def create_travel_model_input_file(self,
config,
year,
zone_set,
#dataset_pool,
delimiter = ',',
*args,**kwargs):
"""Writes to file specified by 'urbansim_to_tm_variable_file'
to [travel_model_data_directory]/[year_directory], which travel model
will use as input.
"""
tm_config = config['travel_model_configuration']
column_names = tm_config['tm_variable_order']
variable_list = []
for name in column_names:
variable_list.append(tm_config['urbansim_to_tm_variable_mapping'][name])
# compute our variables
dataset_pool = SessionConfiguration().get_dataset_pool()
zone_set.compute_variables(variable_list, dataset_pool=dataset_pool)
variable_short_name = [VariableName(x).get_alias() for x in variable_list]
# the short names are generated by the zone_set, e.g. ['autogenvar1', 'autogenvar5', 'autogenvar7' ... ]
# logger.log_status(variable_short_name)
# prepare the data for writing.
# not packing it into a numpy array because we lose the int/float information
data = {} # colnum -> data array
for i in range(len(variable_short_name)):
this_column = zone_set.get_attribute(variable_short_name[i])
data[i] = this_column
# make the travel model directory
tm_input_data_dir = os.path.join(tm_config['travel_model_base_directory'], tm_config[year]['year_dir'])
if not os.path.exists(tm_input_data_dir):
os.makedirs(tm_input_data_dir)
tm_file = tm_config['urbansim_to_tm_variable_file'] + '_' + tm_config[year]['year_dir'] + '.csv'
self._update_travel_model_data_file(tm_config, data, column_names,
os.path.join(tm_input_data_dir, tm_file), delimiter)
dbf.from_csv(csvfile = os.path.join(tm_input_data_dir, tm_file), to_disk = True, field_names = None)
#https://pythonhosted.org/dbf/
import dbf
some_table = dbf.from_csv(csvfile='./csv/example.csv', filename='./dbf/example',field_names='test1,test2,id'.split(","), to_disk=True)
#https://pythonhosted.org/dbf/
import dbf
some_table = dbf.from_csv(csvfile='./export/csv/property_tax.csv', filename='./export/dbf/property_tax',field_names='zoneId,zone,wardNo,streetId,street,asstNo,nameAddr,category,hlfYrlyTax,penalty,total,typeOfBldg'.split(","), to_disk=True)
# coding: utf-8
# In[ ]:
####generating DBF file
# In[2]:
###this creates a new DBF from a CSV file
import dbf
some_table = dbf.from_csv(csvfile='C:/Users/titog/Desktop/city lab/knox test/files/prueba python/ca10y10ons.csv', to_disk=True, field_names='x y time'.split())
#some_table = dbf.from_csv(csvfile='data.csv', filename='mytable',
#field_names='name age birth'.split())
# In[ ]:
###print DBF
# In[ ]:
###knox, this is working! We tried changing just the DBF file for a new one and it does not work.
### this is the error we get ValueError: total size of new array must be unchanged
import numpy as np
import pysal
from datetime import timedelta
# coding: utf-8
# In[ ]:
####generating DBF file
# In[2]:
###this creates a new DBF from a CSV file
import dbf
some_table = dbf.from_csv(
csvfile=
'C:/Users/titog/Desktop/city lab/knox test/files/prueba python/ca10y10ons.csv',
to_disk=True,
field_names='x y time'.split())
#some_table = dbf.from_csv(csvfile='data.csv', filename='mytable',
#field_names='name age birth'.split())
# In[ ]:
###print DBF
# In[ ]:
###knox, this is working! We tried changing just the DBF file for a new one and it does not work.
### this is the error we get ValueError: total size of new array must be unchanged
import numpy as np
import pysal
from datetime import timedelta
#pandasDF = pd.DataFrame(db[:]) #Convert to Pandas DF
pandasDF = pd.DataFrame(d) #Convert to Pandas DF
if upper == True: #Make columns uppercase if wanted
pandasDF.columns = map(str.upper, db.header)
db.close()
return pandasDF
if __name__ == "__main__":
'''
Load .dbf into DataFrame
'''
df = dbf2DF('test.dbf')
'''
Save DF into .CSV
'''
df.columns = ['UNO', 'DOS', 'TRES']
df.to_csv('test.csv',index=None, header=False)
'''
Load CSV
'''
columns = list(df.columns)
dbf_table = dbf.from_csv(csvfile='test.csv',filename='mytable',
field_names=columns, to_disk=True)
