def fromFiles(cls, inventory_file, collapse_file, casualty_file, workforce_file):
"""Create SemiEmpiricalFatality object from a number of input files.
:param inventory_file:
HDF5 file containing Semi-Empirical building inventory data in an HDFContainer. (described in __init__).
:param collapse_file:
HDF5 file containing Semi-Empirical collapse rate data in an HDFContainer. (described in __init__).
:param casualty_file:
HDF5 file containing Semi-Empirical casualty rate data in an HDFContainer.(described in __init__).
:param workforce_file:
HDF5 file containing Semi-Empirical workforce data in an HDFContainer. (described in __init__).
:param growth_file:
Excel spreadsheet containing population growth rate data (described in PopulationGrowth.fromUNSpreadsheet()).
:returns:
SemiEmpiricalFatality object.
"""
# turn the inventory,collapse, and casualty spreadsheets into Panels...
inventory = HDFContainer.load(inventory_file)
collapse = HDFContainer.load(collapse_file)
casualty = HDFContainer.load(casualty_file)
workforce = HDFContainer.load(workforce_file)
# extract the one dataframe from the Panel
workforce = workforce.getDataFrame('Workforce')
workforce = workforce.set_index('CountryCode')
# read the growth spreadsheet into a PopulationGrowth object...
popgrowth = PopulationGrowth.fromDefault()
return cls(inventory, collapse, casualty, workforce, popgrowth)
def test_hdf_dictonaries():
f, testfile = tempfile.mkstemp()
os.close(f)
try:
container = HDFContainer.create(testfile)
# before we put anything in here, let's make sure we get empty lists from
# all of the methods that are supposed to return lists of stuff.
assert container.getDictionaries() == []
assert container.getLists() == []
assert container.getArrays() == []
assert container.getStrings() == []
assert container.getDataFrames() == []
# test simple dictionary
print('Test simple dictionary...')
indict1 = {'name': 'Fred', 'age': 34,
'dob': datetime(1950, 1, 1, 23, 43, 12).strftime(TIMEFMT)}
container.setDictionary('person', indict1)
outdict = container.getDictionary('person')
assert outdict == indict1
# this should fail because we can't serialize datetimes to json.
try:
indict1 = {'name': 'Fred', 'age': 34,
'dob': datetime(1950, 1, 1, 23, 43, 12)}
container.setDictionary('person', indict1)
except TypeError as te:
print(f'Expected failure: {str(te)}')
assert 1 == 1
# test more complicated dictionary
print('Test complex dictionary...')
indict2 = {'names': ['Fred', 'Akyüz'], 'ages': [34, 33]}
container.setDictionary('people', indict2)
outdict = container.getDictionary('people')
assert outdict == indict2
# test getDictionaryNames()
print('Test dictionary names...')
names = container.getDictionaries()
assert sorted(names) == sorted(['person', 'people'])
# test dropping a dictionary
container.dropDictionary('person')
assert container.getDictionaries() == ['people']
# try closing container and reopening
container.close()
container2 = HDFContainer.load(testfile)
assert container2.getDictionaries() == ['people']
except Exception:
assert 1 == 2
finally:
os.remove(testfile)
def test_hdf_dataframes():
f, testfile = tempfile.mkstemp()
os.close(f)
try:
container = HDFContainer.create(testfile)
# test pandas dataframe
print('Test dataframe...')
ttime1 = datetime(1900, 1, 1)
ttime2 = datetime(2000, 1, 1)
utc = pytz.timezone('UTC')
utc_time1 = utc.localize(ttime1)
utc_time2 = utc.localize(ttime2)
d = {
'Time': [utc_time1, utc_time2],
'ID': ['thing1', 'thing2'],
'Number': np.array([12.34, 25.67])
}
df = pd.DataFrame(d)
container.setDataFrame('testframe1', df)
outdf = container.getDataFrame('testframe1')
assert outdf['Number'].sum() == df['Number'].sum()
assert pd.to_datetime(outdf['Time'][0]) == df['Time'][0]
# test another dataframe
df2 = pd.DataFrame(data=[4, 5, 6, 7], index=range(0, 4), columns=['A'])
container.setDataFrame('testframe2', df2)
outdf = container.getDataFrame('testframe2')
outdf['A'].sum() == df2['A'].sum()
# test getdataframes
assert sorted(
container.getDataFrames()) == ['testframe1', 'testframe2']
# drop a dataframe
container.dropDataFrame('testframe1')
assert container.getDataFrames() == ['testframe2']
# close container, re-open
container.close()
container2 = HDFContainer.load(testfile)
assert container2.getDataFrames() == ['testframe2']
except Exception:
assert 1 == 2
finally:
os.remove(testfile)
def test_hdf_strings():
f, testfile = tempfile.mkstemp()
os.close(f)
try:
container = HDFContainer.create(testfile)
# test simple string
print('Test simple string...')
string1 = "These are the times that try men's souls."
container.setString('test_string1', string1)
outstring = container.getString('test_string1')
assert outstring == string1
# test unicode string
print('Test unicode string...')
string2 = "#SOURCE: Barka, A., H. S. Akyüz, E. Altunel, G. Sunal, Z. Çakir,"
container.setString('test_string2', string2)
outstring = container.getString('test_string2')
assert outstring == string2
# test getstrings
print('Test string names...')
names = container.getStrings()
assert names == ['test_string1', 'test_string2']
# drop string
container.dropString('test_string1')
assert container.getStrings() == ['test_string2']
# test a really big string
sets = string.ascii_uppercase + string.digits + string.ascii_lowercase
num_chars = 1000000
print('Making a really big string...')
big_string = ''.join(random.choice(sets) for _ in range(num_chars))
container.setString('big', big_string)
big_string2 = container.getString('big')
assert big_string == big_string2
# close container, re-open
container.close()
container2 = HDFContainer.load(testfile)
assert container2.getStrings() == ['big', 'test_string2']
except Exception:
assert 1 == 2
finally:
os.remove(testfile)
def test_hdf_arrays():
f, testfile = tempfile.mkstemp()
os.close(f)
try:
container = HDFContainer.create(testfile)
# test simple array, without compression
print('Test simple array...')
data = np.random.rand(4, 3)
metadata = {'xmin': 54.1, 'xmax': 123.1}
container.setArray('testdata1', data, metadata, compression=False)
outdata, outmetadata = container.getArray('testdata1')
np.testing.assert_array_equal(outdata, data)
assert outmetadata == metadata
# test array with nans, and compression on
print('Test nans array...')
data = np.random.rand(4, 3)
data[1, 1] = np.nan
metadata = {'xmin': 54.1, 'xmax': 123.1}
container.setArray('testdata2', data, metadata, compression=True)
outdata, outmetadata = container.getArray('testdata2')
np.testing.assert_array_equal(outdata, data)
assert outmetadata == metadata
# test getArrayNames
print('Test array names...')
names = container.getArrays()
assert sorted(names) == sorted(['testdata1', 'testdata2'])
# drop an array
container.dropArray('testdata1')
names = container.getArrays()
assert names == ['testdata2']
# close container, re-open
container.close()
container2 = HDFContainer.load(testfile)
assert container2.getArrays() == ['testdata2']
except Exception:
assert 1 == 2
finally:
os.remove(testfile)
def test_hdf_lists():
f, testfile = tempfile.mkstemp()
os.close(f)
try:
container = HDFContainer.create(testfile)
# test setting a list of strings
inlist = ['one', 'two', 'three']
container.setList('test_list1', inlist)
assert container.getList('test_list1') == inlist
# test setting a list of numbers
inlist = [5.4, 1.2, 3.4]
container.setList('test_list2', inlist)
assert container.getList('test_list2') == inlist
# test getlists
assert sorted(container.getLists()) == [
'test_list1', 'test_list2']
# test setting a list with dictionaries in it
inlist = [{'a': 1}, {'b': 2}]
container.setList('test_list3', inlist)
# drop a list
container.dropList('test_list1')
assert sorted(container.getLists()) == ['test_list2', 'test_list3']
# close container, re-open
container.close()
container2 = HDFContainer.load(testfile)
assert sorted(container2.getLists()) == ['test_list2', 'test_list3']
except Exception:
assert 1 == 2
finally:
os.remove(testfile)