vilterp

[Jun 27 15:34:27.967] Initializing community_wsgi.ini from community_wsgi.ini.sample
[Jun 27 15:34:27.972] Initializing tool_parameters_conf.xml from tool_parameters_conf.xml.sample
[Jun 27 15:34:27.975] Initializing external_service_types_conf.xml from external_service_types_conf.xml.sample
[Jun 27 15:34:28.104] Initializing reports_wsgi.ini from reports_wsgi.ini.sample
[Jun 27 15:34:28.107] Initializing shed_tool_conf.xml from shed_tool_conf.xml.sample
[Jun 27 15:34:28.111] Initializing tool_conf.xml from tool_conf.xml.sample
[Jun 27 15:34:28.242] Initializing tool_sheds_conf.xml from tool_sheds_conf.xml.sample
[Jun 27 15:34:28.246] Initializing openid_conf.xml from openid_conf.xml.sample
[Jun 27 15:34:28.382] Initializing tool-data/add_scores.loc from add_scores.loc.sample
[Jun 27 15:34:28.385] Initializing tool-data/alignseq.loc from alignseq.loc.sample

vilterp

import pandas as pd
import os
import re

def df_for_all_houses(year, month):
	"""month: number"""
	dir_name = 'A-{0}-{1:02d}'.format(year, month)
	dir_path = 'Home Group A/{0}'.format(dir_name)
	use_series = {}
	for entry in os.listdir(dir_path):

vilterp

from netCDF4 import Dataset
ds = Dataset('Wheat.NetCDF')
ds
hwam = ds.variables['HWAM']
hwam.dimensions
hwam.shape
data = hwam[:]
reshaped = data.reshape(150, 8)
reshaped
import pandas as pd

vilterp

def write_to_db(conn, file):
  df = pd.read_csv(file, parse_dates=[1])
  df2 = df.rename(columns={'dataid': 'house_id', 'use': 'total_energy'})
  df3 = df2.fillna(0)
  df3.utc = df3.utc.map(str)
  sql.write_frame(df3, con=conn, name='readings', if_exists='append', flavor='mysql')
  

vilterp

vilterp

// Java

class Point {
	int x;
	int y;

	public Point(int x, int y) {
		x
	}

vilterp

vilterp

def make_table(locations, variable):
	columns = {}
	for location in locations:
		path = "C:\Users\Diego.Diego-PC\Documents\RDCEP\Experiments\DSSAT Outputs\\" + location + '.dssat_output'
		table = pd.read_csv(path, skiprows=3, sep=' ', skipinitialspace=1)
		columns[location] = table[variable]
	return pd.DataFrame(data=columns)

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# primitives

def literal(lit):
  def parse(input):
      if len(input) > 0 and input[0] == lit:
          return input[1:]
      else:
          return False
  return parse

vilterp

Traceback (most recent call last):
  File "/nfs/software/galaxy-es/galaxy/lib/galaxy/jobs/runners/condor.py", line 108, in queue_job
    job_wrapper.prepare()
  File "/nfs/software/galaxy-es/galaxy/lib/galaxy/jobs/__init__.py", line 187, in prepare
    config_filenames = self.tool.build_config_files( param_dict, self.working_directory )
  File "/nfs/software/galaxy-es/galaxy/lib/galaxy/tools/__init__.py", line 2443, in build_config_files
    f.write( fill_template( template_text, context=param_dict ) )
  File "/nfs/software/galaxy-es/galaxy/lib/galaxy/util/template.py", line 9, in fill_template
    return str( Template( source=template_text, searchList=[context] ) )
  File "/nfs/software/galaxy-es/galaxy/eggs/Cheetah-2.2.2-py2.7-linux-x86_64-ucs4.egg/Cheetah/Template.py", line 1004, in __str__