefig(eco_probs_file, bbox_inches="tight")
eco_figure.savefig(eco_probs_file_png, bbox_inches="tight")
eco_figure.savefig(eco_probs_file_small, bbox_inches="tight", dpi=57)
eco_figure.savefig(eco_probs_file_smaller, bbox_inches="tight", dpi=35)
return (fat_probs_file, eco_probs_file)
def img_test():
# NOTE: This isn't a great test, so I am turning it off for now,
# until I can find a more reliable way to test images.
testhash1 = b'\\\x03\xa9\x04\xe6\x8e\x99\x87r\xf2\xd9\xb9\xd9\xf8T\x83'
testhash2 = b'\xe0\x19\xee$\x1a\xdcp\xdfX\x16\x8c\xb4\x95!t\xe0'
testhash3 = b"xuw\xde0\x0c\xa23[P'\xf3\xab^\x9d\xb7"
testhash4 = b'P\xcc\xc8n\xc2Z\x9fGH\x1d\x1cu\xd8\x00\x05n'
try:
homedir = tempfile.mkdtemp()
ranges = OrderedDict([('0-1', 0.03),
('1-10', 0.14),
('10-100', 0.32),
('100-1000', 0.325),
('1000-10000', 0.15),
('10000-100000', 0.03),
('100000-10000000', 0.01)])
f = drawImpactScale(ranges, 'economic', debug=False)
outfile = os.path.join(homedir, 'test1.png')
f.savefig(outfile)
plt.close(f)
data = open(outfile, 'rb').read()
m = hashlib.md5()
m.update(data)
print('Testing first economic plot is consistent with prior results...')
assert m.digest() == testhash1
print('Passed.')
ranges = OrderedDict([('0-1', 0.8),
('1-10', 0.1),
('10-100', 0.05),
('100-1000', 0.03),
('1000-10000', 0.02),
('10000-100000', 0.0),
('100000-10000000', 0.0)])
f = drawImpactScale(ranges, 'fatality', debug=False)
outfile = os.path.join(homedir, 'test2.png')
f.savefig(outfile)
plt.close(f)
data = open(outfile, 'rb').read()
m = hashlib.md5()
m.update(data)
print('Testing first fatality plot is consistent with prior results...')
assert m.digest() == testhash2
print('Passed.')
ranges = OrderedDict([('0-1', 0.1),
('1-10', 0.6),
('10-100', 0.25),
('100-1000', 0.03),
('1000-10000', 0.02),
('10000-100000', 0.0),
('100000-10000000', 0.0)])
f = drawImpactScale(ranges, 'fatality', debug=False)
outfile = os.path.join(homedir, 'test3.png')
f.savefig(outfile)
plt.close(f)
data = open(outfile, 'rb').read()
m = hashlib.md5()
m.update(data)
print('Testing second fatality plot is consistent with prior results...')
assert m.digest() == testhash3
print('Passed.')
ranges = OrderedDict([('0-1', 0.1),
('1-10', 0.6),
('10-100', 0.25),
('100-1000', 0.03),
('1000-10000', 0.0),
('10000-100000', 0.45),
('100000-10000000', 0.)])
f = drawImpactScale(ranges, 'fatality', debug=False)
outfile = os.path.join(homedir, 'test4.png')
f.savefig(outfile)
plt.close(f)
data = open(outfile, 'rb').read()
m = hashlib.md5()
m.update(data)
print('Testing third fatality plot is consistent with prior results...')
assert m.digest() == testhash4
print('Passed.')
except Exception as error:
raise error
finally:
if os.path.isdir(homedir):
shutil.rmtree(homedir)