""" Helper Functions
"""
from __future__ import division
import os
import errno
import shutil
import logging
from urlparse import urlparse
from copy import deepcopy
from log import CONSOLE_LOGGER_NAME
CONSOLE_LOGGER = logging.getLogger(CONSOLE_LOGGER_NAME)
def _mkdir_p(path):
""" Make directory recursively
"""
try:
os.makedirs(path)
except OSError as exc:
if exc.errno == errno.EEXIST and os.path.isdir(path):
pass
else:
raise
def _log_loop_progress(i, length, n_reports=10):
step = int(length/n_reports) if length > 10 else 1
log_steps = range(0, length, step)
if i in log_steps:
progress = i/length*100
CONSOLE_LOGGER.info('%.0f%% complete', progress)
[docs]def estimate_species_composition(n_aw, n_sb, n_sw, n_pl):
'''Calculates species composition based on their densities
:param float N_Aw, N_Sb, N_Sw, and N_Pl: densities of the respective species
'''
n_total = n_aw + n_sb + n_sw + n_pl
if n_total == 0:
sc_aw = 0
sc_sw = 0
sc_sb = 0
sc_pl = 0
else:
sc_aw = n_aw/n_total
sc_sw = n_sw/n_total
sc_sb = n_sb/n_total
sc_pl = n_pl/n_total
return sc_aw, sc_sw, sc_sb, sc_pl
def _append_file(source, dest):
with open(dest, 'wb') as dfd:
with open(source, 'rb') as sfd:
shutil.copyfileobj(sfd, dfd)
def _parse_s3_url(url):
s3_bucket, s3_prefix = None, None
if url.startswith('s3://'):
outdir_url = urlparse(url)
s3_bucket = outdir_url.netloc
s3_prefix = outdir_url.path.strip('/')
return {
'bucket': s3_bucket,
'prefix': s3_prefix,
}
def _copy_file_to_s3(bucket_conn, source, dest):
bucket_conn.upload_file(source, dest)
def _copy_file(source, dest, bucket_conn=None):
if bucket_conn is None:
shutil.copyfile(source, dest)
else:
_copy_file_to_s3(bucket_conn, source, dest)
def _generate_fplot_dict():
"""Generate 'fplot'
Given a known dominant species and its site index, and estimation of all
site indices, generates the 'fplot' dictionary
Return:
dict - ???
..note: topHeight - top height
tage - total age
bhage - breast height age
N - density
BA - current Basal Area
PS - Measured Percent Stocking
StumpDOB - stump diameter outside bark
StumpHeight - stump height
TopDib - top diameter inside bark
site_index - site index
PCT - species proportion in plot
"""
default_species_params = {
'topHeight': 0, 'tage': 0, 'bhage': 0,
'N': 0, 'BA': 0, 'PS': 16.9, 'StumpDOB':13,
'StumpHeight': 0.3, 'TopDib': 7, 'SI': 0, 'PCT': 0
}
species = ('Aw', 'Pl', 'Sw', 'Sb')
fplot_dict = {}
for s in species:
fplot_dict[s] = deepcopy(default_species_params)
return fplot_dict
def _get_gypsy_valid_species(dominant_species):
"""Given the plot dominant species, get the gypsy species
The dominant species in a plot may not be one of the species in the GYPSY
model. Douglas Fir for example is not in the GYPSY model, and it is
appropriate to substitute it with White Spruce.
:param str dominant_species: abbreviation of plot dominant species
"""
if dominant_species == 'Pb':
dominant_species = 'Aw'
elif dominant_species in ['Fd', 'Fb']:
dominant_species = 'Sw'
return dominant_species
def _reclassify_and_sort_species(species_abbrev_perc):
'''Classify all species in valid gypsy species and sort by percent
re-classification of species that are not considered in pygypsy as one of
the species considered in pygypsy (Aw, Sw, Sb, or Pl) and sort the species
to obtain the dominant species in the plot
:param list species_abbrev_perc: list of tuples where each element is a
species abbreviation followed by its percentage
'''
species_perc_dict = {'Aw':0, 'Pl':0, 'Sw':0, 'Sb':0}
for tup in species_abbrev_perc:
species_abbrev = tup[0]
species_perc = tup[1]
if species_abbrev in ['Aw', 'Pb']:
species_perc_dict['Aw'] = species_perc_dict['Aw'] + species_perc
elif species_abbrev in ['Sw', 'Fb', 'Fd']:
species_perc_dict['Sw'] = species_perc_dict['Sw'] + species_perc
elif species_abbrev == 'Pl':
species_perc_dict['Pl'] = species_perc_dict['Pl'] + species_perc
elif species_abbrev == 'Sb':
species_perc_dict['Sb'] = species_perc_dict['Sb'] + species_perc
sorted_species_perc_list = [(k, v) for v, k in sorted(
[(v, k) for k, v in species_perc_dict.items()]
)]
sorted_species_perc_list.reverse()
check_prop1 = sum(species_perc_dict.values())
if check_prop1 != 100:
raise ValueError(('Species proportions after grouping '
'into 4 species is not correct: %s') % check_prop1)
return sorted_species_perc_list, species_perc_dict
