Functions
def	syntax
Variables
list	non_numerical_cols
	showfilename = False
	Analyse options.
	multifilemode = False
	summode = False
	normalize_sums = False
	normalize_all = False
	offset_sums = False
	offset_all = False
	columnbreak = False
list	columns = []
list	files = []
list	sums = []
string	next_sum_type = ""
	column_name = arg
	sum_type = next_sum_type
list	final_data = []
list	lines = []
	now iterate through files and print columns etc.
tuple	file = gzip.open(filename,"r")
	gzipped
	donetitles = False
list	names = []
tuple	token = string.split(l)
	SCORE LINE.
	Error = False
	SCORE LINE HEADERS.
	brokenline = False
	if it does not then ignore this line - we assume it's corrupted
	is_nonnumtag = False
	Check columns for correctness.
tuple	t = float( token[i] )
	print n,i,token[i] if we're here, the tag is considered a numeric one and thus must pass the float conversion test
tuple	newdataline = dict()
	Ignore broken lines!
list	combined_data = []
	record the filename as "data"
int	sum = 0
	sumactive = False
list	new_combined_data_line = []
tuple	range_data = dict()
tuple	perc_high = dict()
tuple	perc_low = dict()
tuple	value = float(i)

Function Documentation

def sd::syntax ( )

Variable Documentation

sd::brokenline = False

if it does not then ignore this line - we assume it's corrupted

sd::column_name = arg

sd::columnbreak = False

list sd::columns = []

list sd::combined_data = []

record the filename as "data"

extract the data itself and append that array to the overall data stack

sd::donetitles = False

sd::Error = False

SCORE LINE HEADERS.

special column

look for names if names match remember index

Referenced by main(), and APDBCMover::read_in_insert_loop_info().

tuple sd::file = gzip.open(filename,"r")

gzipped

plain text

Referenced by add_rosetta_options_0(), MRMover::apply_makefrags(), ca_to_allatom_main(), main(), and basic::options::start_files().

list sd::files = []

Referenced by main(), and basic::options::start_file().

list sd::final_data = []

sd::is_nonnumtag = False

Check columns for correctness.

Allow only special columns to have non-numerical values ( see array at the top of this code file) Figure out if the tag is an official non-numeric one

tuple sd::lines = []

now iterate through files and print columns etc.

gzipped

. gzip/bzip support

sd::multifilemode = False

list sd::names = []

Referenced by basic::options::start_files().

list sd::new_combined_data_line = []

tuple sd::newdataline = dict()

Ignore broken lines!

Ok, if we're here, the line is clean and we can go ahead to extract the data

string sd::next_sum_type = ""

list sd::non_numerical_cols

Initial value:

00001 [
00002 "aln_id",
00003 "user_tag",
00004 "description",
00005 "usid",
00006 "husid",
00007 "__file__"
00008 ]

sd::normalize_all = False

sd::normalize_sums = False

sd::offset_all = False

sd::offset_sums = False

tuple sd::perc_high = dict()

tuple sd::perc_low = dict()

tuple sd::range_data = dict()

sd::showfilename = False

Analyse options.

int sd::sum = 0

sd::sum_type = next_sum_type

sd::sumactive = False

sd::summode = False

list sd::sums = []

tuple sd::t = float( token[i] )

print n,i,token[i] if we're here, the tag is considered a numeric one and thus must pass the float conversion test

tuple sd::token = string.split(l)

SCORE LINE.

tuple sd::value = float(i)

Functions

Variables

Function Documentation

Variable Documentation