Other functions#
- class sage.functions.other.Function_Order#
Bases:
GinacFunction
The order function.
This function gives the order of magnitude of some expression, similar to \(O\)-terms.
EXAMPLES:
sage: x = SR('x') sage: x.Order() Order(x) sage: (x^2 + x).Order() Order(x^2 + x)
- class sage.functions.other.Function_abs#
Bases:
GinacFunction
The absolute value function.
EXAMPLES:
sage: var('x y') (x, y) sage: abs(x) abs(x) sage: abs(x^2 + y^2) abs(x^2 + y^2) sage: abs(-2) 2 sage: sqrt(x^2) sqrt(x^2) sage: abs(sqrt(x)) sqrt(abs(x)) sage: complex(abs(3*I)) (3+0j) sage: f = sage.functions.other.Function_abs() sage: latex(f) \mathrm{abs} sage: latex(abs(x)) {\left| x \right|} sage: abs(x)._sympy_() Abs(x)
Test pickling:
sage: loads(dumps(abs(x))) abs(x)
- class sage.functions.other.Function_arg#
Bases:
BuiltinFunction
The argument function for complex numbers.
EXAMPLES:
sage: arg(3+i) arctan(1/3) sage: arg(-1+i) 3/4*pi sage: arg(2+2*i) 1/4*pi sage: arg(2+x) arg(x + 2) sage: arg(2.0+i+x) arg(x + 2.00000000000000 + 1.00000000000000*I) sage: arg(-3) pi sage: arg(3) 0 sage: arg(0) 0 sage: latex(arg(x)) {\rm arg}\left(x\right) sage: maxima(arg(x)) atan2(0,_SAGE_VAR_x) sage: maxima(arg(2+i)) atan(1/2) sage: maxima(arg(sqrt(2)+i)) atan(1/sqrt(2)) sage: arg(x)._sympy_() arg(x) sage: arg(2+i) arctan(1/2) sage: arg(sqrt(2)+i) arg(sqrt(2) + I) sage: arg(sqrt(2)+i).simplify() arctan(1/2*sqrt(2))
- class sage.functions.other.Function_binomial#
Bases:
GinacFunction
Return the binomial coefficient
\[\binom{x}{m} = x (x-1) \cdots (x-m+1) / m!\]which is defined for \(m \in \ZZ\) and any \(x\). We extend this definition to include cases when \(x-m\) is an integer but \(m\) is not by
\[\binom{x}{m}= \binom{x}{x-m}\]If \(m < 0\), return \(0\).
INPUT:
x
,m
- numbers or symbolic expressions. Eitherm
orx-m
must be an integer, else the output is symbolic.
OUTPUT: number or symbolic expression (if input is symbolic)
EXAMPLES:
sage: binomial(5,2) 10 sage: binomial(2,0) 1 sage: binomial(1/2, 0) 1 sage: binomial(3,-1) 0 sage: binomial(20,10) 184756 sage: binomial(-2, 5) -6 sage: binomial(RealField()('2.5'), 2) 1.87500000000000 sage: n=var('n'); binomial(n,2) 1/2*(n - 1)*n sage: n=var('n'); binomial(n,n) 1 sage: n=var('n'); binomial(n,n-1) n sage: binomial(2^100, 2^100) 1
sage: k, i = var('k,i') sage: binomial(k,i) binomial(k, i)
We can use a
hold
parameter to prevent automatic evaluation:sage: SR(5).binomial(3, hold=True) binomial(5, 3) sage: SR(5).binomial(3, hold=True).simplify() 10
- class sage.functions.other.Function_cases#
Bases:
GinacFunction
Formal function holding
(condition, expression)
pairs.Numbers are considered conditions with zero being
False
. A true condition marks a default value. The function is not evaluated as long as it contains a relation that cannot be decided by Pynac.EXAMPLES:
sage: ex = cases([(x==0, pi), (True, 0)]); ex cases(((x == 0, pi), (1, 0))) sage: ex.subs(x==0) pi sage: ex.subs(x==2) 0 sage: ex + 1 cases(((x == 0, pi), (1, 0))) + 1 sage: _.subs(x==0) pi + 1
The first encountered default is used, as well as the first relation that can be trivially decided:
sage: cases(((True, pi), (True, 0))) pi sage: _ = var('y') sage: ex = cases(((x==0, pi), (y==1, 0))); ex cases(((x == 0, pi), (y == 1, 0))) sage: ex.subs(x==0) pi sage: ex.subs(x==0, y==1) pi
- class sage.functions.other.Function_ceil#
Bases:
BuiltinFunction
The ceiling function.
The ceiling of \(x\) is computed in the following manner.
The
x.ceil()
method is called and returned if it is there. If it is not, then Sage checks if \(x\) is one of Python’s native numeric data types. If so, then it calls and returnsInteger(math.ceil(x))
.Sage tries to convert \(x\) into a
RealIntervalField
with 53 bits of precision. Next, the ceilings of the endpoints are computed. If they are the same, then that value is returned. Otherwise, the precision of theRealIntervalField
is increased until they do match up or it reachesbits
of precision.If none of the above work, Sage returns a
Expression
object.
EXAMPLES:
sage: a = ceil(2/5 + x) sage: a ceil(x + 2/5) sage: a(x=4) 5 sage: a(x=4.0) 5 sage: ZZ(a(x=3)) 4 sage: a = ceil(x^3 + x + 5/2); a ceil(x^3 + x + 5/2) sage: a.simplify() ceil(x^3 + x + 1/2) + 2 sage: a(x=2) 13
sage: ceil(sin(8)/sin(2)) 2
sage: ceil(5.4) 6 sage: type(ceil(5.4)) <class 'sage.rings.integer.Integer'>
sage: ceil(factorial(50)/exp(1))<PHONE_NUMBER>0782480504630258070757734324011354208865721592720336801 sage: ceil(SR(10^50 + 10^(-50)))<PHONE_NUMBER>00000000000000000000000000000000000000001 sage: ceil(SR(10^50 - 10^(-50)))<PHONE_NUMBER>00000000000000000000000000000000000000000
Small numbers which are extremely close to an integer are hard to deal with:
sage: ceil((33^100 + 1)^(1/100)) Traceback (most recent call last): ... ValueError: cannot compute ceil(...) using 256 bits of precision
This can be fixed by giving a sufficiently large
bits
argument:sage: ceil((33^100 + 1)^(1/100), bits=500) Traceback (most recent call last): ... ValueError: cannot compute ceil(...) using 512 bits of precision sage: ceil((33^100 + 1)^(1/100), bits=1000) 34
sage: ceil(sec(e)) -1 sage: latex(ceil(x)) \left \lceil x \right \rceil sage: ceil(x)._sympy_() ceiling(x)
sage: import numpy sage: a = numpy.linspace(0,2,6) sage: ceil(a) array([0., 1., 1., 2., 2., 2.])
Test pickling:
sage: loads(dumps(ceil)) ceil
- class sage.functions.other.Function_conjugate#
Bases:
GinacFunction
Returns the complex conjugate of the input.
It is possible to prevent automatic evaluation using the
hold
parameter:sage: conjugate(I,hold=True) conjugate(I)
To then evaluate again, we currently must use Maxima via
sage.symbolic.expression.Expression.simplify()
:sage: conjugate(I,hold=True).simplify() -I
- class sage.functions.other.Function_crootof#
Bases:
BuiltinFunction
Formal function holding
(polynomial, index)
pairs.The expression evaluates to a floating point value that is an approximation to a specific complex root of the polynomial. The ordering is fixed so you always get the same root.
The functionality is imported from SymPy, see http://docs.sympy.org/latest/_modules/sympy/polys/rootoftools.html
EXAMPLES:
sage: c = complex_root_of(x^6 + x + 1, 1); c complex_root_of(x^6 + x + 1, 1) sage: c.n() -0.790667188814418 + 0.300506920309552*I sage: c.n(100) -0.79066718881441764449859281847 + 0.30050692030955162512001002521*I sage: (c^6 + c + 1).n(100) < 1e-25 True
- class sage.functions.other.Function_elementof#
Bases:
BuiltinFunction
Formal set membership function that is only accessible internally.
This function is called to express a set membership statement, usually as part of a solution set returned by
solve()
. Seesage.sets.set.Set
andsage.sets.real_set.RealSet
for possible set arguments.EXAMPLES:
sage: from sage.functions.other import element_of sage: element_of(x, SR(ZZ)) element_of(x, Integer Ring) sage: element_of(sin(x), SR(QQ)) element_of(sin(x), Rational Field) sage: element_of(x, SR(RealSet.open_closed(0,1))) element_of(x, (0, 1]) sage: element_of(x, SR(Set([4,6,8]))) element_of(x, {8, 4, 6})
- class sage.functions.other.Function_factorial#
Bases:
GinacFunction
Returns the factorial of \(n\).
INPUT:
n
- a non-negative integer, a complex number (except negative integers) or any symbolic expression
OUTPUT: an integer or symbolic expression
EXAMPLES:
sage: factorial(0) 1 sage: factorial(4) 24 sage: factorial(10) 3628800 sage: factorial(6) == 6*5*4*3*2 True sage: x = SR.var('x') sage: f = factorial(x + factorial(x)); f factorial(x + factorial(x)) sage: f(x=3) 362880 sage: factorial(x)^2 factorial(x)^2
To prevent automatic evaluation use the
hold
argument:sage: factorial(5, hold=True) factorial(5)
To then evaluate again, we currently must use Maxima via
sage.symbolic.expression.Expression.simplify()
:sage: factorial(5, hold=True).simplify() 120
We can also give input other than nonnegative integers. For other nonnegative numbers, the
sage.functions.gamma.gamma()
function is used:sage: factorial(1/2) 1/2*sqrt(pi) sage: factorial(3/4) gamma(7/4) sage: factorial(2.3) 2.68343738195577
But negative input always fails:
sage: factorial(-32) Traceback (most recent call last): ... ValueError: factorial only defined for non-negative integers
And very large integers remain unevaluated:
sage: factorial(2**64) factorial(18446744073709551616) sage: SR(2**64).factorial() factorial(18446744073709551616)
- class sage.functions.other.Function_floor#
Bases:
BuiltinFunction
The floor function.
The floor of \(x\) is computed in the following manner.
The
x.floor()
method is called and returned if it is there. If it is not, then Sage checks if \(x\) is one of Python’s native numeric data types. If so, then it calls and returnsInteger(math.floor(x))
.Sage tries to convert \(x\) into a
RealIntervalField
with 53 bits of precision. Next, the floors of the endpoints are computed. If they are the same, then that value is returned. Otherwise, the precision of theRealIntervalField
is increased until they do match up or it reachesbits
of precision.If none of the above work, Sage returns a symbolic
Expression
object.
EXAMPLES:
sage: floor(5.4) 5 sage: type(floor(5.4)) <class 'sage.rings.integer.Integer'> sage: var('x') x sage: a = floor(5.25 + x); a floor(x + 5.25000000000000) sage: a.simplify() floor(x + 0.25) + 5 sage: a(x=2) 7
sage: floor(cos(8) / cos(2)) 0 sage: floor(log(4) / log(2)) 2 sage: a = floor(5.4 + x); a floor(x + 5.40000000000000) sage: a.subs(x==2) 7 sage: floor(log(2^(3/2)) / log(2) + 1/2) 2 sage: floor(log(2^(-3/2)) / log(2) + 1/2) -1
sage: floor(factorial(50)/exp(1))<PHONE_NUMBER>0782480504630258070757734324011354208865721592720336800 sage: floor(SR(10^50 + 10^(-50)))<PHONE_NUMBER>00000000000000000000000000000000000000000 sage: floor(SR(10^50 - 10^(-50)))<PHONE_NUMBER>9999999999999999999999999999999999999999 sage: floor(int(10^50))<PHONE_NUMBER>00000000000000000000000000000000000000000
Small numbers which are extremely close to an integer are hard to deal with:
sage: floor((33^100 + 1)^(1/100)) Traceback (most recent call last): ... ValueError: cannot compute floor(...) using 256 bits of precision
This can be fixed by giving a sufficiently large
bits
argument:sage: floor((33^100 + 1)^(1/100), bits=500) Traceback (most recent call last): ... ValueError: cannot compute floor(...) using 512 bits of precision sage: floor((33^100 + 1)^(1/100), bits=1000) 33
sage: import numpy sage: a = numpy.linspace(0,2,6) sage: floor(a) array([0., 0., 0., 1., 1., 2.]) sage: floor(x)._sympy_() floor(x)
Test pickling:
sage: loads(dumps(floor)) floor
- class sage.functions.other.Function_frac#
Bases:
BuiltinFunction
The fractional part function \(\{x\}\).
frac(x)
is defined as \(\{x\} = x - \lfloor x\rfloor\).EXAMPLES:
sage: frac(5.4) 0.400000000000000 sage: type(frac(5.4)) <class 'sage.rings.real_mpfr.RealNumber'> sage: frac(456/123) 29/41 sage: var('x') x sage: a = frac(5.4 + x); a frac(x + 5.40000000000000) sage: frac(cos(8)/cos(2)) cos(8)/cos(2) sage: latex(frac(x)) \operatorname{frac}\left(x\right) sage: frac(x)._sympy_() frac(x)
Test pickling:
sage: loads(dumps(floor)) floor
- class sage.functions.other.Function_imag_part#
Bases:
GinacFunction
Returns the imaginary part of the (possibly complex) input.
It is possible to prevent automatic evaluation using the
hold
parameter:sage: imag_part(I,hold=True) imag_part(I)
To then evaluate again, we currently must use Maxima via
sage.symbolic.expression.Expression.simplify()
:sage: imag_part(I,hold=True).simplify() 1
- class sage.functions.other.Function_limit#
Bases:
BuiltinFunction
Placeholder symbolic limit function that is only accessible internally.
This function is called to create formal wrappers of limits that Maxima can’t compute:
sage: a = lim(exp(x^2)*(1-erf(x)), x=infinity); a -limit((erf(x) - 1)*e^(x^2), x, +Infinity)
EXAMPLES:
sage: from sage.functions.other import symbolic_limit as slimit sage: slimit(1/x, x, +oo) limit(1/x, x, +Infinity) sage: var('minus,plus') (minus, plus) sage: slimit(1/x, x, +oo) limit(1/x, x, +Infinity) sage: slimit(1/x, x, 0, plus) limit(1/x, x, 0, plus) sage: slimit(1/x, x, 0, minus) limit(1/x, x, 0, minus)
- class sage.functions.other.Function_prod#
Bases:
BuiltinFunction
Placeholder symbolic product function that is only accessible internally.
EXAMPLES:
sage: from sage.functions.other import symbolic_product as sprod sage: r = sprod(x, x, 1, 10); r product(x, x, 1, 10) sage: r.unhold() 3628800
- class sage.functions.other.Function_real_nth_root#
Bases:
BuiltinFunction
Real \(n\)-th root function \(x^\frac{1}{n}\).
The function assumes positive integer \(n\) and real number \(x\).
EXAMPLES:
sage: real_nth_root(2, 3) 2^(1/3) sage: real_nth_root(-2, 3) -2^(1/3) sage: real_nth_root(8, 3) 2 sage: real_nth_root(-8, 3) -2 sage: real_nth_root(-2, 4) Traceback (most recent call last): ... ValueError: no real nth root of negative real number with even n
For numeric input, it gives a numerical approximation.
sage: real_nth_root(2., 3) 1.25992104989487 sage: real_nth_root(-2., 3) -1.25992104989487
Some symbolic calculus:
sage: f = real_nth_root(x, 5)^3 sage: f real_nth_root(x^3, 5) sage: f.diff() 3/5*x^2*real_nth_root(x^(-12), 5) sage: result = f.integrate(x) ... sage: result integrate((abs(x)^3)^(1/5)*sgn(x^3), x) sage: _.diff() (abs(x)^3)^(1/5)*sgn(x^3)
- class sage.functions.other.Function_real_part#
Bases:
GinacFunction
Returns the real part of the (possibly complex) input.
It is possible to prevent automatic evaluation using the
hold
parameter:sage: real_part(I,hold=True) real_part(I)
To then evaluate again, we currently must use Maxima via
sage.symbolic.expression.Expression.simplify()
:sage: real_part(I,hold=True).simplify() 0
EXAMPLES:
sage: z = 1+2*I sage: real(z) 1 sage: real(5/3) 5/3 sage: a = 2.5 sage: real(a) 2.50000000000000 sage: type(real(a)) <class 'sage.rings.real_mpfr.RealLiteral'> sage: real(1.0r) 1.0 sage: real(complex(3, 4)) 3.0
Sage can recognize some expressions as real and accordingly return the identical argument:
sage: SR.var('x', domain='integer').real_part() x sage: SR.var('x', domain='integer').imag_part() 0 sage: real_part(sin(x)+x) x + sin(x) sage: real_part(x*exp(x)) x*e^x sage: imag_part(sin(x)+x) 0 sage: real_part(real_part(x)) x sage: forget()
- class sage.functions.other.Function_sqrt#
Bases:
object
- class sage.functions.other.Function_sum#
Bases:
BuiltinFunction
Placeholder symbolic sum function that is only accessible internally.
EXAMPLES:
sage: from sage.functions.other import symbolic_sum as ssum sage: r = ssum(x, x, 1, 10); r sum(x, x, 1, 10) sage: r.unhold() 55


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Introduction
Welcome to the Clear Payments API - Powered by Clear Treasury. With international payments a daily necessity for many, we have developed our online payments platform that dramatically streamlines the process.
We have designed the Clear Payments API to integrate directly into your process, product or software.
Authentication
To authorize, use this code:
# With shell, you can just pass the correct header with each request
curl "api_endpoint_here"
-H "Authorization: --yourAuthKey--"
const kittn = require('kittn');
let api = kittn.authorize('--yourAuthKey--');
Make sure to replace
--yourAuthKey--
with your API key.
Clear Payments uses API keys to allow access to the API. You can register a new API key at our developer portal.
Clear Payments expects for the API key to be included in all API requests to the server in a header that looks like the following:
Authorization: --yourAuthKey--
Bookquote
Example JSON response:
{
"ID": 0,
"Trade_Date": "string",
"Value_Date": "string",
"CCY_Bought": "string",
"CCY_Sold": "string",
"Rate": 0,
"Bought_Amount": 0,
"Sold_Amount": 0,
"Payment_Fee": 0,
"Trade_ID": "string",
"Trade_Type": "string",
"OurAccountName": "string",
"OurBankName": "string",
"OurIBAN": "string",
"OurSortCode": "string",
"OurSWIFTCode": "string",
"Message": "string"
}
HTTP Request
POST /api/BookQuote/BookQuote
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| quote_id | query | Yes | integer | |
| sourceOfFunds | query | Yes | string | |
| ReasonForTrading | query | Yes | string |
Responses
| Code | Description |
|---|---|
| 200 | OK |
Payment instruction
GET
Example JSON response:
[
{
"Intermediary": "string",
"AccountName": "string",
"AccountNumber": "string",
"Address": "string",
"BankName": "string",
"CCY": "string",
"Notes": "string",
"SortCode": "string",
"Swift": "string",
"CountryCode": "string",
"Email": "string",
"BenAddress": "string",
"CNAPS": "string",
"Purpose": "string",
"ChargeCode": "string",
"Amount": 0,
"PaymentReference": "string",
"TradeReference": "string",
"tra_client_id": 0,
"pin_id": 0,
"PaymentGUID": "string",
"opi_id": 0,
"CreationDate": "2019-10-17T11:27:23.691Z",
"Status": "string",
"exportedDate": "2019-10-17T11:27:23.691Z"
}
]
HTTP Request
GET /api/PaymentInstruction/GetValues
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| fromDate | query | No | string | |
| toDate | query | No | string |
Responses
| Code | Description |
|---|---|
| 200 | OK |
POST
HTTP Request
POST /api/PaymentInstruction/PostValue
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| tr | body | Yes |
Responses
| Code | Description |
|---|---|
| 200 | OK |
Quote
POST
HTTP Request
POST /api/Quote/PostValue
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| ccy_sell | query | No | string | |
| ccy_buy | query | No | string | |
| value_date | query | No | string | |
| sell_amount | query | No | double | |
| buy_amount | query | No | double | |
| quoteID | query | No | integer |
Responses
| Code | Description |
|---|---|
| 200 | OK |
GET
HTTP Request
GET /api/Quote/GetValue
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| quote_id | query | Yes | integer |
Responses
| Code | Description |
|---|---|
| 200 | OK |
calculatequote
Example JSON response:
{
"ID": "string",
"sell_amount": 0,
"buy_amount": 0,
"client_rate": 0,
"bank_rate": 0,
"ccy_sell": "string",
"fee": 0,
"fee_ccy": 0,
"ccy_buy": "string",
"value_date": "string",
"Message": "string",
"Status": true
}
HTTP Request
POST /api/Quote/CalculateQuote
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| quote_id | query | Yes | integer |
Responses
| Code | Description |
|---|---|
| 200 | OK |
Statement
GET
Example JSON response:
[
{
"Date": "2019-10-17T12:24:39.589Z",
"Reference": "string",
"Detail": "string",
"Receipts": 0,
"Payments": 0,
"Bank_Account": "string",
"Balance": 0
}
]
HTTP Request
GET /api/Statement/GetValues
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| ccy | query | Yes | string | |
| fromDate | query | No | string | |
| toDate | query | No | string |
Responses
| Code | Description |
|---|---|
| 200 | OK |
Template
GET
Example JSON response:
[
{
"pin_id": 0,
"pin_link_id": 0,
"pin_link_type": 0,
"pin_ccy": "string",
"pin_bank_name": "string",
"pin_address": "string",
"pin_account_name": "string",
"pin_account_number": "string",
"pin_sort_code": "string",
"pin_iban": "string",
"pin_swift_bic": "string",
"pin_fedwire_bank_code": "string",
"pin_details": "string",
"pin_notes": "string",
"pin_country_code": "string",
"pin_intermediary": "string",
"pin_email": "string",
"pin_alert_date": "string",
"pin_archived": true,
"pin_ben_name": "string",
"pin_ben_contact_name": "string",
"pin_ben_address": "string",
"pin_ben_activity": "string",
"pin_ben_post_code": "string",
"pin_ben_Town": "string",
"pin_bank_post_code": "string",
"pin_bank_Town": "string",
"pin_bank_code": "string",
"pin_bank_branch": "string",
"pin_CPF": "string",
"pin_account_type": "string",
"pin_cnaps": "string",
"pin_purpose": "string",
"pin_validate_date": "string",
"pin_last_external_check_date": "string",
"pin_low_risk": 0,
"pin_recurrent": 0,
"pin_partner": 0,
"pin_check_count": 0
}
]
HTTP Request
GET /api/Template/GetValues
Responses
| Code | Description |
|---|---|
| 200 | OK |
Token
POST
HTTP Request
POST /api/Token/PostValues
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| uc | body | Yes |
Responses
| Code | Description |
|---|---|
| 200 | OK |
Trade
GET
Example JSON response:
[
{
"ID": 0,
"Trade_Date": "string",
"Value_Date": "string",
"CCY_Bought": "string",
"CCY_Sold": "string",
"Rate": 0,
"Bought_Amount": 0,
"Sold_Amount": 0,
"Payment_Fee": 0,
"Trade_ID": "string",
"Trade_Type": "string",
"Status": "string",
"Beneficiary": "string"
}
]
HTTP Request
GET /api/Trade/GetValues
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| fromDate | query | No | string | |
| toDate | query | No | string |
Responses
| Code | Description |
|---|---|
| 200 | OK |
Webhooks
Filters
Example JSON response:
[
{
"Name": "string",
"Description": "string"
}
]
HTTP Request
GET /api/webhooks/filters
Responses
| Code | Description |
|---|---|
| 200 | OK |
Registrations
Example JSON response:
[
{
"Id": "string",
"WebHookUri": "string",
"Secret": "string",
"Description": "string",
"IsPaused": true,
"Filters": [
"string"
],
"Headers": {},
"Properties": {}
}
]
HTTP Request
GET /api/webhooks/registrations
Responses
| Code | Description |
|---|---|
| 200 | OK |
HTTP Request
POST /api/webhooks/registrations
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| webHook | body | Yes |
Responses
| Code | Description |
|---|---|
| 200 | OK |
HTTP Request
DELETE /api/webhooks/registrations
Responses
| Code | Description |
|---|---|
| 200 | OK |
Registrations/{id}
GET
HTTP Request
GET /api/webhooks/registrations/{id}
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| id | path | Yes | string |
Responses
| Code | Description |
|---|---|
| 200 | OK |
PUT
HTTP Request
PUT /api/webhooks/registrations/{id}
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| id | path | Yes | string | |
| webHook | body | Yes |
Responses
| Code | Description |
|---|---|
| 200 | OK |
DELETE
HTTP Request
DELETE /api/webhooks/registrations/{id}
Parameters
| Name | Located in | Description | Required | Type |
|---|---|---|---|---|
| id | path | Yes | string |
Responses
| Code | Description |
|---|---|
| 200 | OK |
Errors
The Clear Payments API uses the following error codes:
| Error Code | Meaning |
|---|---|
| 400 | Bad Request -- The request could not be understood by the server due to malformed syntax. |
| 401 | Unauthorized -- Your API key is wrong. |
| 403 | Forbidden -- The value requested is hidden for administrators only. |
| 404 | Not Found -- The specified value could not be found. |
| 405 | Method Not Allowed -- You tried to access a value with an invalid method. |
| 406 | Not Acceptable -- You requested a format that isn't JSON. |
| 410 | Gone -- The value requested has been removed from our servers. |
| 418 | I'm a teapot. |
| 429 | Too Many Requests -- You're requesting too many values! Slow down! |
| 500 | Internal Server Error -- We had a problem with our server. Try again later. |
| 503 | Service Unavailable -- We're temporarily offline for maintenance. Please try again later. |


R interface to PortfolioEffect cloud service for backtesting high frequency trading (HFT) strategies, intraday portfolio analysis and optimization. Includes auto-calibrating model pipeline for market microstructure noise, risk factors, price jumps/outliers, tail risk (high-order moments) and price fractality (long memory). Constructed portfolios could use client-side market data or access HF intraday price history for all major US Equities. See <https://www.portfolioeffect.com/> for more information on the PortfolioEffect high frequency portfolio analytics platform.
| Version: | 1.8 |
| Depends: | R (≥ 2.13.2), ggplot2 (≥ 2.2.0) |
| Imports: | methods, rJava, grid, zoo |
| Suggests: | testthat |
| Published: | 2017-03-24 |
| Author: | Andrey Kostin [aut, cre], Aleksey Zemnitskiy [aut], Oleg Nechaev [aut], Craig Otis and others [ctb, cph] (OpenFAST library), Daniel Lemire, Muraoka Taro and others [ctb, cph] (JavaFastPFOR library), Joe Walnes, Jorg Schaible and others [ctb, cph] (XStream library), Dain Sundstrom [ctb, cph] (Snappy library), Extreme! Lab, Indiana University [ctb, cph] (XPP3 library), The Apache Software Foundation [ctb, cph] (Apache Log4j and Commons Lang libraries), Google, Inc. [ctb, cph] (GSON library), Free Software Foundation [ctb, cph] (GNU Trove and GNU Crypto libraries) |
| Maintainer: | Andrey Kostin <andrey.kostin at portfolioeffect.com> |
| License: | GPL-3 |
| Copyright: | See file COPYRIGHTS PortfolioEffectHFT copyright details |
| URL: | https://www.portfolioeffect.com/ |
| NeedsCompilation: | no |
| SystemRequirements: | Java (>= 1.7) |
| Materials: | NEWS |
| In views: | Finance |
| CRAN checks: | PortfolioEffectHFT results |
| Reference manual: | PortfolioEffectHFT.pdf |
| Vignettes: |
PorfolioEffectHFT package |
| Package source: | PortfolioEffectHFT_1.8.tar.gz |
| Windows binaries: | r-devel: PortfolioEffectHFT_1.8.zip, r-release: PortfolioEffectHFT_1.8.zip, r-oldrel: PortfolioEffectHFT_1.8.zip |
| OS X binaries: | r-release: PortfolioEffectHFT_1.8.tgz, r-oldrel: PortfolioEffectHFT_1.8.tgz |
| Old sources: | PortfolioEffectHFT archive |
| Reverse depends: | PortfolioEffectEstim |
Please use the canonical form https://CRAN.R-project.org/package=PortfolioEffectHFT to link to this page.


Press n or j to go to the next uncovered block, b, p or k for the previous block.
| File | Statements | Branches | Functions | Lines | |||||
|---|---|---|---|---|---|---|---|---|---|
| LocalBuilder.ts | 22.81% | 13/57 | 0% | 0/12 | 9.09% | 1/11 | 22.81% | 13/57 | |
| SpawnBuilder.ts | 17.65% | 9/51 | 18.75% | 3/16 | 14.29% | 2/14 | 18% | 9/50 | |
| projectIdentifier.ts | 0% | 0/0 | 0% | 0/0 | 0% | 0/0 | 0% | 0/0 | |
| projectVersioner.ts | 35.29% | 6/17 | 100% | 0/0 | 0% | 0/6 | 40% | 6/15 |


In some cases it is convenient to generate scripts, CSS or images dynamically. For instance, Jawr will create certain scripts to, say, copy i18n messages from a ResourceBundle over to a special script. You may need to retrieve some data from a database and create parameters that scripts will need, or simply grab parameters from a configuration file and pass them over to the scripting context. For any case where you may need to generate content you can implement a Resource Generator and register it in Jawr to suit your needs.
Note that a Resource Generator is not a script servlet: it will be only invoked once during application startup to build the bundles in Production mode. The result of this invocation will be added to whichever bundle you decide and reused until the next redeployment. The point is to be able to generate some script dynamically but still to be able to minify it and add it to your bundles. A perfect example is the DWR generator: all DWR script interfaces are created from java classes once during startup but they can be minified and bundled together. In debug mode, it will be called as any resource if needed.
Generators are mapped to bundles using a GeneratorResolver. This resolver is used to determine if a resource is a generated resource or not. Prior to the 3.5 version, users were only able to use a prefix to map resources to a generator. Since the 3.5 version, users can define their own resolver. There are 2 built-in types of resolver :
Example of prefixed path generator :
prefix:path(params)[params]
The prefix is a key you will specify when implementing the Generator, and the path is a string which will have different meaning depending on your generator’s functionality. Also, you have params in parentheses and in brackets (both of which are optional), that further help in parameterizing the mappings. A simple mapping example, with no params, is as follows:
jawr.js.bundle.one.mappings=jar:net/jawr/cpscript.js
In this case we are using the already existing classpath script generator, which reads a script from the classpath, as opposed to reading it from the web application dir structure. So the path in this case is the classpath where the script will be found. The prefix is ‘jar’, which lets Jawr know that this path must be resolved using the classpath generator.
This is an example in which the mapping uses two different parameters:
jawr.js.bundle.one.mappings=messages:com.myapp.messages(mynamespace)[javascript.messages]
Note that if you use the parameters, the order must always be parentheses first, brackets last. If you need only one parameter, you can omit the brackets param.
It is possible to escape the parentheses and the brackets if these characters are used in your resource path using the escape character ‘\’. Here isan example :
jawr.js.bundle.one.mappings=webjars:/datatables-plugins/1.10.9/api/sum\(\).js
This generator generates javascript code with locale specific variants which are loaded depending on the user’s specific language. Full documentation is here.
This generator allows you to bundle and compress together DWR generated interfaces, plus all the utility scripts required by them. Full documentation is here.
This one will let you generate compressed and cacheable versions of the validation scripts generated in Struts by the Apache Commons Validator taglib. Full docs here.
It allows you to include resources present within jar files or simply located anywhere in the application classpath. You will need to use different prefixes if you are generating js or css files. To add javascript resources from the classpath you use jar: as the prefix, followed by the path to the resource using / as separator:
jawr.js.bundle.foo.id=/bundles/fooBundle.js # Map to a script in the com.mycompany.myapp package and to another from the WAR jawr.js.bundle.foo.mappings=jar:/com/mycompany/myapp/foo.js, /js/bar.js
Note the leading slash in the mapping, which is also required. You can of course combine this kind of mappings with regular ones, so you can bundle together resources from the WAR and from the classpath.
If you need to load CSS files from the classpath, you would use the exact same syntax jar:.
jawr.css.bundle.styles.mappings=jar:/com/mycompany/myapp/stylesheet.css, /css/bar.css
CSS files loaded from the classpath may refer to images which will normally be available from the classpath as well. Since version 2.8 Jawr can serve such image files by defining an extra instance of the servlet with its init param type set to img. You can find details on how to set it up at the servlet configuration page.
Unlike the normal mapping, this way of referring to resources does not yet allow wildcards (i.e.: jar:/com/mycompany/myapp/** would not work).
This generator allows you to include resources which are stored in a webjars files. WebJars are client-side web libraries (e.g. jQuery & Bootstrap) packaged into JAR files. You will have to include your webjars as dependencies of your project and then reference them as follow :
jawr.js.bundle.foo.mappings=webjars:/jquery/1.11.1/jquery.js, /js/foo.js
To reference webjars resources, you can now use short reference instead of full one. For example, you can now use : webjars:/css/bootstrap.css/ instead of webjars:/bootstrap/3.2.0/css/bootstrap.css To avoid resource reference collision if there multiple resource with the same name in different webjars, you can specify the webjars in parameter between bracket like below :
jawr.css.bundle.foo.mappings=webjars:/css/bootstrap.css[bootstrap]
Important note* : For CSS resources, it is important to note that you should pay attention to the resource path used in your mapping, because this may lead to issues in binary resources (image, fonts, …) references in the generated resource. We strongly advise you to use the resource path after the version number. For example : The bootstrap CSS resource is under */META-INF/resources/webjars/bootstrap/version/css/bootstrap.css* in the webjars file. To reference this resource you should use the path after the version number like :
jawr.css.bundle.foo.mappings=webjars:/css/bootstrap.css[bootstrap]
To be able to use the short reference for webjars resource, you need to add webjars-locator-core library in you classpath. For maven user, you’ll need to define a dependency in your pom.xml :
<dependency> <groupId>org.webjars</groupId> <artifactId>webjars-locator-core</artifactId> <version>0.27</version> </dependency>
Here is the link to the webjars site for more information : [webjars site(http://www.webjars.org/)
Suffix: .less
This one will handle LESS CSS resources to compile them to plain CSS resources.\ This generator is based on Less4j : https://github.com/SomMeri/less4j.\ Here is an example of mapping :
jawr.css.bundle.styles.mappings=/css/foo.less,/css/bar.less
<dependency> <groupId>com.github.sommeri</groupId> <artifactId>less4j</artifactId> <version>1.14.0</version> </dependency>
It is possible to use less resource from classpath or webjars using the following cnfiguration :
jawr.css.bundle.styles.mappings=jar:/css/foo.less,webjars:/bootstrap/3.2.0/less/theme.less
For information, the less generator switched from an implementation based on LessCss Engine to one based on Less4j since the version 3.8, because the previous implementation is not supported anymore.
This one will handle SASS resources to compile them to plain CSS resources.\ This generator is based on Ruby sass-gems. It is direct implementation of sass-lang based on the Ruby implementation.
Here is an example of mapping :
jawr.css.bundle.styles.mappings=/css/foo.scss,/css/bar.scss
To be able to use the SASS Ruby generator, you need to set the property *jawr.css.sass.generator* as follow :
jawr.css.sass.generator=ruby An you'll need also to add JRuby and sass-gems in your classpath. For maven users, you'll need to add the following dependencies in your pom.xml : <dependency> <groupId>org.jruby</groupId> <artifactId>jruby-core</artifactId> <version><IP_ADDRESS></version> </dependency> <dependency> <groupId>org.jruby</groupId> <artifactId>jruby-stdlib</artifactId> <version><IP_ADDRESS></version> </dependency> <dependency> <groupId>com.darrinholst</groupId> <artifactId>sass-java-gems</artifactId> <version><IP_ADDRESS></version> <exclusions> <exclusion> <groupId>org.jruby</groupId> <artifactId>jruby-complete</artifactId> </exclusion> </exclusions> </dependency> </div>
Jawr provides the following properties to configure the Sass Ruby generator.
| Property name | Type | Purpose | Default value |
|---|---|---|---|
| jawr.css.sass.generator.urlMode | String | Defines the way the resource reference (image, font) will be handled. Possible values : “absolute” or “relative” | absolute |
Known limitation :
It’s not possible to use sass resource from classpath.\ The below mapping will not work :
jawr.css.bundle.styles.mappings=jar:/css/foo.scss,jar:/css/bar.scss
This one will handle SASS resources to compile them to plain CSS resources.
Jawr provides 2 types of Sass generator. One based on Vaadin sass compiler, the other based one the sass-gems ruby.
Here is an example of Sass resource mapping :
jawr.css.bundle.styles.mappings=/css/foo.scss,/css/bar.scss
To be able to use the SASS Vaadin generator, you need to set the property jawr.css.sass.generator as follow :
jawr.css.sass.generator=vaadin
And you need to add vaadin sass compiler library in you classpath. For maven user, you’ll need to add a dependency in your pom.xml :
<dependency> <groupId>com.vaadin</groupId> <artifactId>vaadin-sass-compiler</artifactId> <version>0.9.12</version> </dependency>
Jawr provides the following properties to configure the Sass Vaadin generator.
| Property name | Type | Purpose | Default value |
|---|---|---|---|
| jawr.css.sass.generator.urlMode | String | Defines the way the resource reference (image, font) will be handled. Possible values : “absolute”, “mixed” or “relative” | mixed |
Known limitation :
It’s not possible to use sass resource from classpath.
The below mapping will not work :
jawr.css.bundle.styles.mappings=jar:/css/foo.scss,jar:/css/bar.scss
Suffix: .coffee
This one will handle coffeeScript resources to compile them to plain JS resources
jawr.js.bundle.myScript.mappings=/js/foo.coffee,/js/bar.coffee
Configuration properties
Jawr provides the following properties to configure the CoffeeScript generator.
| Property name | Type | Purpose | Default value |
|---|---|---|---|
| jawr.js.generator.coffee.script.options | String | The coffee script compiler options. Please see : http://coffeescript.org/) | None |
| jawr.js.generator.coffee.script.location | String | The coffee script location | net/jawr/web/resource/bundle/generator/js/coffee/coffee-script.js |
| jawr.js.generator.coffee.script.js.engine | String | The JS engine to use for the coffescript generator | the value of ‘jawr.js.engine’ property |
This one will help you to define CSS skin in your bundles. Full docs here.
This one will generates the JS content for CSS skin switcher. To use it you must configure your Jawr configuration file like this :
jawr.js.bundle.common.id=/js/common.js jawr.js.bundle.common.mappings=skinSwitcher:switcher.js
When you use the Jawr style tag for a bundle containing different CSS skin, you can force Jawr to render the links to the alternate CSS skin by using the displayAlternate property.
<jwr:style src="/css/skinnedBundle.css" displayAlternate="true" media="all" />
This will force Jawr to render the links to all the skin associated to /css/skinnedBundle.css. This generator will generates the script to switch from a skin to another by calling the following JS function and passing as parameter the name of the style to switch to:
JAWR.skin.switchToStyle(newStyle);
You can find an example of it’s use in the basic webapplication sample. For more information about CSS skin, you can take a look to the following documentation.
You will find below the class diagram for generators.
The root interface for resource generator is :
net.jawr.web.resource.bundle.generator.ResourceGenerator. All resource generator must implement a method, which defines the mapping for this generator.
/** * Returns the resource generator resolver * * @return the resource generator resolver */ public ResourceGeneratorResolver getResolver();
The getResolver() method returns the resolver, which will be used when mapping you generator to bundles. Jawr will recognize if a resource is handled by a Generator using the resolver, and use your generator when it applies. So, if your resolver is a PrefixResolver, which handle all resources beginning with ‘foo:’, you would map your generator like this:
jawr.js.bundle.one.mappings=foo:somePath
There are 2 main types of generator:
A JS or a CSS generator is an implementation of the interface net.jawr.web.resource.bundle.generator.TextResourceGenerator. This is a simple interface which exposes two methods:
- public Reader createResource(GeneratorContext context); - public String getDebugModeRequestPath();
The getDebugModeRequestPath simply returns a path to be used in debug mode. This is simply a fake script or CSS name and it really has no importance unless you are mapping the Jawr servlet to a suffix different from *.css or .js. 99% of the use cases don’t need to care about this so you can simply return one of three constants: ResourceGenerator.JAVASCRIPT_DEBUGPATH, ResourceGenerator.CSS_DEBUGPATH or ResourceGenerator.IMG_DEBUGPATH:
public String getDebugModeRequestPath() { return ResourceGenerator.JAVASCRIPT_DEBUGPATH; }
Finally, the createResource() method is where the actual generation takes place. This method takes a single parameter of type GeneratorContext, which contains all the information you need to build a dynamic script or CSS. The useful methods are:
Using this information, you should be able to generate a script or CSS and return in in the form of a Reader object (typically a StringReader is sufficient for the task).
An image generator is an implementation of the interface net.jawr.web.resource.bundle.generator.StreamResourceGenerator. This is a simple interface which exposes one method:
Once you have your Generator implemented, you need to register into Jawr in order to use it. This is simply a matter of mapping its classname in the configuration properties file under the key ‘jawr.custom.generators’. If there is more than one, you simply declare them separated by commas:
jawr.custom.generators=com.mycompany.myapp.MyCustomGeneratorImplementation,com.mycompany.myapp.AnotherGenerator
Here is a sample class which you can use to get started. It simply creates a script that displays an alert message with whichever text is used as the path in the mapping:
package net.jawr.example; public class TestGenerator implements TextResourceGenerator { private ResourceGeneratorResolver resolver; public class TestGenerator(){ resolver = new PrefixedPathResolver("example"); } public Reader createResource(GeneratorContext context) { return new StringReader(";alert('Mapping contained:" + context.getPath() + "');"); } public ResourceGeneratorResolver getResolver() { return resolver; } public String getDebugModeRequestPath() { return ResourceGenerator.JAVASCRIPT_DEBUGPATH; } }
With this class in hand, we first register it in our properties config file:
jawr.custom.generators=net.jawr.example.TestGenerator
And now it’s a matter of creating a bundle and use the generator:
jawr.js.bundle.global.id=/bundles/global.js jawr.js.bundle.global.mappings=example:Hello World!,example:And Hello Again!
And that’s it, now add the bundle to any page and when it’s loaded, you should get an alert box with the text ‘Mapping contained:Hello World!’ followed by a second alert box with the text ‘Mapping contained:And Hello Again!’.
If you develop your own generator, which reads content from resources on your server, you must take care of prevent users to access unauthorized resources. You must check if the requested resource is an allowed one or not. For example, the user must not be able to retrieve the files located under /WEB-INF/ or /META-INF/ in your web application, or directly the content of the JSP files.
To check if your generator is sensible to this issue, you must launch your application in debug mode, and then try to reach your resource using the following URL:
http://localhost:8080/myWebAppContext/sample.js?generationConfigParam=myGen:/WEB-INF/web.xml
In this example, myGen is the prefix of the generator. So you must replace it by the prefix of your generator. If you are able to see the content of the web.xml file, this means that you need to change your generator to fix this issue.
Since version 3.9, Jawr introduce a cache mechanism for the generated content. Like for “smart bundling” feature, Jawr is able for some generators to determine if the content change and only in that case, regenerate the resource content.
It is possible to disable resource cache, using the property jawr.use.generator.cache
jawr.use.generator.cache=true
Here is the list of cache property for the built in generators :
| Generator name | **use cache ** |
|---|---|
| i18n messages script generator | true |
| DWR scripts generator | false |
| Commons Validator generator | false |
| Classpath resource generator | true |
| Webjars generator generator | true |
| Less CSS generator | true |
| SASS Ruby generator | true |
| SASS Vaadin generator | true |
| CoffeeScript generator | true |
| Skin generator | false |
| Skin switcher generator | false |


| I l@ve RuBoard |
In Chapter 5, we presented some basic material about Python and COM. If you have never used Python and COM together or are unfamiliar with basic COM concepts, you should review that chapter before continuing here.
In this chapter we take a more technical look at COM and using Python from COM. We initially provide a discussion of COM itself and how it works; an understanding of which is necessary if you need to use advanced features of COM from Python. We then look at using COM objects from Python in more detail and finish with an in-depth discussion of implementing COM objects using Python.
| I l@ve RuBoard |


How to convert .md to .Html
pip install md-to-html
md-to-html -i [Filename] -o [Outputname]
look at
reference


Constructor
new ViewCompileInstruction(targetShadowDOM?: boolean, compileSurrogate?: boolean): ViewCompileInstruction
Creates an instance of ViewCompileInstruction.
Parameters
targetShadowDOM?: boolean
compileSurrogate?: boolean


Hi, I'm Munib Yones!
Computer science student
What I am all about.
Fresh CS graduate looking for position that related to data management /analyses / technical support with a focused-on software where I can apply my skills in data collection, analysis, effective management, problem solving and database development to make it work more effectively. I am also keen to make decisions regarding database management and auditing to avoid major risks. I have completed the final year project before the deadline and that gives me the time to Improve my project to grant the excellent mark resulting of entering the annual project exhibition
Expertise
Professionally drive
Synergistically strategize customer directed resources rather than principle.
Seamlessly leverage
Quickly repurpose reliable customer service with orthogonal ideas. Competently.
Interactively incubate
Interactively myocardinate high standards in initiatives rather than next-generation.
Globally streamline
Dynamically initiate client-based convergence vis-a-vis performance based.
Skills
Work Experience
Technical support Intern
Aljazzera soft
Saudi Arabia, Jeddah
Certified certifications
Introduction to SQL
2015ORACLE ACADEMY
Malaysia, Melaka
Fundamental in SAP ERP
2015SAP ACADEMY
Malaysia, Melaka
Mobile application development
2014PSTP
Malaysia, Melaka
Education
Bachelor of Computer Science
Technical University of Malaysia Melaka
Malaysia , Melaka
Interest
Travel
Proactively extend market-driven e-tailers rather than enterprise-wide supply chains. Collaboratively embrace 24/7 processes rather than adaptive users. Seamlessly monetize alternative e-business.
Design
Assertively grow optimal methodologies after viral technologies. Appropriately develop frictionless technology for adaptive functionalities. Competently iterate functionalized networks for best-of-breed services.
Photography
Dramatically utilize superior infomediaries whereas functional core competencies. Enthusiastically repurpose synergistic vortals for customer directed portals. Interactively pursue sustainable leadership via.
Contact
6791 Al tubah st, Ash Sharafiyah District
Jeddah , Saudi Arabia Mobile Number
+966 56 5979 029 Email
muneby@gmail.com


Today’s Income
Rp. 1.000.000
+2% YesterdayToday’s Income
Rp. 1.000.000
+2% YesterdayToday’s Income
Rp. 1.000.000
+2% YesterdayFeatured
recent order
| invoice | Cashier | Date | Order | amount |
|---|---|---|---|---|
| Mark | Otto | @mdo | @mdo | @mdo |
Today’s Income
Today’s Income
Today’s Income
| invoice | Cashier | Date | Order | amount |
|---|---|---|---|---|
| Mark | Otto | @mdo | @mdo | @mdo |


dtnsend - sends a bundle with payload of file, tmpfile, message, or date
SYNOPSIS
usage: dtnsend [opts] -s <source_eid> -d <dest_eid> -t <type> -p <payload>
common options:
-v verbose -h help -s <eid|demux_string> source eid) -d <eid|demux_string> destination eid) -r <eid|demux_string> reply to eid) -t <f|t|m|d> payload type: file, tmpfile, message, or date -p <filename|string> payload data -e <time> expiration time in seconds (default: one hour) -P <priority> one of bulk, normal, expedited, or reserved -i <regid> registration id for reply to -n <int> copies of the bundle to send -z <time> msecs to sleep between transmissions -c request custody transfer -C request custody transfer receipts -D request for end-to-end delivery receipt -X request for deletion receipt -R request for bundle reception receipts -F request for bundle forwarding receipts -1 assert destination endpoint is a singleton -N assert destination endpoint is not a singleton -W set the do not fragment option -w wait for bundle status reports -E <int> include extension block and specify type -M <int> include metadata block and specify type -O <int> flags to include in extension/metadata block -S <string> extension/metadata block content


Running "global_domination.exe" ... Success!
Observing Humans.
They do not suspect a thing.
Now Monitoring ...


CROAM - objective analysis
In my study for the 'perfect' project analysis tool, I developed a new analysis model , I'll call CROAM from now (Core Recursive Objective Analysis Model).
With this model, one should be able to analyze almost anything. The whole new idea of this model is the fact that it's a recursive model, it gets recursed by refining the objectives.
This model can be used to map business processes, create project plans, ...
I' ll explain this model with an imaginary company called 'Xmastree', a company that sells Christmas trees.
The graph for each objective in this model looks like this :
Example objectives:
- The CEO wants the management to increase the profit, and let the accounting division inform him (the manager) about it.
- The Management wants the Marketing Division to Increase Customer sales, and lets a survey company inform them (the management)
- The Marketing division wants the regional television to publish a documentary about ecologic awareness within the company , and lets the regional television inform the customers.
- The Marketing division wants the national newspaper to publish a marketing campaign, and lets the newspaper inform the customers.
- The Marketing division wants The Marketing division to do a mailing to it's high potentials, and lets the Marketing division inform the customers
- The Management wants the HRM Division to Streamline personnel costs, and lets the accounting division inform them (the management)
- The Hrm division wants the accounting division to report all logistic costs by division and lets the accounting division inform them(the hrm division)
- The Hrm division wants The Hrm division to apply logistic hrm savings and lets The Hrm division inform the management.
- The Management asks the ICT Division to Optimize communication costs, and lets the accounting division inform them (the management)
- The Accounting division wants the accounting division to report profit gains, and lets the accounting division inform the CEO
- The Management wants the Marketing Division to Increase Customer sales, and lets a survey company inform them (the management)
This gives an easy to define analysis method. Each step mentioned in the example above, contains a Requester, a negotiator, an objective, a deliverer and an acceptor.
The following step is to define when a certain objective can be put in a certain state.
As an example, objective 1.2.2 should be put in a Refused state when objective 1.2.1 receives a Decline or Refused state. Objective 1.2.2 should be put in a Request state when objective 1.2.1 receives an Accept state
Using this simple technique one should be able to describe all business processes of a company in a simple way.
The next step for me will be creating a program that implements work flows using this kind of analysis as a proof of concept. The final idea is to implement this in CUDI (my universal database framework).


A ROW record describes a single row on an Excel sheet. ROW records and their associated cell records occur in blocks of up to 32 rows. Each block ends with a DBCELL record. For more information about row blocks and about optimizing your code when searching for cell records, see “Finding Cell Records in BIFF Files EXB0250 ”.
Record Data
|
Offset |
Name |
Size |
Contents |
|
4 |
rw |
2 |
Row number. |
|
6 |
colMic |
2 |
First defined column in the row. |
|
8 |
colMac |
2 |
Last defined column in the row, plus 1. |
|
10 |
miyRw |
2 |
Row height. |
|
12 |
irwMac |
2 |
Used by Excel to optimize loading |
|
14 |
(Reserved) |
2 |
|
|
16 |
grbit |
2 |
Option flags. |
|
18 |
ixfe |
2 |
If fGhostDirty=1
(see grbit
field), this is the index to the XF record for the row.
Otherwise, this field is undefined. |
The grbit field contains the following option flags:
|
Offset |
Bits |
Mask |
Name |
Contents |
|
0 |
2–0 |
07h |
iOutLevel |
Outline level of the row |
|
|
3 |
08h |
(Reserved) |
|
|
|
4 |
10h |
fCollapsed |
=1 if the row is collapsed in outlining |
|
|
5 |
20h |
fDyZero |
=1 if the row height is set to 0 (zero) |
|
0 |
6 |
40h |
fUnsynced |
=1 if the font height and row height are not compatible |
|
|
7 |
80h |
fGhostDirty |
=1 if the row has been formatted, even if it contains all blank cells |
|
1 |
7–0 |
FFh |
(Reserved) |
|
The rw field contains the 0-based row number. The colMic and colMac fields give the range of defined columns in the row.
The miyRw field contains the row height, in units of 1/20 th of a point. The miyRw field may have the 8000h (2 15 ) bit set, indicating that the row is standard height. The low-order 15 bits must still contain the row height. If you hide the row — either by setting row height to 0 (zero) or by using the Hide command — miyRw still contains the original row height. This allows Excel to restore the original row height when you click the Unhide button.
Each row can have default cell attributes that control the format of all undefined cells in the row. By specifying default cell attributes for a particular row, you are effectively formatting all the undefined cells in the row without using memory for those cells. Default cell attributes do not affect the formats of cells that are explicitly defined.
For example, if you want all of row 3 to be left-aligned, you could define all 256 cells in the row and specify that each individual cell be left-aligned. This would require storage for each of the 256 cells. An easy alternative would be to set the default cell for row 3 to be left-aligned and not define any individual cells in row 3.


|
| | Space () |
| |
| | Space (const Space< Scalar > &sp) |
| |
| virtual | ~Space () |
| |
| virtual DataContainer * | buildDataContainer () const =0 |
| | returns a dynamically allocated DataContainer. More...
|
| |
| virtual bool | operator== (const Space< Scalar > &sp) const =0 |
| | compare two vector spaces - useful for sanity checking in applications More...
|
| |
| bool | operator!= (const Space< Scalar > &sp) const |
| |
| virtual bool | isCompatible (DataContainer const &dc) const =0 |
| | detect compatibility with foreign data container - also useful for sanity checking More...
|
| |
| virtual Scalar | inner (DataContainer const &x, DataContainer const &y) const =0 |
| | core linear algebra methods More...
|
| |
| virtual void | zero (DataContainer &x) const =0 |
| | assign to data of zero vector More...
|
| |
| virtual void | linComb (Scalar a, DataContainer const &x, Scalar b, DataContainer &y) const =0 |
| | linear combination y=ax+by. More...
|
| |
| virtual void | copy (DataContainer &tgt, DataContainer const &src) const |
| | virtual convenience methods, implemented in the base class using linComb. More...
|
| |
| virtual void | negate (DataContainer &tgt) const |
| | negate, unary version. More...
|
| |
| virtual void | negate (DataContainer &tgt, DataContainer const &src) const |
| | negation, binary version. More...
|
| |
| virtual void | scale (DataContainer &tgt, Scalar c) const |
| | scale, unary version. More...
|
| |
| virtual void | scale (DataContainer &tgt, Scalar c, DataContainer const &src) const |
| | Scale, binary version. More...
|
| |
| NormRetType | normsq (DataContainer const &x) const |
| | return Norm Squared. More...
|
| |
| NormRetType | norm (DataContainer const &x) const |
| | return Norm. More...
|
| |
| virtual ostream & | write (ostream &str) const =0 |
| | Report state of object to ostream. More...
|
| |
| virtual | ~Writeable () |
| |
| void | write (RVLException &e) const |
| | Report state of object to RVLException. More...
|
| |
template<class Scalar>
class RVL::Space< Scalar >
RVL abstract base class for Hilbert Spaces.
A vector space over a field of scalars is set of objects, called vectors, together with two operations, scalar multiplication and vector addition, obeying certain axioms. Hilbert spaces add inner product op.
Access to vector objects is implemented through access to their underlying data structures (DataContainers). The build() method returns a pointer to a dynamically allocated DataContainer.
The three linear algebra methods "teach the DataContainer
how to behave like a vector" (S. Scott, Y2K).
Definition at line 56 of file space.hh.
Except within other space classes acting as containers, Spaces should always be allocated on the stack.
Various RVL classes store Space references as data members, and RVL does not reference count. Therefore public dynamic allocation of Spaces risks dangling references. However dynamic space construction in containers (intrusive handles) does not create such a risk. The virtual copy constructor (clone) method is protected, to avoid any possibility of dangling references.
Version 1.0: for those who must, we will allow dynamically allocated spaces - caveat emptor!
Implemented in RVL::CartesianPowerSpace< Scalar >, and RVL::StdProductSpace< Scalar >.


|
KlusterKite
0.0.0
A framework to create scalable and redundant services based on awesome Akka.Net project.
|
Testing publishing and resolving integration More...
Public Member Functions | |
| ApiProviderPublishResolveIntegration (ITestOutputHelper output) | |
| Initializes a new instance of the ApiProviderPublishResolveIntegration class. More... | |
| async Task | ConnectionQueryTest () |
| Testing connection query request from ApiDescription More... | |
| async Task | ConnectionMethodQueryTest () |
| Testing connection method query request from ApiDescription More... | |
| async Task | ConnectionQueryWithDoubleFragmentsTest () |
| Testing connection query request from ApiDescription More... | |
| async Task | ConnectionQuerySplitRequestTest () |
| Testing connection query split request from ApiDescription More... | |
| async Task | ConnectionQueryWithAliasesTest () |
| Testing connection query request from ApiDescription More... | |
| async Task | ConnectionMutationInsertTest () |
| Testing connection create request from ApiDescription More... | |
| async Task | ConnectionMutationInsertWithAliasesTest () |
| Testing connection create request from ApiDescription More... | |
| async Task | ConnectionMutationDeleteTest () |
| Testing connection delete request from ApiDescription More... | |
| async Task | ConnectionMutationAdditionalTest () |
| Testing connection delete request from ApiDescription More... | |
| async Task | ConnectionMutationUpdateTest () |
| Testing connection update request from ApiDescription More... | |
| async Task | ConnectionMutationNestedUpdateTest () |
| Testing connection update request from ApiDescription More... | |
| async Task | ConnectionMutationFaultedUpdateTest () |
| Testing connection update request from ApiDescription More... | |
| async Task | NodeQueryTest () |
| Testing node requests from ApiDescription More... | |
Static Public Member Functions | |
| static string | CleanResponse (string response) |
| Removes formatting values from response json More... | |
Testing publishing and resolving integration
Definition at line 48 of file ApiProviderPublishResolveIntegration.cs.
| KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ApiProviderPublishResolveIntegration | ( | ITestOutputHelper | output | ) |
Initializes a new instance of the ApiProviderPublishResolveIntegration class.
| output | The output. |
Definition at line 61 of file ApiProviderPublishResolveIntegration.cs.
|
static |
Removes formatting values from response json
| response | The json string |
Definition at line 71 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionMethodQueryTest | ( | ) |
Testing connection method query request from ApiDescription
Definition at line 201 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionMutationAdditionalTest | ( | ) |
Testing connection delete request from ApiDescription
Definition at line 1191 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionMutationDeleteTest | ( | ) |
Testing connection delete request from ApiDescription
Definition at line 1014 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionMutationFaultedUpdateTest | ( | ) |
Testing connection update request from ApiDescription
Definition at line 1609 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionMutationInsertTest | ( | ) |
Testing connection create request from ApiDescription
Definition at line 680 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionMutationInsertWithAliasesTest | ( | ) |
Testing connection create request from ApiDescription
Definition at line 831 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionMutationNestedUpdateTest | ( | ) |
Testing connection update request from ApiDescription
Definition at line 1456 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionMutationUpdateTest | ( | ) |
Testing connection update request from ApiDescription
Definition at line 1305 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionQuerySplitRequestTest | ( | ) |
Testing connection query split request from ApiDescription
Definition at line 390 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionQueryTest | ( | ) |
Testing connection query request from ApiDescription
Definition at line 81 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionQueryWithAliasesTest | ( | ) |
Testing connection query request from ApiDescription
Definition at line 514 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.ConnectionQueryWithDoubleFragmentsTest | ( | ) |
Testing connection query request from ApiDescription
Definition at line 286 of file ApiProviderPublishResolveIntegration.cs.
| async Task KlusterKite.Web.Tests.GraphQL.ApiProviderPublishResolveIntegration.NodeQueryTest | ( | ) |
Testing node requests from ApiDescription
Definition at line 1760 of file ApiProviderPublishResolveIntegration.cs.


A channel to discuss trading.
Alexfrog30-May-19 02:51 AM
Rebrand coming when KMD at 100k sats. market will be like: KMD was already awesome, doesnt need a rebrand. Then price will drop.
FlyingDutchman30-May-19 02:51 AM
they claim on the official channel that the rebrand and new product launches are coming "later this summer"
lets hope they stick to that
one of KMDs strong points has been its ability to deliver results through the bear market
if we start making promises and never fulfilling them
we become like every other shitcoin on the market
and the 60 second blockchain builder
plus CHIPS gui and new version of barterDEX
basically everything theyve been working on
richardt30-May-19 02:55 AM
Mobile DEX suppose to go public any day now
stnabben30-May-19 02:59 AM
Whats you guys take on EINSTEINIUM (EMC2) ?
Tek30-May-19 03:02 AM
reee
i slept for 3 hours
1
oh wew both kmd and bch broke free
1
richardt30-May-19 03:03 AM
@FlyingDutchman It'll all be ready when it's ready!
FlyingDutchman30-May-19 03:04 AM
lets at least try to get it by the end of the summer
we dont want to miss big bull market bc new tech isnt being pushed out
Alexfrog30-May-19 03:05 AM
KMD is pumping, as is every shitty bitcoin fork lol. Even bitcoin gold and diamond.
richardt30-May-19 03:06 AM
Yeah we'll see. I sincerely hope everything works out and will be different this time around, but we'll see. Just grateful we're finally out of the bear market
Tek30-May-19 03:08 AM
whats a good buy in after this whalebro pumping?
18k?
Alexfrog30-May-19 03:10 AM
holding one's coins from 14k is a good buy
Tek30-May-19 03:12 AM
heh. I bought back at whalebros wall before I went to bed
and just sold
1
yeah well im having luck this time but I still have a huge bag of kmd
all bought above 20k
Alexfrog30-May-19 03:13 AM
im holding my coins from 25k though
Tek30-May-19 03:13 AM
i got coins from 20k up to 28k lol
I fomod at 28k it looked like it was gonna make a new level to 33k
Tek30-May-19 03:24 AM
wtf man(edited)
bsv is still going up
dukeleto30-May-19 03:26 AM
itsatrap.jpg
Tek30-May-19 03:26 AM
i really don't know
csw and calvin might just be pumping millions in it
dukeleto30-May-19 03:26 AM
@Alexfrog trying to figure out how to dump my BTCD without getting a disease
@Deleted User thank you fine sir
1
Tek30-May-19 03:29 AM
ETH might continue its move up too
target for ETH is 0.056
dukeleto30-May-19 03:30 AM
is it time for insane amounts of dumb money to pour into LTC again?


{% extends "layout.html" %} {% block content %}
you are just one step closer help {{ donation.Protagonist.username }}


Food Store
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This is your mysterious dream vacation!
Fly over enormous land figures of Nazca, Peru.
This is your mysterious dream short trip!
Take a tour of Seattle's underground.
This is your adventure dream vacation!
Ski in Georgia (the Country, not the State).
This is your adventure dream short trip!
Go indoor skydiving or take a hot air balloon ride from Snohomish.
This is your explorer dream vacation!
Explore the Egyptian Pyramids.
This is your city tour dream short trip!
Explore Seattle through the smartphone Scavenger Hunt game.
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Drive a Porsche from Cancun to the Himalayas.
This is your eventful dream short trip!
Learn more about Native Americans with a trip to Tillicum.
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Calm your mind in a Wellnes Spa Resort.


| DiscreteWavelets Toolbox |
Convert from YCbCr space to RGB space
A=YCbCrToRGB(B)
A = YCbCrToRGB(B) takes either a vector of length 3 or a three-dimensional array with depth three and converts the input to RGB space.
A = YCbCrToRGB(B,'DisplayMode','True') scales the conversion for display with Matlab's image or ImagePlot. In this case,
A is assumed to be a three-dimensional array.
If B is a length 3 vector, then the 0 <= B(1) <= 1 and -.5 <= B(2),B(3) <= .5.
If A is a three-dimensional array, then its depth must be three and it is assumed that the red, green, and blue channels are contained in A(:,:,1), A(:,:,2), and A(:,:,3), respectively. The elements of A(:,:,1) must be integers y in the range 16 <= y <= 235 and the elements of A(:,:,2) and A(:,:,3) must be integers i in the range 16 <= i <= 240.See Section 3.2 for more information on color space conversion.
Convert the YCbCr vectors to RGB space.
v=RGBToYCbCr([1 0 0])' red=YCbCrToRGB(v)' w=RGBToYCbCr([0 0 1])' blue=YCbCrToRGB(w)'
produces
v = 0.0012 -0.0007 0.0020 red = 1.0000 0.0000 -0.0000 w = 0.0004 0.0020 -0.0003 blue = 0.0000 0.0000 1.0000
Convert Y Cb Cr channels to RGB space.
clr=ImageNames('ImageType','Color'); %Get names of all color images included with the toolbox A=ImageRead(clr{5}); %Read a color image B=RGBToYCbCr(A,'DisplayMode','True'); %Convert to YCbCr space [Y,Cb,Cr]=Split3D(B); %Get the channels ImagePlot(Y,'Title','Y Channel'); %Plot the Y channel figure ImagePlot(Cb,'Title','Cr Channel'); %Plot the Cr channel figure ImagePlot(Cr,'Title','Cb Channel'); %Plot the Cb channel
Now convert to YCbCr space and plot the resulting images
A=YCbCrToRGB(B,'DisplayMode','True'); %Do the color space conversion [R,G,B]=Split3D(A); %Split A into the three channels figure ImagePlot(R,'ChannelColor',[1 0 0]); %Plot the red channel figure ImagePlot(G,'ChannelColor',[0 0 1]); %Plot the green channel figure ImagePlot(R,'ChannelColor',[0 0 1]); %Plot the blue channel figure ImagePlot(A);
© 2007-2008 Patrick Van Fleet


Poruri Sai Rahul,
BS & MS in Physics,
Indian Institute of Technology - Madras,
Chennai, India.
My research interests lie in Astronomy & Astrophysics. I've worked with Prof. Jeremy Mould to construct a Tully-Fisher relation for SAMI galaxies and I've worked with Prof. Anand Narayanan to replicate and extend the results of Richards et al. (2001) on the Colors of Quasars to 146,659 quasars in the SDSS DR9.
I've also attended the Pulsar Observatory for Students program at the Ooty Radio Telescope, NCRA-TIFR, the ARIES Training School on Observational Astronomy and the IIST Astronomy & Astrophysics School.


9 mdepriv: Synthetic scores of multiple deprivation
9.1 Purpose
mdepriv
is a R package for combining binary, continuous and suitably
transformed ordinal items/indicators of deprivation into synthetic
measures of deprivation. As such, it is a tool of poverty analysis. It
is suitable also for generating composite measures of severity and
vulnerability in the humanitarian realm. The R implementation translates
the original Stata version by Pi Alperin & Van Kerm
(2009), with additional
features (notably, non-integer sampling weights are admitted).
mdepriv returns unit-level synthetic scores of multiple deprivation and their statistical summaries. It offers several methods for determining item/indicator weights in response to user preferences for rewarding better discrimination and penalizing redundancy.
mdepriv is particularly appropriate in situations where the underlying concept of deprivation / severity / vulnerability is intuitively multi-dimensional, but the structure of dimensions is poorly understood; plausibly they overlap, i.e. they reinforce each other to unknown degrees.
Also, the measures produced under mdepriv do not presume normative
standards (e.g., poverty lines). There are no a-priori cut-offs of the
kind that are fundamental to multi-dimensional poverty measures in the
Alkire-Foster tradition (implemented in R for example in the functions
svyafc
and svyafcdec
of the package
convey
). Shortfall
indicators (e.g., years of basic education missed) can be used the same
way as non-normative ones (e.g., workdays lost to illness).
9.2 Installation
# install package devtools if not yet installed
# install.packages("devtools")
# install fast from GitHub without vignettes (not recommanded)
# devtools::install_github("a-benini/mdepriv")
Fundamentally, the four methods
- Equi-proportionate
- Desai & Shah (1988)
- Cerioli & Zani (1990)
- Betti & Verma (1998)
differ by their increasing sensitivity to deprivations / adverse conditions suffered by the poorest / most oppressed units (individuals, households, communities). The idea is to weight more strongly specific deprivations / adverse conditions that the more advantaged units have overcome, but which are still afflicting those at the bottom. Typically, in poverty studies, this makes good sense with durable household assets, which are observed as dichotomous “has / does not have” and recorded as binary (0/1) variables.
In humanitarian assessments it is less common that the severity of a lacking / suffering / threat is inversely proportionate to its prevalence. When prevalence-dependent weighting is not appropriate, mdepriv gives the user three options:
- Equi-proportionate weighting
- Unequal weights chosen for substantive considerations
- Switching off prevalence-sensitivity
This third option is meaningful primarily in combination with the Betti-Verma method. This method deserves particular attention. Its defining feature is a double-weighting algorithm:
- The first weighting factor gauges the discriminating power of an item / indicator through its coefficient of variation (= standard deviation / mean). For dichotomous items / indicators, this implies high sensitivity to prevalence (the C.o.V. grows exponentially as the proportion tends towards zero). For continuous ones, higher C.o.V.s imply higher information content.
- The second weighting factor results from the correlations among the items / indicators. Those correlated strongly positively with most others are considered more highly redundant and are penalized with lower weights. Those with comparatively low positive or negative sums of correlation coefficients are considered capturing more unique aspects of deprivation / humanitarian conditions and are rewarded with higher weights.
Betti-Verma is the only one among the four methods sensitive to the information content of continuous items / indicators. mdepriv automatically computes the weight of each item / indicator proportionate to the product of its two weighting factors.
The mdepriv
function makes the second weighting factor available also for the other three methods, but not all combinations are practically meaningful. mdepriv
automatically recognizes the appropriate type of correlations between pairs of items / indicators, but the user can impose a particular type collectively on all pairs (rarely meaningful!).
When the user opts for double-weighting (other than in Betti-Verma, where it is the default), the options have to be specified for both factors. mdepriv
notation for the first factor is wa
, for the second it is wb
. However, not all combinations are practically meaningful. Recommended combinations depend on the analytic objective. Plausibly, the most relevant are:
| Objective | First weighting factor (wa) | Second weighting factor (wb) |
|---|---|---|
| Indifferent to prevalence (dichotomous items) and to information content (continuous). But controlling for redundancy is important. | Equi-proportionate | on |
| Items are all dichotomous. Limited sensitivity to low prevalence desired. Not controlling for redundancy. | Desai-Shah | off |
| Items are all dichotomous. High sensitivity to low prevalence desired. Not controlling for redundancy. | Betti-Verma | off |
| All items are continuous, and controlling for redundancy is important. | Betti-Verma | on |
| Items are mixed dichotomous / continuous. Indifferent to prevalence of the dichotomous, but concerned for information content of the continuous. Redundancy control is important. i.e. Two-level deprivation / severity model: | ||
| Level 1: Combine all dichotomous items, save scores as one more continuous indicator for the second level. | Equi-proportionate | on |
| Level 2: Combine continuous items and indicator saved from first level. Produces aggregate deprivation / severity statistic. | Betti-Verma | on |
The Cerioli-Zani model appears to be primarily of historic interest. It was one of the first to pursue the so-called fuzzy-set approach to multi-dimensional poverty measurement, which Betti and Verma subsequently deepened. The interested user may consult the reader edited by Lemmi and Betti (2006), but familiarity with fuzzy sets is not required for the understanding and application of mdepriv.
As a final introductory remark, it should be said that the Betti-Verma method is particularly appropriate when a concept (deprivation, severity of conditions, etc.) has many aspects, its dimensionality is not well understood, and classical methods to unravel the dimensions (e.g., factor analysis) are likely distorted by redundancies among the available indicators.
The following focuses on the technical handling of the mdepriv
package. Context and rationale are not discussed here. The purpose is to walk the user through the manifold arguments and outputs of the core function mdepriv
. Familiarity with the basics of R is presumed. Still, things are kept at a pretty low skill level so that users with little R experience can follow. The code provided is intended as copy-and-paste material, which users can modify for practice or for real-world data analysis.
Chiefly we will use the simulated dataset simul_data
with 100 observations, which are enough to demonstrate functionality. To showcase a two-level deprivation model we put the dataset MSNA_HC
to use. Both datasets are part of the mdepriv
-package; thus they do not require further sourcing.


Before you get started you should create a God user to make changes at a later point
Click the button to get your wallet address showing you are God. If the value is 0 something has gone wrong
This will set the name of the Lawyer for this address. It can only be run once.
Click the button to get the Lawyer Name for his wallet
The data isn't store in the blockchain only a hash of the data. You can set the URL where the data will be stored here. This function is bound to database 0 and can only be run once.
Click the button to get url address.
Set the name of the document, as well as include some hash. This text will automatically be hashed and stored in the blockchain
Javascript calls being made:


Status and information flowing endlessly, giving a certain ambience.
Even if information is not functionally meaningful, the experience is enhance by giving a feeling of authenticity.
Presumably, you want to fill the screen pretty evenly, if browser were in fullscreen mode. But also becareful not to overflow or else you get scrollbars that spoil the effect a little. Hopefully this page is clean and clear enough that you could copy it, rename it, then start copy and pasting segments that you like and just replace the content and order a little and then you have yourself a custom faux console.
Scan cycle 1,200,342 in progress. — μJT coefficient, in °K/Pa
| Hydrogen | 4.0402 | H2 | -.052 |
| Aqua | 2.040 | H2O | .082 |
| Nitrogen | 70.0402 | N2 | .063 |
| Oxygen | 11.0402 | O2 | .077 |
| Ozone | 1.0233 | O3 | .077 |
| Carbon Monoxide | .0402 | CO | .101 |
| Carbon Dioxide | .0023 | CO2 | .124 |
| Nitrous Oxide | .0200 | N2O | .091 |
| Acetylene | .0333 | C2H2 | .034 |
| Ethylene | .0233 | C2H4 | .033 |
| Propane | .0333 | C3H8 | .061 |
| Methane | 500 | CH4 | 7002 |
| Methanol | 70 | CH3OH | 125 |
| Ethanol | 30 | C2H6O | 125 |
| 2-propanol | 30 | C3H8O | 125 |
| 1-butanol | 50 | C4H9OH | 125 |
| Formaldehyde | 5 | CH2O | 12 |
| Acetaldehyde | 30 | CH3CHO | 15 |
| Propionaldehyde | 50 | CH3CH2CHO | 125 |
| Toluene | 6 | C7H8 | 27 |
| Perfluoropropane | 100 | C3F8 | 245 |
| Ammonia | 4 | NH3 | 12 |
Relative Humidity: 42%
| - |
| - |
| - |
| - |
| - |
| = |
| — |
| - |
| - |
| - |
| - |
| - |
Goldilocks bounds:
| Port | Central | Starboard | |
|---|---|---|---|
| Bow | 22.040 | 21.34 | 20.34 |
| Mid | 24.040 | 30.34 | 21.43 |
| Aft | 22.040 | 21.37 | 22.14 |
Ambient Temparature 23°C scale of Kelvin w/ centigrade range . Add in trends, or at least deltas
Atmospheric Autoignition Temperature: 536°C
Average Accoustic Energy Load: 90.2mJ
MAG FLD STR: 100 ev
ELEC FLD STR: 58 CN
WARP FLD STR: 240 Cch
| α | β | γ | n | x | |
|---|---|---|---|---|---|
| Bow | 2.040 | 1.34 | 0.24 | 0.34 | 1.34 |
| Mid | 2.040 | 1.34 | 2.34 | 3.57 | 1.88 |
| Aft | 2.040 | 1.37 | 1.32 | 1.76 | 1.34 |


Celtics Own Warriors in the Third Quarter of Big Victory
Over the last four seasons, the Golden State Warriors have owned the third quarter. Any game, no matter what the score at halftime, has seemed to tilt their way as soon as the second half begins. The Boston Celtics turned that notion on its head Thursday night, completely taking over in the third against the Warriors. And after they made the defending champions sweat, they outfought them in the fourth quarter for a shocking 92-88 victory. It was a strong enough performance by the Celtics that Stephen Curry was asked after the game about potentially returning to Boston for the N.B.A. Finals. Curry noted that the Celtics would have to get past Cleveland first but was far from dismissive. “I hear the weather is great here in June,” he said, drawing a big laugh from the assembled crowd of reporters. It was a game of highs and lows for Boston. Jaylen Brown had multiple highlight-reel dunks, Al Horford was quietly excellent, and the team reeled off an outrageous 19-0 run in the third quarter. But for much of the night they were struggling to overcome a terrible start from both Kyrie Irving and Jayson Tatum. In the end, the early struggles by those two starters proved inconsequential, as Boston’s winning streak reached 14 games thanks in part to Irving and Tatum being right in the middle of the action in the game’s closing moments.
Lyubomir Tomanov


2 Corinthians 11:21
I speak as concerning reproach, as though we had been weak. Howbeit whereinsoever any is bold, (I speak foolishly,) I am bold also.


title = "About" url = "/about" layout = "layoutPage" is_hidden = 0 robot_index = "index" robot_follow = "follow" [RecordList skill] modelClass = "Avirdigital\Elm\Models\Skill" scope = "-" scopeValue = "{{ :scope }}" displayColumn = "name" noRecordsMessage = "No records found" detailsPage = "-" detailsUrlParameter = "id" pageNumber = "{{ :page }}" sortColumn = "sort_order" sortDirection = "desc" whereIsActive = 1 [RecordList work] modelClass = "Avirdigital\Elm\Models\Work" scope = "-" scopeValue = "{{ :scope }}" displayColumn = "title" noRecordsMessage = "No records found" detailsPage = "-" detailsUrlParameter = "id" pageNumber = "{{ :page }}" sortColumn = "created_at" sortDirection = "desc" whereIsActive = 1 ==
{{ rec.description }}


The Game of Life, also known simply as Life, is a cellular automaton devised by the British mathematician John Horton Conway in 1970. Wiki
The game is a zero-player game, meaning that its evolution is determined by its initial state, requiring no further input. One interacts with the Game of Life by creating an initial configuration and observing how it evolves, or, for advanced players, by creating patterns with particular properties.
The universe of the Game of Life is an infinite, two-dimensional orthogonal grid of square cells, each of which is in one of two possible states, alive or dead, (or populated and unpopulated, respectively). Every cell interacts with its eight neighbours, which are the cells that are horizontally, vertically, or diagonally adjacent. At each step in time, the following transitions occur:
The initial pattern constitutes the seed of the system. The first generation is created by applying the above rules simultaneously to every cell in the seed; births and deaths occur simultaneously, and the discrete moment at which this happens is sometimes called a tick. Each generation is a pure function of the preceding one. The rules continue to be applied repeatedly to create further generations.


R/classify_occ.R
classify_occ.Rd
Classifies occurrence records in levels of confidence in species identification
classify_occ( occ, spec = NULL, na.rm.coords = TRUE, crit.levels = c("det_by_spec", "not_spec_name", "image", "sci_collection", "field_obs", "no_criteria_met"), ignore.det.names = NULL, spec.ambiguity = "not.spec", institution.code = "institutionCode", collection.code = "collectionCode", catalog.number = "catalogNumber", year = "year", date.identified = "dateIdentified", species = "species", identified.by = "identifiedBy", decimal.latitude = "decimalLatitude", decimal.longitude = "decimalLongitude", basis.of.record = "basisOfRecord", media.type = "mediaType", occurrence.id = "occurrenceID", institution.source, year.event, scientific.name, determined.by, latitude, longitude, basis.of.rec, occ.id )
| occ | data frame with occurrence records information. |
|---|---|
| spec | data frame with specialists' names. See details. |
| na.rm.coords | logical. If |
| crit.levels | character. Vector with levels of confidence in decreasing
order. The criteria allowed are |
| ignore.det.names | character vector indicating strings in
|
| spec.ambiguity | character. Indicates how to deal with ambiguity in
specialists names. |
| institution.code | column name of |
| collection.code | column name of |
| catalog.number | column name of |
| year | Column name of |
| date.identified | Column name of |
| species | column name of |
| identified.by | column name of |
| decimal.latitude | column name of |
| decimal.longitude | column name of |
| basis.of.record | column name with the specific nature of the data record. See details. |
| media.type | column name of |
| occurrence.id | column name of |
| institution.source | deprecated, use |
| year.event | deprecated, use |
| scientific.name | deprecated, use |
| determined.by | deprecated, use |
| latitude | deprecated, use |
| longitude | deprecated, use |
| basis.of.rec | deprecated, use |
| occ.id | deprecated, use |
The occ
data frame plus the classification of each record
in a new column, named naturaList_levels
.
spec
data frame must have columns separating LastName
,
Name
and Abbrev
. See create_spec_df
function for a easy way to produce this data frame.
When ignore.det.name = NULL
(default), the function ignores
strings with "RRC ID Flag", "NA", "", "-" and "_".
When a character
vector is provided, the function adds the default strings to the provided
character vector and ignore all these strings as being a name of a taxonomist.
The function classifies the occurrence records in six levels of confidence in species identification. The six levels are:
det_by_spec
- when the identification was made by a specialists
which is present in the list of specialists provided in the spec
argument;
not_spec_name
- when the identification was made by a name who is
not a specialist name provide in spec
;
image
- the occurrence have not name of a identifier, but present
an image associated;
sci_collection
- the occurrence have not name of a identifier,
but preserved in a scientific collection;
field_obs
- the occurrence have not name of a identifier,
but it was identified in field observation;
no_criteria_met
- no other criteria was met.
The (decreasing) order of the levels in the character vector determines the classification level order.
basis.of.record
is a character vector with one of the following
types of record: PRESERVED_SPECIMEN
, PreservedSpecimen
,
HUMAN_OBSERVATION
or HumanObservation
, as in GBIF data
'basisOfRecord'.
media.type
uses the same pattern as GBIF mediaType column,
indicating the existence of an associated image with stillImage
.
Arthur V. Rodrigues


I am excited to share my portfolio with you. I am a good candidate for the role, because I have experience working with many types of people, and have performed research, development, and data entry in my previous analytical positions. In addition, I have a studied computer comprehension that allows me to troubleshoot many software and hardware issues. It has been great exercise for problem solving, thinking, and seeking efficiency. I have more than a decade of diverse professional experience, including project management at Honda Research and Development, production supervision at Jeni's Splendid Ice Cream, systems and machine maintenance at Umicore Specialty Materials Recycling, and administration and engineering operations at my grandparents’ farm. This experience, and my post-secondary education, have prepared me well to assist in achieving project goals and organizational outcomes at your organization. Throughout my career, I have applied my aptitude for problem-solving and a technology-based education to reach any objective I set out to achieve. From a young age, my family has inspired me to work with enthusiasm and commitment. The discipline I learned from my parents, both U.S. Marine Corps service members, and my grandparents, commercial farmers, has kept me focused in work and life. My aunt, a Pulitzer Prize-winning journalist, taught me the importance of passion, and instilled in me a drive to ask meaningful questions in order to explore new perspectives. While my formal training in writing is limited, it is bolstered by significant research and practice. I am confident in my unique style and strong voice. Being a skilled communicator easily connects me with new people. My passion for photography and visual art has connected me with a rich community of artists and makers, and given me the opportunity to organize events. Additionally, computer technology has been a favorite hobby of mine since I was a young child. I am comfortable installing and troubleshooting a variety of hardware and software. I feel this diverse life experience, combined with my strong professional skill set, has prepared me to excel at any project I will encounter in the role of Help Desk/Computer Support. As science historian James Burke said, innovation happens in the spaces between formal disciplines. I recently moved back to my hometown of Cleveland with my fiancee, and wish to find a position at an organization that shares my values of collaboration and commitment to community growth. I would very much like the opportunity to learn how I can meet the demands of this position and advance the overall mission of your company. Thank you for reviewing my site.
Dear Doctor is an application made to give people the ability to record intake (food & drink) as well as symptoms. This information will be presented in table form to be shared with the user's healthcare provider in order to find potential correlations between symptoms and intake over time.