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Lorem ipsum
So, this is solitary
Hazel
Dilapidated, dewy eyes
that bruise easily
Used to recognize dust in the
cracks
of new hardwood
Even the roach finds herself
turned off, bewildered
Mass-produced dead
smiles hum along to the dishwasher,
no
Still I find
crystalline necessities in
your canopies and filth, find
in your intimidation the slightest
form of
battery
Stain your glass with my toothpaste
Extra white
Sensitive
Cheer on with arches
Exchange 237 thumbprint recognitions for damage
that filles the holes it creates
How uniform and moody every
righteous melody must
be
Scaling octaves and Pop-Tarts in
foil-wrapped condominiums
How solitary every shower
that cries on command
New bruises and bedroom views
Mostly green
Sometimes blue
How complete the
vanishing
How nefarioius the absence
Bicycles, supposedly, are
inclined to stay
upright.


Trees
Indices
Help
Pylon
[
hide private
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frames
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]
Identifier Index
[
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
X
Y
Z
_
]
A
ac_pf
(in
pylon
)
add_constraint()
(in
OPFModel
)
add_vars()
(in
OPFModel
)
actual_pgen
(in
CaseReport
)
add_constraints()
(in
OPFModel
)
at
(in
pylon.io.parsing_util
)
actual_qgen
(in
CaseReport
)
add_var()
(in
OPFModel
)
B
Bdc
(in
Case
)
BRANCH_CHANGE
(in
pylon.dyn
)
BUS_ATTRS
(in
pylon.io.common
)
bids_to_pwl()
(in
Generator
)
branch_qinj
(in
CaseReport
)
BUS_CHANGE
(in
pylon.dyn
)
boolean
(in
pylon.io.parsing_util
)
BranchChange
(in
pylon.dyn
)
BusChange
(in
pylon.dyn
)
Branch
(in
pylon.case
)
bslash
(in
pylon.io.parsing_util
)
BX
(in
pylon.ac_pf
)
BRANCH_ATTR
(in
pylon.io.dot
)
Bus
(in
pylon.case
)
BRANCH_ATTRS
(in
pylon.io.common
)
BUS_ATTR
(in
pylon.io.dot
)
C
case
(in
pylon
)
comma
(in
pylon.io.parsing_util
)
Cost
(in
pylon.opf
)
Case
(in
pylon.case
)
comma_sep
(in
pylon.io.parsing_util
)
cost_N
(in
OPFModel
)
CASE_GUESS
(in
pylon.estimator
)
common
(in
pylon.io
)
create()
(in
DotWriter
)
CaseReport
(in
pylon.util
)
connected_buses
(in
Case
)
CSVWriter
(in
pylon.io.excel
)
CLASSICAL
(in
pylon.dyn
)
CONST_EXCITATION
(in
pylon.dyn
)
colon
(in
pylon.io.parsing_util
)
CONST_POWER
(in
pylon.dyn
)
D
d2AIbr_dV2()
(in
Case
)
DCPF
(in
pylon.dc_pf
)
dSbr_dV()
(in
Case
)
d2ASbr_dV2()
(in
Case
)
decimal_sep
(in
pylon.io.parsing_util
)
dSbus_dV()
(in
Case
)
d2Ibr_dV2()
(in
Case
)
detect_data_file()
(in
pylon.main
)
dyn
(in
pylon
)
d2Sbr_dV2()
(in
Case
)
dIbr_dV()
(in
Case
)
DynamicCase
(in
pylon.dyn
)
d2Sbus_dV2()
(in
Case
)
DISPATCHABLE_LOAD
(in
pylon.generator
)
DynamicGenerator
(in
pylon.dyn
)
dAbr_dV()
(in
Case
)
dot
(in
pylon.io
)
DynamicSolver
(in
pylon.dyn
)
dc_pf
(in
pylon
)
dot
(in
pylon.io.parsing_util
)
DCOPFSolver
(in
pylon.solver
)
DotWriter
(in
pylon.io.dot
)
E
EPS
(in
pips
)
Event
(in
pylon.dyn
)
exciter()
(in
DynamicCase
)
EPS
(in
pylon.dyn
)
excel
(in
pylon.io
)
exciterInit()
(in
DynamicCase
)
equals
(in
pylon.io.parsing_util
)
ExcelWriter
(in
pylon.io.excel
)
estimator
(in
pylon
)
Exciter
(in
pylon.dyn
)
F
fair_max()
(in
pylon.ud_opf
)
fixed_p_demand
(in
CaseReport
)
format_from_extension()
(in
pylon.util
)
FastDecoupledPF
(in
pylon.ac_pf
)
fixed_q_demand
(in
CaseReport
)
FOURTH_ORDER
(in
pylon.dyn
)
feq()
(in
pylon.util
)
FLAT_START
(in
pylon.estimator
)
FROM_INPUT
(in
pylon.estimator
)
G
GENERAL_IEEE
(in
pylon.dyn
)
get_bids()
(in
Generator
)
getSbus()
(in
Case
)
generator
(in
pylon
)
get_cost_params()
(in
OPFModel
)
getV0()
(in
StateEstimator
)
GENERATOR
(in
pylon.generator
)
get_lin_constraint()
(in
OPFModel
)
getYbus()
(in
Case
)
Generator
(in
pylon.generator
)
get_nln_constraint()
(in
OPFModel
)
Governor
(in
pylon.dyn
)
generator()
(in
DynamicCase
)
get_offers()
(in
Generator
)
governor()
(in
DynamicCase
)
GENERATOR_ATTR
(in
pylon.io.dot
)
get_var()
(in
OPFModel
)
governorInit()
(in
DynamicCase
)
GENERATOR_ATTRS
(in
pylon.io.common
)
get_var_N()
(in
OPFModel
)
generatorInit()
(in
DynamicCase
)
getAugYbus()
(in
DynamicCase
)
I
IEEE_DC1A
(in
pylon.dyn
)
init()
(in
PSSEReader
)
ipopf
(in
pylon
)
IFLOW
(in
pylon.solver
)
integer
(in
pylon.io.parsing_util
)
IPOPFSolver
(in
pylon.ipopf
)
index_branches()
(in
Case
)
interties
(in
CaseReport
)
is_load
(in
Generator
)
index_buses()
(in
Case
)
io
(in
pylon
)
ISOLATED
(in
pylon.case
)
K
known_extensions
(in
pylon.util
)
L
lbrace
(in
pylon.io.parsing_util
)
load_psat()
(in
Case
)
logger
(in
pylon.io.pickle
)
lbrack
(in
pylon.io.parsing_util
)
load_psse()
(in
Case
)
logger
(in
pylon.io.psat
)
lin_N
(in
OPFModel
)
logger
(in
pylon.ac_pf
)
logger
(in
pylon.io.psse
)
lin_NS
(in
OPFModel
)
logger
(in
pylon.case
)
logger
(in
pylon.io.rdf
)
LINE
(in
pylon.case
)
logger
(in
pylon.dc_pf
)
logger
(in
pylon.main
)
linear_constraints()
(in
OPFModel
)
logger
(in
pylon.dyn
)
logger
(in
pylon.opf
)
LinearConstraint
(in
pylon.opf
)
logger
(in
pylon.estimator
)
logger
(in
pylon.solver
)
load()
(in
_Serializable
)
logger
(in
pylon.generator
)
logger
(in
pylon.ud_opf
)
load_from_file_object()
(in
_Serializable
)
logger
(in
pylon.io.common
)
losses
(in
CaseReport
)
load_matpower()
(in
Case
)
logger
(in
pylon.io.dot
)
lparen
(in
pylon.io.parsing_util
)
load_pickle()
(in
_Serializable
)
logger
(in
pylon.io.matpower
)
M
machineCurrents()
(in
DynamicCase
)
MATPOWERWriter
(in
pylon.io.matpower
)
min_p_lambda
(in
CaseReport
)
main
(in
pylon
)
max_p_lmbda
(in
CaseReport
)
min_q_lmbda
(in
CaseReport
)
main()
(in
pylon.main
)
max_p_losses
(in
CaseReport
)
min_v_angle
(in
CaseReport
)
make_unique_name()
(in
pylon.io.parsing_util
)
max_q_lmbda
(in
CaseReport
)
min_v_magnitude
(in
CaseReport
)
makeB()
(in
Case
)
max_q_losses
(in
CaseReport
)
minus
(in
pylon.io.parsing_util
)
makeBdc()
(in
Case
)
max_v_angle
(in
CaseReport
)
ModifiedEuler
(in
pylon.dyn
)
matlab_comment
(in
pylon.io.parsing_util
)
max_v_magnitude
(in
CaseReport
)
ModifiedEuler2
(in
pylon.dyn
)
matpower
(in
pylon.io
)
Measurement
(in
pylon.estimator
)
MATPOWERReader
(in
pylon.io.matpower
)
mfeq2()
(in
pylon.util
)
N
n_areas
(in
CaseReport
)
n_interties
(in
CaseReport
)
name
(in
_Named
)
n_branches
(in
CaseReport
)
n_loads
(in
CaseReport
)
negative_integer
(in
pylon.io.parsing_util
)
n_buses
(in
CaseReport
)
n_online_generators
(in
CaseReport
)
negative_real
(in
pylon.io.parsing_util
)
n_connected_buses
(in
CaseReport
)
n_online_vloads
(in
CaseReport
)
NewtonPF
(in
pylon.ac_pf
)
n_fixed_loads
(in
CaseReport
)
n_shunts
(in
CaseReport
)
nln_N
(in
OPFModel
)
n_generators
(in
CaseReport
)
n_transformers
(in
CaseReport
)
NonLinearConstraint
(in
pylon.opf
)
O
offers_to_pwl()
(in
Generator
)
online_pgen_capacity
(in
CaseReport
)
OPF
(in
pylon.opf
)
online_branches
(in
Case
)
online_qgen_capacity
(in
CaseReport
)
OPFModel
(in
pylon.opf
)
online_generators
(in
Case
)
online_vloads
(in
CaseReport
)
output_solution()
(in
StateEstimator
)
online_generators
(in
CaseReport
)
opf
(in
pylon
)
P
p_demand
(in
CaseReport
)
poly_to_pwl()
(in
Generator
)
PSSEWriter
(in
pylon.io.psse
)
parsing_util
(in
pylon.io
)
POLYNOMIAL
(in
pylon.generator
)
PT
(in
pylon.estimator
)
PF
(in
pylon.estimator
)
positive_integer
(in
pylon.io.parsing_util
)
push_bus()
(in
PSATReader
)
pf_solution()
(in
Case
)
positive_real
(in
pylon.io.parsing_util
)
push_demand()
(in
PSATReader
)
PFLOW
(in
pylon.solver
)
postParse()
(in
ToBoolean
)
push_line()
(in
PSATReader
)
PG
(in
pylon.estimator
)
postParse()
(in
ToFloat
)
push_pq()
(in
PSATReader
)
pickle
(in
pylon.io
)
postParse()
(in
ToInteger
)
push_pv()
(in
PSATReader
)
pickle_matpower_cases()
(in
pylon.util
)
PQ
(in
pylon.case
)
push_slack()
(in
PSATReader
)
PickleReader
(in
pylon.io.pickle
)
psat
(in
pylon.io
)
push_supply()
(in
PSATReader
)
PickleWriter
(in
pylon.io.pickle
)
PSATReader
(in
pylon.io.psat
)
PV
(in
pylon.case
)
pips
psse
(in
pylon.io
)
PW_LINEAR
(in
pylon.generator
)
pips()
(in
pips
)
psse_comment
(in
pylon.io.parsing_util
)
pwl_to_poly()
(in
Generator
)
PIPSSolver
(in
pylon.solver
)
PSSEReader
(in
pylon.io.psse
)
pylon
Q
q_demand
(in
CaseReport
)
QF
(in
pylon.estimator
)
QT
(in
pylon.estimator
)
q_limited
(in
Generator
)
QG
(in
pylon.estimator
)
q_string
(in
pylon.io.parsing_util
)
qps_pips()
(in
pips
)
R
rbrace
(in
pylon.io.parsing_util
)
read()
(in
PSSEReader
)
ReSTWriter
(in
pylon.io.rst
)
rbrack
(in
pylon.io.parsing_util
)
read()
(in
RDFReader
)
rparen
(in
pylon.io.parsing_util
)
rdf
(in
pylon.io
)
read_case()
(in
pylon.main
)
rst
(in
pylon.io
)
RDFReader
(in
pylon.io.rdf
)
real
(in
pylon.io.parsing_util
)
run()
(in
StateEstimator
)
RDFWriter
(in
pylon.io.rdf
)
REFERENCE
(in
pylon.case
)
RungeKutta
(in
pylon.dyn
)
read()
(in
_CaseReader
)
reset()
(in
Branch
)
RungeKuttaFehlberg
(in
pylon.dyn
)
read()
(in
MATPOWERReader
)
reset()
(in
Bus
)
RungeKuttaHighamHall
(in
pylon.dyn
)
read()
(in
PickleReader
)
reset()
(in
Case
)
read()
(in
PSATReader
)
reset()
(in
Generator
)
S
s_demand()
(in
Case
)
scolon
(in
pylon.io.parsing_util
)
solve()
(in
RungeKuttaFehlberg
)
s_supply()
(in
Case
)
semi
(in
pylon.io.parsing_util
)
solve()
(in
RungeKuttaHighamHall
)
s_surplus()
(in
Case
)
SFLOW
(in
pylon.solver
)
solve()
(in
OPF
)
save()
(in
_Serializable
)
shunt_pinj
(in
CaseReport
)
solve()
(in
DCOPFSolver
)
save_csv()
(in
Case
)
shunt_qinj
(in
CaseReport
)
solve()
(in
PIPSSolver
)
save_dot()
(in
Case
)
sign
(in
pylon.io.parsing_util
)
solve()
(in
_Solver
)
save_excel()
(in
Case
)
SlackBusError
(in
pylon.ac_pf
)
solve()
(in
UDOPF
)
save_matpower()
(in
Case
)
slash
(in
pylon.io.parsing_util
)
solveNetwork()
(in
DynamicCase
)
save_pickle()
(in
_Serializable
)
solve()
(in
_ACPF
)
solver
(in
pylon
)
save_psat()
(in
Case
)
solve()
(in
DCPF
)
sort_buses()
(in
PSATReader
)
save_psse()
(in
Case
)
solve()
(in
DynamicSolver
)
sort_generators()
(in
Case
)
save_rst()
(in
Case
)
solve()
(in
ModifiedEuler
)
special_chars
(in
pylon.io.parsing_util
)
save_to_file_object()
(in
_Serializable
)
solve()
(in
ModifiedEuler2
)
star
(in
pylon.io.parsing_util
)
Sbus
(in
Case
)
solve()
(in
RungeKutta
)
StateEstimator
(in
pylon.estimator
)
T
ToBoolean
(in
pylon.io.parsing_util
)
total_cost()
(in
Generator
)
total_tie_pflow
(in
CaseReport
)
ToFloat
(in
pylon.io.parsing_util
)
total_pgen_capacity
(in
CaseReport
)
total_tie_qflow
(in
CaseReport
)
ToInteger
(in
pylon.io.parsing_util
)
total_qgen_capacity
(in
CaseReport
)
TRANSFORMER
(in
pylon.case
)
U
ud_opf
(in
pylon
)
UDOPF
(in
pylon.ud_opf
)
util
(in
pylon
)
V
VA
(in
pylon.estimator
)
Variable
(in
pylon.opf
)
vload_q_demand
(in
CaseReport
)
var_N
(in
OPFModel
)
vload_p_demand
(in
CaseReport
)
VM
(in
pylon.estimator
)
W
write()
(in
_CaseWriter
)
write_bus_data()
(in
_CaseWriter
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write_generator_cost_data()
(in
_CaseWriter
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write()
(in
DotWriter
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write_bus_data()
(in
DotWriter
)
write_generator_cost_data()
(in
MATPOWERWriter
)
write()
(in
CSVWriter
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write_bus_data()
(in
CSVWriter
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write_generator_data()
(in
_CaseWriter
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write()
(in
ExcelWriter
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write_bus_data()
(in
ExcelWriter
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write_generator_data()
(in
DotWriter
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write()
(in
MATPOWERWriter
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write_bus_data()
(in
MATPOWERWriter
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write_generator_data()
(in
CSVWriter
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write()
(in
PickleWriter
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(in
PSSEWriter
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write_generator_data()
(in
ExcelWriter
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write_area_data()
(in
MATPOWERWriter
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write_bus_data()
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ReSTWriter
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write_generator_data()
(in
MATPOWERWriter
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_CaseWriter
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_CaseWriter
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PSSEWriter
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DotWriter
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(in
DotWriter
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ReSTWriter
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CSVWriter
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CSVWriter
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(in
ReSTWriter
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(in
ExcelWriter
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(in
ExcelWriter
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(in
ReSTWriter
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(in
MATPOWERWriter
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(in
MATPOWERWriter
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(in
ReSTWriter
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(in
PSSEWriter
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write_case_data()
(in
PSSEWriter
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(in
ReSTWriter
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write_case_data()
(in
ReSTWriter
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X
XB
(in
pylon.ac_pf
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Y
Y
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Case
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_
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FastDecoupledPF
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OPF
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_name
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_Named
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_ACPF
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OPF
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_Named
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__init__()
(in
Branch
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_costfcn()
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PIPSSolver
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_Named
(in
pylon.util
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__init__()
(in
Bus
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_d2f()
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PIPSSolver
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_nln_constraints()
(in
OPF
)
__init__()
(in
Case
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_df()
(in
PIPSSolver
)
_offbids_to_points()
(in
Generator
)
__init__()
(in
DCPF
)
_dg()
(in
IPOPFSolver
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_one_iteration()
(in
NewtonPF
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__init__()
(in
BranchChange
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_dgh()
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PIPSSolver
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_p_iteration()
(in
FastDecoupledPF
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__init__()
(in
BusChange
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(in
_Solver
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MATPOWERReader
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DynamicCase
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NewtonPF
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MATPOWERReader
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DynamicGenerator
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FastDecoupledPF
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MATPOWERReader
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DynamicSolver
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PIPSSolver
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PSSEReader
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__init__()
(in
Event
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IPOPFSolver
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MATPOWERReader
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(in
Exciter
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(in
_Named
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MATPOWERReader
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(in
Governor
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(in
PSATReader
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(in
MATPOWERReader
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__init__()
(in
ModifiedEuler2
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PSATReader
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RDFReader
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RungeKutta
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PSATReader
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OPF
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RungeKuttaFehlberg
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PSATReader
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(in
OPF
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__init__()
(in
RungeKuttaHighamHall
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(in
PSATReader
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(in
DCOPFSolver
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__init__()
(in
Measurement
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(in
_Named
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(in
OPF
)
__init__()
(in
StateEstimator
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(in
OPF
)
_q_iteration()
(in
FastDecoupledPF
)
__init__()
(in
Generator
)
_get_pq_array_construct()
(in
PSATReader
)
_quadratic_costs()
(in
DCOPFSolver
)
__init__()
(in
_CaseWriter
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_get_pv_array_construct()
(in
PSATReader
)
_ref_bus_angle_constraint()
(in
PIPSSolver
)
__init__()
(in
DotWriter
)
_get_qgen_var()
(in
OPF
)
_ref_check()
(in
OPF
)
__init__()
(in
CSVWriter
)
_get_qtyprc()
(in
Generator
)
_remove_isolated()
(in
OPF
)
__init__()
(in
MATPOWERReader
)
_get_reference_index()
(in
DCPF
)
_run_opf()
(in
DCOPFSolver
)
__init__()
(in
MATPOWERWriter
)
_get_slack_array_construct()
(in
PSATReader
)
_run_power_flow()
(in
FastDecoupledPF
)
__init__()
(in
PSSEReader
)
_get_supply_array_construct()
(in
PSATReader
)
_run_power_flow()
(in
NewtonPF
)
__init__()
(in
RDFWriter
)
_get_v_angle()
(in
DCPF
)
_run_power_flow()
(in
_ACPF
)
__init__()
(in
Cost
)
_get_v_angle_guess()
(in
DCPF
)
_Serializable
(in
pylon.util
)
__init__()
(in
LinearConstraint
)
_get_voltage_angle_var()
(in
OPF
)
_Set
(in
pylon.opf
)
__init__()
(in
OPF
)
_get_voltage_magnitude_var()
(in
OPF
)
_set_name()
(in
_Named
)
__init__()
(in
OPFModel
)
_get_writer()
(in
CSVWriter
)
_solve()
(in
IPOPFSolver
)
__init__()
(in
Variable
)
_gh()
(in
PIPSSolver
)
_solve()
(in
PIPSSolver
)
__init__()
(in
_Set
)
_h()
(in
IPOPFSolver
)
_Solver
(in
pylon.solver
)
__init__()
(in
DCOPFSolver
)
_hessfcn()
(in
PIPSSolver
)
_transform_coefficients()
(in
DCOPFSolver
)
__init__()
(in
PIPSSolver
)
_index_buses()
(in
_ACPF
)
_unpack_case()
(in
_ACPF
)
__init__()
(in
_Solver
)
_initial_interior_point()
(in
_Solver
)
_unpack_model()
(in
_Solver
)
__init__()
(in
UDOPF
)
_initial_voltage()
(in
_ACPF
)
_update_case()
(in
DCOPFSolver
)
__init__()
(in
CaseReport
)
_k1()
(in
RungeKutta
)
_update_case()
(in
PIPSSolver
)
_ACPF
(in
pylon.ac_pf
)
_k2()
(in
RungeKutta
)
_update_model()
(in
DCPF
)
_adjust_limits()
(in
Generator
)
_k3()
(in
RungeKutta
)
_update_solution_data()
(in
DCOPFSolver
)
_branch_flow_dc()
(in
OPF
)
_k4()
(in
RungeKutta
)
_update_solution_data()
(in
PIPSSolver
)
_build_jacobian()
(in
NewtonPF
)
_k4()
(in
RungeKuttaFehlberg
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_var_bounds()
(in
_Solver
)
_CaseReader
(in
pylon.io.common
)
_k5()
(in
RungeKuttaFehlberg
)
_voltage_angle_diff_limit()
(in
OPF
)
_CaseWriter
(in
pylon.io.common
)
_k6()
(in
RungeKuttaFehlberg
)
_write_data()
(in
_CaseWriter
)
_check_convergence()
(in
FastDecoupledPF
)
_k6()
(in
RungeKuttaHighamHall
)
_write_data()
(in
DotWriter
)
_check_convergence()
(in
NewtonPF
)
_k7()
(in
RungeKuttaHighamHall
)
_write_data()
(in
PSSEWriter
)
_combine_costs()
(in
DCOPFSolver
)
_linear_constraints()
(in
_Solver
)
_write_data()
(in
RDFWriter
)
_consfcn()
(in
PIPSSolver
)
_loss()
(in
CaseReport
)
_write_data()
(in
ReSTWriter
)
Trees
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Help
Pylon
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This is a jumbotron example, that is used in many of the designs you would like to use for your portfolio pages.
Learn moreThis is a nice text about me
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--- layout: post title: SQLite3 Bindings for Ruby post_id: 317 categories: - projects date: 2004-12-19 14:51:00.000000000 -07:00 author: Jamis permalink: 2004/12/19/sqlite3-bindings-for-ruby.html ---
One of my more popular contributions to the Ruby community has been the bindings I wrote for the embeddable SQLite database engine. These bindings were developed for use with SQLite 2.8.x, which is unfortunate now that SQLite3 is out and gaining wider usage. One of the most common questions I get regarding my SQLite bindings is “will you create bindings for SQLite3?”
I’ve got them. Sitting right here on my hard disk. Largely untested, but my ad-hoc, shoot-blindly-into-the-testing-space tests have been quite promising. Even better, these SQLite3 bindings do not require any compilation. They use the Ruby/DL library that comes standard with Ruby 1.8.x, and call directly into the SQLite3 binary, from Ruby.
This was done largely in an attempt to learn Ruby/DL, but the bindings are working so well (so far) that I think I may actually release them. After some cleaning up and unit testing, of course.
The interface for this SQLite3 module is very similar to my bindings for the older SQLite engine, but it is not identical. Changes in this new version include (and be forewarned—the list of changes may grow):
And many more less-visible changes.
My favorite change, though, is that Database#prepare takes a block. Consider this for rapidly populating a database:
require 'sqlite3' include SQLite3 File.delete "test.db" rescue nil db = Database.open( "test.db" ) db.execute_batch <<-SQL create table foo ( id integer primary key, name varchar(30) not null, object blob, description text ) SQL values = [ [ "foo", Blob.new( Marshal.dump :foo => "bar", :baz => "bump" ), "A sample row for the database" ], [ "bar", Blob.new( Marshal.dump :ping => "pong" ), "Another row, with a smaller hash" ], [ "baz", Blob.new( Marshal.dump :sword => "play", :day => "time" ), "And another row, purely for demonstration purposes" ] ] db.prepare( "insert into foo " + "( name, object, description ) " + "values ( ?, ?, ? )" ) do |stmt| values.each { |parms| stmt.execute *parms } end p db.execute( "select * from foo" ) db.close
Anyway, just wanted to let the world know that the SQLite3 bindings are being worked on, and should be available by the beginning of January if I can keep finding time to work on them. I’m liking this newer interface enough that I may even go back and bump the older bindings up a notch version-wise and try to use this same interface…


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Hi !!!You're Welcome !!
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The value of simplicity
The most complex requirement in software development is simplicity. In this post I will describe a technique for measuring the simplicity of a UI design. This can be used to choose the simplest design from a selection.
I recently ran a training exercise in problem solving with an audience of 50 top developers at a large corporation. Technology companies need to innovate in order to stay ahead of the competition but innovation requires problem solving. But before we can solve problems we need to find them. For example, I never knew that I absolutely had to have a fingerprint reader on my phone until my wife got one. Whoever discovered that we all need a fingerprint reader was a genius.
The true genious of this invention is that it is so simple; even a toddler can learn to unlock a phone if the parents are crazy enough to register his fingerprints on it. Simplification (represented by the meme “Less if More”) is part of solution refinement, the often skipped last step in problem solving.
The meaning of simplicity
Simplicity has different manifestations in different domains. In mathematics it is often referred to as elegance. An elegant solution is clear, concise, and surprising. My favorite example is Cantor’s demonstration that the real numbers are uncoutably infinite. Here he explains it to David Hilbert:
If Cantor’s proof had been clunky, the result would have been just as beneficial to mathematicians. A clunky proof woudn’t really matter as long as it was still correct.
Simplicity in software matters. Your product (whether it’s an app or a service) is not an end in itself but a means to an end. In the UI complexity impedes the end user from doing his task. In code complexity impedes maintainability. In software design complexity impedes flexibility. A clunky UI, a clunky design and a clunky implementation do matter.
Simplicity in software design which closely resembles elegance in mathematics, is the subject of a future blog post. Here we will stick with the user experience and in particular simplicity in the UI.
A model for the interaction of a human with the UI
A milestone in the field of usability in computer systems was the publication of “The Psychology of Human-Computer Interaction” by Card, Moran, and Newell (1983). The authors proposed a model of the “Human processor” citing ten scientific principles of operation, like Fitts’s law and the Power Law of Practice based on empirical data.
Models are useful for analysis. The suitability of a model can be judged by its predictive accuracy. Our model of human-computer interaction will be simpler than the image above which comes from the book, but it will use some of the same ideas.
Suppose automated analysis could be added to a UI design tool such as Balamiq Mockups to help assess the usability of a UI for performing a specific task at the design stage. Given a task, the UI designer would click, type and drag to complete the actions needed to complete the task using the mock, imitating the future user. These would be recorded and analyzed.
A UI can be designed to accomplish multiple tasks. For example, the same UI may be used to create an account or change a password: two distinct tasks. In that case both tasks would be considered in the analysis of the UI. These would not be given equal weight however. The weight of a task to a given persona will be proportional to its frequency. For example the number of times that task needs to be accomplished in a typical year, month or week.
Being able to accomplish a task is not enough. That’s basic suitability testing. Each interaction with and transition between UI components has a cost. Clicking on an item that is a big target costs less than if it were small. The distance the pointer has to move has a cost. Picking an item in a cluttered menu has a higher cost than clean ones. The sum of the costs is “inefficiency”. Our goal will be to minimize inefficiency over the task.
Simplicity can be measured by the amount of “ink” or “clutter” in the UI. Less is more! In a good UI the quotient of task value, divided by simplicity and efficiency is the metric by which I will judge the UI.
The sequence is not necessarily unique. Sometimes the sequence is constrained, as when a button is disabled until certain fields are filled in properly. These variation can be measured as well.
This has gotten long enough. In a future blog post I will discuss:
- the model of human behavior while interacting with a UI
- measuring the cost of learning a UI by repeated performance of the same tasks
- metric limitations, given different users have different experience levels
- use of deep learning to refine the model
References
[1] Card, Stuart K.; Moran, Thomas P.; Newell, Allen (1983). The Psychology of Human–Computer Interaction. Hillsdale, NJ: L. Erlbaum Associates. ISBN<PHONE_NUMBER>.


{% extends "u2f/base.html" %} {% load i18n %} {% block content %} {{ block.super }}
{% trans 'Scan this in your authenticator app:' %}
{{ qr_svg|safe }}{% trans "Or, if you can't scan a QR Code, enter this key as a time-based account:" %} {{ base32_key }}
{% trans 'Then, enter the token it gives you.' %}
{% endblock %}


Bob Downs
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Your classroom should be a reflection of your personal
learning style. So we made classrooms customizable.
Fig rooms provide students with a modularized real-time
collaborative learning environment. Fig allows students to
build a virtual ‘classroom’ where they can use built-in
learning modules to work and study together on a variety of
subjects.
Since real-time collaboration is integral to our platform,
we leveraged Google Firestore’s listeners and callbacks to
instantly sync application data across users. Data was
modeled shallowly for read efficiency and scalability. Our
stack included Express and the Twilio API for video chat
capabilities.
On the front-end, we used React for its
modularity and reusability. In developing the canvas module,
we ran into the challenge of optimizing rendering and
decided to batch the HTML Canvas micro-strokes (pixel to
pixel) as larger macro-strokes objects to elevate the strain
on database reads, which improved performance.
Another
consideration during development was protecting code editors
against malicious or non-terminating code. We set up
execution time-outs and sanitized code before evaluation.
Material UI and React Drag and Drop libraries were used to
help provide a clean aesthetic and great fig user
experience.
Technology Stack:
Google Firebase Firestore
React
Express
Semantic UI / Material UI
EYEZ
A staring contest where you can play anyone in the world.
EYEZ was built using React Native in conjuction with the
Expo XDE. EYEZ is a project built over the course of a 4 day Stackathon. It's purpose is to break the physical barrier of a staring contest and allow users to play anyone in the world.
I achieved this through use of the True Depth sensor on the iPhone X series. Expo helped provided access and helped me leverage these native device features with ease. The True Depth
sensor provides 50 blendshape coeffecients which map the
expression of the human face. I used these coeffecients
to tell whether a person was blinking or smiling.
Socket.io
was used to enable users to compete realtime. When a combination of blendshapes indicates that a user is smiling or blinking (fulfilling the lost condition) an event is emitted to the players in the room to update them of the change in game status. Users also have the ability to send one-time powerups in the form of comedic short clips to try and distract their opponent and make them laugh to tip the game in their favor.
Technologies Used:
React Native
Socket.io
iPhone X True Depth Sensor
Vroom
Your one-stop shop for all things luxury cars.
Vroom is an ecommerce site built on the NERD stack. Vroom
offers customers a beautifully designed shopping experience,
as well as fully fledged backend administrator capabilities
for fulfilling orders.
We created a single page appliation to provide users with a seamless and fast shopping experience. React was used on the front-end in and a Redux store was implemented to facilitate easier access to centralized data to all of the React components.
Local storage was used so that a user's cart would persist even with page refreshes. Usage of local storage also allows for guest users to maintain a cart without logging in.
Backend admin functionality was added to facilitate order fulfillment.
Technologies Used:
Node.js / Express.js
React / Redux
PostgreSQL
Chad App
Connecting users through location based chatrooms, both
private and public.
Chad is an iOS app currently available in the Apple App
Store that was built using React Native.
Chad uses Google Firebase in the backend to store and serve data at lightning speeds. Speed is imperative to the Chad platform to provide users
with a quick and responsive messaging experience. Much time was spent crafting a backend architecture that would scale well as the user base grows.
Building the application with React Native allowed myself and the engineering team to create an application that would work on both iOS and Android from one codebase. React Native also made it easy to leverage my experience with React to create reusable components that could be used multiple times throughout the application.
I implemented Redux to provide a central data store for information in the applicaiton. This provided several benefits included reducing the number of API calls made to Firebase as well as reducing application loading times.
Technologies Used:
React Native
Google Cloud Firestore
React / Redux
Flashcard Academy
Learn coding on the go, along an optimal timeline. Built
entirely in React Native.
Flashcard Academy is a spaced repetition flashcard
application where students are quizzed on material along a
timeline which optimizes information retention.
Students engage with the app in two main environments:
Information Playground and Quizzable Land (cheesy I
know...). In the Information Playground users have the
ability to choose flashcards by Topic, Difficulty, or
Random. Flashcards contain bitsize facts about various
software development concepts. They are designed to be
short, and digestable, something that you can retain during
your commute.
When a student feels confident that they've understood any
given card's content they can swipe up to have related
questions to that card set as quizzable. If they feel that a
card is irrelevant to their studies and they'd choose not to
see it again they can swipe down to discard it.
In Quizzable Land students can select quiz cards along
Topic, Difficulty, Random, or Timeline to be quizzed on.
Quiz cards contain a question and four multiple choice
answers. Answering these questions correctly / incorrectly
updates a spaced repetition algorithm that determines how
comfortable a student is with any concept and adjusts the
frequency in which that student is presented with that
material.


in shortest-paths algorithms,
641 pr.
data-movement instructions,
22
direct-address tables,
222–223
exponential search trees,
182,
433
order-statistic trees,
302–308
weight-balanced trees,
301
decision by an algorithm,
976
and optimization problems,
969
degree
of a binomial-tree root,
457
minimum, of a B-tree,
439
deletion
from binary search trees,
262–263
from chained hash tables,
226
from direct-address tables,
222
from Fibonacci heaps,
492,
496 pr.
from open-address hash tables,
238
from order-statistic trees,
307
from sweep-line statuses,
942
from 2-3-4 heaps,
473 pr.
density of prime numbers,
887–888
dependence
and indicator random variables,
96
depth
average, of a node in a randomly built binary search tree,
270 pr.
of a comparison network,
707
of a node in a rooted tree,
1088
of quicksort recursion tree,
153 ex.
of a sorting network,
708 ex.
depth-determination problem,
519 pr.
in finding articulation points, bridges, and biconnected components,
558 pr.
in finding strongly connected components,
552–557
in topological sorting,
549–552
and matrix multiplication,
759 ex.
DFT (Discrete Fourier Transform),
833
differentiation of series,
1060
for all-pairs shortest paths,
620,
639
implemented with a Fibonacci heap,
599
implemented with a min-heap,
599
with integer edge weights,
600–601 ex.
in Johnson's algorithm,
639
similarity to breadth-first search,
599,
600 ex.
similarity to Prim's algorithm,
570,
599
directed acyclic graph (dag),
1083
and component graphs,
554
and hamiltonian-path problem,
983 ex.
single-source shortest-paths algorithm for,
592–595
all-pairs shortest paths in,
620–642
hamiltonian cycle of,
967
single-source shortest paths in,
580–619
singly connected,
549 ex.
transitive closure of,
632
directed version of an undirected graph,
1082
discharge of an overflowing vertex,
683
discovery time, in depth-first search,
541
Discrete Fourier Transform,
833
discrete logarithm theorem,
877
discrete probability distribution,
1101
disjoint-set data structure,
498–522
in depth determination,
519 pr.
disjoint-set-forest implementation of,
505–509
in Kruskal's algorithm,
569
linear-time special case of,
522
linked-list implementation of,
501–505
in off-line least common ancestors,
521 pr.
in off-line minimum,
518 pr.
in task scheduling,
404 pr.
distributive laws for sets,
1072
divide-and-conquer method,
28–33
for binary search,
37 ex.
for conversion of binary to decimal,
856 ex.
for Fast Fourier Transform,
834–836
for finding the closest pair of points,
958–961
for finding the convex hull,
948
for multiplication,
844 pr.
relation to dynamic programming,
323
solving recurrences for,
62–90
for Strassen's algorithm,
735–742
DNF (disjunctive normal form),
1000
does-not-divide relation (
∤),
850
minimum-spanning-tree algorithm for,
574 ex.
transitive closure of,
641 pr.
dynamic order statistics,
302–308
dynamic-programming method,
323–369
for activity selection, 378 ex.
for all-pairs shortest paths,
622–632
for assembly-line scheduling,
324–331
for bitonic euclidean traveling-salesman problem,
364 pr.
for edit distance,
364 pr.
for Floyd-Warshall algorithm,
629–632
for longest common subsequence,
350–356
for matrix-chain multiplication,
331–339
for optimal binary search trees,
356–363
optimal substructure in,
339–344
overlapping subproblems in,
344–346
for printing neatly,
364 pr.
reconstructing an optimal solution in,
346–347
for transitive closure,
632–635
for Viterbi algorithm,
367 pr.
for 0-1 knapsack problem,
384 ex.
analyzed by accounting method,
419
analyzed by aggregate analysis,
418–419


Welcome to the Pizza ticket maker
Order here.
Please select size and toppings.
All pizzas have base price of 5. proteins are 2$ a topping and veggies are 1$ per.
Small:3$ Medium:6$ Large:9$
Pizza size
Small
Medium
Large
Protein Toppings
Pepperoni
Chicken
Tofu
Beef
Vegetable toppings
Onion
Peppers
Olives
Pineapple
Build my Pie
Your Pizza
Pizza Size:
Your toppings:
Total price: $
Order Now!
Welcome to GeofAthers Pizza!


 When you start the game, your ship is in the middle of the screen. You can control the ship by using the following keys:
| Left arrow, A, J | Rotate left |
| Right arrow, D, L | Rotate right |
| Up arrow, W, I | Thrust |
| Space, Z, M | Fire |
If your ship does not move, click the game area with a mouse and try again. If arrow keys cause some strange behaviour (like scrolling), try to move your ship with alternative keys. If the game works slowly, make sure that you do not use any zooming in your browser. The game is implemented with JavaScript so obviously you must have it enabled in your browser.
Please note that this is not a complete game. Evil amebas are actually quite friendly and they do not even harm your ship in any way. If you want to restart the game, just refresh the current browser page.


An angularjs directive that extends the functionality of bootstrap dropdown control to show simple trees
{{(selectedSubject.Description)?selectedSubject.Description:'Nothing selected yet'}}


{%extends 'base.html'%} {%block content%} {%block styles%} {{block.super}} {%endblock%}
Description: {{project.Description}}
Average ratings
Design:
Usability:
Content:
Average:
As rated by {{rating.Rater.name}}


Open was the first division of ultimate. Before there were enough players or interest to play Men-only, Women-only, or Mixed, anybody could play on any team. It is known as Open because a team is allowed to play Women if they so choose. Their opponent does not have to match the number of Women, or play any Women, or even carry any on their roster. Hence the name "Open" rather than "Men's" -- it is Open-gender. Traditionally it is Men only.
Women's Ultimate follows the exact same rules as Open, with the same size field, and disc. The only difference is that no team is allowed to play with any Men on the field. It is Women only. Men are allowed to be coaches or team staff (trainers, statisticians, etc) but not players.
Mixed Ultimate is played with both Men and Women on the field at the same time. A team must have at least 3 Women on the field at all times. The team that receives the disc determines whether the point will be played with 4 Men and 3 Women (called "4-3"), or 3 Men and 4 Women ("3-4"). This rule is known as "Offense Dictates."


Mushrooms - P. cubensis
It had been a beautiful friday afternoon. Me and my friend K were planning to purchase some dried Cubenesis mushrooms for $50 an eighth (quite costly if you ask me). Me and K planned to take half of the bag each, which would be approximately 2 grams each. We had arrived at our lady friend's house and purchased our bag. We were both very excited to do shrooms, K was more excited because he had been studying about them for a while but didn't have the chance to try them out.
Preparation Methods:
Since I love the taste of shrooms, I decided to chew on them so they would kick in faster, then I followed that by some orange juice. Quite a tasty combination if you ask me and the acidity in the orange juice would help to kick them in much faster than usual.
K smelled his share of the bag and exclaimed that they smelled putrid. So he decided to make a peanut butter sandwich and layed the shrooms right in between the two buns. He took about 5-10 minutes to thoroughly chew them up.
The Voyage:
Me, K, and another kid A all decided to meet up with a good friend, M. So we went walking threw the park and neither me nor K had felt anything yet. We then met up with M and S, we smoked a cig and me and K decided to go to my good friend D's house to toke up some buds.
It had been about 25 minutes from initial consumption of the shrooms and halfway to D's house I noticed a strange feeling in my body. I felt really giddy and it felt as if my eyes were watering (always happens to me on shrooms). K had a potentially big smile on his face also since I hadn't mentioned what he would feel like during the trip, I would have more fun watching him find out for himself.I stopped and started laughing and staring at the sky, but K insisted that we make it to D's soon. So we were almost there! Untill I forgot that we would have to take a short trip threw the forest.
Me and K had a blast walking threw this mud field and we both agreed that we were lost. Though it is technically hard to get lost on a sunny day in a tiny forest that stretched one block. Finally we had made it to D's, I had such a passion to get a tissue to wipe my nose that it was unbelievable.  This amused me greatly and I ran up to his living room to grab some tissues.
I had a really hard time trying to walk straight. I've always had trouble walking on shrooms since I tend to make strange wave movements with my body as I move, as if a strong wind was pushing my upper body and another strong wind was pulling my lower body. At this point of the trip, time seemed worthless and was going by quite fast. I also loved to trip at D's because I would have a wonderful time just hanging out with his dog, my first shroom experience at D's house was amazing since I had a conversation with his dog.
After all this which seemed like it took an hour to go through, was only actually about 10 minutes or so. Then I went back downstairs where D and 3 other friends were token up some ganja.  While we were smoking, several impressive hallucinations began. One very cool thing that I saw was when I stared off at 2 soda cans that suddenly started to swirl together in green and white colors. I then shut my eyes, to my surprise my CEVs (Closed Eye Visuals) were just big pictures of color and brightness. I then opened my eyes and the color flowed all throughout D's garage. I always notice that in order for me to induce hallucinations on a low dose mushroom trip, I have to stare at something and then it will begin to dance and turn colors.
One thing that annoys me the most on mushroom trips are is that I get so damn confusing sometimes that I can't remember what I was just talking about or where I was the whole day.
After some more interesting color patterns and dancing objects, me and K decided to go to our friend's house where we heard some other friends would be. The journey there was very VERY long, but actually only took us 15 minutes. On the way there we decided to jump the fence in the woods instead of going all the way around and maybe getting lost. It was impossible for me to jump this gigantic thing, but I finally made it.
As soon as we made it to J's house, we had been 4 hours into our trip and when we first entered J's house everything was so hilarious and my body was getting many rushes of euphoria. Slightly after that my trip was over and I was kind of sad but happy with what I experienced. K was still trippin when I stopped but then we just talked about mushrooms as being the best thing K has ever tried.
Overall this experience was amazing for only 2 grams of dried P. Cubensis but it proved most rewarding since it kicked in so fast, I suggest to drink orange juice with your shrooms to reduce nausea and to get them started quicker. Shrooms absolutely had no hangover and the next day colors seemed brighter and I was full of joy.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Next: broadcast-stream-streams, Previous: make-synonym-stream, Up: Streams Dictionary
synonym-stream-symbol
synonym-stream ⇒ symbol
synonym-stream—a synonym stream.
symbol—a symbol.
Returns the symbol whose symbol-value the synonym-stream is using.


Thiago B. Procaci
Posts
Skills and Publications
Posts
Skills and Publications
Those are my blogs
and also my life
Innovation and Invention
innovation
invention
Are we really innovating? ...
Read More


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Blackpink is a South Korean girl group formed ny YG Entertainment, consisting of members Jisoo, Jennie, Rose and Lisa. They call their fans BLINKS.
Jisoo: Lead vocalist and visual.
Jennie: Main rapper and vocalist.
Rose: Main vocalist and dancer.
Lisa: Main dancer, rapper and vocalist.
You can read more about them on their website
Most recent songs: "How You Like That" and "Sour Candy"
Some of their songs.
Like them on Social Media: Facebook
Submit your name if you are one of the blinks.
Note that your privicy is protected.


The controller input channels use sustain and sostenuto controls for the right and left footswitches, but the {_preprocessor} can remap the latter to the portamento control, in which case the output will produce that control instead.


I have recently faced some difficulties in installing the oracle client in ubuntu and have JBoss ‘see’ the client installation, since it is approved for RedHat distributions, so I would like to share with you the settings that I, with the help of some friends of the work, I was able to make the connection with the UNICAMP - University of Campinas (where the project is located).
Installing the JDK and setting JAVA_HOME
First follow the step-by-step here.
After that set the environment variables in /etc/profile
file adding the follow lines:
$ export JAVA_HOME=/usr/lib/jvm/java-6-oracle
$ export PATH=$PATH:$JAVA_HOME/bin
PS.: Now restart the PC
Getting started OracleClient 64 on ubuntu
Step 1: Downloading the stuff
Go ahead and download Oracle Client 11g X64 (I’m using R1 cause I had it before, but R2 might work as well)
Warning: From now on, you should run all command as a root user.
Step 2: Updates
$ apt-get install alien build-essential gawk ksh lesstif2
libaio1 libaio-dev libtool expat unixodbc sysstat libxml2-dev
libxml2-utils zlib1g zlib1g-dev libjpeg8-dev libpng12-dev
libfreetype6-dev autoconf
Step 3: Dash to Bash (as Dash is the default sh and we need Bash):
$ cd /bin
$ ln -sf bash /bin/sh
Step 4: Creating user/group
$ adduser oracle
Ubuntu will create an ‘oracle’ group aswell, just type ‘oracle’ as password and leave everything blank then ur done.
Step 5: A Few Symlinks
$ cd /bin
$ ln -s /usr/bin/awk /bin/awk
$ ln -s /usr/bin/rpm /bin/rpm
$ ln -s /usr/bin/basename /bin/basename
$ mkdir /usr/lib64
$ ln -s /usr/lib/x86_64-linux-gnu/libpthread_nonshared.a /usr/lib64/libpthread_nonshared.a
$ ln -s /usr/lib/x86_64-linux-gnu/libc_nonshared.a /usr/lib64/libc_nonshared.a
Step 6: Create Oracle Client’s directory
$ mkdir -p /u01/app/
$ chown -R oracle:oracle /u01
$ xhost +
$ apt-get install synaptic
Open synaptic, to search **libstdc++ 5 **and install it, in some versions of Ubuntu is shipping a higher version.
Step 7: Get ready to runInstaller
When you start the installation you’ll choose the “Administrator option”, because it’s a bit complete, even I need a client oracle oci connection. After that the oracle client installation will be displayed many errors, so you’ll need to run the sh scripts.
$ su oracle
$ ./runInstaller
Step 8: Update the file name databases
After to run the installation and its corrections run:
$ updatedb
Step 9: Setting environment variables
Info: the oracle_home is the directory where the installation was performed, check in your environment…
Add the environment variables in the /etc/profile
file by adding the 2 lines below at the end of the file.
$ export ORACLE_HOME=/u01/app/oracle/product/11.2.0/client_1
$ export PATH=$PATH:$ORACLE_HOME/bin
Step 10: Publish libs to Linux
You should register the oracle 11g lib path in /etc/ld.so.conf.d
:
Create a file called oracle.conf
, inside /etc/ld.so.conf.d
directory, with this content on the first line:
/u01/app/oracle/product/11.2.0/client_1/lib
Run the touch command:
$ touch /etc/ld.so.conf.d/oracle.conf
Finally
$ ldconfig -v #Update the links/cache
$ ldconfig -p | grep oracle
the terminal may return an alert saying that it could not find the link for a given lib, normal this ‘error’ appears)
That’s all


Hi Myself Jhon Smith
Professional Graphic Designer
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About Me
Creative Graphic Designer
Create Awesome Project As You Need
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125+
Active Client
605+
Client Feedback
800+
Project Complete
My Provide Services
Graphic Design
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SEO Marketing
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Data Analysis
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Digital Marketing
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Video Editing
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Photography
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Software Skill
Latest Project
Project Name
Client : Rodex Group
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Client Feedback
It uses a dictionary of over 200 Latin words, combined with a handful of model sentence structures, to generate Lorem Ipsum which looks reasonable.
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We give solution
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Latest News
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Border wall fundraiser to seek US approval on Texas project
by Nomaan Merchant, The Associated PressHOUSTON — The private group that wants to build its own southern border wall next to the Rio Grande in Texas won’t begin construction until the U.S. government certifies the project won’t worsen flooding.
The agency that oversees the river under treaties signed with Mexico has asked the group We Build the Wall to halt construction until it submits more information about the project so the commission could study it.
We Build the Wall’s founder, Brian Kolfage, said Tuesday that the group won’t build until it has the approval of the agency, the International Boundary and Water Commission.
The group had announced on Facebook that it was starting to build a barrier on 3.5 miles (5.6 kilometres) of private land in South Texas.
Nomaan Merchant, The Associated Press


And when it comes to styling these boxes and how they appear on the page, we can apply CSS to essentially wrap around each and every HTML element. This wrapping consists of: margins, borders, padding, and the actual content itself. Take a look below for an overview of what I'm saying.
Let’s start with padding. Padding is a property that can be used to create transparent space around an elements content. It can be applied to all four sides of the element, or just specific sides. Below are examples of how you can apply padding to an element:
In the example below, you can see that the two boxes each have different padding applied to them. One has 20px applied around the entire element, and one has 30px applied to the top and bottom and 40px to the right and left.
See the Pen padding by carter-bardellmunro (@carter-bardellmunro) on CodePen.
Borders are where you can get slightly more creative! By using borders, the user can decide the style, width, and colour of the border around a certain element.
Just like padding, a border can wrap around the entire element, or just certain sides. Below are some examples of how you can apply a border:
Below you can see three borders that have had different styles applied to them.
See the Pen BapGrBo by carter-bardellmunro (@carter-bardellmunro) on CodePen.
Margins are the outer layer of an element, outside of any defined borders, and can be used to create space between neighbouring elements. The greater the margin, the greater the distance between elements.
The same happens in reverse. If the margin is negative, you can start to overlap elements. Below are some examples of margins in action.
As we can see in Box #1, it has 20px applied to the left margin, hence moving it 20px away from the left hand side of the screen.
With Box #2, it has 40px appled to the top margin, moving it down from the top of the screen, and -20px applied to the left margin, hence overlaying it over Box #1.
Box #3 has 15px and 30px applied to the left and bottom margin respectively, moving it away to the right and slightly higher than the other two boxes.
See the Pen margin by carter-bardellmunro (@carter-bardellmunro) on CodePen.


College Life
Well since I have only been in college for two years this page is probably going to be shorter. However, I think I have already done way more than I expected to do by now. A quick overview I currently attend the illustrious Howard University as a rising junior computer science major.


This inspection reports local variables with 'var' types when they can be replaced with explicit types


| Path: | website/index.txt |
| Last Update: | Sun Oct 26 23:06:45 -0200 2008 |
h1. ‘appointme‘
Appointme is a simple schedule in natural language. With this, you can put your appointments in your schedule simply typing what you will do and when you will do it.
h2. Installing

sudo gem install appointme

h2. The basics
Just with "Chronic gem":http://chronic.rubyforge.org I parse some phrase like:
 puts Chronic.parse("next saturday at 8").inspect # Sat Nov 01 08:00:00 -0200 2008
 with a lot of options like this I just split the rest of the time description to see and put new appointments on the schedule:
 include Appointme schedule = Schedule.new go_to_english_class = Appointment.new :when => "next saturday at 3", :description => "english class" schedule.appointments << go_to_english_class puts schedule.appointments # when?: Saturday(01) at 15:00 - english class

h2. Using static methods to be more easy

 Appointme.understand "tomorrow at 8 wake up man!" Appointme.understand "tomorrow at 9 work, work" Appointme.understand "eat some japanese food with mary tomorrow at noon" Appointme.understand "tomorrow at 6:10pm get out job drink some beers" Appointme.understand "tomorrow at 6:30pm happy hour! woohooo" puts Appointme.understand "show tomorrow at 6 pm" when?: Monday(27) at 18:10 - get out job drink some beers when?: Monday(27) at 18:30 - happy hour! woohooo

h2. License
This code is free to use under the terms of the MIT license.
h2. Contact
Comments are welcome. Send an email to "Jônatas Davi<EMAIL_ADDRESS>via the "forum":groups.google.com/group/appointme


{{ partial "header.html" . }}
A list of all the great things that OpenBSD has. Why this site exists, see About.