def test_nothing_is_correct():
norec, nomean = get_sightings(filename, 'NotPresent')
assert norec == 0, 'Biosignature missing should return zero records'
assert nomean == 0, 'Biosignature missing should return zero mean'
def test_animal_not_present():
animrec, animmean = get_sightings(filename, 'NotPresent')
assert animrec == 0, 'Animal missing should return zero records'
assert animmean == 0, 'Animal missing should return zero mean'
def test_owl_is_correct(): owlrec, owlmean = get_sightings(filename, 'Owl') # assert test_statement message_if_test_is_false assert owlrec == 2, 'Number of records for owl is wrong' assert owlmean == 17#, 'Mean sightings for owl is wrong'
def test_arg_capitalization_wrong():
owlrec, owlmean = get_sightings(filename, 'oWl')
assert owlrec == 2, 'Number of records for owl is wrong'
assert owlmean == 17, 'Mean sightings for owl is wrong'
def test_pig_is_correct(): pigrec, pigmean = get_sightings(filename, 'Pig') assert pigrec == 1, 'Number of records for Pig is wrong' assert pigmean == 4, 'Mean sightings for Pig is wrong'
def test_water_is_correct(): watrec, watmean = get_sightings(filename,'water') assert watrec==2, 'Number of records for water is wrong' assert watmean==17, 'Mean for water is wrong'
def test_owl_is_correct():
owlrec, owlmean = get_sightings(filename, 'Owl')
assert owlrec == 2, 'Number of records for owl is wrong'
assert owlmean == 17, 'Mean sightings for owl is wrong'
def test_bay_is_correct():
bayrec, baymean = get_sightings(filename, 'Nazan Bay')
assert bayrec == 2, 'Number of records for Nazan Bay is wrong'
assert baymean == 17, 'Mean Tidal wave sightings for owl is wrong'
def test_fireisland_is_correct():
oxrec, oxmean = get_sightings(filename, 'Fire Island')
assert oxrec == 2, 'Number of records for Fire Island is wrong'
assert oxmean == 25.5, 'Mean Tidal wave sightings for Fire Island is wrong'
def test_clay_is_corrrect():
clayrec,claymean = get_sightings(filename,"Clay")
assert clayrec==2, "number of records for clay is wrong"
assert claymean==25.5, "clay mean is wrong"
figFILE = os.path.join(outDIR,'spp_fig.png')
# Set names of species to count
spp_names = ['Fox', 'Wolf', 'Grizzly', 'Wolverine']
# ------------------------------------------------------------------------
# Perform analysis
# ------------------------------------------------------------------------
# Declare empty list to hold counts of records
spp_recs = []
# Get total number of records for each species
for spp in spp_names:
totalrecs, meancount = get_sightings(dataFILE, spp)
spp_recs.append(totalrecs)
print('spp_names')
print( spp_names )
print('spp_recs')
print( spp_recs )
print('[spp_names, spp_recs]')
print( [spp_names, spp_recs] )
print('np.transpose([spp_names, spp_recs])')
print( np.transpose([spp_names, spp_recs]) )
# ------------------------------------------------------------------------
def test_water_is_corrrect():
watrec,watmean = get_sightings(filename,"Water")
assert watrec==2, "number of records for water is wrong"
assert watmean==17, "water mean is wrong"
def test_not_present():
norec,nomean = get_sightings(filename, "not present")
assert norec==0, "Biosig not present"
assert nomean ==0, "mean is not present"
def test_not_present():
norec, nomean = get_sightings(filename, 'Not Present')
assert norec == 0, 'Biosigniture not present'
assert nomean==0, 'Mean is not present'
def test_anonymouse_is_correct(): anirec, animean = get_sightings(filename, 'NotPresent') assert anirec == 0, 'Number of anonymous records is wrong' assert animean == 0 , 'Mean for anonymous animal rec is wrong'
def test_station_not_present():
statrec, statmean = get_sightings(filename, 'NotPresent')
print statrec, statmmean
assert statrec == 0, 'Station`s data missing should return zero records'
assert statmean == 0, 'Station`s data missing should return zero mean'
def test_Mouse_is_correct(): mouserec, mousemean = get_sightings(filename, 'Mouse') assert mouserec == 12, 'Mouse number wrong' assert mousemean == 1, 'Mouse mean wrong'
def test_arg_capitalization_wrong():
bayrec, baymean = get_sightings(filename, 'Nazan bAy')
assert bayrec == 2, 'Number of records for Nazan Bay is wrong'
assert baymean == 17, 'Mean Tidal wave sightings for Nazan Bay is wrong'
# ---
data_path = '../data/'
results_path = '../results/'
data_name = 'sightings_tab_lg.csv'
table_name = 'spp_table.csv'
fig_name = 'spp_fig.png'
spp_names = ['Fox', 'Wolf', 'Wolverine']
# Generate reesutls
spp_recs = []
for spp in spp_names:
n_records, mu_sightings = ms.get_sightings(data_path + data_name, spp)
spp_recs.append(n_records)
print spp_names
print spp_recs
# Save table
table = pd.DataFrame({'species': spp_names, 'recs': spp_recs})
table.to_csv(results_path + table_name, index=False)
# Save figure
fig, ax = plt.subplots(1,1)
ax.bar([0,1,2], spp_recs)
ax.set_xticklabels(spp_names)
fig.savefig(results_path + fig_name)
fig_name = 'spp_fig.png'
# Set names of species to count
spp_names = ['Fox', 'Wolf', 'Grizzly', 'Wolverine']
# ------------------------------------------------------------------------
# Perform analysis
# ------------------------------------------------------------------------
# Declare empty list to hold counts of records
spp_recs = []
# Get total number of records for each species
for spp in spp_names:
totalrecs, meancount = get_sightings(data_dir + data_name, spp)
spp_recs.append(totalrecs)
print spp_names
print spp_recs
# ------------------------------------------------------------------------
# Save results as table
# ------------------------------------------------------------------------
# Put two lists into a pandas DataFrame
table = pd.DataFrame(np.array(zip(spp_names, spp_recs),
dtype=[('species', 'S12'), ('recs', int)]))
# Save DataFrame as csv
table.to_csv(results_dir + table_name, index=False)
def test_muskox_is_correct():
oxrec, oxmean = get_sightings(filename, 'Muskox')
assert oxrec == 2, 'Number of records for muskox is wrong'
assert oxmean == 25.5, 'Mean sightings for muskox is wrong'
def test_Muskox_is_correct():
muskrec, muskmean = get_sightings(filename, 'Muskox')
assert muskrec == 2, 'Number of records for Muskox is wrong'
assert muskmean == 25.5, 'Mean sightings for Muskox is wrong'
def test_lion_is_correct():
lionrec, lionmean = get_sightings(filename, 'Lion')
assert lionrec == 2, 'Number of records for Lion is wrong'
assert lionmean == 25.5, 'Mean sightings for Lion is wrong'
def test_not_present(): norec,nomean = get_sightings(file,'Not present') assert norec == 0, 'Biosignature not present, has zero recs.' assert nomean == 0, 'Mean is not present for missing Biosig.'
def test_cow_is_correct():
cowrec, cowmean = get_sightings(filename, 'Cow')
assert cowrec == 2, 'Number of records for Cow is wrong'
assert cowmean == 17, 'Mean sightings for Cow is wrong'
def test_water(): watrec,watmean = get_sightings(file,'Water') assert watrec == 2, 'Number of records for water is wrong.' assert watmean == 17, 'Mean for water is wrong'
def test_animal_case():
animrec, animmean = get_sightings(filename, 'oWL')
assert animrec == 2
assert animmean == 17
def test_Clay():
clayrec,claymean = get_sightings(file,'Clay')
assert clayrec == 2, 'Number of records for clay is wrong.'
assert claymean == 25.5, 'Mean for clay is wrong'
def test_muskox_is_correct(): muskoxrec, muskoxmean = get_sightings(filename, 'Muskox') # assert test_statement message_if_test_is_false assert muskoxrec == 2, 'Number of records for muskox is wrong' assert muskoxmean == 25.5#, 'Mean sightings for muskox is wrong'
def test_owl_is_correct():
owlrec, owlmean = get_sightings(filename, 'Owl')
assert owlrec == 2, 'Number of records for owl is wrong'
assert owlmean == 17, 'Mean sightings for owl is wrong'
def test_not_present():
notrec, notmean = get_sightings(filename,'Not present')
assert notrec==0, "Number of records for Not present is null"
assert notmean==0, 'Mean for Not present is null'
def test_muskox_is_correct():
oxrec, oxmean = get_sightings(filename, 'Muskox')
assert oxrec == 2, 'Number of records for muskox is wrong'
assert oxmean == 25.5, 'Mean sightings for muskox is wrong'
def test_pig_is_correct(): pigrec, pigmean = get_sightings(filename, 'Pig') #See mean_sightings for explaination of how this works assert pigrec == 1, 'Number of records for Pig is wrong' assert pigmean == 4, 'Mean sightings for pig is wrong'
def test_animal_not_present():
animrec, animmean = get_sightings(filename, 'NotPresent')
print animrec, animmean
assert animrec == 0, 'Animal missing should return zero records'
assert animmean == 0, 'Animal missing should return zero mean'
def test_not_presemt(): norec, nomean = get_sightings(filename, 'Not Present') assert norec==0, 'Biosignature not present has zero recs' assert nomean==0, 'Mean is not present for missing biosig'
def test_arg_capitalization_wrong():
owlrec, owlmean = get_sightings(filename, 'oWl')
assert owlrec == 2, 'Number of records for owl is wrong'
assert owlmean == 17, 'Mean sightings for owl is wrong'
def test_clay_is_correct():
clayrec, claymean = get_sightings(filename,'Clay')
assert clayrec==2, 'Number of records for clay is wrong'
assert claymean==25.5, 'Mean for clay is wrong'
fig_name = 'spp_fig.png'
# Set names of species to count
spp_names = ['Fox', 'Wolf', 'Grizzly', 'Wolverine']
# ---------------------------------------------------------------------------
# Perform analysis
# ---------------------------------------------------------------------------
# Declare empty list to hold counts of records
spp_recs = []
# Get total number of records for each species
for spp in spp_names:
totalrecs, meancount = get_sightings(data_dir + data_name, spp)
spp_recs.append(totalrecs)
print spp_names
print spp_recs
# ---------------------------------------------------------------------------
# Save results as table
# ---------------------------------------------------------------------------
# Put two lists into a recarray table
table = np.array(zip(spp_names, spp_recs),
dtype=[('species', 'S12'), ('recs', int)])
# Save recarray as csv
ml.rec2csv(table, results_dir + table_name)