There are various global options that can be set for {gtsummary}. Here we review a complete list of options available to users.
The {gtsummary} package includes various default functions for styling and formatting statistics. These defaults can be modified with global options.
P-values are reported throughout {gtsummary} tables. The default function to style p-values is style_pvalue()
, where large p-values are rounded to one decimal place. Use the gtsummary.pvalue_fun
option to change the function that styles p-values. For example, to report large p-values rounded to two decimal places rather that one, change the default function to style_pvalue(x, digits = 2)
.
or equivalently
In tbl_summary()
, the default function for styling percentages is style_percent()
. If you’d like to update the default, for example, because you’d prefer percentages rounded to one decimal place, you may include the gtsummary.tbl_summary.percent_fun
option.
Similar to the above options, the default function for styling estimates in tbl_survival()
can be modified with gtsummary.tbl_survival.estimate_fun
.
{gtsummary} uses the {gt} package to print all summary tables. In addition to supporting {gt}, the {gtsummary} package works well with knitr::kable()
. This is particularly useful when outputting documents to Microsoft Word. If the {gt} package is not installed, {gtsummary} will fall back to knitr::kable()
. To explicitly set the printing engine, set the option in the script or in the user- or project R profile, .Rprofile
.
or
Output from {gt} is more full-featured compared to a summary table produced with {kable}. For example, {gt} summary tables can include indentation, footnotes, and spanning header rows.
Tables created with the {gt} package are incredibly customizable. You can set an option to apply additional {gt} formatting to all {gtsummary} tables. Every table returned from {gtsummary} contains a list of {gt} calls that are applied when printed. For example, here are the first few associated with a tbl_summary()
table.
library(gtsummary)
tbl_summary(trial)$gt_calls %>% head(n = 4)
#> $gt
#> gt::gt(data = x$table_body)
#>
#> $cols_align
#> gt::cols_align(align = 'center') %>% gt::cols_align(align = 'left', columns = gt::vars(label))
#>
#> $fmt_missing
#> gt::fmt_missing(columns = gt::everything(), missing_text = '')
#>
#> $tab_style_text_indent
#> gt::tab_style(style = gt::cell_text(indent = gt::px(10), align = 'left'),locations = gt::cells_data(columns = gt::vars(label),rows = row_type != 'label'))
You may append additional {gt} calls to this list using the gtsummary.as_gt.addl_cmds
option—with the following caveats:
Only include {gt} functions you want to apply to all tables. For example, a {gt} function that changes the font size would be appropriate. A table-specific header may not.
All {gt} functions must be referenced using the double-colon prefix (i.e. gt::foo()
). These functions will execute when the {gt} library is not loaded.
Do not include the data=
argument in any {gt} function call. The function will appear in a chained sequence of {gt} calls with the %>%
operator. The data argument is taken from the previous function in the sequence.
In the example below, the font size and cell padding are reduced globally.
add_p()
To update the default tests in the add_p()
function, you can set the following global options.
| Option Name | Tests Modified |
|---|---|
| gtsummary.add_p.test.continuous_by2 | continuous variables with 2-level by variable |
| gtsummary.add_p.test.continuous | continuous variables with 3- or more level by variable |
| gtsummary.add_p.test.categorical | categorical/dichotomous variables |
| gtsummary.add_p.test.categorical.low_count | categorical/dichotomous variables with minimum expected count <5 in one cell |
| gtsummary.add_p.test.categorical.group_by2 | categorical/dichotomous grouped/correlated variables with 2-level by variable |
| gtsummary.add_p.test.continuous.group_by2 | continuous grouped/correlated variables with 2-level by variable |
For example, to report the t-test and one-way ANOVA for continuous variables, use the following options:


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Gelfand: Chunk 10 - Factoring 101
January 17, 2017
Numbers have factors. The number has factors of and (as in ) and also and (as in ).
Expressions also have factors.
The expression has the factors and . We can write this as .
The expression has the factors and .
I’m assuming these two factorisations Which is what we call pulling out factors. look familiar to you as the Square-of-a-Sum and Difference-of-Squares. (Take a glance back at Chunk 6 - Squares, Sums, Differences etc. if you need to.)
If all this looks incredibly like we’re just doing the reverse of what we’ve been doing up til nowWhich has been called expanding by the way. you’d be right. But it’s harder. Expanding is just laboriously following a bunch of rules. You need to pay attention, but you don’t need to think. With factoring it’s hard and you need to think a lot.
It’s for this reason that factoring is something I remember utterly failing at in school - I had a mental block about it.
Consequently I’m going to go slowly (and break this topic into multiple posts) if only for my own benefit.
Gelfand Problem 107(d)
You can brute-force this one by just staring at it hard and figuring out how it should shake out, but there is a better way. And better ways are, well, better.
First the starting point
You don’t need to be a maths genius to spot that our powers of are going up by one at a time (especially if you recall that anything to the power of is and that is ). You might also have eagle-eyed that we have four of them. This means that we can probably find some repetition.
And we can, possibly starting off in the second pair of powers.
Given this, we can then, to make the repetition of really clear
Which then just leaves us to collect the and together and we have a nice result
Tricks Arising (Pt. 1)
When Factoring, Look for Patterns of Common Multiplicands
This initial pattern-spot we used in Problem 107(d) (above) (of the shared multiplicand) helps a lot in many factorings. It’s a trick you’ll rely on a frequently, and get better at intuitively spotting as you go on.
When trying to spot these, things which can help are making powers of zero and super-evident
And making co-efficients explicit can also sometimes come in handy
Starting with Some Simple Ones
With our new-found confidence in hand, let’s march onward.
Gelfand Problem 107(c)
After banging my head on this for a while I caved and went to the answers by Durham. His first point made perfect sense and I realised I’d been constrained in my thinking - I’d been looking for a pattern of a pair of terms, but as I had an input consisting of an odd number of monomials this would never work. I had to try a different number. That number turns outFor a possible first step anyway. to be another odd number, and that odd number is three.
Why three? Because we have fifteen terms (an odd number) we couldn’t use two. But fifteen divides into three nicely. That’s why three.
Can we go further than this? (I.e. factor the ) Durham says no, but beacuse he’s using terminology I’m not yet entirely familiar with to explain why, I’m going to leave it here - is it fundamentally beacuse we have five remaining terms, but five is a prime? Perhaps. Anyway, it feels as if the learning goal has been achieved.
What Durham does explain is what would have happened if we’d had one more term in our starting point, and it is instructive to re-state what happened here.
Here we can consider the in the same manner that we considered our original starting point.
There is a minor subtlety to notice - we’re going to have to start nesting our parentheses. That’s conceptually not too problematic for me (I coded some Clojure once which was far worse than this) but it’s worth pointing out. I, following Durham, have used square brackets (‘[ and ‘]’) for this inner parentheses.
And yet again, we have another pattern we can factor further in the same way
Phew!
Before we move on, its worth pointing out that Durham reckons and an both be further factored, but he’s sitting on a mound of additional knowledge that I’m not (yet) party to, so I’m going to leave it here.
Gelfand Problem 107(d)
After that minor brain-melting, 107(d) is a nice little re-applcation of the core concepts we already have at out disposal. To make things clear, it helps to make all powers and co-efficients super-evident, just as we highlighted earlier
Gelfand Problems 109(a) and (b)
Another lesson to learn here. When multiplying polynomials we collect similar terms, so when we’re factoringWhich is essentially attempting to fall back through this trapdoor. it seems perfectly reasonable to have to split up what had previously been collected.
Problem (a) first
And now problem (b)
(b) is a little different than the ones we’ve seen. It only has one variable, but things still work in the same way as before.
Tricks Arising (Pt. 2)
When Factoring, It Can Help to Split Similar Terms
Remember the ones you collected when you were doing the busy-work of obtaining nice, clean “Standard Form” polynomials? Well if you’re working backwards (as you are when “Factoring Down the Line”) then you need to break things up.
How do you know which term to split? A good guess Though I’ve not tested this theory fully. is to pick the term with the largest co-efficient. E.g in the following from Gelfand 109(b) it’s .
Why the biggest? Because that then helps you when you get to the next question, how do you know where to the co-efficient of your chosen term numerically? It seems When things are simple at least. that looking at the other, smaller co-efficients can give you a clue. E.g. in the following from Gelfand 109(a), these are (for ) and (for ), and added together, these give which is the co-efficient of the thing we’re looking to split ().
Please note, this idea is from my own head, and may be revised, or updated at a later stage.
Gelfand Problems 110(a), (b) and (c)
Now on to problem 110(a). This one I found challenging too. We’re supposed to be learning again. I took it step by step.
Checking again against Durham, I ended up at the right answer but he’s keen to show there is a hidden realisation and a consequent shortcut. I could have also noticed that this is a perfect square, but just using rather than .
I must admit, this passed me by, though it makes sense given the output of my working.
110(b) next, but now looking out for this additional element
Now I’m aware of it, this too is a perfect square, but of rather than . Let’s keep stepping it through though
Great. Now the final one, 110(c)
All good. In fact, this is actually getting a little easy. Surely there must be a catch…?
Unfortunately there is, and that’s the topic of the next post in this series.


preact-habitat is a 1.6kb module that will help you ship your Preact components to any world wide DOM page in a very easy and neat way.
What's new in v1.0.0:
✨ Pass props from client's HTML to your components
✨ Bundle multiple independent widgets and mount them seperatly
✨ Mount multiple clones of a widget with different props with new `data-mount` attribute


Package org.revapi
Interface Element<E extends Element<E>>
-
- Type Parameters:
E
- the common base class of all elements of some api analyzer
- All Superinterfaces:
Comparable<E>
- All Known Implementing Classes:
BaseElement
,SimpleElement
public interface Element<E extends Element<E>> extends Comparable<E>
An element in a forest representation of given "language" under API inspection. In case of programming languages this will usually be a (trimmed down) abstract syntax tree, in case of XSD this can be an actual DOM tree.An element is comparable with all other element types for given language, giving a total ordering across all and any element types given language defines.
The
Comparable.compareTo(Object)
method is used by Revapi to match up the pairs of elements from the old and new API. Revapi sorts the elements from old and new API (using their natural order, i.e. using thecompareTo
method) and then iterates through both sets at the same time, comparing the elements.
The result from the above comparison is handed over to the difference analyzer which is assumed to do a more detailed analysis on the elements and return a (possibly empty) set of differences.API traversal outline Comparison Meaning Result Iteration Progress old < new New is considered removed from the API (old, null) Old moves forward, new stays old > new Old is considered removed from the API (null, new) New moves forward, old stays old == new New is considered equal to old (old, new) Old moves forward, new moves forward - Since:
- 0.1
- Author:
- Lukas Krejci
- See Also:
CoIterator
-
-
Method Summary
All Methods Instance Methods Abstract Methods Default Methods Deprecated Methods Modifier and Type Method Description default <T extends Element<?>>
Tas(Class<T> type)
Casts this element to the provided type.API
getApi()
Archive
getArchive()
SortedSet<E>
getChildren()
default Set<Reference<E>>
getCumulativeReferencedElements()
This returns thereferenced elements
of this element and of all its children, recursively.default Set<Reference<E>>
getCumulativeReferencingElements()
This returns thereferencing elements
of this element and of all its children, recursively.String
getFullHumanReadableString()
Provides the full "path" to the element in the forest in a human readable way.E
getParent()
default Set<Reference<E>>
getReferencedElements()
If the API analyzer supports the feature, this returns the set of elements that are referenced by this element in some way (typically, those would be the elements somehow used by this element).default Set<Reference<E>>
getReferencingElements()
If the API analyzer supports the feature, this returns the set of elements that reference this element in some way (typically, those would be the use sites of this element).<T extends Element<E>>
Iterator<T>iterateOverChildren(Class<T> resultType, boolean recurse, Filter<? super T> filter)
Deprecated.use the more standardstream(Class, boolean)
<T extends Element<E>>
List<T>searchChildren(Class<T> resultType, boolean recurse, Filter<? super T> filter)
Deprecated.in favor ofstream(Class, boolean)
<T extends Element<E>>
voidsearchChildren(List<T> results, Class<T> resultType, boolean recurse, Filter<? super T> filter)
Deprecated.in favor ofstream(Class, boolean)
void
setParent(E parent)
Sets a new parent.default <T extends Element<E>>
Stream<T>stream(Class<T> elementType, boolean recurse)
A stream equivalent ofiterateOverChildren(Class, boolean, Filter)
.-
Methods inherited from interface java.lang.Comparable
compareTo
-
-
-
-
Method Detail
-
as
default <T extends Element<?>> T as(Class<T> type)
Casts this element to the provided type.- Parameters:
type
- the type to cast this instance to- Returns:
- this cast as the provided type
- Throws:
ClassCastException
- if this instance cannot be cast to the provided type
-
getApi
API getApi()
- Returns:
- the API version this element comes from
-
getArchive
@Nullable Archive getArchive()
- Returns:
- the archive the element comes from or null if that cannot be determined
-
setParent
void setParent(@Nullable E parent)
Sets a new parent.- Parameters:
parent
- the new parent of this element
-
getFullHumanReadableString
String getFullHumanReadableString()
Provides the full "path" to the element in the forest in a human readable way. This method is meant to be used by the reporters to identify the element in the reports.- Returns:
- human readable representation of the element
-
getReferencingElements
default Set<Reference<E>> getReferencingElements()
If the API analyzer supports the feature, this returns the set of elements that reference this element in some way (typically, those would be the use sites of this element).
-
getCumulativeReferencingElements
default Set<Reference<E>> getCumulativeReferencingElements()
This returns thereferencing elements
of this element and of all its children, recursively.
-
getReferencedElements
default Set<Reference<E>> getReferencedElements()
If the API analyzer supports the feature, this returns the set of elements that are referenced by this element in some way (typically, those would be the elements somehow used by this element).
-
getCumulativeReferencedElements
default Set<Reference<E>> getCumulativeReferencedElements()
This returns thereferenced elements
of this element and of all its children, recursively.
-
searchChildren
@Deprecated <T extends Element<E>> List<T> searchChildren(Class<T> resultType, boolean recurse, @Nullable Filter<? super T> filter)
Deprecated.in favor ofstream(Class, boolean)
This method is functionally equivalent tosearchChildren(java.util.List, java.lang.Class, boolean, org.revapi.query.Filter)
but returns the result in a newly allocated list instance. This is basically a convenience method to enable a more succinct expressions.- Type Parameters:
T
- the type of the elements to look for- Parameters:
resultType
- the type of the elements to look forrecurse
- false to search only in direct children of the element, true to search recursivelyfilter
- optional filter to further trim the number of results @return the list of child elements of given type potentially satisfying given filter- Returns:
- the list of found elements
-
searchChildren
@Deprecated <T extends Element<E>> void searchChildren(List<T> results, Class<T> resultType, boolean recurse, @Nullable Filter<? super T> filter)
Deprecated.in favor ofstream(Class, boolean)
Recursively searches the children of this element for elements of given type, potentially applicable to given filter.This is identical to
searchChildren(Class, boolean, org.revapi.query.Filter)
in behavior but avoids the instantiation of a new list.- Type Parameters:
T
- the type of the elements to look for- Parameters:
results
- the list of the results to fillresultType
- the type of the elements to look forrecurse
- false to search only in direct children of the element, true to search recursivelyfilter
- optional filter to further trim the number of results
-
iterateOverChildren
@Deprecated <T extends Element<E>> Iterator<T> iterateOverChildren(Class<T> resultType, boolean recurse, @Nullable Filter<? super T> filter)
Deprecated.use the more standardstream(Class, boolean)
Similar to search methods but avoids the traversal over the whole forest. Instead the traversal is incremental and governed by the returned iterator.- Type Parameters:
T
- the type of the elements to look for- Parameters:
resultType
- the type of elements to look forrecurse
- if true, the iterator traverses the element forest using depth first searchfilter
- optional filter to further trim the number of results- Returns:
- the iterator that will iterate over the results
- See Also:
searchChildren(Class, boolean, org.revapi.query.Filter)
-
stream
default <T extends Element<E>> Stream<T> stream(Class<T> elementType, boolean recurse)
A stream equivalent ofiterateOverChildren(Class, boolean, Filter)
. The resulting stream contains distinct non-null elements.- Type Parameters:
T
- the type of the elements to look for- Parameters:
elementType
- the type of elements to look forrecurse
- if true, the iterator traverses the element forest using depth first search- Returns:
- the stream of elements complying to the filter
-
-


Implementation of the Taylor Regression Estimator method which is described in Christopoulos (2014,<https://www.researchgate.net/publication/261562841>) for finding the root, extreme or inflection point of a curve, when we only have a set of probably noisy xy points for it. The method uses a suitable polynomial regression in order to find the coefficients of the relevant Taylor polynomial for the function that has generated our data. Optional use of parallel computing under request.
| Version: | 1.1 |
| Depends: | iterators, foreach, parallel, doParallel |
| Suggests: | stats, graphics, grDevices |
| Published: | 2017-05-10 |
| Author: | Demetris T. Christopoulos |
| Maintainer: | Demetris T. Christopoulos <dchristop at econ.uoa.gr> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| In views: | NumericalMathematics |
| CRAN checks: | RootsExtremaInflections results |
| Reference manual: | RootsExtremaInflections.pdf |
| Package source: | RootsExtremaInflections_1.1.tar.gz |
| Windows binaries: | r-devel: RootsExtremaInflections_1.1.zip, r-release: RootsExtremaInflections_1.1.zip, r-oldrel: RootsExtremaInflections_1.1.zip |
| OS X binaries: | r-release: RootsExtremaInflections_1.1.tgz, r-oldrel: RootsExtremaInflections_1.1.tgz |
| Old sources: | RootsExtremaInflections archive |
Please use the canonical form https://CRAN.R-project.org/package=RootsExtremaInflections to link to this page.


r"""
Sparse distributed elements of free modules over multivariate (generalized)
polynomial rings.
This code and its data structures are very much like the distributed
polynomials, except that the first "exponent" of the monomial is
a module generator index. That is, the multi-exponent ``(i, e_1, ..., e_n)``
represents the "monomial" `x_1^{e_1} \dots x_n^{e_n} f_i` of the free module
`F` generated by `f_1, \dots, f_r` over (a localization of) the ring
`K[x_1, \dots, x_n]`. A module element is simply stored as a list of terms
ordered by the monomial order. Here a term is a pair of a multi-exponent and a
coefficient. In general, this coefficient should never be zero (since it can
then be omitted). The zero module element is stored as an empty list.
The main routines are ``sdm_nf_mora`` and ``sdm_groebner`` which can be used
to compute, respectively, weak normal forms and standard bases. They work with
arbitrary (not necessarily global) monomial orders.
In general, product orders have to be used to construct valid monomial orders
for modules. However, ``lex`` can be used as-is.
Note that the "level" (number of variables, i.e. parameter u+1 in
distributedpolys.py) is never needed in this code.
The main reference for this file is [SCA],
"A Singular Introduction to Commutative Algebra".
"""
from __future__ import print_function, division
from itertools import permutations
from sympy.polys.monomials import (
monomial_mul, monomial_lcm, monomial_div, monomial_deg
)
from sympy.polys.polytools import Poly
from sympy.polys.polyutils import parallel_dict_from_expr
from sympy import S, sympify
from sympy.core.compatibility import range
# Additional monomial tools.
[docs]def sdm_monomial_mul(M, X):
"""
Multiply tuple ``X`` representing a monomial of `K[X]` into the tuple
``M`` representing a monomial of `F`.
Examples
========
Multiplying `xy^3` into `x f_1` yields `x^2 y^3 f_1`:
>>> from sympy.polys.distributedmodules import sdm_monomial_mul
>>> sdm_monomial_mul((1, 1, 0), (1, 3))
(1, 2, 3)
"""
return (M[0],) + monomial_mul(X, M[1:])
[docs]def sdm_monomial_deg(M):
"""
Return the total degree of ``M``.
Examples
========
For example, the total degree of `x^2 y f_5` is 3:
>>> from sympy.polys.distributedmodules import sdm_monomial_deg
>>> sdm_monomial_deg((5, 2, 1))
3
"""
return monomial_deg(M[1:])
def sdm_monomial_lcm(A, B):
"""
Return the "least common multiple" of ``A`` and ``B``.
IF `A = M e_j` and `B = N e_j`, where `M` and `N` are polynomial monomials,
this returns `\lcm(M, N) e_j`. Note that ``A`` and ``B`` involve distinct
monomials.
Otherwise the result is undefined.
>>> from sympy.polys.distributedmodules import sdm_monomial_lcm
>>> sdm_monomial_lcm((1, 2, 3), (1, 0, 5))
(1, 2, 5)
"""
return (A[0],) + monomial_lcm(A[1:], B[1:])
[docs]def sdm_monomial_divides(A, B):
"""
Does there exist a (polynomial) monomial X such that XA = B?
Examples
========
Positive examples:
In the following examples, the monomial is given in terms of x, y and the
generator(s), f_1, f_2 etc. The tuple form of that monomial is used in
the call to sdm_monomial_divides.
Note: the generator appears last in the expression but first in the tuple
and other factors appear in the same order that they appear in the monomial
expression.
`A = f_1` divides `B = f_1`
>>> from sympy.polys.distributedmodules import sdm_monomial_divides
>>> sdm_monomial_divides((1, 0, 0), (1, 0, 0))
True
`A = f_1` divides `B = x^2 y f_1`
>>> sdm_monomial_divides((1, 0, 0), (1, 2, 1))
True
`A = xy f_5` divides `B = x^2 y f_5`
>>> sdm_monomial_divides((5, 1, 1), (5, 2, 1))
True
Negative examples:
`A = f_1` does not divide `B = f_2`
>>> sdm_monomial_divides((1, 0, 0), (2, 0, 0))
False
`A = x f_1` does not divide `B = f_1`
>>> sdm_monomial_divides((1, 1, 0), (1, 0, 0))
False
`A = xy^2 f_5` does not divide `B = y f_5`
>>> sdm_monomial_divides((5, 1, 2), (5, 0, 1))
False
"""
return A[0] == B[0] and all(a <= b for a, b in zip(A[1:], B[1:]))
# The actual distributed modules code.
[docs]def sdm_LC(f, K):
"""Returns the leading coeffcient of ``f``. """
if not f:
return K.zero
else:
return f[0][1]
[docs]def sdm_to_dict(f):
"""Make a dictionary from a distributed polynomial. """
return dict(f)
[docs]def sdm_from_dict(d, O):
"""
Create an sdm from a dictionary.
Here ``O`` is the monomial order to use.
>>> from sympy.polys.distributedmodules import sdm_from_dict
>>> from sympy.polys import QQ, lex
>>> dic = {(1, 1, 0): QQ(1), (1, 0, 0): QQ(2), (0, 1, 0): QQ(0)}
>>> sdm_from_dict(dic, lex)
[((1, 1, 0), 1), ((1, 0, 0), 2)]
"""
return sdm_strip(sdm_sort(list(d.items()), O))
def sdm_sort(f, O):
"""Sort terms in ``f`` using the given monomial order ``O``. """
return sorted(f, key=lambda term: O(term[0]), reverse=True)
def sdm_strip(f):
"""Remove terms with zero coefficients from ``f`` in ``K[X]``. """
return [ (monom, coeff) for monom, coeff in f if coeff ]
[docs]def sdm_add(f, g, O, K):
"""
Add two module elements ``f``, ``g``.
Addition is done over the ground field ``K``, monomials are ordered
according to ``O``.
Examples
========
All examples use lexicographic order.
`(xy f_1) + (f_2) = f_2 + xy f_1`
>>> from sympy.polys.distributedmodules import sdm_add
>>> from sympy.polys import lex, QQ
>>> sdm_add([((1, 1, 1), QQ(1))], [((2, 0, 0), QQ(1))], lex, QQ)
[((2, 0, 0), 1), ((1, 1, 1), 1)]
`(xy f_1) + (-xy f_1)` = 0`
>>> sdm_add([((1, 1, 1), QQ(1))], [((1, 1, 1), QQ(-1))], lex, QQ)
[]
`(f_1) + (2f_1) = 3f_1`
>>> sdm_add([((1, 0, 0), QQ(1))], [((1, 0, 0), QQ(2))], lex, QQ)
[((1, 0, 0), 3)]
`(yf_1) + (xf_1) = xf_1 + yf_1`
>>> sdm_add([((1, 0, 1), QQ(1))], [((1, 1, 0), QQ(1))], lex, QQ)
[((1, 1, 0), 1), ((1, 0, 1), 1)]
"""
h = dict(f)
for monom, c in g:
if monom in h:
coeff = h[monom] + c
if not coeff:
del h[monom]
else:
h[monom] = coeff
else:
h[monom] = c
return sdm_from_dict(h, O)
[docs]def sdm_LM(f):
r"""
Returns the leading monomial of ``f``.
Only valid if `f \ne 0`.
Examples
========
>>> from sympy.polys.distributedmodules import sdm_LM, sdm_from_dict
>>> from sympy.polys import QQ, lex
>>> dic = {(1, 2, 3): QQ(1), (4, 0, 0): QQ(1), (4, 0, 1): QQ(1)}
>>> sdm_LM(sdm_from_dict(dic, lex))
(4, 0, 1)
"""
return f[0][0]
[docs]def sdm_LT(f):
r"""
Returns the leading term of ``f``.
Only valid if `f \ne 0`.
Examples
========
>>> from sympy.polys.distributedmodules import sdm_LT, sdm_from_dict
>>> from sympy.polys import QQ, lex
>>> dic = {(1, 2, 3): QQ(1), (4, 0, 0): QQ(2), (4, 0, 1): QQ(3)}
>>> sdm_LT(sdm_from_dict(dic, lex))
((4, 0, 1), 3)
"""
return f[0]
[docs]def sdm_mul_term(f, term, O, K):
"""
Multiply a distributed module element ``f`` by a (polynomial) term ``term``.
Multiplication of coefficients is done over the ground field ``K``, and
monomials are ordered according to ``O``.
Examples
========
`0 f_1 = 0`
>>> from sympy.polys.distributedmodules import sdm_mul_term
>>> from sympy.polys import lex, QQ
>>> sdm_mul_term([((1, 0, 0), QQ(1))], ((0, 0), QQ(0)), lex, QQ)
[]
`x 0 = 0`
>>> sdm_mul_term([], ((1, 0), QQ(1)), lex, QQ)
[]
`(x) (f_1) = xf_1`
>>> sdm_mul_term([((1, 0, 0), QQ(1))], ((1, 0), QQ(1)), lex, QQ)
[((1, 1, 0), 1)]
`(2xy) (3x f_1 + 4y f_2) = 8xy^2 f_2 + 6x^2y f_1`
>>> f = [((2, 0, 1), QQ(4)), ((1, 1, 0), QQ(3))]
>>> sdm_mul_term(f, ((1, 1), QQ(2)), lex, QQ)
[((2, 1, 2), 8), ((1, 2, 1), 6)]
"""
X, c = term
if not f or not c:
return []
else:
if K.is_one(c):
return [ (sdm_monomial_mul(f_M, X), f_c) for f_M, f_c in f ]
else:
return [ (sdm_monomial_mul(f_M, X), f_c * c) for f_M, f_c in f ]
[docs]def sdm_zero():
"""Return the zero module element."""
return []
[docs]def sdm_deg(f):
"""
Degree of ``f``.
This is the maximum of the degrees of all its monomials.
Invalid if ``f`` is zero.
Examples
========
>>> from sympy.polys.distributedmodules import sdm_deg
>>> sdm_deg([((1, 2, 3), 1), ((10, 0, 1), 1), ((2, 3, 4), 4)])
7
"""
return max(sdm_monomial_deg(M[0]) for M in f)
# Conversion
[docs]def sdm_from_vector(vec, O, K, **opts):
"""
Create an sdm from an iterable of expressions.
Coefficients are created in the ground field ``K``, and terms are ordered
according to monomial order ``O``. Named arguments are passed on to the
polys conversion code and can be used to specify for example generators.
Examples
========
>>> from sympy.polys.distributedmodules import sdm_from_vector
>>> from sympy.abc import x, y, z
>>> from sympy.polys import QQ, lex
>>> sdm_from_vector([x**2+y**2, 2*z], lex, QQ)
[((1, 0, 0, 1), 2), ((0, 2, 0, 0), 1), ((0, 0, 2, 0), 1)]
"""
dics, gens = parallel_dict_from_expr(sympify(vec), **opts)
dic = {}
for i, d in enumerate(dics):
for k, v in d.items():
dic[(i,) + k] = K.convert(v)
return sdm_from_dict(dic, O)
[docs]def sdm_to_vector(f, gens, K, n=None):
"""
Convert sdm ``f`` into a list of polynomial expressions.
The generators for the polynomial ring are specified via ``gens``. The rank
of the module is guessed, or passed via ``n``. The ground field is assumed
to be ``K``.
Examples
========
>>> from sympy.polys.distributedmodules import sdm_to_vector
>>> from sympy.abc import x, y, z
>>> from sympy.polys import QQ, lex
>>> f = [((1, 0, 0, 1), QQ(2)), ((0, 2, 0, 0), QQ(1)), ((0, 0, 2, 0), QQ(1))]
>>> sdm_to_vector(f, [x, y, z], QQ)
[x**2 + y**2, 2*z]
"""
dic = sdm_to_dict(f)
dics = {}
for k, v in dic.items():
dics.setdefault(k[0], []).append((k[1:], v))
n = n or len(dics)
res = []
for k in range(n):
if k in dics:
res.append(Poly(dict(dics[k]), gens=gens, domain=K).as_expr())
else:
res.append(S.Zero)
return res
# Algorithms.
[docs]def sdm_spoly(f, g, O, K, phantom=None):
"""
Compute the generalized s-polynomial of ``f`` and ``g``.
The ground field is assumed to be ``K``, and monomials ordered according to
``O``.
This is invalid if either of ``f`` or ``g`` is zero.
If the leading terms of `f` and `g` involve different basis elements of
`F`, their s-poly is defined to be zero. Otherwise it is a certain linear
combination of `f` and `g` in which the leading terms cancel.
See [SCA, defn 2.3.6] for details.
If ``phantom`` is not ``None``, it should be a pair of module elements on
which to perform the same operation(s) as on ``f`` and ``g``. The in this
case both results are returned.
Examples
========
>>> from sympy.polys.distributedmodules import sdm_spoly
>>> from sympy.polys import QQ, lex
>>> f = [((2, 1, 1), QQ(1)), ((1, 0, 1), QQ(1))]
>>> g = [((2, 3, 0), QQ(1))]
>>> h = [((1, 2, 3), QQ(1))]
>>> sdm_spoly(f, h, lex, QQ)
[]
>>> sdm_spoly(f, g, lex, QQ)
[((1, 2, 1), 1)]
"""
if not f or not g:
return sdm_zero()
LM1 = sdm_LM(f)
LM2 = sdm_LM(g)
if LM1[0] != LM2[0]:
return sdm_zero()
LM1 = LM1[1:]
LM2 = LM2[1:]
lcm = monomial_lcm(LM1, LM2)
m1 = monomial_div(lcm, LM1)
m2 = monomial_div(lcm, LM2)
c = K.quo(-sdm_LC(f, K), sdm_LC(g, K))
r1 = sdm_add(sdm_mul_term(f, (m1, K.one), O, K),
sdm_mul_term(g, (m2, c), O, K), O, K)
if phantom is None:
return r1
r2 = sdm_add(sdm_mul_term(phantom[0], (m1, K.one), O, K),
sdm_mul_term(phantom[1], (m2, c), O, K), O, K)
return r1, r2
[docs]def sdm_ecart(f):
"""
Compute the ecart of ``f``.
This is defined to be the difference of the total degree of `f` and the
total degree of the leading monomial of `f` [SCA, defn 2.3.7].
Invalid if f is zero.
Examples
========
>>> from sympy.polys.distributedmodules import sdm_ecart
>>> sdm_ecart([((1, 2, 3), 1), ((1, 0, 1), 1)])
0
>>> sdm_ecart([((2, 2, 1), 1), ((1, 5, 1), 1)])
3
"""
return sdm_deg(f) - sdm_monomial_deg(sdm_LM(f))
[docs]def sdm_nf_mora(f, G, O, K, phantom=None):
r"""
Compute a weak normal form of ``f`` with respect to ``G`` and order ``O``.
The ground field is assumed to be ``K``, and monomials ordered according to
``O``.
Weak normal forms are defined in [SCA, defn 2.3.3]. They are not unique.
This function deterministically computes a weak normal form, depending on
the order of `G`.
The most important property of a weak normal form is the following: if
`R` is the ring associated with the monomial ordering (if the ordering is
global, we just have `R = K[x_1, \dots, x_n]`, otherwise it is a certain
localization thereof), `I` any ideal of `R` and `G` a standard basis for
`I`, then for any `f \in R`, we have `f \in I` if and only if
`NF(f | G) = 0`.
This is the generalized Mora algorithm for computing weak normal forms with
respect to arbitrary monomial orders [SCA, algorithm 2.3.9].
If ``phantom`` is not ``None``, it should be a pair of "phantom" arguments
on which to perform the same computations as on ``f``, ``G``, both results
are then returned.
"""
from itertools import repeat
h = f
T = list(G)
if phantom is not None:
# "phantom" variables with suffix p
hp = phantom[0]
Tp = list(phantom[1])
phantom = True
else:
Tp = repeat([])
phantom = False
while h:
# TODO better data structure!!!
Th = [(g, sdm_ecart(g), gp) for g, gp in zip(T, Tp)
if sdm_monomial_divides(sdm_LM(g), sdm_LM(h))]
if not Th:
break
g, _, gp = min(Th, key=lambda x: x[1])
if sdm_ecart(g) > sdm_ecart(h):
T.append(h)
if phantom:
Tp.append(hp)
if phantom:
h, hp = sdm_spoly(h, g, O, K, phantom=(hp, gp))
else:
h = sdm_spoly(h, g, O, K)
if phantom:
return h, hp
return h
def sdm_nf_buchberger(f, G, O, K, phantom=None):
r"""
Compute a weak normal form of ``f`` with respect to ``G`` and order ``O``.
The ground field is assumed to be ``K``, and monomials ordered according to
``O``.
This is the standard Buchberger algorithm for computing weak normal forms with
respect to *global* monomial orders [SCA, algorithm 1.6.10].
If ``phantom`` is not ``None``, it should be a pair of "phantom" arguments
on which to perform the same computations as on ``f``, ``G``, both results
are then returned.
"""
from itertools import repeat
h = f
T = list(G)
if phantom is not None:
# "phantom" variables with suffix p
hp = phantom[0]
Tp = list(phantom[1])
phantom = True
else:
Tp = repeat([])
phantom = False
while h:
try:
g, gp = next((g, gp) for g, gp in zip(T, Tp)
if sdm_monomial_divides(sdm_LM(g), sdm_LM(h)))
except StopIteration:
break
if phantom:
h, hp = sdm_spoly(h, g, O, K, phantom=(hp, gp))
else:
h = sdm_spoly(h, g, O, K)
if phantom:
return h, hp
return h
def sdm_nf_buchberger_reduced(f, G, O, K):
r"""
Compute a reduced normal form of ``f`` with respect to ``G`` and order ``O``.
The ground field is assumed to be ``K``, and monomials ordered according to
``O``.
In contrast to weak normal forms, reduced normal forms *are* unique, but
their computation is more expensive.
This is the standard Buchberger algorithm for computing reduced normal forms
with respect to *global* monomial orders [SCA, algorithm 1.6.11].
The ``pantom`` option is not supported, so this normal form cannot be used
as a normal form for the "extended" groebner algorithm.
"""
h = sdm_zero()
g = f
while g:
g = sdm_nf_buchberger(g, G, O, K)
if g:
h = sdm_add(h, [sdm_LT(g)], O, K)
g = g[1:]
return h
[docs]def sdm_groebner(G, NF, O, K, extended=False):
"""
Compute a minimal standard basis of ``G`` with respect to order ``O``.
The algorithm uses a normal form ``NF``, for example ``sdm_nf_mora``.
The ground field is assumed to be ``K``, and monomials ordered according
to ``O``.
Let `N` denote the submodule generated by elements of `G`. A standard
basis for `N` is a subset `S` of `N`, such that `in(S) = in(N)`, where for
any subset `X` of `F`, `in(X)` denotes the submodule generated by the
initial forms of elements of `X`. [SCA, defn 2.3.2]
A standard basis is called minimal if no subset of it is a standard basis.
One may show that standard bases are always generating sets.
Minimal standard bases are not unique. This algorithm computes a
deterministic result, depending on the particular order of `G`.
If ``extended=True``, also compute the transition matrix from the initial
generators to the groebner basis. That is, return a list of coefficient
vectors, expressing the elements of the groebner basis in terms of the
elements of ``G``.
This functions implements the "sugar" strategy, see
Giovini et al: "One sugar cube, please" OR Selection strategies in
Buchberger algorithm.
"""
# The critical pair set.
# A critical pair is stored as (i, j, s, t) where (i, j) defines the pair
# (by indexing S), s is the sugar of the pair, and t is the lcm of their
# leading monomials.
P = []
# The eventual standard basis.
S = []
Sugars = []
def Ssugar(i, j):
"""Compute the sugar of the S-poly corresponding to (i, j)."""
LMi = sdm_LM(S[i])
LMj = sdm_LM(S[j])
return max(Sugars[i] - sdm_monomial_deg(LMi),
Sugars[j] - sdm_monomial_deg(LMj)) \
+ sdm_monomial_deg(sdm_monomial_lcm(LMi, LMj))
ourkey = lambda p: (p[2], O(p[3]), p[1])
def update(f, sugar, P):
"""Add f with sugar ``sugar`` to S, update P."""
if not f:
return P
k = len(S)
S.append(f)
Sugars.append(sugar)
LMf = sdm_LM(f)
def removethis(pair):
i, j, s, t = pair
if LMf[0] != t[0]:
return False
tik = sdm_monomial_lcm(LMf, sdm_LM(S[i]))
tjk = sdm_monomial_lcm(LMf, sdm_LM(S[j]))
return tik != t and tjk != t and sdm_monomial_divides(tik, t) and \
sdm_monomial_divides(tjk, t)
# apply the chain criterion
P = [p for p in P if not removethis(p)]
# new-pair set
N = [(i, k, Ssugar(i, k), sdm_monomial_lcm(LMf, sdm_LM(S[i])))
for i in range(k) if LMf[0] == sdm_LM(S[i])[0]]
# TODO apply the product criterion?
N.sort(key=ourkey)
remove = set()
for i, p in enumerate(N):
for j in range(i + 1, len(N)):
if sdm_monomial_divides(p[3], N[j][3]):
remove.add(j)
# TODO mergesort?
P.extend(reversed([p for i, p in enumerate(N) if not i in remove]))
P.sort(key=ourkey, reverse=True)
# NOTE reverse-sort, because we want to pop from the end
return P
# Figure out the number of generators in the ground ring.
try:
# NOTE: we look for the first non-zero vector, take its first monomial
# the number of generators in the ring is one less than the length
# (since the zeroth entry is for the module generators)
numgens = len(next(x[0] for x in G if x)[0]) - 1
except StopIteration:
# No non-zero elements in G ...
if extended:
return [], []
return []
# This list will store expressions of the elements of S in terms of the
# initial generators
coefficients = []
# First add all the elements of G to S
for i, f in enumerate(G):
P = update(f, sdm_deg(f), P)
if extended and f:
coefficients.append(sdm_from_dict({(i,) + (0,)*numgens: K(1)}, O))
# Now carry out the buchberger algorithm.
while P:
i, j, s, t = P.pop()
f, sf, g, sg = S[i], Sugars[i], S[j], Sugars[j]
if extended:
sp, coeff = sdm_spoly(f, g, O, K,
phantom=(coefficients[i], coefficients[j]))
h, hcoeff = NF(sp, S, O, K, phantom=(coeff, coefficients))
if h:
coefficients.append(hcoeff)
else:
h = NF(sdm_spoly(f, g, O, K), S, O, K)
P = update(h, Ssugar(i, j), P)
# Finally interreduce the standard basis.
# (TODO again, better data structures)
S = set((tuple(f), i) for i, f in enumerate(S))
for (a, ai), (b, bi) in permutations(S, 2):
A = sdm_LM(a)
B = sdm_LM(b)
if sdm_monomial_divides(A, B) and (b, bi) in S and (a, ai) in S:
S.remove((b, bi))
L = sorted(((list(f), i) for f, i in S), key=lambda p: O(sdm_LM(p[0])),
reverse=True)
res = [x[0] for x in L]
if extended:
return res, [coefficients[i] for _, i in L]
return res


Explore our amazing courses
| Course | Area | Instructor | Duration | Starting Date | Details |
|---|---|---|---|---|---|
| Data Analytics | Statistical Learning | Aziz | 30 hr | 2016-10-27 | |
| Machine Learning | Big Data | Mike | 6 hr | 2016-10-28 | |
| Cloud Computing | Advanced Computing | Ann | 10 hr | 2016-10-29 | |
| Database Management Systems | Big Data | Sam | 10 hr | 2016-11-02 | |
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MARCH 12, 2017 BY XADF327
Aqours First Live Concert Guide
This concert guide features the following:
- What to bring to the concert!
- What to do (… and not do) at a concert!
- A comprehensive guide to all the different kinds of lightsticks!
Guidehttps://onibe.moe/pdf/web/Aqours_First_Live_Fan_Concert_Book.pdf


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Five arrested for betting during Ind vs Ban test match
by PTIFive people were arrested, including three from Eden Gardens, for allegedly betting using a mobile phone app during India's first day-night test match, police said.
The test match was being played between India and Bangladesh.
"Two of their associates were arrested from a hotel in southern part of the city’s Sudder Street," a senior police official said.
"Sambhu Dayal, Mukesh Gare and Chetan Sharma were arrested by anti-rowdy section of Kolkata Police from G1 Block of Eden Gardens," he said.
“We had a tip-off that there was a live betting taking place among some spectators at the Eden Gardens while watching the Test match. Our officers were keeping eyes open at blocks F1 & G1. And after prolonged watch they arrested three persons from the galleries,” the IPS officer said.
"Grilling the three, our officers arrested Abhishek Suwalka, Ayub Ali from the hotel from where they were operating the betting," he added.
"Cash amounting to Rs 1,40,000, six mobile phones, one laptop were seized from the hotel rooms," the police officer said.
"We have started a probe into the matter and trying to find out whether they are part of any big betting racket or not,” he said, adding that a specific case under relevant sections of the IPC, and West Bengal Gambling Act was registered at the Maidan Police Station.


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Development
Unfeel Tournament was made for a game development course in UCI (COMP SCI 113). My team and I came up with this idea of emotions, Angry, Happy, Sad, Worried, fighting for control over a person's feelings. The last emotion standing would end up being the emotion that person feels. The emotions begin at a landscape, representing the natural world (and space), and utilize weapons scattered throughout to fight for control. The goal of this game, was to create a fast-paced, simple, and fun multiplayer experience. Unfeel Tournament was made in Unity3D and C#.
The main menu includes a background that shows all four emotions. From the main menu, you can choose to play a game, look at the controls, or check out the team.
To accommodate four player local multiplayer, we added Xbox 360 controller support. Two players would use the keyboard + mouse, and two others would use controllers (or extra keyboards).
When you begin a game, you must first decide on the game settings: number of lives, number of players, and duration. Each player begins with the number of lives chosen, and once a player loses all of their lives, they are dead. The game ends when the game time has elapsed the duration chosen. Once the game ends by time, the player with the most kills is chosen as a winner. Otherwise, the game ends when there is only one player left alive, and that player is chosen as a winner.
Once the game settings are chose, each player takes turns choosing an emotion. Only one of each emotion can appear. Emotions have no impact on gameplay.
Finally, after the characters are selected, the level must be chosen. The game comes with 4 different levels- each with its own theme: Mountain, Graveyard, Snowy, Space.
The players now enter the game, and can start playing. There are specific spawn points for items, and each spawn point has its own selection of items that can spawn. Certain items have a higher chance of spawning. Players pick up items, and use them. If it is a weapon, the player equips that weapon and replacing their previously wewapon. Otherwise, the player immediately gains the effects of that item for a short time.
There are a number of different weapons and items:
- Bubble Gun - A regular gun that fires bubbles.
- Assault Bubble Gun - A bubble gun with a much faster fire rate.
- Bubble Shotgun - A shotgun that fires 5 bubbles in a cone.
- Bubble Sniper - A very long-range bubble gun that fires high-damaging bubbles.
- Mega Bubble Launcher - A launcher that fires a large, explosive bubble in an arc.
- Bubble Thrower - A weapon that fires a stream of tiny bubbles.
- Baseball Bat - A regular, ol' baseball bat.
- Cake - Increases your health, and makes you bigger.
- Star - Makes you move faster, and jump higher.
Once the game has ended, the players enter the results screen, showing the stats and the winner.
The character models and animations were created from a single texture from bevouliin.com. The item and bubble textures, the map textures, the sfx, and the music were also retrieved from royalty-free assets online.


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Where the Rubber Meets the Roof | RV PRO
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Treatment for Herniated or Bulging Discs
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Tech Tips: Re-Roofing Your RV (Part I) | Tech Tips
May 1, 2010 . But with time, RVers began to notice a few problems. . The Carriage Travel Club (CTC), founded in 1976 by Carriage. . Trailer leveling jacks helped push the sagging ceiling back in place. . hard we worked at making repairs, there would soon be a new tear in the roof membrane that let the rain come in.
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travel trailer membrane roof problems Herniated or Bulging Discs
RV Roof Repair -- DIY Fix for RV EPDM Roof | RV Tips
Roof repair of your RV EPDM roof is an easy do it yourself fix. . Our RV Travel Log . Use a primer and adhesive product which is compatible to your EPDM membrane roof. . Cleaning RV Rubber Roof to Identify Roof Fix Maintenance Issues . DIY Roof Repair for RV Metal Roof · RV Trailer Metal Roof Maintenance .
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RV Roof Care and Maintenance - the Basics - RV Basics .com
If your motor home, travel trailer or fifthwheel was made in the last few years, chances . EPDM rubber roofing membrane is made to last 20 years or longer and .
http://rvbasics.com/techtips/rv-roof-care.html
Official Impairment Listing for Spinal Disorders
How to Fix a Leaky Travel Trailer Roof | eHow.com
Most travel trailers are roofed with a sheet of ethylene propylene diene monomer (EPDM) rubber, a thermoplastic polyolefin (TPO) membrane, fiberglass or .
http://www.ehow.com/how_5414588_fix-leaky-travel-trailer-roof.html
- jardiner par les photos (narrowing of the spine)
Keystone Passport ultra-lite travel trailer RV review - Roaming Times
Luckily we noticed that the roof membrane came detached from the substraint. . Re: Keystone Passport travel trailer, Roger Wright, I have had problems with .
http://www.roamingtimes.com/rvreports/8/keystone-passport-travel-trailer-2011.aspxNew PVC membrane plastic roof for RVs - YouTube
Sep 19, 2009 . PVC membrane roofing has been available from IB Roof Systems . u use on the roof edm pvc aluminum thats not the problem its the calk . 1973 travel Aire? . RV Trailer Roof Replacementby mrlitho38,913 views · 2/7 PVC .
http://www.youtube.com/watch?v=rZLktJ0ZCLs
DICOR RUBBER ROOFING PRODUCTS - Sahara RV Center
your rubber roof membrane. Provides . motor home, travel trailer, fifth wheel, or mobile home. 20/20 is a . ments, and solve many problems for home, auto .
http://www.sahararv.com/pdfs/116-130_RV_Maintenance.pdf
ComposiTek Construction - EverGreen Recreational Vehicles
Exclusive to EverGreen Ever-Lite travel trailers and fifth wheels, . With ComposiTek Construction the walls, roof and floor of every Ever-Lite RV . In addition, rubber membrane on a conventional 30 foot trailer adds over 80 pounds of weight!
http://www.goevergreenrv.com/page/70/ComposiTek-Construction
Medical-Vocational Allowance for Herniated Disc
WHITE EPDM Roofing Membrane, 60 mil, 10 feet wide (per foot)
Custom-cut items are non-returnable or cancellable. Note: EPDM roofing can have factory lap-seams. These are a normal part of the manufacturing process, and .
http://www.bestmaterials.com/detail.aspx?ID=15884
Top 10 Problems
When a travel trailer or 5th wheel is new the axles are lined up properly at a true 90 . or winds cause branches to blow down and penetrate the roof membrane.
http://dondavis.htlnw.com/top10things.htm
How To Clean And Repair Your RV's Rubber Roof - The Fun Times ...
Rest assured, if a tree branch punctures or rips the rubber membrane, all is not lost. . include cooking at home, living with an aging dog, and dealing with diabetic issues. . Bought a used 2008 Surveyor travel trailer a few months ago.
http://rv-roadtrips.thefuntimesguide.com/2008/09/rv_rubber_roof.php
Appealing a Denial of Benefits
Buffalo RV - Rubber Roofs
General RV Information | Rubber Roofs Continue to Gain Popularity . EPDM use in truck campers and lower-priced travel trailers and fifth wheels. . in the manufacturing process to keep the EPDM membrane from sticking together before application. . Overall, EPDM advantages seems to outweigh problems, and several .
http://rvdirectbuffalo.com/index.php/rubberroofs


Export Objects bookmarklet
Export objects, such as Users, Groups, Directory Users, App Users, App Groups, Apps.
Setup
1. Show your bookmarks toolbar. In Chrome, ... > Bookmarks > Show Bookmarks Bar. In Firefox/IE, right-click in the title bar and click Bookmarks Toolbar.
2. Drag this to the bookmark toolbar:
Export Objects
Usage
1. Login to Okta Admin. Chrome and Firefox work best. IE is untested.
2. Go to one of these:
- Directory > People
- Directory > Groups
- Directory > Directory Integrations and click on a Directory (to export Users)
- Applications > Applications and click on an App (to export Users or Groups)
- Applications > Applications (to export Apps)
3. Click the bookmark from your toolbar.
4. When the export is done, the objects are downloaded to a CSV file.
source


Hello!
Could anybody please post me a short example script for DC voltage measurement (maybe taking some samples to reduce noise) with the EmonTX?
Of cause I know that I have to modify the schematic, but that's no problem for me. I only need a software example to understand how to do it.
Re: Measuring DC voltage?
What d.c. voltage are you trying to measure?
Re: Measuring DC voltage?
Hello Robert!
I want to measure the voltage of a 255W solar panel, maximum voltage will be about 40V. The panel is mounted on my garden shed.
When the voltage measuring works I will add a current sensor (ACS712) on a second channel, but first I have to understand the software part. The hardware is no problem, I allready did this using a PIC, but not with an ATMEL.
Re: Measuring DC voltage?
I was concerned that without isolation - both on the voltage side and the current side - that you would be at great risk, because direct voltages can be much more harmful than alternating. Do please be aware of the potential dangers and treat the panel as being live at all times.
I assume you will probably be using an op-amp with a differential input so that you don't need to tie the common rail to either of the d.c. connections, neither of which need to be at or even near earth potential. You'll need to make sure you have minimal d.c drift, because this will have a direct effect on accuracy.
I've not seen a sketch mentioned for measuring the direct output from the panels, though I understand some have decoded the data output from their inverter, to obtain the same information.
Basically, you can use the sketch here http://openenergymonitor.org/emon/node/31 as a strarting point, because once the input has been digitised, you treat voltage exactly the same as you treat current. The library has a filter built-in to smooth the values, but obviously you'll need to understand and change the calibration.
Re: Measuring DC voltage?
I keep meaning to remove the dc shunt page and replacing it with what I found to work better in the end when I was doing DC sensing which was these nice little modules from cool components:
Voltage and current monitoring:
http://www.coolcomponents.co.uk/catalog/attopilot-voltage-current-sense-...
Current only
http://www.coolcomponents.co.uk/catalog/acs715-current-sensor-breakout-p...
Re: Measuring DC voltage?
Hallo Jürgen :-),
it would also be possible to use this board (shunt missing) :
http://jeelabs.com/products/analog-plug
for bi-directional current measurement with very high accuracy. The emontx provides 'Jeelab ports', so it should be possible to use the software routines provided by the jeelib library (/examples/ports/analog_demo).
I have already used the same chip (4 channel MCP3424) for other purposes and found it to be very nice and accurate (and quite cheap also). There are also one and two channel versions.
Re: Measuring DC voltage?
Hello Robert!
I'm aware of the special danger with direct voltages and currents, I attended a school for electrical engineeering. So I know about the dangers and risks in theory and practice.
I will use a box where I put all compoents and the EmonTX into, so there will be only two wires going into from the panel and two wires leaving the box to the inverter. (I'll measure the AC current too with a CT).
For the current measurement I will use a ACS712 that allready isolates between the current and the voltage output.
As the ACS712 uses 5V and can measure currents bidirectional (-20 to +20A) the output is centered around 2,5V. Higher voltage means positive current, lower means negative current. If I connect the current path in reverse direction I'll get 2,5V (0A) to 0,5V (20A), so no problem for the ATMEL 3,3V inputs, only a litte bit of mathematics for the ATMEL.
Re: Measuring DC voltage?
Are you wiring this panel into an inverter? If so that may be the best place to get the readings from?
Re: Measuring DC voltage?
Ok I found the function in the /examples/ports/analog_demo file. That's really simple. I only had to multiply the value by 3,225 to get the correct value in milivolts.
Udc = analogRead(A0)*3.226; // Read input from Analog Pin 0=CT2. Pin 1=CT3.


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lurker
`Prev `__
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**lurker**: n.
One of the ‘silent majority’ in an electronic forum; one who posts
occasionally or not at all but is known to read the group's postings
regularly. This term is not pejorative and indeed is casually used
reflexively: “Oh, I'm just lurking.” Often used in the lurkers, the
hypothetical audience for the group's
`*flamage* <../F/flamage.html>`__-emitting regulars. When a lurker
speaks up for the first time, this is called delurking.
The creator of the popular science-fiction TV series *Babylon 5* has
ties to SF fandom and the hacker culture. In that series, the use of the
term ‘lurker’ for a homeless or displaced person is a conscious
reference to the jargon term.
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|
PieDock
1.6.3
|
#include <PieMenu.h>
Public Member Functions | |
| PieMenu (Application *, Surface &) | |
| const bool | cursorInCenter () const |
| const int & | getRadius () const |
| Blender * | getBlender () |
| void | invalidate () |
| virtual bool | update (std::string="", Window=0) |
| virtual bool | isObsolete (int, int) |
| virtual void | draw (int, int) |
| virtual void | turn (double) |
| virtual void | turn (int) |
| virtual void | setTwistForSelection () |
| Public Member Functions inherited from PieDock::Menu | |
| Menu (Application *) | |
| void | setWindowBelowCursor (Window w) |
| const Window & | getWindowBelowCursor () const |
| MenuItem * | getSelected () const |
| const std::string & | getName () const |
| virtual bool | change (Settings::Action=Settings::Launch) |
| virtual void | execute (Settings::Action=Settings::Launch) |
| virtual std::string | getItemTitle () const |
Protected Member Functions | |
| virtual double | getAngleDifference (double a, double b) |
| virtual double | getValidAngle (double a) |
| Protected Member Functions inherited from PieDock::Menu | |
| Application * | getApp () const |
| void | setSelected (MenuItem *s) |
| MenuItems * | getMenuItems () const |
| virtual int | run (std::string) const |
Realize a pie menu
| PieMenu::PieMenu | ( | Application * | a, |
| Surface & | s | ||
| ) |
Initialize menu
| a | - application |
| s | - surface to draw menu into |
|
virtual |
Draw menu
| x | - x coordinate of cursor position within target surface |
| y | - y coordinate of cursor position within target surface |
Reimplemented from PieDock::Menu.
References PieDock::Blender::blend(), getAngleDifference(), and getValidAngle().
Referenced by PieDock::PieMenuWindow::draw().
|
inlineprotectedvirtual |
Return the difference of two angles in radians; implemented here to ensure the method will be compiled inline
| a | - angle in radians |
| b | - angle in radians |
Referenced by draw().
|
inlineprotectedvirtual |
Recalculate angle to be within a valid range; implemented here to ensure the method will be compiled inline
| a | - angle in radians |
Referenced by draw().
|
virtual |
Returns true if menu needs to be redrawn
| x | - x coordinate of cursor position within target surface |
| y | - y coordinate of cursor position within target surface |
Referenced by PieDock::PieMenuWindow::draw().
|
virtual |
Set twist to have the last selected item selected again
Referenced by PieDock::PieMenuWindow::appear().
|
virtual |
|
virtual |
Turn menu by the given number of cells
| c | - cells to turn |
|
virtual |
Reset and update menu
| n | - menu name (optional) |
| w | - window id (optional) |
Reimplemented from PieDock::Menu.
References PieDock::Menu::update().
Referenced by PieDock::PieMenuWindow::appear().


{% extends "tutorial.html" %} {% load mixin from templatefilters %} {% block head %} {% endblock %} {% block content %}
One of the biggest evolutions happening around HTML5 today is the availability of persistent storage on browsers. Before HTML5, we had no choice other than using cookies to store some kind of data on client side. With HTML5, you have several choices for storing your data, depending on what you want to store.
The most broadly used technology is called WebStorage, an API for persistent key-value data storage which most major browsers have supported for a while. WebStorage has persistent storage called LocalStorage, and temporary storage called SessionStorage which will be cleared after a session.
WebSQL Database is a relational database solution for browsers. Even though it is essentially deprecated and the W3C no longer maintains the specification, meaning browsers may or may not continue to support it, people still use it because it is the only common answer for structured data storage on mobile browsers.
Indexed Database is an object store. Since it's considered to be the final solution for storing structured data on browsers, its support and usage is gradually expanding.
FileSystem API is a file system solution for the web. Developers can store large objects in a sandboxed part of the user's file system and directly link to them via URL. Although Chrome and Opera are the only browsers that currently implement the feature, its standardization is ongoing.
As web apps get richer and richer, more and more developers are using browser-side storage. However, there hasn't been a major study comparing the limitations of the various storage mechanisms. It is time consuming for developers to research each method and browser. So in this article, I'm going to show you the results of my research on the upper limit of each browser's storage implementation, as well as how you can inspect them.
To do this research, I have built a tool called Browser Storage Abuser to minimize the manual work. You can store as much data as possible to see the limit of each storage on your browser.
Following is a quick summary of results from this research using the tool.
Note: Opera is not listed here because it uses Blink, the same browser engine that Chrome uses, and so my research results using Opera were very similar to my results with Chrome.
| Browser | Chrome | Android Browser | Firefox | Safari | iOS WebView |
|---|---|---|---|---|---|
| Version | 33 | 4.3 | 26 | 6, 7 | 6, 7 |
| FileSystem | up to quota | N/A | N/A | N/A | N/A |
| IndexedDB | up to quota | N/A | 5MB, Unlimited | N/A | N/A |
| WebSQL | up to quota | 200MB~ | N/A | 5MB, 10MB, 25MB, 50MB | 50MB |
| LocalStorage | 10MB | 2MB | 10MB | 5MB | 5MB |
| SessionStorage | 10MB | Unlimited | 5MB | 5MB |
| Browser | Chrome | Firefox | Safari | IE | IE |
|---|---|---|---|---|---|
| Version | 33 | 26 | 6, 7 | 9 | 10, 11 |
| FileSystem | up to quota | N/A | N/A | N/A | N/A |
| IndexedDB | up to quota | 50MB, Unlimited | N/A | N/A | 10MB, 250MB (~999MB) |
| WebSQL | up to quota | N/A | 5MB, 10MB, 50MB, 100MB, 500MB, 600MB, 700MB... | N/A | N/A |
| LocalStorage | 10MB | 10MB | 5MB | 10MB | 10MB |
| SessionStorage | 10MB | 10MB | Unlimited | 10MB | 10MB |
OK, now you have a summary of storage limitations. Let's dive into the details of each browser's implementation and see how you can inspect and debug each storage.
| FileSystem | IndexedDB | WebSQL | LocalStorage | SessionStorage | |
|---|---|---|---|---|---|
| Chrome 33 | up to quota | up to quota | up to quota | 10MB | 10MB |
| Chrome for Android 33 | up to quota | up to quota | up to quota | 10MB | 10MB |
Chrome can use all of the types of storage listed here including FileSystem API, IndexedDB, WebSQL, LocalStorage and SessionStorage. All of the storage mechanisms except LocalStorage and SessionStorage, which use asynchronous input and output, are under managed by Quota Management API; their limitation varies depending on the amount of storage the device has left.
Current quota rule is as follows:
Please refer to this page for further information regarding Quota Management API (as of January 2014). The Quota Management API specification is under active discussion and subject to change in the future.
You can inspect details of LocalStorage, SessionStorage, IndexedDB and WebSQL if you open DevTools' Resources panel.
For inspecting FileSystem API, you need to
You should now see "FileSystem" item the Resources panel.
For clearing and initializing storage content including cookies, follow instructions below.
Desktop:
Or
Android:
On Chrome for Android, you can inspect storage types by following the same procedure as desktop version described above. Refer to "Remote debugging" article to learn how to debug Chrome for Android.
| FileSystem | IndexedDB | WebSQL | LocalStorage | SessionStorage | |
|---|---|---|---|---|---|
| Firefox 26 | N/A | 50MB, Unlimited | N/A | 10MB | |
| Firefox for Android 26 | N/A | 5MB, Unlimited | N/A | 10MB |
Firefox can use IndexedDB, LocalStorage and SessionStorage. LocalStorage and SessionStorage can use up to 10MB of storage but the number is actually the sum of both.
For IndexedDB, you can use up to 50MB on desktop, 5MB on mobile for free. However, the user can allow the limit to be removed by granting permission. A user can also change the warning quota by changing about:config
's dom.indexedDB.warningQuota
Note: Firefox actually stores the IndexedDB data as a compressed BLOB in sqlite, so the size of original object won't be reflected as is)
You can inspect actual consumption by using an Add-on called Tahoe Data Manager on desktop, but the Storage tab doesn't seem to work on Firefox 26. You can actually use sqlite command to inspect content of the database. The sqlite files are located under idb folder under profile directory of respective OSes.
Windows: %AppData%\Mozilla\Firefox\Profiles\xxxxxxxx.default
Mac: ~/Library/Application Support/Firefox/Profiles/xxxxxxxx.default
Add-on called SQLite Manager might be a good choice for inspection using a GUI.
If you want to remove permissions per domain, go to the about:permissions
page.
For Android version, I couldn't find any way to inspect or delete stored data per domain. To learn more about debugging mobile Firefox, see this document.
| FileSystem | IndexedDB | WebSQL | LocalStorage | SessionStorage | |
|---|---|---|---|---|---|
| Android Browser | N/A | N/A | 200MB~? | 2MB | Unlimited |
Android Browser can use WebSQL, LocalStorage and SessionStorage.
Compared to the other browsers, Android Browser only has 2MB for LocalStorage. SessionStorage is unlimited since it stores data on memory instead of disks.
It is tough to examine WebSQL on Android Browser. Storing around 500KB data in one transaction returns a quota error, but dividing it into multiple transactions seemed to work ok. I could store up to around 200MB without permission, before it crashed.
You can inspect stored data on WebSQL, LocalStorage and SessionStorage by using an open source tool called weinre, which can interact with the browser remotely using the DevTools protocol.
You can delete those data individually on weinre. If you don't have weinre installed, you need to follow the instructions below to delete them. Note that you can't delete per domain.
Open system's "Settings" > "Apps" > "Browser" and tap "Clear data"
| FileSystem | IndexedDB | WebSQL | LocalStorage | SessionStorage | |
|---|---|---|---|---|---|
| Safari 6, 7 | N/A | N/A | 5MB, 10MB, 50MB, 100MB, 500MB, 600MB, 700MB... | 5MB | Unlimited |
| Mobile Safari 6, 7 | N/A | N/A | 5MB, 10MB, 25MB, 50MB | 5MB | 5MB |
| iOS WebView | N/A | N/A | 50MB | 5MB | 5MB |
Safari can use WebSQL, LocalStorage and SessionStorage.
For desktop, you can use up to 5MB for LocalStorage. Similar to Android Browser, SessionStorage is unlimited since it stores data on memory instead of disks.
WebSQL's quota policy is a bit unique here. Safari asks a user for permissions in multiple size points as described above. But if openDatabase
is called with more than 5MB of size on database creation, Safari will ask the user for a permission of the closest upper limit. If granted, it won't ask user another permission until actual data size exceeds that number.
For mobile, the rule is similar but the upper limits are different.
SessionStorage's limit is 5MB as it is on LocalStorage. On WebSQL, it asks a user for permissions but you can't store data any more than 50MB.
Note: Safari after iOS 7 has a bug that throws an exception when more than 5MB is requested on database creation. This is not fixed as of iOS 7.0.4. Work around is to request less than 5MB and let Safari ask for a permission. This is annoying for users, but no way around.
On iOS WebView, WebSQL's upper limit is also 50MB but it won't ask for permission.
On desktop, you can use Web Inspector to inspect LocalStorage, SessionStorage and WebSQL.
On mobile, you can only inspect LocalStorage and SessionStorage. To learn more about debugging mobile Safari, see this document.
| FileSystem | IndexedDB | WebSQL | LocalStorage | SessionStorage | |
|---|---|---|---|---|---|
| IE 9 | N/A | N/A | N/A | 10MB | 10MB |
| IE 10, 11 | N/A | 10MB, 250MB (~999MB) | N/A | 10MB | 10MB |
Internet Explorer supports LocalStorage and SessionStorage after version 9. Version 10 started to support IndexedDB as well.
On LocalStorage and SessionStorage, users can store up to 10MB each.
On IndexedDB, the browser asks users for permission at 10MB, then allows up to 250MB by default. It can store up to 999MB without permission but requires the user to change their settings to allow it; a developer cannot change this setting.
Unfortunately, there's no good way to inspect LocalStorage, SessionStorage or IndexedDB on Internet Explorer yet.
You can still delete stored data per domain by
What should you do when your app is over quota? It's up to app's design what to do, but I would like to share some sample code since there's not much existing examples on internet.
There are multiple cases where FileSystem generates quota exceeded error.
When quota exceeds on FileEntry
or DirectoryEntry
's getFile()
, copyTo()
or moveTo()
functions, an error calls the second function argument with FileError
as an argument.
When quota exceeds on FileWriter
's write()
function, an error calls onerror()
function with ProgressEvent
as an argument. FileError
(planned to be replaced with DOMError
) is attached as ProgressEvent.target.error
.
To determine if the error is caused by a quota exceed, check if the name
property of the FileError
object is "QuotaExceededError
" or not.
Note that FileSystem will throw a DOMException
if you use sync version of the API (FileSystemSync).
filesystem.root.getDirectory(dirName, {create:true, exclusive:false},
function getDirectorySuccess(dirEntry) {
dirEntry.getFile(fileName, {create:true, exclusive:false},
function getFileSuccess(fileEntry) {
fileEntry.createWriter(function(writer) {
writer.onwriteend = function() {
...
};
writer.onerror = function(progressEvent) {
var fileError = progressEvent.target.error;
if (fileError.name === 'QuotaExceededError') {
// Fallback code comes here.
}
};
writer.write(blob);
});
},
// argument will be DOMError in the future
function getFileError(fileError) {
if (fileError.name == 'QuotaExceededError') {
// Fallback code comes here.
}
});
},
// argument will be DOMError in the future
function getDirectoryError(fileError) {
if (fileError.name == 'QuotaExceededError') {
// Fallback code comes here.
}
});
When quota exceeds on IndexedDB API, the error calls the transaction's onabort()
function with Event
as an argument. To determine if the error is caused by a quota exceed, check if name
property of DOMError
object is "QuotaExceededError
" or not.
When a browser requests user permission for expanding storage size, all browsers call this function only when a user don't allow it, otherwise, continue the transaction.
var transaction = idb.transaction(['entries'], 'readwrite');
transaction.oncomplete = function(e) {
...
};
transaction.onerror = function(e) {
...
};
transaction.onabort = function(event) {
var error = event.target.error; // DOMError
if (error.name == 'QuotaExceededError') {
// Fallback code comes here
}
};
var req = transaction.objectStore('entries').put(data);
req.onerror = function(e) {
// Quota error won't call this function
};
WebSQL is a bit tricky. When quota exceeds on WebSQL, the error calls the transaction's second function argument with SQLError
as an argument. To determine if the error is caused by a quota exceed, check if code
property of SQLError
object matches SQLError.QUOTA_ERR
or not.
Unfortunately, Safari calls this function regardless of if the user granted extending storage size or not. Also, there's no way for a developer to know if the user actually granted the permission.
db.transaction(function onTransaction(t) {
t.executeSql('INSERT INTO entries (name, size, date, payload) VALUES(?, ?, ?, ?)', data,
function onExecuteSqlCallback(t, results) {
...
},
function onExecuteSqlError(t, e) {
// Returning true to rollback, false to continue the transaction;
return false;
});
},
function onTransactionError(sqlError) {
// Safari calls this function regardless if user permits more quota or not.
// And there's no way for a developer to know user's reaction.
if (sqlError.code === sqlError.QUOTA_ERR) {
// Start over the transaction again to check if user permitted or not.
}
},
function onTransactionSuccess() {
...
});
When quota exceeds on LocalStorage or SessionStorage, catch exception using try catch
. To determine if the error is caused by a quota exceed, check if the name
property of DOMException
is either "QuotaExceededError
" or "NS_ERROR_DOM_QUOTA_REACHED
" (on Firefox).
try {
localStorage.setItem(data.name, JSON.stringify(data));
} catch(domException) {
if (domException.name === 'QuotaExceededError' ||
domException.name === 'NS_ERROR_DOM_QUOTA_REACHED') {
// Fallback code comes here.
}
}
As you can see above, each browser has unique characteristics when it comes to storage, quota, and limits. It is important to make sure your app won't fail on exceeding quota and gracefully fall back to a meaningful result. Also, check out the ServiceWorker and the new Quota Management API which specifications are under discussion. They will drastically change the way you will interact with the limitations this article described when implemented.
Lastly, please feel free to send us a Pull Request if you find any correction or updates in this article.
{% endblock %}


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INTRODUCING
Juniro CSS UI
A collection of varieties of HTML UI Kits and components.
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This small, vibrant city lies on Norway's Southwest coast about 100km south of Bergen. It is a major fishing and processing centre for herring, mackerel, and lobster
The harbour is right in the centre of the town and is very popular, especially during the film, jazz and Viking Boat festivals held here each year.
Visitors berth on the stone quay, avoiding those areas reserved for the ferries and commercial boats.


--- title: "Themed Gardens" layout: "default" ---
Red Butte Garden is Utah's Botanical Garden. Covering over 100 acres, it is comprised of many different gardens suited for different kinds of plants, landscaping, and watering needs.
Themed gardens include the Four Seasons Garden, Herb Garden, Children's Garden, Fragrance Garden, Floral Walk, Medicinal Garden, Water Pavilion Garden, Rose Garden, Wildflower Meadow, Water Conservation Garden, and others. Stay tuned for more information about our themed gardens as we continue to update this page.


Moringa School
HTML, CSS and Javascript languages to develop websites.
SEO and SEM, Web analytics Websites, use of Social media etc.
December 2011 – To Date (Part-time)
Personal Assistant to the MD – Ensure the smooth day to day running of the business, any pending work is completed in due time. Ensure the MD is kept up to date with reports on the position of the company.
Accountant – I handle petty cash, monthly VAT tax returns, initiate and make purchase from supplier and follow up on payments from the customer.
Sales – Source products from suppliers, send out quotations requested by the client.
Vice Chair to the graduating class commitee of 2018. This entailed the events leading to graduation go according to plan. These were:
Campus Ambassador. Creating awareness among youth especially those in campus on the importance of personal financial management.
B.Com Management Information System
Kenya Certificate of Secondary Education
Kenya Certificate of Primary Education


|
|
long | Key [get] |
| | - Returns
- The unique key of the job
|
| |
|
string | Type [get] |
| | - Returns
- The type of the job
|
| |
|
long | ProcessInstanceKey [get] |
| | - Returns
- Key of the process instance
|
| |
|
string | BpmnProcessId [get] |
| | - Returns
- BPMN process id of the process
|
| |
|
int | ProcessDefinitionVersion [get] |
| | - Returns
- Version of the process
|
| |
|
long | ProcessDefinitionKey [get] |
| | - Returns
- Key of the process
|
| |
|
string | ElementId [get] |
| | - Returns
- Id of the process element
|
| |
|
long | ElementInstanceKey [get] |
| | - Returns
- Key of the element instance
|
| |
|
string | Worker [get] |
| | - Returns
- the assigned worker to complete the job
|
| |
|
int | Retries [get] |
| | - Returns
- remaining retries
|
| |
| DateTime | Deadline [get] |
| |
|
string | Variables [get] |
| | - Returns
- JSON-formatted variables
|
| |
|
string | CustomHeaders [get] |
| | - Returns
- JSON-formatted Custom Headers
|
| |
◆ Deadline
| DateTime Zeebe.Client.Api.Responses.IJob.Deadline |
|
get |
- Returns
- The time until when the job is exclusively assigned to this worker. If the deadline is exceeded, it can happen that the job is handed to another worker and the work is performed twice.
The documentation for this interface was generated from the following file:
- Client/Api/Responses/IJob.cs


|
PX4 Firmware
PX4 Autopilot Software http://px4.io
|
otp estimation More...
#include <px4_config.h>
#include <board_config.h>
#include <stdio.h>
#include <math.h>
#include <unistd.h>
#include <string.h>
#include "conversions.h"
#include "otp.h"
#include "err.h"
#include <assert.h>
Go to the source code of this file.
Functions | |
| int | val_read (void *dest, volatile const void *src, int bytes) |
| int | write_otp (uint8_t id_type, uint32_t vid, uint32_t pid, char *signature) |
| int | lock_otp (void) |
| static int | F_GetStatus (void) |
| void | F_unlock (void) |
| void | F_lock (void) |
| int | F_write_word (unsigned long Address, uint32_t Data) |
| int | F_write_byte (unsigned long Address, uint8_t Data) |
otp estimation
Definition in file otp.c.
|
static |
Definition at line 151 of file otp.c.
References F_BSY, F_BUSY, F_COMPLETE, F_ERROR_OPERATION, F_ERROR_PROGRAM, F_ERROR_WRP, F_OPERR, F_WRPERR, and FLASH.
Referenced by F_write_byte().
| void F_unlock | ( | void | ) |
| int F_write_byte | ( | unsigned long | Address, |
| uint8_t | Data | ||
| ) |
Definition at line 203 of file otp.c.
References CR_PSIZE_MASK, F_BUSY, F_COMPLETE, F_CR_PG, F_GetStatus(), F_PSIZE_BYTE, FLASH, IS_F_ADDRESS, and status.
Referenced by F_write_word(), lock_otp(), and write_otp().
| int F_write_word | ( | unsigned long | Address, |
| uint32_t | Data | ||
| ) |
Definition at line 188 of file otp.c.
References F_write_byte().
Referenced by write_otp().
| int lock_otp | ( | void | ) |
Definition at line 121 of file otp.c.
References ADDR_OTP_LOCK_START, F_write_byte(), and OTP_LOCK_LOCKED.
| int val_read | ( | void * | dest, |
| volatile const void * | src, | ||
| int | bytes | ||
| ) |
| int write_otp | ( | uint8_t | id_type, |
| uint32_t | vid, | ||
| uint32_t | pid, | ||
| char * | signature | ||
| ) |
Definition at line 71 of file otp.c.
References ADDR_OTP_START, F_write_byte(), F_write_word(), and warnx.


CSPICE_WNSUMD summarizes the contents of a double precision window.
Given:
window SPICE window containing zero or more intervals.
[2n,1] = size(window); double = class(window)
the call:
[ meas, avg, stddev, shortest, longest ] = cspice_wnsumd( window )
returns:
meas total measure of the intervals in the input window. This is
just the sum of the measures of the individual intervals.
[1,1] = size(meas); double = class(meas)
avg average measure of the intervals in the input window.
[1,1] = size(avg); double = class(avg)
stddev standard deviation of the measures of the intervals in the
input window.
[1,1] = size(stddev); double = class(stddev)
shortest,
longest indices of the left endpoint of, respectively, the shortest
and longest intervals in the data contained in 'window'.
[1,1] = size(longest); int32 = class(longest)
The following algorithm describes the relation of
'shortest' and 'longest' to the window data:
The shortest interval:
[ window(shortest), window(shortest+1) ]
The longest interval:
[ window(longest), window(longest+1) ]
Any numerical results shown for this example may differ between
platforms as the results depend on the SPICE kernels used as input
and the machine specific arithmetic implementation.
%
% Define an array representing a window with six intervals.
% The values in 'window' have correct order for a
% SPICE window.
%
window = [ [ 1.; 3.]; ...
[ 7.; 11.]; ...
[ 18.; 18.]; ...
[ 23.; 27.]; ...
[ 30.; 69.]; ...
[ 72.; 80.] ];
%
% Calculate the summary for 'window'.
%
[ meas, avg, stddev, shortest, longest] = cspice_wnsumd( window );
%
% 'shortest' and 'longest' refer to the indices of
% the 'cell' data array.
%
intrvl_short= (shortest+1)/2;
intrvl_long = (longest+1)/2;
fprintf( 'Measure : %f\n', meas )
fprintf( 'Average : %f\n', avg )
fprintf( 'Standard Dev : %f\n', stddev )
fprintf( 'Index shortest : %i\n', shortest )
fprintf( 'Index longest : %i\n', longest )
fprintf( 'Interval shortest : %i\n', intrvl_short)
fprintf( 'Interval longest : %i\n', intrvl_long )
fprintf( 'Shortest interval : %f %f\n', window(shortest), ...
window(shortest+1) )
fprintf( 'Longest interval : %f %f\n', window(longest), ...
window(longest+1) )
MATLAB outputs:
Measure : 57.000000
Average : 9.500000
Standard Dev : 13.413302
Index shortest : 5
Index longest : 9
Interval shortest : 3
Interval longest : 5
Shortest interval : 18.000000 18.000000
Longest interval : 30.000000 69.000000
This routine provides a summary of the input window, consisting
of the following items:
- The measure of the window.
- The average and standard deviation of the measures
of the individual intervals in the window.
- The indices of the left endpoints of the shortest
and longest intervals in the window.
All of these quantities are zero if the window contains no
intervals.
For important details concerning this module's function, please refer to
the CSPICE routine wnsumd_c.
MICE.REQ
WINDOWS.REQ
-Mice Version 1.0.1, 12-MAR-2012, EDW (JPL), SCK (JPL)
Edited I/O section to conform to NAIF standard for Mice documentation.
-Mice Version 1.0.0, 15-DEC-2008, EDW (JPL)
summary of a d.p. window
|


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assert(got, [msg])
Assert that the gotten expression is true.
Example
assert(3 < 5); //Assertion OK
assert(5 < 3); //Assertion failed
GMAssert is a library containing useful assertions for debugging and automated unit testing. You can use it to alert you to undesirable runtime conditions and pause the debugger at that point for further inspection.
Simply drag GMAssert.gml into your open project and import constants.txt as macros. If you wish to use the debugger, open __GMA_BREAKPOINT__ and place a breakpoint on the marked line.
Assert that the gotten expression is true.
assert(3 < 5); //Assertion OK
assert(5 < 3); //Assertion failed
Assert that the gotten expression is false.
assert_fail(3 > 5); //Assertion OK
assert_fail(5 > 3); //Assertion failed
Assert that the gotten expression is equal to the expected expression.
var total = 3+5;
assert_equal(total, 8); //Assertion OK
assert_equal(total, "8"); //Assertion failed
Assert that the gotten expression is approximately equal to the expected expression.
assert_equalish(math_get_epsilon(), 0); //Assertion OK
assert_equalish(0.1, 0); //Assertion failed
Assert that the gotten expression is not equal to the expected expression.
var total = 583+907; assert_not_equal(total, 2016); //Assertion OK
assert_not_equal(total, 1490); //Assertion failed
Assert that the gotten expression is not approximately equal to the expected expression.
assert_not_equalish(0.5, 0); //Assertion OK
assert_not_equalish(math_get_epsilon(), 0); //Assertion failed
Assert that the gotten expression is not exactly equal to the expected expression (as compared using ==).
var arrayA, arrayB;
arrayA[0] = 5;
arrayB[0] = 5;
arrayA[1] = 8;
arrayB[1] = 8;
assert_isnt(arrayA, arrayB); //Assertion OK
assert_isnt(arrayA, arrayA); //Assertion failed
Assert that the gotten expression is greater than the expected expression.
var result = sin(pi/3); //sqrt(3)/2
assert_greater_than(result, 0.5); //Assertion OK
assert_greater_than(result, 1); //Assertion failed
Assert that the gotten expression is less than the expected expression.
var list = ds_list_create();
ds_list_add(list, 1, 2, 3);
assert_less_than(ds_list_size(list), 5); //Assertion OK
assert_less_than(ds_list_size(list), 3); //Assertion failed
Assert that the gotten expression is greater than or equal to the expected expression..
var spd = 5,
dir = 90;
assert_greater_than_or_equal(lengthdir_x(spd, dir), 0); //Assertion OK
assert_greater_than_or_equal(lengthdir_y(spd, dir), 0); //Assertion failed
Assert that the gotten expression is less than or equal to the expected expression.
assert_less_than_or_equal(dcos(220), 0); //Assertion OK
assert_less_than_or_equal(dcos(330), 0); //Assertion failed
Assert that the gotten expression is a string.
var str = "waahoo",
num = pi;
assert_is_string(str); //Assertion OK
assert_is_string(num); //Assertion failed
Assert that the gotten expression is a real number.
var num = pi;
assert_is_real(num); //Assertion OK
assert_is_real(string(num)); //Assertion failed
Assert that the gotten expression is an array.
var array;
array[0] = 5;
array[1] = 8;
var str = "waahoo";
assert_is_array(array); //Assertion OK
assert_is_array(str); //Assertion failed
Assert that the gotten expression is not undefined.
var numA = 583,
numB = undefined;
assert_is_defined(numA); //Assertion OK
assert_is_defined(numB); //Assertion failed
Assert that the gotten expression is not a string.
var str = "waahoo",
num = pi;
assert_isnt_string(num); //Assertion OK
assert_isnt_string(str); //Assertion failed
Assert that the gotten expression is not a real number.
var str = "3.14";
assert_isnt_real(str); //Assertion OK
assert_isnt_real(real(str)); //Assertion failed
Assert that the gotten expression is not an array.
var array;
array[0] = 5;
array[1] = 8;
var str = "waahoo";
assert_isnt_array(str); //Assertion OK
assert_isnt_array(array); //Assertion failed
Assert that the gotten expression is undefined.
var numA = 583,
numB = undefined;
assert_isnt_defined(numB); //Assertion OK
assert_isnt_defined(numA); //Assertion failed
Assert that the gotten expression is within the inclusive range between lower and upper.
assert_in_range(pi, 3, 4); //Assertion OK
assert_in_range(exp(1), 3, 4); //Assertion failed
Assert that the gotten expression is not within the inclusive range betwee, lower and upper.
assert_not_in_range(sin(pi/4), 0, 1/2); //Assertion OK
assert_not_in_range(sin(pi/8), 0, 1/2); //Assertion failed
Assert that the gotten string, list or array contains a value exactly equal to content.
var list = ds_list_create();
ds_list_add(list, 1, 2, "waahoo", 3, 4);
assert_contains(list, "waahoo"); //Assertion OK
assert_contains(list, "WAAHOO"); //Assertion failed
Assert that the gotten string, list or array contains a value exactly equal to content (as compared using ==).
var sentence = "The quick brown fox jumps over the lazy dog";
assert_contains_exact(sentence, "fox"); //Assertion OK
assert_contains_exact(sentence, "armadillo"); //Assertion failed
Assert that the gotten string, list or array does not contain a value equal to content.
var animals;
animals[0] = "ant";
animals[1] = "bear";
animals[2] = "cat";
assert_doesnt_contain(animals, "butterfly"); //Assertion OK
assert_doesnt_contain(animals, "bear"); //Assertion failed
Assert that the gotten string, list or array does not contain a value exactly equal to content (as compared using ==).
var list = ds_list_create();
ds_list_add(list, 1, 2, "waahoo", 3, 4);
assert_doesnt_contain_exact(list, "WAAHOO"); //Assertion OK
assert_doesnt_contain_exact(list, 4); //Assertion failed