LATERAL Join
Starting in Drill 1.15, the lateral join functionality is enabled by default. If you are running earlier versions of Drill, use the SET command to enable the planner.enable_unnest_lateral
option.
A lateral join is essentially a foreach loop in SQL. A lateral join is represented by the keyword LATERAL with an inner subquery in the FROM clause, as shown in the following simple representation:
SELECT <columns>
FROM <tableReference>
LATERAL <innerSubquery>;
Similar to a correlated subquery, a lateral inner subquery can refer to fields in rows of the table reference to determine which rows to return. A lateral subquery iterates through each row in the table reference, evaluating the inner subquery for each row, like a foreach loop. The rows returned by the inner subquery are added to the result of the join with the outer query. Without the LATERAL keyword, each subquery is evaluated independently and cannot refer to items in FROM.
Syntax
...FROM tableReference
tableReference:
with_subquery_table_name [ [ AS ] alias [ ( column_alias [, ...] ) ] ]
| table_name [ [ AS ] alias [ ( column_alias [, ...] ) ] ]
| ( subquery ) [ AS ] alias [ ( column_alias [, ...] ) ]
| <join_clause>
| [ LATERAL ] [<lateral_join_type>] <lateral_subquery> [ON TRUE]
join_clause:
tableReference <join_type> tableReference [ON <join_condition>]
lateral_subquery:
<unnest_table_expr>
| ( SELECT_clause FROM <unnest_table_expr> [,...] )
lateral_join_type:
[INNER] JOIN
LEFT [OUTER] JOIN
unnest_table_expr:
UNNEST '(' expression ')' [AS] <alias_table_name>(<alias_column_name>)
Parameters
The following parameters are specific to lateral join. The list does not include all of the parameters applicable to the FROM clause:
-
join_clause
Identifies the tables with the data you want to join, the type of join to be performed on the tables, and the conditions on which to join the tables. Starting in Drill 1.14, Drill supports lateral joins. -
LATERAL
Keyword that represents a lateral join. A lateral join is essentially a foreach loop in SQL. A lateral join combines the results of the outer query with the results of a lateral subquery. When you use the UNNEST relational operator, Drill infers the LATERAL keyword. -
lateral_sub_query
A lateral subquery is like correlated subqueries except that you use a lateral subquery in the FROM clause instead of the WHERE clause. Also, lateral subqueries can return any number of rows; correlated subqueries return exactly one row. -
unnest_table_expr
References the table produced by the UNNEST relational operator. UNNEST converts a collection to a relation. You must use the UNNEST relational operator with LATERAL subqueries when a field contains repeated types, like an array of maps. You must also indicate an alias for the table produced by UNNEST. -
lateral_join_type
The type of join used with the lateral subquery. Lateral subqueries support [INNER] JOIN and LEFT [OUTER] JOIN, for example:...FROM table1 LEFT OUTER JOIN LATERAL (select a from t2) ON TRUE;
If you do not indicate the join type, Drill infers an INNER JOIN.
-
ON TRUE
The join condition when the results of a lateral subquery are joined with fields in rows of the table referenced. This condition is implicit. You do not have to include the condition in the query.
Usage Notes
LATERAL Subqueries
-
Lateral subqueries are similar to correlated subqueries except that you use a lateral subquery in the FROM clause instead of the WHERE clause. Also, lateral subqueries can return any number of rows; correlated subqueries return exactly one row.
-
You can use lateral subqueries with the LEFT OUTER and INNER join types, for example:
...FROM table1 LEFT OUTER JOIN LATERAL (select a from t2) ON true;
-
If you use the LATERAL keyword in a query, you must include the UNNEST relational operator in the subquery. However, if you use UNNEST without LATERAL, Drill infers the LATERAL keyword.
-
Use LATERAL subqueries with the UNNEST operator when a field contains repeated types, like an array of maps.
-
Lateral subqueries support the following operators:
- Limit - Filter - Project - TopN - Sort - HashAgg
UNNEST Relational Operator
- A relational operator that behaves like a table function; UNNEST converts a collection to a relation.
- UNNEST works on arrays; it creates a table with one field and multiple rows (one row for each entry in the array).
- You can only use UNNEST in the FROM clause.
- You cannot use UNNEST without LATERAL; if you use UNNEST without LATERAL, Drill infers a LATERAL join.
- UNNEST can only unnest one column. However, the array in the column can be a multi-nested array.
- Unnests data in small chunks, which typically provides a performance advantage when applying filters or running subqueries.
- Unnest operators on each row of the source table; data can be partitioned without having to use a window function.
- For queries with nested laterals, you must provide a name (alias) for the table that UNNEST generates.
- UNNEST and LATERAL work similarly to FLATTEN, but differ from FLATTEN in the follow ways:
- UNNEST is a SQL standard, whereas FLATTEN is not.
- FLATTEN is only allowed in the SELECT list of query, not in the FROM clause.
- FLATTEN does not work with schema changes, but UNNEST can if the queries do not have hash aggregates. FLATTEN requires all data in a column to be of the same type. For example, if a column contains integers in some rows and float in others, UNNEST can process the query, whereas FLATTEN cannot.
- LATERAL and UNNEST cover a wider set of use cases than FLATTEN. For example, when you use LATERAL and UNNEST, Drill can perform a LEFT OUTER JOIN on data. If you used FLATTEN, Drill must scan the source table twice to perform an OUTER JOIN after flattening the data. Also, with LATERAL and UNNEST, you can apply a filter, aggregate, or limit on each row. With FLATTEN, the filter or aggregate is applied after flattening, however you cannot apply the limit on each row.
- FLATTEN unnests data into a table and processes the entire table; filters and subqueries are applied on the entire table at the same time.
LATERAL Join Query Examples
The following sections provide query examples to demonstrate the use of lateral joins.
Simplified Query using LATERAL and UNNEST
The following customer table contains customer data, including customer orders and returns, with the order and return data stored as complex types (arrays of maps). The store_id column is a foreign key.
|
cust_id |
cust_name |
store_id |
orders |
returns |
|
101 |
Fred |
5 |
[ {order_id: 2,
order_date: |
[ {order_id: 2,
return_date: 11/20/2017, return_amount: $200, |
|
102 |
Jack |
7 |
<orders |
<returns |
|
... |
... |
... |
... |
If you want to query the Customer table for the average order amount for each customer in the month of November, you could write the following query, which uses a combination of a left outer join, group by, and the flatten function to unnest the orders field that contains complex types:
SELECT t1.cust_name, t2.avg_orders
FROM customer t1
LEFT
OUTER JOIN
(SELECT f.cust_id,
AVG(f.order_amount) as avg_orders
FROM (SELECT
cust_id, FLATTEN(customer.orders) FROM customer) f
WHERE
f.order_date between date ‘11012017’
and date ‘11302017’
GROUP BY
f.cust_id
) t2 on t1.cust_id =
t2.cust_id
However, this query is complex and inefficient. Writing the query with a lateral subquery resolves the inefficiencies:
SELECT cust_name, avg_orders
FROM customer c
LATERAL (SELECT AVG(order_amount) as avg_orders FROM UNNEST(c.orders)o
WHERE o.order_date BETWEEN date ‘11012017’ and date ‘11302017’);
Note that the FROM clause in the subquery references the ‘orders’ array from the table alias ‘c’ which is the outer table. The reference to an outer table within the subquery makes this look like a correlated subquery. However, there is an important difference in that a correlated subquery is used in the WHERE clause whereas what we really want is the set of rows from the un-nested array exposed as a ‘sub-table’ such that relevant filtering, aggregation, and so on can be performed.
Example Queries with LATERAL, UNNEST, and Aliases
The following query examples demonstrate the use of the LATERAL keyword and UNNEST relational operator with aliases.
Example 1: One level lateral with an alias and implicit LATERAL
Drill infers a LATERAL join when you use the UNNEST relational operator. In the following query, UNNEST produces a table with one column that contains an unnested customer.c_orders column. In this query, the table produced by unnest is aliased as _orders and the column is aliased as c_order.
SELECT
customer.c_name, customer.c_address, _orders.c_order.o_orderkey, _orders.c_order.o_totalprice
FROM
dfs.`/Users/user1/work/data/complex/cust_order` customer,
UNNEST(customer.c_orders) _orders(c_order)
;
Example 2: One level lateral with an alias and explicit LATERAL
The following query contains the LATERAL keyword with a subquery that selects all the columns (SELECT *) from the table produced by the UNNEST relational operator. The table produced by UNNEST is aliased as _orders(c_order). The subquery result is a table aliased as t_orders. Drill performs the lateral join on the table that results from the subquery (t_orders). The query produces the same query plan as the previous example (Example 1) where LATERAL was inferred.
SELECT
customer.c_name, customer.c_address, t_orders.c_order.o_orderkey, t_orders.c_order.o_totalprice
FROM
dfs.`/Users/user1/work/data/complex/cust_order` customer,
LATERAL (
SELECT * from UNNEST(customer.c_orders) _orders(c_order)
) t_orders
;
Example 3: Multi-level lateral with alias
A multi-level lateral is a nested lateral query. When a query contains nested laterals, you must use aliases for the tables generated by the UNNEST relational operator. If you do not include aliases, the query parser cannot discern between table and column names and returns parsing errors.
In the following query, the first level UNNEST (line 8) that corresponds to the first level LATERAL (line 5) produces a table with a single column that is aliased as _order(c_order). Since c_order is a map, the select clause in the corresponding subquery (line 7) projects only the required fields. As a result, the subquery produces a table that is aliased as t_orders(orderkey, orderamt, lineitems).
The table t_orders is then processed by the second level LATERAL (line 10) and the corresponding second level UNNEST (line 13) will unnest the field t_orders.lineitems. The second level lateral subquery produces a table aliased as t_items.
Note that the SELECT in the outer query can now refer to the tables t_orders and t_items.
1: SELECT
2: customer.c_name, customer.c_address, t_orders.orderkey, t_orders.orderamt, t_items.item.l_partkey, t_items.item.l_linenumber
3: FROM
4: dfs.`/Users/pchandra/work/data/complex/cust_order` customer,
5: LATERAL
6: (
7: select _orders.c_order.o_orderkey orderkey, _orders.c_order.o_totalprice orderamt, _orders.c_order.o_lineitems as lineitems
8: FROM UNNEST(customer.c_orders) _orders(c_order)
9: ) t_orders,
10: LATERAL
11: (
12: SELECT *
13: FROM UNNEST(t_orders.lineitems) AS _items(item)
14: ) t_items
15: ;
Example 4: One level lateral with aggregation
For every customer, the following query returns the number of orders for each priority level. The subquery that corresponds to the lateral, aggregates the order count, grouped by the priority, in the table _orders(c_order) produced by UNNEST.
SELECT
customer.c_name, customer.c_address, t_orders.o_orderCount, t_orders.o_orderpriority
FROM
dfs.`/Users/user1/work/data/complex/cust_order` customer,
lateral (
select count(_orders.c_order.o_orderkey) as o_orderCount, _orders.c_order.o_orderpriority as o_orderpriority from UNNEST(customer.c_orders) _orders(c_order) group by _orders.c_order.o_orderpriority
) t_orders
;
FLATTEN vs LATERAL and UNNEST Queries
Each of the following examples shows a query written with the FLATTEN function and also written with a lateral join and UNNEST relational operator, which performs like a table function. These queries demonstrate how to use LATERAL and UNNEST instead of FLATTEN to simplify the writing of such queries.
Example 1
The queries in this example return the order total for the top 50 customers.
FLATTEN
SELECT l.c_custkey, l.c_name, r.orderkey,
SUM(r.totalprice) sum_order
FROM customer l
INNER JOIN (SELECT g.custkey custkey, g.name, g.orderkey, g.totalprice totalprice
FROM (SELECT row_number() OVER(PARTITION BY c_custkey)
AS rn, f.c_custkey custkey, f.c_name name, f.o.o_orderkey orderkey, f.o.o_totalprice totalprice
FROM (SELECT c_custkey, c_name,
FLATTEN(c_orders)
AS o
FROM customer) f) g) r
ON (l.c_custkey = r.custkey)
GROUP BY l.c_custkey, l.c_name, r.orderkey
ORDER BY sum_order
LIMIT 50;
LATERAL and UNNEST
SELECT customer.c_custkey, customer.c_name, orders.o_orderkey, sum(orders.o_totalprice) total_spending from customer,
LATERAL (SELECT t.o.o_orderkey o_orderkey, t.o.o_totalprice o_totalprice
FROM
UNNEST(customer.c_orders) t(o)) orders
GROUP BY customer.c_custkey, customer.c_name, orders.o_orderkey
ORDER BY total_spending
LIMIT 50;
Example 2
The queries in this example return the first 2000 orders of the top 50 customers for orders greater than one thousand dollars.


--- layout: post title: "The Week in Robots" date: 2016-05-28 08:35:00 +0000 tags: image: https://s3.amazonaws.com/audreywatters/2016-05-28-robot.jpg imagecredits: https://www.flickr.com/photos/boris/3228482568 ---
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Reboot: Adidas to make shoes in Germany again – but using robots


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1.Sinharajaya |
| This unique tract of undisturbed tropical rainforest is a botanical treasure trove of global significance, with UNESCO World Heritage Site status. Sinharaja is just how you imagine a jungle to be: intense humidity, the cacophonous sounds of animals and insects, dense foliage and huge trees.Located in south-west Sri Lanka, Sinharaja is the country's last viable area of primary tropical rainforest. More than 60% of the trees are endemic and many of them are considered rare. There is much endemic wildlife, especially birds, but the reserve is also home to over 50% of Sri Lanka's endemic species of mammals and butterflies, as well as many kinds of insects, reptiles and rare amphibians.
Encompassing the last extensive patch of primary lowland rainforest in Sri Lanka, Sinharaja Forest Reserve is situated in the south-west lowland wet zone of Sri Lanka. Covering an area of 8,864 ha and ranging from an altitude of 300 – 1,170 meters, it consists of 6,092 ha of Forest Reserve and 2,772 ha of Proposed Forest Reserve. This narrow strip of undulating terrain encompasses a series of ridges and valleys that are crisscrossed by an intricate network of streams. |
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2. Yala National Park |
| Yala combines a strict nature reserve with a national park. Divided into 5 blocks, the park has a protected area of nearly 130,000 hectares of land consisting of light forests, scrubs, grasslands, tanks and lagoons. Two blocks are currently opened to the public.
Situated in Sri Lanka’s south-east hugging the panoramic Indian Ocean, Yala was designated a wildlife sanctuary in 1900 and was designated a national park in 1938. Ironically, the park was initially used as a hunting ground for the elite under British rule. Yala is home to 44 varieties of mammal and 215 bird species. Among its more famous residents are the world’s biggest concentration of leopards, majestic elephants, sloth bears, sambars, jackals, spotted dear, peacocks, and crocodiles. The best time to visit Yala is between February and July when the water levels of the park are quite low, bringing animals into the open.
that brings you up, close and personal with untamed world of wildlife. Whether you are an avid nature lover or visiting a wildlife park for the first time, if you come here with a mind that’s eager to explore and learn, you will go away with new-found meaning to life. |
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3. Mirissa |
| This unique tract of undisturbed tropical rainforest is a botanical treasure trove of global significance, with UNESCO World Heritage Site status. Sinharaja is just how you imagine a jungle to be: intense humidity, the cacophonous sounds of animals and insects, dense foliage and huge trees.Located in south-west Sri Lanka, Sinharaja is the country's last viable area of primary tropical rainforest. More than 60% of the trees are endemic and many of them are considered rare. There is much endemic wildlife, especially birds, but the reserve is also home to over 50% of Sri Lanka's endemic species of mammals and butterflies, as well as many kinds of insects, reptiles and rare amphibians.
Encompassing the last extensive patch of primary lowland rainforest in Sri Lanka, Sinharaja Forest Reserve is situated in the south-west lowland wet zone of Sri Lanka. Covering an area of 8,864 ha and ranging from an altitude of 300 – 1,170 meters, it consists of 6,092 ha of Forest Reserve and 2,772 ha of Proposed Forest Reserve. This narrow strip of undulating terrain encompasses a series of ridges and valleys that are crisscrossed by an intricate network of streams. |
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4. Galle |
| This unique tract of undisturbed tropical rainforest is a botanical treasure trove of global significance, with UNESCO World Heritage Site status. Sinharaja is just how you imagine a jungle to be: intense humidity, the cacophonous sounds of animals and insects, dense foliage and huge trees.Located in south-west Sri Lanka, Sinharaja is the country's last viable area of primary tropical rainforest. More than 60% of the trees are endemic and many of them are considered rare. There is much endemic wildlife, especially birds, but the reserve is also home to over 50% of Sri Lanka's endemic species of mammals and butterflies, as well as many kinds of insects, reptiles and rare amphibians.
Encompassing the last extensive patch of primary lowland rainforest in Sri Lanka, Sinharaja Forest Reserve is situated in the south-west lowland wet zone of Sri Lanka. Covering an area of 8,864 ha and ranging from an altitude of 300 – 1,170 meters, it consists of 6,092 ha of Forest Reserve and 2,772 ha of Proposed Forest Reserve. This narrow strip of undulating terrain encompasses a series of ridges and valleys that are crisscrossed by an intricate network of streams. |
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5. Arugam Bay |
| This unique tract of undisturbed tropical rainforest is a botanical treasure trove of global significance, with UNESCO World Heritage Site status. Sinharaja is just how you imagine a jungle to be: intense humidity, the cacophonous sounds of animals and insects, dense foliage and huge trees.Located in south-west Sri Lanka, Sinharaja is the country's last viable area of primary tropical rainforest. More than 60% of the trees are endemic and many of them are considered rare. There is much endemic wildlife, especially birds, but the reserve is also home to over 50% of Sri Lanka's endemic species of mammals and butterflies, as well as many kinds of insects, reptiles and rare amphibians.
Encompassing the last extensive patch of primary lowland rainforest in Sri Lanka, Sinharaja Forest Reserve is situated in the south-west lowland wet zone of Sri Lanka. Covering an area of 8,864 ha and ranging from an altitude of 300 – 1,170 meters, it consists of 6,092 ha of Forest Reserve and 2,772 ha of Proposed Forest Reserve. This narrow strip of undulating terrain encompasses a series of ridges and valleys that are crisscrossed by an intricate network of streams. |
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6. Sigiriya |
| Referred by locals as the Eighth Wonder of the World this ancient palace and fortress complex has significant archaeological importance and attracts thousands of tourists every year. It is probably the most visited tourist destination of Sri Lanka.
The palace is located in the heart of the island between the towns of Dambulla and Habarane on a massive rocky plateau 370 meters above the sea level.
Sigiriya rock plateau, formed from magma of an extinct volcano, is 200 meters higher than the surrounding jungles.
The palace is located in the heart of the island between the towns of Dambulla and Habarane on a massive rocky plateau 370 meters above the sea level.
Sigiriya rock plateau, formed from magma of an extinct volcano, is 200 meters higher than the surrounding jungles.
Its view astonishes the visitors with the unique harmony between the nature and human imagination.
The fortress complex includes remnants of a ruined palace, surrounded by an extensive network of fortifications, vast gardens, ponds, canals, alleys and fountains.
The surrounding territories of Sigiriya were inhibited for several thousand years.
Since 3th century BC the rocky plateau of Sigiriya served as a monastery. In the second half of the 5th century king Kasyapa decided to construct a royal residence here.
Its view astonishes the visitors with the unique harmony between the nature and human imagination. |
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7. The Pettah, Colombo |
| Colombo Fort is the cultural, financial and economic hub of the city and is home to many important buildings and offices. It is the supreme business district of Srilanka and is home to the Stock Exchange building and the World Trade Centre, which is the tallest building in the country.
The area is a very dynamic area as it not only facilitates trade and business in its lanes but also has some of the finest food stalls, tourist places, casinos and bars. Colombo Fort also has the popular Galle Face Green Promenade which is sea-facing ground built-in 1859.
It is one of the finest and most popular places in the city. In the yesteryears, the area was home to the biggest palace in Sri Lanka which was demolished and repaired from the Dutch-era to the Portuguese-era. Till date, the remains of the palace are in existence like the Bastin Dan Briel, Battenburg Batteries, etc. Colombo Fort is also home to the official residence of the President of Sri Lanka and other important Ministers.
The fort area also has the Consulate of Spain, Seychelles, Latvia, Denmark and Lithuania. Colombo Fort is the ultimate place to enjoy the original vibe of the Island nation and embrace the rich culture of the country through its food and various other things and activities.
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8. Rock temples, Dambulla |
| Dambulla cave temple (Sinhalese: Dam̆būlū Len Vihāraya, Tamil Tampuḷḷai Poṟkōvil) also known as the Golden Temple of Dambulla is a World Heritage Site (1991) in Sri Lanka, situated in the central part of the country.[1] This site is situated 148 kilometres (92 mi) east of Colombo , 72 kilometres (45 mi) north of Kandy and 43 km (27 mi) north of Matale
Dambulla is the largest and best-preserved cave temple complex in Sri Lanka. The rock towers 160 m over the surrounding plains. There are more than 80 documented caves in the surrounding area. Major attractions are spread over five caves, which contain statues and paintings. These paintings and statues are related to Gautama Buddha and his life. There are a total of 153 Buddha statues, three statues of Sri Lankan kings and four statues of gods and goddesses. The latter include Vishnu and the Ganesha. The murals cover an area of 2,100 square metres (23,000 sq ft). Depictions on the walls of the caves include the temptation by the demon Mara, and Buddha's first sermon.
Prehistoric Sri Lankans would have lived in these cave complexes before the arrival of Buddhism in Sri Lanka as there are burial sites with human skeletons about 2700 years old in this area, at Ibbankatuwa near the Dambulla cave complexes.
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9. Adam’s Peak |
| This unique tract of undisturbed tropical rainforest is a botanical treasure trove of global significance, with UNESCO World Heritage Site status. Sinharaja is just how you imagine a jungle to be: intense humidity, the cacophonous sounds of animals and insects, dense foliage and huge trees.Located in south-west Sri Lanka, Sinharaja is the country's last viable area of primary tropical rainforest. More than 60% of the trees are endemic and many of them are considered rare. There is much endemic wildlife, especially birds, but the reserve is also home to over 50% of Sri Lanka's endemic species of mammals and butterflies, as well as many kinds of insects, reptiles and rare amphibians.
Encompassing the last extensive patch of primary lowland rainforest in Sri Lanka, Sinharaja Forest Reserve is situated in the south-west lowland wet zone of Sri Lanka. Covering an area of 8,864 ha and ranging from an altitude of 300 – 1,170 meters, it consists of 6,092 ha of Forest Reserve and 2,772 ha of Proposed Forest Reserve. This narrow strip of undulating terrain encompasses a series of ridges and valleys that are crisscrossed by an intricate network of streams. |
|
|
10. Jaffna and the Islands |
| This unique tract of undisturbed tropical rainforest is a botanical treasure trove of global significance, with UNESCO World Heritage Site status. Sinharaja is just how you imagine a jungle to be: intense humidity, the cacophonous sounds of animals and insects, dense foliage and huge trees.Located in south-west Sri Lanka, Sinharaja is the country's last viable area of primary tropical rainforest. More than 60% of the trees are endemic and many of them are considered rare. There is much endemic wildlife, especially birds, but the reserve is also home to over 50% of Sri Lanka's endemic species of mammals and butterflies, as well as many kinds of insects, reptiles and rare amphibians.
Encompassing the last extensive patch of primary lowland rainforest in Sri Lanka, Sinharaja Forest Reserve is situated in the south-west lowland wet zone of Sri Lanka. Covering an area of 8,864 ha and ranging from an altitude of 300 – 1,170 meters, it consists of 6,092 ha of Forest Reserve and 2,772 ha of Proposed Forest Reserve. This narrow strip of undulating terrain encompasses a series of ridges and valleys that are crisscrossed by an intricate network of streams. |


mne.decoding.
LinearModel
(model=None)[source]¶Compute and store patterns from linear models.
The linear model coefficients (filters) are used to extract discriminant neural sources from the measured data. This class computes the corresponding patterns of these linear filters to make them more interpretable [R38].
| Parameters: | model : object | None
|
|---|
See also
Notes
New in version 0.10.
References
| [R38] | (1, 2) Haufe, S., Meinecke, F., Gorgen, K., Dahne, S., Haynes, J.-D., Blankertz, B., & Biebmann, F. (2014). On the interpretation of weight vectors of linear models in multivariate neuroimaging. NeuroImage, 87, 96-110. |
Attributes
filters_ |
(ndarray) If fit, the filters used to decompose the data. |
patterns_ |
(ndarray) If fit, the patterns used to restore M/EEG signals. |
Methods
__hash__ () <==> hash(x) |
|
fit (X, y) |
Estimate the coefficients of the linear model. |
fit_transform (X, y) |
Fit the data and transform it using the linear model. |
get_params ([deep]) |
Get parameters for this estimator. |
plot_filters (*args, **kwargs) |
Warning DEPRECATED: plot_filters is deprecated and will be removed in 0.15, use EvokedArray instead. |
plot_patterns (*args, **kwargs) |
Warning DEPRECATED: plot_filters is deprecated and will be removed in 0.15, use EvokedArray instead. |
predict (X) |
Compute predictions of y from X. |
score (X, y) |
Score the linear model computed on the given test data. |
set_params (**params) |
Set the parameters of this estimator. |
transform (X) |
Transform the data using the linear model. |
__hash__
() <==> hash(x)¶fit
(X, y)[source]¶Estimate the coefficients of the linear model.
Save the coefficients in the attribute filters_
and
computes the attribute patterns_
.
| Parameters: | X : array, shape (n_samples, n_features)
y : array, shape (n_samples,)
|
|---|---|
| Returns: | self : instance of LinearModel
|
fit_transform
(X, y)[source]¶Fit the data and transform it using the linear model.
| Parameters: | X : array, shape (n_samples, n_features)
y : array, shape (n_samples,)
|
|---|---|
| Returns: | y_pred : array, shape (n_samples,)
|
get_params
(deep=True)[source]¶Get parameters for this estimator.
| Parameters: | deep : boolean, optional
|
|---|---|
| Returns: | params : mapping of string to any
|
plot_filters
(*args, **kwargs)[source]¶Warning
DEPRECATED: plot_filters is deprecated and will be removed in 0.15, use EvokedArray instead.
Plot topographic filters of the linear model.
The filters are used to extract discriminant neural sources from the measured data (a.k.a. the backward model).
| Parameters: | info : instance of Info
|
|---|---|
| Returns: | fig : instance of matplotlib.figure.Figure
|
plot_patterns
(*args, **kwargs)[source]¶Warning
DEPRECATED: plot_filters is deprecated and will be removed in 0.15, use EvokedArray instead.
Plot topographic patterns of the linear model.
The patterns explain how the measured data was generated from the neural sources (a.k.a. the forward model).
| Parameters: | info : instance of Info
|
|---|---|
| Returns: | fig : instance of matplotlib.figure.Figure
|
predict
(X)[source]¶Compute predictions of y from X.
| Parameters: | X : array, shape (n_samples, n_features)
|
|---|---|
| Returns: | y_pred : array, shape (n_samples,)
|
score
(X, y)[source]¶Score the linear model computed on the given test data.
| Parameters: | X : array, shape (n_samples, n_features)
y : array, shape (n_samples,)
|
|---|---|
| Returns: | score : float
|
set_params
(**params)[source]¶Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects
(such as pipelines). The latter have parameters of the form
<component>__<parameter>
so that it’s possible to update each
component of a nested object.
Returns
——-
self


PSALMS 103
A psalm written by David.
1 I tell myself that I should praise Yahweh.
I will praise him because he is holy.
2 I tell myself that I should praise Yahweh
and never forget all the kind things he has done for me.
3 He forgives all my sins,
and he heals me from all my diseases;
4 he keeps me from dying,
and he blesses me by faithfully loving me and acting mercifully to me as he promised to do.
5 He gives me good things during my entire life.
He makes me feel young and strong like eagles.
6 Yahweh judges justly all those who have been treated unfairly.
7 Long ago he revealed to Moses what he planned to do;
he showed to the ancestors of us Israelites the mighty things that he was able to do.
8 Yahweh acts mercifully and kindly;
he does not quickly get angry when we sin;
he is always showing us that he faithfully loves us.
9 He will not keep rebuking us,
and he will not remain angry forever.
10 He has not punished us for our sins as we deserved.
11 The skies are very high above the earth,
and Yahweh's faithful love for all those who revere him is just as great.
12 He has taken away the guilt for our sins
and put it as far from us as the east is from the west.
13 Just as parents act mercifully toward their children,
Yahweh is kind to those who revere him.
14 He knows what our bodies are like;
he remembers that he created us from dust
and that we therefore quickly fail to do what pleases him .
15 We humans do not live forever;
we are like grass which withers and dies.
We are like wild flowers that bloom for a short while;
16 but then the hot wind blows over them, and they disappear;
no one sees them again.
17 But Yahweh will faithfully keep loving forever
all those who revere him, as he promised.

I also will praise Yahweh!


Education
Withering Madness University - Planet Vhoorl
Major:Public Relations
Major:Scale Tending
Skills
Office skills
Office and records management, database administration, event organization, customer support, travel coordination
Computer skills
Microsoft productivity software (Word, Excel, etc), Adobe Creative Suite, Windows
Hobbies
World Domination, Deep Sea Diving, Murder Most Foul
References
Available on request


--- layout: post title: All Stacked Up date: 2009-09-18 18:57:14.000000000 +05:30 categories: - kiranoncemore - S3 IS tags: - B&W - experimental - rural - stack - village status: publish type: post published: true meta: _edit_last: '2' author: login: kiranoncemore email<EMAIL_ADDRESS>display_name: kiranoncemore first_name: Kiran last_name: '' ---
Tv: 1/160s; Av: F/3.2; f:8.1mm (35m-equiv:52mm)
I took this pic at my native village. What you see here are trunks of betelnut trees stacked up. These trunks are used in the betelnut "harvesting" season to build temporary one-storey high structures on which the betel-nuts are dried after coloring them. These structures are called "atta" in Kannada, and are a common sight in rural Karnataka during the season.
How this snap could have been improved?
Well, whats your opinion?


I'm a paragraph and I find this offensive (p)
Gray whales are unique to the species because they are one of the only whales that consistently eat from the bottom of the ocean. In order to obtain food these whales will swim to the bottom of the ocean and role on their side (strong, b); causing the water to lift up various sea sediments and prey. These whales will eat everything that comes up from crabs and larvae to plankton and small fish. Gray whales are very large and can consume in excess of 3,000 pounds of food on a daily basis From Whalefacts. (a)
I'm a random textLorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker (span class="code") including versions of Lorem Ipsum.
I’m happy to concede that when some of you saw the two asterisks in * + * at the beginning of this article, you started shaking your head with vigorous disapproval. There is a precedent for that. The universal selector is indeed a powerful tool. But it can be good powerful, not just bad powerful. Before we get into that, though, I want to address the perceived performance issue.
(div class="cite-by")The great thing about d3.scale.ordinal() is it supports range banding. Instead of returning a continuous range, as any quantitative scale (like d3.scale.linear()) would, ordinal scales use discrete ranges, meaning the output values are determined in advance, and could be numeric or not. We could use range() like everyone else, or we can be smooth and use rangeBands(), which takes a low and high value, and automatically divides it into even chunks or “bands”, based on the length of the domain.
Using cryptic numeric codes to represent node types is not a very JavaScript-like thing to do. Later in this chapter, we’ll see that other parts of the DOM interface also feel cumbersome and alien. The reason for this is that the DOM wasn’t designed for just JavaScript. Rather, it tries to define a language-neutral interface that can be used in other systems as well—not just HTML but also XML, which is a generic data format with an HTML-like syntax.
This is unfortunate. Standards are often useful. But in this case, the advantage (cross-language consistency) isn’t all that compelling. Having an interface that is properly integrated with the language you are using will save you more time than having a familiar interface across languages.
As an example of such poor integration, consider the childNodes property that element nodes in the DOM have. This property holds an array-like object, with a length property and properties labeled by numbers to access the child nodes. But it is an instance of the NodeList type, not a real array, so it does not have methods such as slice and forEach.
Lorem Ipsum (strong) is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
The standard chunk of Lorem Ipsum used since the 1500s is reproduced below for those interested. Sections 1.10.32 and 1.10.33 from "de Finibus Bonorum et Malorum (span class="cite-inline")" by Cicero are also reproduced in their exact original form, accompanied by English versions from the 1914 translation by H. Rackham.


____ __ ___ ______________________ ____ / __ \/ / / / | / / ____/ ___/_ __/ | / __ \ / /_/ / / / / |/ / __/ \__ \ / / / /| | / /_/ / / _, _/ /_/ / /| / /___ ___/ // / / ___ |/ _, _/ /_/ |_|\____/_/ |_/_____//____//_/ /_/ |_/_/ |_| ____ _ _ / __ \ ____ (_)___ _ (_)___ ___ ------- / /_/ // __// // _ `// // _ \ (_-< ------- \____//_/ /_/ \_, //_//_//_//___/ /___/
A Roguelike Retro Game Made for the 7DRL Challenge 2019
A keyboard is required to play.
Press Enter to begin.
Coding by Luke @ Deathray Games
Uses the open source libraries: rote js and rot js
Fonts: "Fix15Mono-Bold" by LambdaHack and "AppleII"
Thanks to Rougelike Radio and the /r/roguelikedev subreddit for inspiration.
Uses the open source libraries: rote js and rot js
Fonts: "Fix15Mono-Bold" by LambdaHack and "AppleII"
Thanks to Rougelike Radio and the /r/roguelikedev subreddit for inspiration.


We design and build beautiful arbors, decks, patios and outdoor kitchens. Make anytime a great time to be outside with family and friends. Let us create an outdoor living space that you and your family can enjoy for years to come.
Arbors are a perfect addition to the home because they can provide year round shade for outdoor grilling, entertaining guests or just lounging by the pool. They can turn a nice patio into a beautiful retreat.
Call Amazing Arbors today and get a FREE ESTIMATE<PHONE_NUMBER>! Get a free estimate for a beautiful arbor, deck, patio cover, or outdoor kitchen.
Increase the quality of life at your house, make all your memories and family gatherings special under a beautiful arbor from Amazing Arbors.


Checks if cell is to be exported and returns the name of the module to export it if provided.
Parses the cell of a Jupyter Notebook, checks if it has the #code tag,
and returns the name of the module it is associated with, otherwise returns
None.
Args:
cell: dict of the JSON of the cell
default: name of the default module where all #code will be added
Returns:
The string of the name of the cell it is associated if #code is present,
else None
Creates a Neptune ML experiment, wrapped with meta data.
Args:
project: Neptune Project
nb_name: str name of the current notebook to be recorded
globs: dict of the global variables. Simply set globs = globals() and then pass it.
return_files: bool, True if we want to send files recorded in the parameters.
default: str name of the default code
kwargs: additional args passed to Neptune ML when the experiment is created


Type Function Library (globals) Return value Elements of given table between i
andj
Revision Current Public Release (2013.2076) Keywords unpack, global Sample code none See also
Returns the elements from the given table. This function is equivalent to the following:
return list[i], list[i+1], ..., list[j]
The difference is that the above code can be written only for a fixed number of elements. By default, i
is 1 and j
is the length of the list, as defined by the length operator (#).
unpack( list [, i [, j ]] )
Table. The table whose elements will be unpacked.
Number. The index of the table element at which the function will begin unpacking values. Default: 1.
Number. The index of the table element at which the function will stop unpacking values. Default: length of the given table provided by the length
(#) operator.
local t =
{
[1] = "first",
[2] = "second",
[3] = "third",
[4] = "fourth",
[5] = "fifth"
}
local two, three, four = unpack( t, 2, 4 )
print( two, three, four )
-- OUTPUT: second third fourth


You have 60 seconds to answer each of the following questions. If you fail, you will be demoted to Assistant TO THE Regional Manager and sent to the Utica Branch.


×
−
Transfur
source
❱❭❭
target
Uploads
Watches
Favorites
Transfur
initializing
0
/
0
source
❱❭❭
target


You must have Proximity installed locally to complete the exercises in the tutorial. If you have not already installed the Proximity software, see the instructions in Appendix B, Installation for complete instructions on obtaining and installing Proximity.
The tutorial uses the PROX_HOME
environment variable to refer to the location of your local Proximity
installation. Windows
users must set this variable to use
Proximity. Linux and Mac users may want to define this environment
variable for their convenience in working through the tutorial. The
exercises and examples in this tutorial show PROX_HOME
set to /proximity
; however, you can install
Proximity in any directory.
The exercises in this tutorial use the ProxWebKB database, which is included in the Proximity distribution. Exercise 3.1 describes how to import this database into Proximity.


|
接口
ByteChannel Channel GatheringByteChannel InterruptibleChannel ReadableByteChannel ScatteringByteChannel WritableByteChannel |
|
类
Channels DatagramChannel FileChannel FileChannel.MapMode FileLock Pipe Pipe.SinkChannel Pipe.SourceChannel SelectableChannel SelectionKey Selector ServerSocketChannel SocketChannel |


| Number of Classes | Line Coverage | Mutation Coverage |
|---|---|---|
| 10 | 100% | 70% |
| Name | Line Coverage | Mutation Coverage |
|---|---|---|
| ContentType.java | 100% |
100% |
| ContentTypeTest.java | 100% |
0% |
| ErrorResponses.java | 100% |
67% |
| HTMLFileResponseTest.java | 100% |
67% |
| HTTP200OKFileResponse.java | 100% |
75% |
| HTTP400BadRequest.java | 100% |
100% |
| HTTP403Forbidden.java | 100% |
100% |
| HTTP404FileNotFoundResponse.java | 100% |
100% |
| HTTP405MethodNotSupportedResponse.java | 100% |
100% |
| HTTPResponse.java | 100% |
50% |


Luperon harbour (also known as Puerto Blanco) is a large enclosed bay providing excellent shelter (hurricane hole). Its position on the north coast, opposite the Turks and Caicos Islands, make it a useful shelter for yachts with southbound cruising plans and is the first and only really major anchorage for boats heading East.
Unfortunately however, whilst Luperon has a welcoming long-term cruising community, the local Authorities (in the recent past) have not been so friendly towards yachts and "made up" charges seem to increase on an annual basis. Cruisers considering cruising to this port should read all the information below, including feedback from cruisers at the bottom of the page, before deciding if they want to deal with the potential problems that may arise should they visit.
Cruising reports elsewhere on the net in 2016 have been more favourable, so perhaps the "illegal fees" are a thing of the past. A new commandante has been appointed and he appears to be more sympathetic towards the yachting community. Note however that commandantes change on a regular basis in the DR.

Position 19° 54'22"N, 70° 56'34"W (bay entrance)
See DR Formalities for detailed clearance information and fees.
Whilst the authorities in Luperon have received many negative reports in the past, it does appear in 2016 that they are showing greater compliance with the official rate list (see Clearance Fees for the DR).
Anchor anywhere and hoist a Q flag and wait for Dominican entry officials. You will likely be visited by 3 officials: the Military, Immigration and Drug Control. It is customary to offer them a cold soft drink.
After the inspection on board, take your dinghy to the government dock and walk into town to complete paperwork ashore. At the outskirts, to the left is a path leading to a small bridge and the hilltop naval outpost. The commandante will record your presence, giving you legal permission to land.
All officials are situated in a group of temporary portacabins at the end of the pier next to the dinghy dock. Visit Immigration first where you pay for your vessel and number of passengers. Next office is The Ministry of Tourism where you buy your tourist cards. Then the Port Authority who just want vessel information. Finally the Department of Agriculture where there is a small fee to cover garbage disposal etc.
Obtaining an international zarpe here is reported to take some time, so visit the authorities 2 days before departure to ensure you get the zarpe the day you need it.
Ocean World Marina, just East of Luperon, is also an official port of entry.
Important Note re. Clearance Charges in Luperon
Luperon has a long history of "made up charges". In the past cruisers have reported being charged harbour entrance fees, pet landing fees and a daily anchoring fee etc. These charges are all "made up" by the local officials. Read feedback from cruisers (in comments at bottom of page) before considering this port as an option.
Cruisers Net: VHF channel 68 Sunday & Wednesday: for local help and knowledge, fuel etc.
Last updated June 2016.
The Puerto Blanco Yacht Club, Marina & Restaurant is a gathering place for cruising sailors and various social activities are organised. It underwent a major renovation during the Autumn of 2014 and re-opened in December 2014 with a new owner Leonard Perdomo (Leo).
There is now also two new marinas, the refurbished one at the Luperon Yacht Club and another, Marina Tropical, further improving facilities here.
Papo (call on VHF channel 68) can help with moorings.
See Report on Luperon, for tips on anchoring. Be aware of the risk of entering Luperon bay at night due to numerous fishing nets located outside the channel.
Access to the harbour is shallow and the harbour water is foul. One should avoid swimming or using a watermaker here.
Non-potable water is available at the boatyard and the dinghy dock near the old yacht club. Potable water can be delivered to your boat (as can fuel).
Security
Cruisers have reported that it is wise to lock your dinghy at the public dinghy dock. Thefts were common here in the past, however, security has improved with the appointment of a new commandante and an armed patrol boat does operate at night now.
If leaving your boat here for any length of time it is recommended you appoint a caretaker. Only use caretakers recommended and used by other cruising boats.
Last updated June 2016.


Two Girls and a Guy (1997)
Seen on 26 April 1998 for $8.50 with Laura at Angelika.
Not knowing much about *2 Girls and a Guy*, I went into it without any preconceived notions or expectations. It started out interestingly enough, as two women standing on the steps of a Sohoi loft slowly discover the boyfriend they hoping to surprise upon his return from London is in fact the same boyfriend, Blake (Robert Downey Jr.). Carla (Heather Graham, most recently seen as Boogie Night's "Rollergirl") is tall, blonde, refined, and innocent looking. Lou (Natasha Wagner) is short, dark-haired, speaks in streetsmart tones, and has no problem scaling a fire escape and breaking into Blake's window so the two can really surprise him upon his return.
The first 45 minutes to an hour of this movie work very well, as the two cuckolded women bond as they rehash all of Blake's lines and realize he's been seeing both of them for almost the same length of time--ten months. As Carla, wide-eyed, recites Blake's romantic mantras, Lou is able to finish them, word for word. The fun, therefore, is really supposed to begin when Blake returns and the women confront him and turn tables on him.
Blake does return and immediately calls his mother. We learn from Carla and Lou that he is fixated on his mother. This plays prominently into the film, and it is interesting to see Downey tune the women out to call his mother, and then her doctor, and completely focus on everything but them.
This movie takes place completely in Blake's loft, so it is interesting to see how director James Toback is able to keep it from getting too claustrophobic, and too talky, like My Dinner with Andre.
However, the move takes a sharp left turn halfway through and never quite recovers. The things you might expect and look forward to do not happen, and instead, the films ends unsatisfactorily. Considering the sharp emotions and strong start the movie made, it is disappointing--to say the least--to see the characters do things no one would ever do, and basically wimp out.
Despite the script, Downey and Graham sustain a level of energy that still keeps you wondering what is going to happen, way after that bad turn is made. Wagner's performance, however, despite promising delivery in the first half, peters out and leaves you unimpressed. Watching three characters that are eventually revealed to be emotionally confused is not for everyone. It's hard to figure out whether the conclusions we can draw are that a) the director is misogynist, or b) "Why try being honest with people? Life is so futile?"
CINEMA FAN NOTE: In the loft you will notice a poster for Truffaut's film Jules et Jim, a movie about 2 Guys and a Girl.
More movie reviews by Seth Bookey, with graphics, can be found at http://www.geocities.com/Athens/2679/kino.html
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


--- title: The validation set approach in caret author: Gertjan Verhoeven date: '2019-03-21' summary: In this blog post, we explore how to implement the validation set approach in caret. This is the most basic form of the train/test machine learning concept. draft: FALSE slug: validation-set-approach-in-caret categories: - Machine learning tags: - R - caret baseurl: "https://gsverhoeven.github.io" header: image: "headers/balls-blur-close-up-278911.jpg" preview: FALSE ---
In this blog post, we explore how to implement the validation set approach in caret
. This is the most basic form of the train/test machine learning concept. For example, the classic machine learning textbook "An introduction to Statistical Learning" uses the validation set approach to introduce resampling methods.
In practice, one likes to use k-fold Cross validation, or Leave-one-out cross validation, as they make better use of the data. This is probably the reason that the validation set approach is not one of caret
's preset methods.
But for teaching purposes it would be very nice to have a caret
implementation.
This would allow for an easy demonstration of the variability one gets when choosing different partionings. It also allows direct demonstration of why k-fold CV is superior to the validation set approach with respect to bias/variance.
We pick the BostonHousing
dataset for our example code.
# Boston Housing
knitr::kable(head(Boston))
| crim | zn | indus | chas | nox | rm | age | dis | rad | tax | ptratio | black | lstat | medv |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.00632 | 18 | 2.31 | 0 | 0.538 | 6.575 | 65.2 | 4.0900 | 1 | 296 | 15.3 | 396.90 | 4.98 | 24.0 |
| 0.02731 | 0 | 7.07 | 0 | 0.469 | 6.421 | 78.9 | 4.9671 | 2 | 242 | 17.8 | 396.90 | 9.14 | 21.6 |
| 0.02729 | 0 | 7.07 | 0 | 0.469 | 7.185 | 61.1 | 4.9671 | 2 | 242 | 17.8 | 392.83 | 4.03 | 34.7 |
| 0.03237 | 0 | 2.18 | 0 | 0.458 | 6.998 | 45.8 | 6.0622 | 3 | 222 | 18.7 | 394.63 | 2.94 | 33.4 |
| 0.06905 | 0 | 2.18 | 0 | 0.458 | 7.147 | 54.2 | 6.0622 | 3 | 222 | 18.7 | 396.90 | 5.33 | 36.2 |
| 0.02985 | 0 | 2.18 | 0 | 0.458 | 6.430 | 58.7 | 6.0622 | 3 | 222 | 18.7 | 394.12 | 5.21 | 28.7 |
Our model is predicting medv
(Median house value) using predictors indus
and chas
in a multiple linear regression. We split the data in half, 50% for fitting the model, and 50% to use as a validation set.
To check if we understand what caret
does, we first implement the validation set approach ourselves. To be able to compare, we need exactly the same data partitions for our manual approach and the caret
approach. As caret
requires a particular format (a named list of sets of train indices) we conform to this standard. However, all caret
partitioning functions seem to perform stratified random sampling. This means that it first partitions the data in equal sized groups based on the outcome variable, and then samples at random within those groups to partitions that have similar distributions for the outcome variable.
This not desirable for teaching, as it adds more complexity. In addition, it would be nice to be able to compare stratified vs. random sampling.
We therefore write a function that generates truly random partitions of the data. We let it generate partitions in the format that trainControl
likes.
# internal function from caret package, needed to play nice with resamples()
prettySeq <- function(x) paste("Resample", gsub(" ", "0", format(seq(along = x))), sep = "")
createRandomDataPartition <- function(y, times, p) {
vec <- 1:length(y)
n_samples <- round(p * length(y))
result <- list()
for(t in 1:times){
indices <- sample(vec, n_samples, replace = FALSE)
result[[t]] <- indices
#names(result)[t] <- paste0("Resample", t)
}
names(result) <- prettySeq(result)
result
}
createRandomDataPartition(1:10, times = 2, p = 0.5)
## $Resample1
## [1] 4 3 7 9 10
##
## $Resample2
## [1] 8 6 1 7 10
Here is the validation set approach without using caret. We create a single random partition of the data in train and validation set, fit the model on the training data, predict on the validation data, and calculate the RMSE error on the test predictions.
set.seed(1234)
parts <- createRandomDataPartition(Boston$medv, times = 1, p = 0.5)
train <- parts$Resample1
# fit ols on train data
lm.fit <- lm(medv ~ indus + chas , data = Boston[train,])
# predict on held out data
preds <- predict(lm.fit, newdata = Boston[-train,])
# calculate RMSE validation error
sqrt(mean((preds - Boston[-train,]$medv)^2))
## [1] 7.930076
If we feed caret
the same data partition, we expect exactly the same test error for the held-out data. Let's find out!
Now we use the caret
package. Regular usage requires two function calls, one to trainControl
to control the resampling behavior, and one to train
to do the actual model fitting and prediction generation.
As the validation set approach is not one of the predefined methods, we need to make use of the index
argument to explicitely define the train partitions outside of caret
. It automatically predicts on the records that are not contained in the train partitions.
The index
argument plays well with the createDataPartition
(Stratfied sampling) and createRandomDataPartition
(our own custom function that performs truly random sampling) functions, as these functions both generate partitions in precisely the format that index
wants: lists of training set indices.
In the code below, we generate four different 50/50 partitions of the data.
We set savePredictions
to TRUE
to be able to verify the calculated metrics such as the test RMSE.
set.seed(1234)
# create four partitions
parts <- createRandomDataPartition(Boston$medv, times = 4, p = 0.5)
ctrl <- trainControl(method = "repeatedcv",
## The method doesn't matter
## since we are defining the resamples
index= parts,
##verboseIter = TRUE,
##repeats = 1,
savePredictions = TRUE
##returnResamp = "final"
)
Now we can run caret and fit the model four times:
res <- train(medv ~ indus + chas, data = Boston, method = "lm",
trControl = ctrl)
res
## Linear Regression
##
## 506 samples
## 2 predictor
##
## No pre-processing
## Resampling: Cross-Validated (10 fold, repeated 1 times)
## Summary of sample sizes: 253, 253, 253, 253
## Resampling results:
##
## RMSE Rsquared MAE
## 7.906538 0.2551047 5.764773
##
## Tuning parameter 'intercept' was held constant at a value of TRUE
From the result returned by train
we can verify that it has fitted a model on four different datasets, each of size 253
. By default it reports the average test error over the four validation sets. We can also extract the four individual test errors:
# strangely enough, resamples() always wants at least two train() results
# see also the man page for resamples()
resamples <- resamples(list(MOD1 = res,
MOD2 = res))
resamples$values$`MOD1~RMSE`
## [1] 7.930076 8.135428 7.899054 7.661595
# check that we recover the RMSE reported by train() in the Resampling results
mean(resamples$values$`MOD1~RMSE`)
## [1] 7.906538
summary(resamples)
##
## Call:
## summary.resamples(object = resamples)
##
## Models: MOD1, MOD2
## Number of resamples: 4
##
## MAE
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## MOD1 5.516407 5.730172 5.809746 5.764773 5.844347 5.923193 0
## MOD2 5.516407 5.730172 5.809746 5.764773 5.844347 5.923193 0
##
## RMSE
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## MOD1 7.661595 7.839689 7.914565 7.906538 7.981414 8.135428 0
## MOD2 7.661595 7.839689 7.914565 7.906538 7.981414 8.135428 0
##
## Rsquared
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## MOD1 0.2339796 0.2377464 0.2541613 0.2551047 0.2715197 0.2781167 0
## MOD2 0.2339796 0.2377464 0.2541613 0.2551047 0.2715197 0.2781167 0
Note that the RMSE value for the first train/test partition is exactly equal to our own implementation of the validation set approach. Awesome.
Since we now know what we are doing, let's perform a simulation study to compare stratified random sampling with truly random sampling, using the validation set approach, and repeating this proces say a few thousand times to get a nice distribution of test errors.
# simulation settings
n_repeats <- 3000
train_fraction <- 0.8
First we fit the models on the random sampling data partitions:
set.seed(1234)
parts <- createRandomDataPartition(Boston$medv, times = n_repeats, p = train_fraction)
ctrl <- trainControl(method = "repeatedcv", ## The method doesn't matter
index= parts,
savePredictions = TRUE
)
rand_sampl_res <- train(medv ~ indus + chas, data = Boston, method = "lm",
trControl = ctrl)
rand_sampl_res
## Linear Regression
##
## 506 samples
## 2 predictor
##
## No pre-processing
## Resampling: Cross-Validated (10 fold, repeated 1 times)
## Summary of sample sizes: 405, 405, 405, 405, 405, 405, ...
## Resampling results:
##
## RMSE Rsquared MAE
## 7.868972 0.2753001 5.790874
##
## Tuning parameter 'intercept' was held constant at a value of TRUE
Next, we fit the models on the stratified sampling data partitions:
set.seed(1234)
parts <- createDataPartition(Boston$medv, times = n_repeats, p = train_fraction, list = T)
ctrl <- trainControl(method = "repeatedcv", ## The method doesn't matter
index= parts,
savePredictions = TRUE
)
strat_sampl_res <- train(medv ~ indus + chas, data = Boston, method = "lm",
trControl = ctrl)
strat_sampl_res
## Linear Regression
##
## 506 samples
## 2 predictor
##
## No pre-processing
## Resampling: Cross-Validated (10 fold, repeated 1 times)
## Summary of sample sizes: 407, 407, 407, 407, 407, 407, ...
## Resampling results:
##
## RMSE Rsquared MAE
## 7.83269 0.277719 5.769507
##
## Tuning parameter 'intercept' was held constant at a value of TRUE
Then, we merge the two results to compare the distributions:
resamples <- resamples(list(RAND = rand_sampl_res,
STRAT = strat_sampl_res))
We now analyse our resampling results. We can use the summary
method on our resamples object:
summary(resamples)
##
## Call:
## summary.resamples(object = resamples)
##
## Models: RAND, STRAT
## Number of resamples: 3000
##
## MAE
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## RAND 4.406326 5.475846 5.775077 5.790874 6.094820 7.582886 0
## STRAT 4.401729 5.477664 5.758201 5.769507 6.058652 7.356133 0
##
## RMSE
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## RAND 5.328128 7.323887 7.847369 7.868972 8.408855 10.78024 0
## STRAT 5.560942 7.304199 7.828765 7.832690 8.328966 10.44186 0
##
## Rsquared
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## RAND 0.06982417 0.2259553 0.2733762 0.2753001 0.3249820 0.5195017 0
## STRAT 0.05306875 0.2263577 0.2752015 0.2777190 0.3277577 0.4977015 0
We can also use the plot function provided by the caret
package. It plots the mean of our performance metric (RMSE), as well as estimation uncertainty of this mean. Note that the confidence intervals here are based on a normal approximation (One sample t-test).
# caret:::ggplot.resamples
# t.test(resamples$values$`RAND~RMSE`)
ggplot(resamples, metric = "RMSE")
My personal preference is to more directly display both distributions. This is done by bwplot()
(caret
does not have ggplot version of this function).
bwplot(resamples, metric = "RMSE")
It does seems that stratified sampling paints a slightly more optimistic picture of the test error when compared to truly random sampling. However, we can also see that random sampling has somewhat higher variance when compared to stratified sampling.
Based on these results, it seems like stratified sampling is indeed a reasonable default setting for caret
.
set.seed(1234)
ctrl <- trainControl(method = "LGOCV", ## The method doesn't matter
repeats = n_repeats,
number = 1,
p = 0.5,
savePredictions = TRUE
)
## Warning: `repeats` has no meaning for this resampling method.
lgocv_res <- train(medv ~ indus + chas, data = Boston, method = "lm",
trControl = ctrl)
lgocv_res
## Linear Regression
##
## 506 samples
## 2 predictor
##
## No pre-processing
## Resampling: Repeated Train/Test Splits Estimated (1 reps, 50%)
## Summary of sample sizes: 254
## Resampling results:
##
## RMSE Rsquared MAE
## 8.137926 0.2389733 5.763309
##
## Tuning parameter 'intercept' was held constant at a value of TRUE


To understand why would need defense against malwares, we need to know that in current digital world there are many malicious software lurking around. Therefore, from the lecture we first learn about malwares’ behavior. We first need to identify the attack vectors which is how does those threats get into our system. After those threats get inside what does it do. From these two big questions, we can split the malwares’ behavior into four major steps.
For the first contact we can counter spam with anti-spam, network attacks with firewall, or check the site’s reputation, or we can encrypt our disk to prevent physical access attacks. There are many ways the user can take precaution from malicious attacks to the highest level but it would greatly reduce user experience.
If the user has accidently opened or accessed compromised files or websites, there are still preventions we can take for example, an executable file would ask the user if they want to run it. This can serve as a warning sign that you should not run any unknown executable file so you can protect yourself. During this local execution stage we would want to use any content filtering to filter our unknown files. If it is on a network, we would want to use network IPS which stands for network intrusion prevention system or content filtering or scanning to prevent execution of malicious codes. If it is a file or code on the user system then we can use host IPS, anti-virus or whitelisting as another defense layer against execution of malicious file or code.
However, if the user has already executed the malicious file or the malicious code is already executed through some vulnerability in the file or browser, then we are in the establish presence stage. In this stage there are another layer of defense we can put up to fight against the malicious software which would be anti-virus, whitelisting or host IPS. If it is in the network, then we would use firewall, network IPS, IP, domain and URL reputations to block out those malicious codes.
Even if the system is in the malicious activity stage, the best form of defense on the system is still the anti-virus and/or prevent any data loss by backing up your data and restore your system. If it is network based attack, then the best defense would still be a firewall or network IPS.
By forming multiple layers of defense will make it that much harder for the malicious software from getting into your system and defend your system from any threats.
All of the layers of defense that can be used to protect us from any malicious threats all have a common protocol which is to determine what is good and what is bad. By developing the content rules for the content engine to interpret it and determine what is good or bad is a major key in the defense. How do you determine if a file is malicious or not? Here, we would need to use some tools like YARA, which is a tool that we can use to develop a list of rules for it to run against the files we want. Generally we would want to find out what are common that is among the malicious files and then find out the unique string that we can put in our rule so it will only filter out the bad files and not create any false positive on our system files. When going through the suspecious files, we can always use google to look up if any of the unkonwn string match online and find out what they are if they are safe or not to decide to add to the rules. If we don't know where to start, we can always use YARA's auto generate a list of common string from the list of the malicious files for us as well but the rules it create is too big, we would need to go through them and narrow it down to more unique and lessand amount of rules since it would not be idea for the anti-virus company to use such a large list of rules because all AV companies wants to deploy updates that are small and yet effective so the rules have to be as unique enough that it can capture the malware and small enough that user can accept, otherwise the update size would be too big and take too long. So a good clear set of rules are very important so it can detect the malware on the machine but also try to anticipate possible threats that may have come from same family of malware. However, we would still need to becareful of what files we open, what websites we visit and set up your network with filters, firewalls and your host system with anti-virus softwares so you can better defend against any threats.
Through this week’s lab, we learned how to use the yara tool and cuckoo tool. For the yara tool we learned how to use it to scan files using the content rules we developed. We then apply those rules on system files to see if they will return any false positives, if there is then that means our rules aren’t unique enough to only the malicious files. Using yara to scan files are very useful to find malicious files and remove them but there are some draw backs as well, it can be subjected to some tricks used by the malicious tools to avoid detection like packers, portable executables or other tricks. Another useful way to use yara is to scan the memory because in memory, the malware will have to unpack and strip away their layers of wrapper that prevented them from being discovered.
Another tool we used in the lab is cuckoo. Using cuckoo in the VM at first caused some errors to show up because cuckoo is a tool that is better run in an environment that has a cuckoo host and the analysis VM will run those malware so the whole thing will be in an virtual network but since we are running it in our VM as the host it gave errors but we ignored it since the main thing we wanted is to see the log. The big useful function about cuckoo is that it allows us to trace and follow the course of the malware execution to what it is trying to do, what files it created or opened, or where did it modify data…etc. Using this we can even see a lot of things that happened in the background that the malware was downloading or executing that we did not observe or find using other tools.
In conclusion from this week’s lecture, I have learned a great deal about how the behaviors of the malicious software help us understand there are different stages in threat execution and from their behavior we can form a line of defense in each stage of security breach. I also find the lab to be extremely interesting and fun to develop our own rules by finding the strings or hex of the malware so we can isolate them from normal system files. I learned that in the AV defense industry, they are not only developing defense against past and current threats but also anticipating for future defense against new threats and coming out with better and smarter ways to help us defend against threats.


--- layout: default title: Caley In Progress ---
My ultimate goal is support my folks to grow their skills, deepen their expertise, and drive their careers forward. I aim to gain trust through listening, collaborating, and following through on promises.
We spend most of our waking hours at work. I want to create an environment where my writers can be their authentic selves, where they feel safe, seen, heard, and understood... and where they can be successful, creative, productive, and happy.
I am against micromanaging, and I believe that writers thrive when given the chance to simply do what they do best: create content, research features, analyze information, and help users be successful.
In short, I’m here to support my folks when they face challenges, be a coach on their journey to grow into new roles and skills, and cheer on their successes and hard-earned wins.


Prajval RavalCommunity Lead
Umesh PatelCore Team Member
Vaishnavi ShahCore Team Member
Darshil ShahCore Team Member
Milki PatelCore Team Member


UK Police Rush to Buckingham Palace as ‘Suspicious Car Abandoned Outside the Gates' - Report
On 1 November, Vauxhall Bridge in London was shut down amid a police investigation of an area where an unidentified vehicle had been abandoned.
British police were earlier reported to have rushed to Buckingham Palace in order to investigate a "suspicious" car abandoned outside the gates. Police were said to be closing nearby roads after receiving unconfirmed reports of a bomb.
According to eyewitness reports shared on Twitter, police were shouting at people to move away from the palace and a section of The Mall nearby. Some claimed that around 50 policemen were present at the scene.
The incident at Buckingham Palace has been "stood down", according to reports by British police. Nothing suspicious has been found so far.
Buckingham Palace is a popular tourist attraction and also the residence of British monarch Queen Elizabeth II.
Two weeks ago, London's Vauxhall Bridge was also shut down as law enforcement investigated another vehicle that had been abandoned – just yards away from the MI6 headquarters. No arrests were made following the incident, according to police reports.


Alexandre Lacazette speaks out in support of under-fire Arsenal boss Unai Emery
Emery has come under mounting pressure following a string of poor performances and a record of just two wins from their last 10 Premier League games
by Matt Maltby, https://www.mirror.co.uk/authors/matt-maltby/Alexandre Lacazette has insisted that the Arsenal squad are fully behind Unai Emery despite the club's woeful start to the season.
The Gunners head coach has come under mounting pressure following a string of poor performances and a record of just two wins from their last 10 Premier League games.
A 2-0 loss at Leicester on Saturday evening saw Arsenal fall eight points behind the current top four, with Emery's target of a return to the Champions League looking as far away as ever.
But Lacazette says that the squad are desperate to turn things around - and wants to keep Emery in his job.
"We're working together everyday on a constant basis to pick up the slack," he told the club website .
"The group definitely supports the coach and I'm sure the club does as well.
"We're a very tight group, and we're doing everything we can to improve."
Lacazette's comments come after head of football Raul Sanllehi and managing director Vinai Venkatesham insisted the club still have the right man in charge.
"We are as disappointed as everyone else with both our results and performances at this stage of the season," they told Arsenal staff at a pre-planned meeting.
"We share the frustration with our fans, Unai, players and all our staff as they are not at the level we want or expect. Things need to improve to meet our objectives for the season, and we firmly believe Unai is the right man for the job, together with the backroom team we have in place."
Sanllehi and Venkatesham added: "We are all working intensively behind the scenes to turn things around and are confident we will.
"We never take our fantastic support for granted. We hope we can all stick together and get behind the team in this challenging period, as together we are stronger."


From the newsletter ... |
|
Love Luv LoveWell it's that time of year again...... the shops are bulging with big red fluffy cards, small discrete cards, humorous verging on the obscene cards......all in praise of LOVE. Yes Valentine's Day approaches!! For women it's a very important occasion when the blokes who are sometimes not the best in the `I love you' stakes...... have the chance to buy a card and maybe go out for a candlelit meal to make up for things. Relationships and marriage are great. I am sure we can all think of people who seem to have `the perfect marriage'. People are not meant to live alone ... after all once God had created Adam, he realized he needed a partner and created Eve out of one of Adam's ribs so the bible says. You know the humorous response that after God has made Eve she had very little sleep for the first week. She kept getting up and checking that Adam still had all his other ribs !!! But is a burst of romance on Valentine's Day really enough? Look...... I am not knocking romance, but if the other 364 days of the year are `loveless' then all the flowers, cards, and meals out in the world are not going to be put right on one day. Love is fostered by the acts of kindness, the caring attitude, the commitment that people give to one another. That's true in friendships as well as romantic relationships. As a single person I am so appreciative of the acts of love my friends offer me. So what's the ideal attitude of love then? At weddings people often use the passage from 1 Corinthians 13 as their text
Now that's a set of values to live up to! It seems to me that these values are really encompassed in one sentiment of being `unselfish' in our relationships of love with one another. As naturally self centred humans, that's not easy to do!! I am always so moved by television reports that show acts of self sacrifice and love, the events like LIVE 8 that tried to heighten awareness of the needs of others crippled through debt constraints. I am also moved as a Christian by the act of love of God who sent Jesus to die on a cross for us, a painful death, a sacrificial death and a selfless death. Jesus was God's Valentine card of love to us, Wow! Cogges Parish | Other articles | Feedback © 2006; Published in Cogges Parish monthly newsletter, February 2006 |


anyone checked if altsbit has depo/withdraw still open?
hyperDEX13-Nov-19 11:41 AM
97.5c
Markus13-Nov-19 11:41 AM
crossed 200 ma daily
lets close above it
steinsg813-Nov-19 11:42 AM
Komodo actually going up
Dafuk
hyperDEX13-Nov-19 11:43 AM
upside down world
1
Acura13-Nov-19 11:46 AM
McBeastie13-Nov-19 11:47 AM
@Cryptoon deposit/withdraw on altsbit looks good
Acura13-Nov-19 11:47 AM
McBeastie13-Nov-19 11:48 AM
quite a difference for ARRR between altsbit and tradeogre
Cryptoon13-Nov-19 12:10 PM
Oof, didnt even notice that
TO also with the higher volume
Sherdogz13-Nov-19 12:21 PM
Damn
Neko13-Nov-19 12:27 PM
@Alexfrog considering how much I bought when it was $4, I'm still down 75%
Mark8113-Nov-19 12:27 PM
I still feel none.
pinkolin13-Nov-19 12:29 PM
Max was 12$. Still long way
I hodling long time, im plus in $
jeezy13-Nov-19 12:40 PM
any reason why deposit/withdrawal is deactivated on the big exchanges?
Acura13-Nov-19 12:45 PM
Upcoming hardupdate @jeezy
jeezy13-Nov-19 01:02 PM
@Acura were is the information about it? cant find anything
Neko13-Nov-19 01:11 PM
hello $1
PHBA206113-Nov-19 01:28 PM
soon back to top 50 on cmc
Acura13-Nov-19 01:28 PM
@jeezy
Neko13-Nov-19 01:34 PM
nSPV nice
this will make some news
jeezy13-Nov-19 01:43 PM
@Acura sure, my point was more like shouldnt there be an official announcement / info page clearly visible and easy to find somewhere for this important update? just to clarify... it will be a hardfork?
jl777c13-Nov-19 01:43 PM
it is in the process
it is a hardupdate
jeezy13-Nov-19 01:44 PM
whats the definition of hardupdate
jl777c13-Nov-19 01:44 PM
a mandatory update
jeezy13-Nov-19 01:45 PM
so there will be no hardfork?
jl777c13-Nov-19 01:45 PM
if you dont update, you will go on a fork, that is why exchanges are stopped. if we dont do that, then it becomes very likely some would skip the update and go on a fork
what do you mean by hardfork?
it is an update, that is a hardforking update, so it is a hardfork, but not one with new coins
jeezy13-Nov-19 01:47 PM
makes sense
so to get back on topic, this is planned for end of this months
so some of those big exchanges will have dep/withdr deactivated for 2 more weeks
jl777c13-Nov-19 01:53 PM
as soon as they update, they can reopen
i dont have an exact time the update is ready yet, team is working on it to get it done soonest
joe2x413-Nov-19 02:05 PM
Perfect time for a pump, when it's hard to dump.
jl777c13-Nov-19 02:06 PM
there is 10 million+ KMD on binance. no lack of KMD to sell
jorian13-Nov-19 02:12 PM
i'm sure some peeps would've deposited and sold with these prices
joe2x413-Nov-19 02:14 PM
Cold storage peeps left out? I guess we would see an uptick in atomicdex offers then.
designer13-Nov-19 02:14 PM
what is Komodo's strategy in this bull market?
jl777c13-Nov-19 02:17 PM
same as during the bear market and last bull market
continue to improve things
i guess this bull market, KMD becomes popular in asia
Blockchain News - Dutch Police Bust CEO of Blockchain Game Firm, Komodore64 - €78 million Gone?
Oszy13-Nov-19 05:31 PM
#talk-other-topics please
except if it's his mugshot (edited)
1
1
richardt13-Nov-19 05:31 PM
KMD pumping and exchanges stopping deposits/withdrawals does seem like too much of a coincidence. But maybe I'm just paranoid
Oszy13-Nov-19 05:32 PM
exchanges stopping deposits/withdrawals because of a network upgrade
Mark8113-Nov-19 05:34 PM
Well it was same thing going on last years hard fork update if i am memorizing correctly.(edited)
1
Sherdogz13-Nov-19 05:34 PM
Yes same and after a day or so a huge dump...
Oszy13-Nov-19 05:35 PM
there is 10 million KMD on binance if someone wants to dump would have done it by now
Mark8113-Nov-19 05:37 PM
Well this time we have come out from bottom pattern so it might be different story. Also other alts are having good gains.(edited)
Oszy13-Nov-19 05:37 PM
BTC hasn't moved the past couple days
not crashing the parties
jeffjam13-Nov-19 05:46 PM
Of course it is manipulation due to closed deposits/withdrawals across the board.
richardt13-Nov-19 05:51 PM
Most of that 10mil KMD could be owned by Binance
Or other whales.
Cryptoon13-Nov-19 05:52 PM
Altbits withdraw/depo open
Oszy13-Nov-19 05:52 PM
either way it goes I read manipulation here
Cryptoon13-Nov-19 05:53 PM
Feel free to dump there
Oszy13-Nov-19 05:53 PM
there's atomicdex too, I don't see bigger orders on either of them just complaints here :p(edited)
Markus13-Nov-19 05:53 PM
in the end we are back to more healthier numbers so we should just be happy about it, any market where money can be made being manipulated one or another way so its nothing new
2
jorian13-Nov-19 05:54 PM
you can't track trades on atomicdex so nothing to say about that unfortunately
Oszy13-Nov-19 05:54 PM
yes but i can see the orderbook and i haven't seen anything new the past 2 days
apart from 2-3 LP's and me
there are 7 KMD sell orders 4 with decent volume
Cryptoon13-Nov-19 05:56 PM
Yeah complainers gonna complain and not look for solutions to their ‘problems’
Oszy13-Nov-19 05:56 PM
where is the complaining people's orders?(edited)
jorian13-Nov-19 05:56 PM
atomicdex open 24/7
Oszy13-Nov-19 05:57 PM
So am I
Cryptoon13-Nov-19 05:59 PM
I feel like there’s a ‘that’s what she said joke to be made here’
Oszy13-Nov-19 05:59 PM
Sherdogz13-Nov-19 06:01 PM
Who's complaining
Privatoshi13-Nov-19 06:05 PM
Ain'ters gonna ain't
KMD, BNB, TRX & LINK
actionslacks13-Nov-19 06:22 PM
the ptsd from 2 yrs of kmd price abuse is real. this is usually the part where btc crashes
Neko13-Nov-19 06:22 PM
I feel it
Alexfrog13-Nov-19 06:39 PM
btc moves either up or down, and KMD back to 50 cents


Coronation Street star Andy Whyment was a late arrival to the jungle camp, but has never been happier, says his long-suffering wife Nicola.
"Andy is living his best life in the jungle," she told OK! magazine.
"I think he just showed everyone how excited he is to be there. I've not seen him laugh that much in so long. I hope he doesn't struggle too much in the jail camp as he loves his food and sleep."
Andy went in at the same time as Cliff Parisi, and was in paroxysms of laughter as the pair did their first Bushtucker trial in Ol' Dingo Town.
And while some of his I'm A Celebrity campmates have already grown weary of the lack of food and sleep, Andy's had a smile on his face ever since he arrived.
"I think the hardest part will be the hunger," he had said before jetting Down Under.
"My co-star Jennie [McAlpine] did the show in 2017 and warned me about how hungry you get when you're on basic rations. Antony Cotton also did the show in 2011 and he said I was going to feel starving."
He added to OK!: "I just love my food! There's a joke on the Corrie set that as soon as they announce it's lunchtime, I bomb it straight to the canteen. Sometimes the cast have physically held me back to stop me getting to the queue first!
"I've got a little pot belly, so maybe it'll be good for getting rid of that. As for the gross eating challenges, I think that's a lot about mindset. When you want to do well for your camp and you’re starving, I'm sure you find a way to power through it."
But Andy admitted the hardest part of his jungle stint would be the time away from his family.
"Even when I work away from home, I can call Nic and FaceTime the kids," he added.
Andy, who plays Kirk Sutherland on the ITV soap, has previously opened up about the horrific bullying he experienced as a child.
He began ballet aged eight, but other kids at his Bolton school were jealous and would relentlessly tease him.
"It was verbal rather than physical, but once one started a few of them would join in," Andy said.
"It was jealousy more than anything else. I was doing something with my life and they were just hanging about the street corners getting hammered every week.
"At one stage my dad was thinking of pulling me out of the school.
"But I told him I didn't want him to, because if I left then they'd have won. So I stayed and got on with it."
Andy has been on TV since he was a teenager, starting with roles on shows including Where The Heart Is and The Royle Family.
He also sang in a rock band and busked in Manchester for three years so he didn't have to "sponge off" his parents.
Andy only entered the jungle camp on Thursday, but he's already become the new favourite to win the show.
He won the hearts of the viewers with his rolling commentary during a Bushtucker Trial which saw Cliff Parisi try to avoid buffaloes, and lucky dipped his way through fish guts to find his five stars.
Whyment's commentary and comparing it to "just like watching it on the telly" had hosts Ant and Dec in stitches throughout before he was sent to Jungle Jail by the sherif.
*I'm A Celebrity continues tonight at 9pm on ITV


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This should be a unique name for this service. Cannot be changed once created.
Total Number of Partitions. This should be a good deal higher then the max number of servers you want to support. It is not possible to change this number (at least not easily). Choose wisely.
How many times the data will be replicated. higher is more tolerant of failures, but slower inserts. This can be changed.
The keys that this service should partition on. These will be used in order, each originating request should contain at least one of these as params
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AA Dashboard
Aviation Accident Statistics
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Commercial vs. Private Flights
Commercial
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the other 5 are buttons
Press here to reset
the disable
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Fore


Provides missing features for altering tables that are common
in other supported databases, but are missing from SQLite.
These are needed in order to support migrations during testing
when another database is used as the primary engine, but
SQLite in memory databases are used for faster test execution.
|
package
|
CodeIgniter\Database\SQLite3
|
Methods
Table constructor.
__construct(\CodeIgniter\Database\SQLite3\Connection $db, \CodeIgniter\Database\SQLite3\Forge $forge)
Copies data from our old table to the new one,
taking care map data correctly based on any columns
that have been renamed.
copyData()
Creates the new table based on our current fields.
createTable()
Drops a column from the table.
dropColumn(string $column) : \CodeIgniter\Database\SQLite3\Table
Attempts to drop all indexes and constraints
from the database for this table.
dropIndexes()
Reads an existing database table and
collects all of the information needed to
recreate this table.
fromTable(string $table) : \CodeIgniter\Database\SQLite3\Table
Modifies a field, including changing data type,
renaming, etc.
modifyColumn(array $field) : \CodeIgniter\Database\SQLite3\Table
Called after `fromTable` and any actions, like `dropColumn`, etc,
to finalize the action. It creates a temp table, creates the new
table with modifications, and copies the data over to the new table.
run() : boolean
Properties
All of the fields this table represents.
fields : array
All of the unique/primary keys in the table.
keys : array
All of the foreign keys in the table.
foreignKeys : array
The name of the table we're working with.
tableName : string
The name of the table, with database prefix
prefixedTableName : string
db
db : \CodeIgniter\Database\SQLite3\Connection
forge
forge : \CodeIgniter\Database\SQLite3\Forge


Example usage of log4j including source code.
Note that class files for the example code is not included in any
of the distributed log4j jar files. You will have to add the directory
/dir-where-you-unpacked-log4j/classes
to your classpath
before trying out the examples.
This package's shows how log4j can be used to output log
statements.
- See source code of Trivial.java for a trivial usage
example.
- See source code of Sort.java and
SortAlgo.java to for a slightly
more advanced example.
- See {@link org.apache.log4j.examples.NumberCruncherServer} for a {@link
org.apache.log4j.NDC} based technique to distinguish the log output from
requests from multiple clients.
Last modified: Fri May 5 10:20:04 MDT 2000


This inspection is intended for J2ME and other highly resource constrained environments.
Applying the results of this inspection without consideration might have negative effects on code clarity and design.
Reports method calls in the condition part of a
loop statement. In highly resource constrained environments, such calls may
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Won the honor of “Shenzhen High-tech Enterprise”
Launched the first 7GE+3XG 10 Gigabit industrial ring network switch solution
Launched a series of solutions supporting ERPS public ring industrial switches
Innovative laboratory for building high-speed Ethernet design and testing with Xintai
Launched the first IP coaxial converter solution
Launched the first solution to support 802.1X user access management industrial switch
Won the honor of “National High-tech Enterprise”
Launched the first Gigabit 2 optical 8 electric industrial ring network switch solution
Introduced several cross-device isolated 100M/Gigabit switches
Launched Gigabit 16+2/24+4 Enterprise Switch Solution
Received a national AAA credit rating certificate
Launched the first full-network management platform for the industrial ring switch
Launched the first 24GE+4XG 10 Gigabit core switch solution
Launched the first high-speed rail single-loop + link aggregation dual protection industrial switch solution
Launched a series of industrial ring network switch solutions and applied for 3 patent inventions
Holding the fifth anniversary of the founding and launching the new headquarters
Launched 6GE Gateway Series Solution
Participated in China (Beijing) International Information and Communication Exhibition
The general manager accepted an interview with CCTV CCTV at the Beijing Communication booth
Launched Gigabit 2WAN VPN Router Solution
Join hands with the School of Information Engineering of Wuhan University of Technology to build a production, research and research base
Hand in hand Tianyue Real Estate to build a new marketing center at Liuxiandong Headquarters Base
Introduced a variety of 4/8/16/24 port Gigabit switch solutions
Introducing the industry's first 10 Gigabit fiber optic transceiver solution
Launched the first Gigabit 2 optical 2 high reliability industrial switch solution
Introducing the industry's first 24GE optical + 4GE Combo or 16GE optical + 8GE Combo switch solution
Introduced the first 24GE electric + 4GE optical or 16GE electric + 2GE optical switch solution
Launched the first 8GE industrial switch solution
Launched Gigabit 2WAN VPN Router Solution
Established R&D Department II, leading communication design
Launched the first 7FE+3GE ring industrial switch
Introduced the first high-performance Gigabit fiber transceiver solution
Launched the first 5-port Gigabit router solution
Introduced several 8/16/24 port 100M or Gigabit switch solutions
Introduced the industry's first Gigabit 8-light 1 electric fool-configurable switch solution
Launched the first 4GE L2+ EPON (OLT+ONU) package
Launched a test solution for Ethernet communication products such as switches/PTN/fiber transceivers
Launched the first 8-port 100M ring industrial switch
Introduced the first 24FE+2GE PoE fool-configurable switch solution
Practice technology, science and technology, and create a full-fledged technology
Establish the business philosophy of "advocating communication and good technology, leading the new trend of the program"
Established R&D Technology Center
Become a supplier of Foxconn Group
Launched the first Gigabit 2 light 4 electric fool type configurable switch solution


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