Code: Select all
import numpy as np
from nohrio.ohrstring import *
from nohrio.wrappers import OhrData
from nohrio.dtypes import dt
def get_field_decoder(dtype, name):
"""
Depack a (possibly compound) field of a dtype, returning a (header, decoder) tuple
A header is a list of one or more field names.
A decoder takes a data field and returns a list (same length as header) of ints/floats/strings
"""
ty = dtype[name]
if len(ty):
# compound field
if ty.names[0] == 'length':
# it's a string. Assume vstr2, since that's the only one used in ITM
decoder = lambda x: ['"' + get_str16(x) + '"']
header = [name]
else:
# a tuple
decoder = lambda x: x
header = [name + ':' + n for n in ty.names]
elif len(ty.shape):
# array
assert len(ty.shape) == 1
decoder = list
header = [name + ' ' + str(i) for i in range(ty.shape[0])]
else:
# simple integer/float
decoder = lambda x: [x]
header = [name]
return header, decoder
def lump2csv(lump, fields):
headers2, decoders = [], []
for name in fields:
headers, decoder = get_field_decoder(lump.dtype, name)
headers2.extend(headers)
decoders.append(decoder)
ret = [','.join(headers2)]
for item in lump:
stuff = []
for i, name in enumerate(fields):
stuff.extend(decoders[i](item[name]))
ret.append(','.join(str(a) for a in stuff))
return '\n'.join(ret)
itm = np.memmap("viking.itm", dtype = dt['itm'], mode = 'r+')
# If you're interested in ALL data
#fields = dt['itm'].names
# Only interested in some...
fields = (
'name',
'info',
'value',
'attack',
'weaponattack',
'equippable',
# 'teach',
# 'oobuse',
'weaponpic',
'weaponpal',
'bonuses',
# 'equippableby',
# 'bitsets',
'consumability',
# 'own_tag',
# 'in_inventory_tag',
# 'equipped_tag',
# 'equippedby_active_tag',
# 'frame2handle',
# 'frame1handle',
# 'elemdmg'
)
print lump2csv(itm, fields)