quantify
aggregation engine¶
Data concept¶
| class: | quantipy.Quantity(link, weight=None, xsect_filter=None) |
|---|
The quantipy.Quantity
object consists of a matrix-like 1/0 representation
of the case data alongside simple, yet flexible manipulation and analysis
methods. Since Quantity
effectively converts each variable into its dummy
equivalent, Quantipy handles e.g. multiple choice variables natively, i.e. as
if they were “regular” ones. Data aggregation is implemented using the numpy
library’s vectorization and broadcasting features to offer support for the
full range of statistical analyses using arbitray case record weights. The
data conversion can be illustrated as follows:
------------------------------
| xsect | ysect | wv |
==============================
| @ 1 2 3 4 5 | @ 1 2 3 | 1 |
==============================
| 1 0 1 0 0 0 | 1 0 1 0 | 1 |
------------------------------
| 1 0 0 1 0 0 | 1 1 1 1 | 1 |
------------------------------
| 1 0 0 0 0 1 | 1 0 0 1 | 1 |
------------------------------
| ... ... ... | ... ... | .. |
------------------------------
xsect and ysect are the x- and y-variables dummy components of the matrix.
They are extended by their respective total vectors (a series of 1s, indicated
with the @ symbol) and followed by the corresponding weight vector, (wv,
which turns into a vector of 1-entries as well if no weight is selected).
Generating a Quantity
object by is done by passing a Quantipy.Link
(and an optional weight variable) to its constructor. Inspecting a new
Quantity
instance will show:
>>> link = stack[name_project]['no_filter']['q8']['gender']
>>> q = qp.Quantity(link)
>>> q
Quantity - x: q8, xdef: [1, 2, 3, 4, 5, 96, 98] y: gender, ydef: [1, 2], w: @1
The data’s matrix representation is accessed via the matrix
property. As
the matrix is of type numpy.ndarray
a quick look at its shape helps to
demonstrate the basic data concept:
>>> q.matrix
[[[ 1. 1. 0.]
[ 0. 0. 0.]
[ 0. 0. 0.]
[ 0. 0. 0.]
[ 0. 0. 0.]
[ 1. 1. 0.]
[ 0. 0. 0.]
[ 0. 0. 0.]]
...,
>>> q.matrix.shape
(2367L, 8L, 3L)
We can see that the matrix shows data for 2367 row entries (the cases) and the
sectional definitions of the columns reflects the information from above:
q.xdef
has a length of 7, q.ydef
one of 2. With the addition of their
total indicators (x
: 7 codes + 1 total = 8 and y
: 2 codes + 1 total = 3)
the shape reflects the data concept outlined above.
Computation methods¶
Cell frequencies¶
| method: | quantipy.Quantity.count(show='freq', margin=True, as_df=True) |
|---|
Using count()
allows to quickly produce contigency table analyses on data
distributions:
>>> link = stack[name_project]['no_filter']['q8']['gender']
>>> q = qp.Quantity(link, 'weight_a')
>>> q.count()
Question gender
Values All 1 2
Question Values
q8 All 2259.769789 1156.803818 1102.965971
1 870.282554 449.982974 420.299580
2 235.316156 129.877415 105.438740
3 531.955628 270.823427 261.132200
4 905.357857 466.994617 438.363240
5 1204.815742 619.453850 585.361892
96 262.102580 144.078833 118.023747
98 41.822422 24.899174 16.923248
By providing margin=False
in the method call, the ‘All’-margins that show
the column and row base sizes are omitted from the output:
>>> q.count(margin=False)
Question gender
Values 1 2
Question Values
q8 1 449.982974 420.299580
2 129.877415 105.438740
3 270.823427 261.132200
4 466.994617 438.363240
5 619.453850 585.361892
96 144.078833 118.023747
98 24.899174 16.923248
It is also possible to exclusively show the x- and y-axis base sizes using the
axis
parameter, which is set to None
by default. For instance, the
column bases can be computed via:
>>> q.count(axis='x', margin=True)
Question gender
Values All 1 2
Question Values
q8 All 2259.769789 1156.803818 1102.965971
>>> q.count(show='y', margin=False)
Question gender
Values All
Question Values
q8 1 870.282554
2 235.316156
3 531.955628
4 905.357857
5 1204.815742
96 262.102580
98 41.822422
Numerical statistics¶
| method: | quantipy.Quantity.summarize(self, stat='summary', axis='x', margin=True, as_df=True) |
|---|
Similar to count()
, the summarize()
method will by default generate a
summary table of distribution statistics. The margin
parameter controls
showing and hiding the analysis for the total (bivariate) number of cases of
the Link definition:
>>> link = stack[name_project]['no_filter']['q5_1']['gender']
>>> q = qp.Quantity(link, 'weight_a')
>>> q.summarize()
Question gender
Values All 1 2
Question Values
q5_1 All 8255.000000 3970.518490 4284.481510
mean 25.601017 23.970385 27.112158
stddev 39.929528 38.969433 40.745416
min 1.000000 1.000000 1.000000
25% 3.000000 3.000000 3.000000
median 5.000000 4.000000 5.000000
75% 5.000000 5.000000 5.000000
max 98.000000 98.000000 98.000000
>>> q.summarize(margin=False)
Question gender
Values 1 2
Question Values
q5_1 mean 23.970385 27.112158
stddev 38.969433 40.745416
min 1.000000 1.000000
25% 3.000000 3.000000
median 4.000000 5.000000
75% 5.000000 5.000000
max 98.000000 98.000000
It is also possible to only show isolated statistics by specifying the stat
parameter as one of the following values:
stat |
Calculation | Notes |
|---|---|---|
'mean' |
Arithmetic mean | |
'lower_q' |
Lower quartile, 0.25-percentile | see 'median' |
'median' |
Median, 0.5-percentile | per SPSS Statistics/ Dimensions approach, method 6 in [1] |
'upper_q' |
Upper quartile, 0.75-percentile | see 'median' |
'var' |
Unbiased (n-1) sample variance | |
'stddev' |
Standard deviation | np.sqrt(var) |
'varcoeff' |
Coefficient of variation | |
'sem' |
Standard error of the mean | |
'max' |
Maximum | always unweighted |
'min' |
Minimum | always unweighted |
>>> q.summarize(show='mean', margin=True)
Question gender
Values All 1 2
Question Values
q5_1 mean 25.601017 23.970385 27.112158
Post-aggregation arithmetic¶
| method: | quantipy.Quantity.calc(expression, axis='x', result_only=False) |
|---|
In contrast to count()
and summarize()
, that are referencing the raw
case data, the Quantity calc()
method can be applied to a selection of
already existing aggregation results. It accepts (very) simple computation
terms given in the expression
parameter, for instance as per:
>>> expr = {'Difference of 1 and 2': (1, sub, 2)}
To use it, one of the former must have been run beforehand or the method will raise an error:
>>> link = stack[name_project]['no_filter']['q8']['gender']
>>> q = qp.Quantity(link)
>>> q.calc(expression=expr)
ValueError: No aggregation to base calculation on.
With a result from the count()
method, however, we can compute the
difference between the counts in group 1 and 2:
>>> q.count().calc(expression=expr)
Question gender
Values All 1 2
Question Values
q8 All 2367 1211 1156
1 949 473 476
2 216 112 104
3 595 293 302
4 970 507 463
5 1235 636 599
96 283 165 118
98 49 26 23
Difference of 1 and 2 733 361 372
It is also possible to use a scalar value in the calculation expression,
indicated by providing the desired value with the constant()
method:
>>> link = stack[name_project]['no_filter']['q5_1']['gender']
>>> q = qp.Quantity(link, 'weight_a')
>>> constant = qp.Quantity.constant
>>> expr = {'Third of mean': ('mean', div, constant(3))}
>>> q.summarize(stat='mean', margin=False)
>>> q.calc(expression=expr)
Question gender
Values 1 2
Question Values
q5_1 mean 23.970385 27.112158
Third of mean 7.990128 9.037386
The outcome of calc()
is appended to the result dataframe by default.
To only show the isolated figures, the result_only
argument can be set to True
:
>>> q.calc(expression=expr, result_only=True)
Question gender
Values 1 2
Question Values
q5_1 Third of mean 7.990128 9.037386
See also
Post-aggregation calculations are supported in conjunction with the large
majority of the Quantity class routines of their parameter settings. For
instance, calc()
is capable to use edited Link data from group()
and
can be performed after normalize()
(i.e. on percentage representations
of counts). The outlined functionality is also fully integrated within
the view method features.
Note, however, that calc()
is not implemented for bases/count-sum
types of count()
aggregations and the 'summary'
option of summarize()
.
Data manipulation and editing¶
Grouping/combining¶
| method: | quantipy.Quantity.group(groups, axis='x', expand=None, complete=False) |
|---|
group()
is a flexible method to arrange code values into groups
on-the-fly using (complex) logical statements. A simple example is to calculate
a net category of values found in the data:
>>> link = stack[name_project]['no_filter']['q8']['gender']
>>> q = qp.Quantity(link, 'weight_a')
>>> q.group(groups=[1, 2])
>>> q.count()
Values All 1 2
Question Values
q8 All 2259.769789 1156.803818 1102.965971
net 980.059615 512.037643 468.021972
The groups
parameter can also be provided as a list of dict mappings grouping
names to lists of codes in order to generate multiple nets at once:
>>> grps = [{'GROUP A': [1,2]},
... {'GROUP B': [4, 5]},
... {'GROUP C': [96, 98]}]
>>> q.group(groups=grps).count(margin=False)
Values 1 2
Question Values
q8 GROUP A 512.037643 468.021972
GROUP B 859.773667 814.457890
GROUP C 168.978007 134.946995
Notice that the expand
parameter can be set to 'before'
or 'after'
to present the originating codes alongside the created groups:
>>> q.group(groups=grps, expand='before').count(margin=False)
Question gender
Values 1 2
Question Values
q8 1 449.982974 420.299580
2 129.877415 105.438740
GROUP A 512.037643 468.021972
4 466.994617 438.363240
5 619.453850 585.361892
GROUP B 859.773667 814.457890
96 144.078833 118.023747
98 24.899174 16.923248
GROUP C 168.978007 134.946995
>>> q.group(groups=grps, expand='after').count(margin=False)
Question gender
Values 1 2
Question Values
q8 GROUP A 512.037643 468.021972
1 449.982974 420.299580
2 129.877415 105.438740
GROUP B 859.773667 814.457890
4 466.994617 438.363240
5 619.453850 585.361892
GROUP C 168.978007 134.946995
96 144.078833 118.023747
98 24.899174 16.923248
In addition to that, the value order of an expanded result can also be fine tuned (or even completely handled) within the construction of the code groups as per:
>>> grps = [{'GROUP A': [1,2], 'expand': 'before'},
... {'GROUP B': [4, 5], 'expand': 'after'},
... {'GROUP C': [96, 98], 'expand': None}]
>>> q.group(grps, expand='after').count(margin=False)
Question gender
Values 1 2
Question Values
q8 1 449.982974 420.299580
2 129.877415 105.438740
GROUP A 512.037643 468.021972
GROUP B 859.773667 814.457890
4 466.994617 438.363240
5 619.453850 585.361892
GROUP C 168.978007 134.946995
As can be seen, expand
settings from a group definition will overwrite the
general setting of expand
provided in the group()
method.
In addition,
it is possible to show all remaining codes of a Link’s data by setting
complete
to True
while preserving any expand
options.
Please note: An exception is None
when set in a group defintion,
which will be transformed to 'before'
in order to show the Link’s complete
code frame:
>>> >>> q.group(grps, expand='after', complete=True).count(margin=False)
Question gender
Values 1 2
Question Values
q8 1 449.982974 420.299580
2 129.877415 105.438740
GROUP A 512.037643 468.021972
3 270.823427 261.132200
GROUP B 859.773667 814.457890
4 466.994617 438.363240
5 619.453850 585.361892
96 144.078833 118.023747
98 24.899174 16.923248
GROUP C 168.978007 134.946995
To conclude this section, the following snippet shows how calc()
interacts with group()
. Based on the previous example, we calculate the
difference between 'GROUP A'
and 'GROUP B'
:
>>> expr = {'NPS (A - B)': ('GROUP A', sub, 'GROUP B')}
>>> q.calc(expression=expr)
Question gender
Values 1 2
Question Values
q8 1 449.982974 420.299580
2 129.877415 105.438740
GROUP A 512.037643 468.021972
3 270.823427 261.132200
GROUP B 859.773667 814.457890
4 466.994617 438.363240
5 619.453850 585.361892
96 144.078833 118.023747
98 24.899174 16.923248
GROUP C 168.978007 134.946995
NPS (A - B) -347.736024 -346.435918
Value scaling¶
| method: | quantipy.Quantity.rescale(scaling, drop=False) |
|---|
Sometimes it is necessary to modify the value range of the answer codes before
calculating summary statistics as the mean or standard deviation. This can be achieved by simply passing a dict that maps old to new codes into the
rescale()
method, as can be demonstrated by the following comparison. The
original codeframe for the cross-tabulation of 'q5_1'
against 'gender'
looks like this:
>>> link = stack[name_project]['no_filter']['q5_1']['gender']
>>> q = qp.Quantity(link, 'weight_a')
>>> q.count(margin=False)
Question gender
Values 1 2
Question Values
q5_1 1 235.582506 201.090692
2 330.422152 387.100024
3 1416.177225 1097.263154
4 80.147116 57.643281
5 1044.869495 1476.411102
97 120.395937 85.547704
98 742.924059 979.425553
After setting up the new value codes and applying them using rescale()
we see this reflected in the aggregation result:
>>> scaling = {1: 0, 2: 25, 3: 50, 4: 75, 5: 100}
>>> q.rescale(scaling)
>>> q.count(margin=False)
Question gender
Values 1 2
Question Values
q5_1 0 235.582506 201.090692
25 330.422152 387.100024
50 1416.177225 1097.263154
75 80.147116 57.643281
100 1044.869495 1476.411102
97 120.395937 85.547704
98 742.924059 979.425553
To report i.e. meaningful summary statistics, however, we should also get rid
of the non-response or other residual codes, which is equally easy to accomplish.
The rescale method can be called with its parameter drop
set to True and all
codes that are not used in the scale determining dict will be automatically
dropped from the aggregation and its margins:
>>> q.rescale(scaling, drop=True)
>>> q.count(margin=False)
Question gender
Values 1 2
Question Values
q5_1 0 235.582506 201.090692
25 330.422152 387.100024
50 1416.177225 1097.263154
75 80.147116 57.643281
100 1044.869495 1476.411102
97 0.000000 0.000000
98 0.000000 0.000000
>>> q.summarize('mean', margin=False)
Question gender
Values 1 2
Question Values
q5_1 mean 61.009105 67.247852
Excluding/limiting¶
| method: | quantipy.Quantity.exclude(codes, axis='x') |
|---|---|
| method: | quantipy.Quantity.limit(codes, axis='x') |
Of course, the inclusion and exclusion of data codes can be handled independently
as well: Using exclude()
will remove the passed codes
in the aggregation
methods from the given axis
, limit()
will restrict results to include them
only.
Note, however, that while exclude()
will also prevent codes to count
against the margin totals, limit()
is leaving those untouched. Given the
following aggregation as a reference...
>>> link = stack[name_data]['no_filter']['q5_1']['gender']
>>> q = qp.Quantity(link)
>>> q.count()
Question gender
Values All 1 2
Question Values
q5_1 All 8255 3952 4303
1 363 186 177
2 700 314 386
3 2598 1452 1146
4 124 67 57
5 2472 1032 1440
97 200 120 80
98 1798 781 1017
... the difference between exclude()
...
>>> q.exclude([97, 98]).count()
Question gender
Values All 1 2
Question Values
q5_1 All 6257 3051 3206
1 363 186 177
2 700 314 386
3 2598 1452 1146
4 124 67 57
5 2472 1032 1440
97 0 0 0
98 0 0 0
... and limit()
becomes apparent:
>>> q.limit([97, 98]).count()
Question gender
Values All 1 2
Question Values
q5_1 All 8255 3952 4303
1 0 0 0
2 0 0 0
3 0 0 0
4 0 0 0
5 0 0 0
97 200 120 80
98 1798 781 1017
Filtering¶
Computation result handling¶
The result
property¶
Quantity
aggregations results are passed and stored in the object’s
result
property, i.e. the __repr__
method will return its content
instead of the general description of the object as long as result
is not
None
:
>>> link = stack[name_project]['no_filter']['q8']['gender']
>>> q = qp.Quantity(link, 'weight_a').count()
>>> q
Question gender
Values 1 2 All
Question Values
q8 All 1156.803818 1102.965971 2259.769789
1 449.982974 420.299580 870.282554
2 129.877415 105.438740 235.316156
3 270.823427 261.132200 531.955628
4 466.994617 438.363240 905.357857
5 619.453850 585.361892 1204.815742
96 144.078833 118.023747 262.102580
98 24.899174 16.923248 41.822422
In the method signatures of count()
, describe()
and combine()
the
as_df
parameter is set to True
by default, which means that computation
results are returned as multi-indexed pandas.DataFrame
before
they are passed to result
: On both the index and the column axis,
the question (=variable) name is presented on the first and the answer code
entries found in the data on the second level of the index.
It is, however, possible to store the underlying raw numpy.array
by setting
as_df=False
:
>>> q = qp.Quantity(link, 'weight_a').count(as_df=False)
>>> q
[[ 1156.80381804 1102.96597105 2259.7697891 ]
[<PHONE_NUMBER>1<PHONE_NUMBER>8<PHONE_NUMBER>9]
[<PHONE_NUMBER>6<PHONE_NUMBER>5<PHONE_NUMBER>1]
[<PHONE_NUMBER><PHONE_NUMBER>5<PHONE_NUMBER>5]
[<PHONE_NUMBER>5<PHONE_NUMBER>2<PHONE_NUMBER>7]
[<PHONE_NUMBER>1<PHONE_NUMBER>9 1204.815742 ]
[<PHONE_NUMBER><PHONE_NUMBER>2<PHONE_NUMBER>2]
[ 24.89917382 16.92324804 41.82242186]]
That makes it possible to use both pandas
and numpy
library methods on
a Quantity
result to further modify the data aggregate:
>>> q.result[1:,:].mean()
385.871708399
to_df()
export¶
| method: | quantipy.Quantity.to_df(row_val=None, col_val=None) |
|---|
Any Quantity.result
that has been stored as type numpy.array
can be
transformed to a pandas.DataFrame
and passed to the result
property
using the to_df()
method. Use cases for a manual export range from simply
changing the text displayed in the Values-level of the pandas.MultiIndex
to
applying a well-formatted layout to customizing aggregations or View method
programming.
Consider the simple case first in which the object’s default
appearance of a column base aggregation result is overwritten: By providing a
new text via the row_val
parameter it changes to:
>>> new_text = 'Sample: women only'
>>> q.count(show='cbase', as_df=False).to_df(row_val=new_text)
Question gender
Values 1 2 All
Question Values
q8 Sample: women only 1156.803818 1102.965971 2259.769789
For more complex operations, however, it is important to be aware of the
shape of the aggregation result and provide the matching number of text values:
Picking up the already known result from the previous paragraph, to_df()
would need to know the values for both the index and the column axis for the
pandas.DataFrame
since it cannot infer them:
>>> q.result = q.result[1:,:].mean()
>>> q.to_df(row_val='mean of all counts', col_val='just a demo')
>>> q
Question gender
Values just a demo
Question Values
q8 mean of all counts 385.871708
Percentages¶
| method: | quantipy.Quantity.normalize(on='col') |
|---|
count()
and combine()
results are always expressed in terms of simple
cell counts. The normalize()
method therefore takes the duty to easily
compute a percentage representation with regard to either the column
(by default) or row base sizes, i.e. changing the result to column or row
percentages. Normalizing works together with both numpy.array
or
pandas.DataFrame
type of results:
>>> q = qp.Quantity(link, 'weight_a').count()
>>> q.normalize()
>>> q
Question gender
Values 1 2 All
Question Values
q8 All 100.000000 100.000000 100.000000
1 38.898815 38.106305 38.512001
2 11.227264 9.559564 10.413280
3 23.411353 23.675454 23.540258
4 40.369388 39.744040 40.064163
5 53.548738 53.071618 53.315862
96 12.454906 10.700579 11.598641
98 2.152411 1.534340 1.850738
>>> q = qp.Quantity(link, 'weight_a').combine(group=[1, 2, 3], as_df=False)
>>> q.normalize('row').to_df('net - row % of codes: 1, 2, 3')
>>> q
Question gender
Values 1 2 All
Question Values
q8 net - row % of codes: 1, 2, 3 52.367773 47.632227 100
Footnotes
| [1] | Hyndman, R. J. and Fan, Y. (1996): Sample Quantiles in Statistical Packages The American Statistician 50, no. 4, 361–365. |


For those that prefer css styles compared to JS-object styles.
There are probably a lot of unhandled cases. Feel free to submit PRs.
Source: https://github.com/simonsterckx/json-to-styled
This effectively does the opposite of the package css-to-react-native
Web example: https://csstox.surge.sh


The Natharex This is the entry. Mosaics are inspired by Psalm 42. Above the main entrance is a mosaic of the Polish Eagle, a symbol of independence during Poland's history. The stained glass crown symbolizes Mary, Queen of Apostles.
The Former Baptistry Enter and go to the left. formerly the Baptistry, now a room of Penance and Reconciliation. It is circular and 8 sided, representing the circle of eternal life and the sacramental life of the church. The four stained glass windows depict the "types" of Baptism: blood, desire, water and adult baptism.
North Side Windows Various depictions of biblical passages. moving towards the front of the church, you will see the statue of St Anthony of Padua, the patron saint of lost things or lost people.
North Transept Walking to the center of the north transcept, there is a small altar dedicated to St Francis of Assisi. The Sacred Heart Shrine at the front of the church on the left side containing a tabernacle used on Holy Thursday. The mosaic represents Easter Morning
Clerestory Windows The 16 windows that rise to the ceiling are made of transparent stained glass, filling the church with light.
The Sanctuary The ceiling mosaic is modeled after a painting by Polish artist Adam Styka. In the lower right corner are Fr. Szok, Fr. Redwick and the installer Ricardo Polmbit. In the lower left corner is the artist of the mosaic:Pietro Cantu, he is carrying a lamb. JHS or IHS is an acronym for the Greek phrase "Jesus Christ, Son of God, Savior". The two large mosaics on the sides depict the Annunciation and the Ascension. The Baptismal Font is at the Sanctuary. The former Communion rail was taken out to bring unity between the sanctuary and the nave.
The South Transcept Near the Blessed Mother Shrine is a statue of St Theresa. There are several windows depicting the life of Christ as well as the life of St Peter.
Stations of the Cross 14 framed marble scenes represent the suffering of Jesus on Good Friday.
The Choir Loft The organ is a Casavant with 2,187 pipes. The windows depict the 12 Apostles, Old Testament Patriarchs(Joseph, Noah,Abraham, Solomon) and several medieval Polish saints. The center panels represent the various titles and events in the life of Mary. The Polish children of Mary are also pictured. The right panels include a parade of Polish Saints, including Pope St Pius X. The arch mosaic recalls Psalm 150, the concluding passage in the book of Psalms, aptly drawing the church tour to a close.
Orchard and Grotto Heading outside to Prescott Street. The rectory is behind the church. The activity center is accessed through the parking lot behind the school. The Orchard contains the wooden cross that sat atop the Papal platform for Pope John Paul II's 1987 visit to Hamtramck.The Grotto contains a Statue of Our Lady Queen of Apostles. Each May she is crowned with flowers.
Stained Glass
Seek and find the following:
The Parable of the Hidden Treasure---- Matthew 13:44
The Parable of the Weeds -- ---- Matthew 13:36-43
The Parable of the Sower ----- Matthew 13:3-9
The Woman of Great Faith ----- Matthew 15:26-27
The four forms of Baptism: Blood, Desire, Water and Adult
The Narrow Door -- --- Luke 13:23-30
The Parable of the Mustard Seed and the Yeast-- Matthew 13:31-33


Duration
Email address
LinkedIn
City
Cuisine
How much did you like working with everyone there?
😀
😐
🙄
How much did you like the work?
😀
😐
🙄
Unattributed quote from
Perfect Strangers
[view]
Diff'rent Strokes
[view]
The Littlest Hobo
[view]
Klingon Proverb
How badly do you want people contacting you?
😀
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🙄


Guinean teen shot dead by police during protest: family, doctor
A Guinean teenager was shot dead on Thursday by police as he tried to flee a crackdown on anti-government protests in the capital Conakry, his family and a doctor said.
Alpha Souleymane Diallo, 19, was caught up in clashes and came face to face with two policemen who shot him in the chest, his elder brother Boubacar said.
A doctor at the Amitie Hospital confirmed that one person had died from bullet wounds.
The poor West African nation of about 13 million people has been shaken by violence during weeks of demonstrations over opposition suspicions that President Alpha Conde is seeking a third term in office, banned by the constitution.
At least 18 civilians and a paramilitary policeman have been killed since October 14. Dozens of people have been wounded and dozens more arrested.


dials.export¶
Introduction¶
This program is used to export the results of dials processing in various formats.
The output formats currently supported are:
MTZ format exports the files as an unmerged mtz file, ready for input to downstream programs such as Pointless and Aimless. The required input is an experiments.json file and an integrated.pickle file.
NXS format exports the files as an NXmx file. The required input is an experiments.json file and an integrated.pickle file.
MMCIF format exports the files as an mmcif file. The required input is an experiments.json file and an integrated.pickle file.
XDS_ASCII format exports intensity data and the experiment metadata in the same format as used by the output of XDS in the CORRECT step - output can be scaled with XSCALE.
SADABS format exports intensity data (and geometry by direction cosines) as an ersatz-SADABS format reverse engineered from the file format used by EvalCCD for input to SADABS.
MOSFLM format exports the files as an index.mat mosflm-format matrix file and a mosflm.in file containing basic instructions for input to mosflm. The required input is an experiments.json file.
XDS format exports an experiments.json file as XDS.INP and XPARM.XDS files. If a reflection pickle is given it will be exported as a SPOT.XDS file.
Examples:
# Export to mtz
dials.export experiments.json integrated.pickle
dials.export experiments.json integrated.pickle mtz.hklout=integrated.mtz
# Export to nexus
dials.export experiments.json integrated.pickle format=nxs
dials.export experiments.json integrated.pickle format=nxs nxs.hklout=integrated.nxs
# Export to mmcif
dials.export experiments.json integrated.pickle format=mmcif
dials.export experiments.json integrated.pickle format=mmcif mmcif.hklout=integrated.mmcif
# Export to mosflm
dials.export experiments.json integrated.pickle format=mosflm
# Export to xds
dials.export strong.pickle format=xds
dials.export indexed.pickle format=xds
dials.export experiments.json format=xds
dials.export experiments.json indexed.pickle format=xds
Basic parameters¶
format = *mtz sadabs nxs mmcif mosflm xds best xds_ascii json summation = False debug = False mtz { ignore_panels = False include_partials = False keep_partials = False scale_partials = True apply_scales = False min_isigi = -5 force_static_model = False filter_ice_rings = False ignore_profile_fitting = False hklout = integrated.mtz } sadabs { hklout = integrated.sad run = 1 predict = False } xds_ascii { hklout = DIALS.HKL } nxs { hklout = integrated.nxs } mmcif { hklout = integrated.cif } mosflm { directory = mosflm } xds { directory = xds } best { prefix = best n_bins = 100 min_partiality = 0.1 } json { filename = rlp.json compact = True n_digits = 6 } output { log = dials.export.log debug_log = dials.export.debug.log }
Full parameter definitions¶
format = *mtz sadabs nxs mmcif mosflm xds best xds_ascii json .help = "The output file format" .type = choice summation = False .help = "Output summation integrated data (default profile fitted)" .type = bool debug = False .help = "Output additional debugging information" .type = bool mtz { ignore_panels = False .help = "Ignore multiple panels / detectors in output (deprecated)" .type = bool include_partials = False .help = "Include partial reflections (scaled) in output" .type = bool keep_partials = False .help = "Keep low partiality reflections" .type = bool scale_partials = True .help = "Scale partial reflections to 100% (unreliable if partiality low)" .type = bool apply_scales = False .help = "Apply scale factors in inverse_scale_factor column if present" .type = bool min_isigi = -5 .help = "Exclude reflections with unfeasible values of I/Sig(I)" .type = float force_static_model = False .help = "Force program to use static model even if scan varying is present" .type = bool filter_ice_rings = False .help = "Filter reflections at ice ring resolutions" .type = bool ignore_profile_fitting = False .help = "Ignore profile fitted intensities. Sometimes necessary for narrow" "wedges or other situations where profile fitting has failed for" "all reflections and we only have summation intensities." .type = bool hklout = integrated.mtz .help = "The output MTZ file" .type = path } sadabs { hklout = integrated.sad .help = "The output raw sadabs file" .type = path run = 1 .help = "Batch number / run number for output file" .type = int predict = False .help = "Compute centroids with static model, not observations" .type = bool } xds_ascii { hklout = DIALS.HKL .help = "The output raw hkl file" .type = path } nxs { hklout = integrated.nxs .help = "The output Nexus file" .type = path } mmcif { hklout = integrated.cif .help = "The output CIF file" .type = path } mosflm { directory = mosflm .help = "The output directory for mosflm output" .type = path } xds { directory = xds .help = "The output directory for xds output" .type = path } best { prefix = best .help = "The prefix for the output file names for best (.hkl, .dat and" ".par files)" .type = str n_bins = 100 .help = "Number of resolution bins for background estimation" .type = int(value_min=1) min_partiality = 0.1 .help = "Minimum partiality of reflections to export" .type = float(value_min=0, value_max=1) } json { filename = rlp.json .type = path compact = True .type = bool n_digits = 6 .help = "Number of decimal places to be used for representing the" "reciprocal lattice points." .type = int(value_min=1) } output { log = dials.export.log .help = "The log filename" .type = path debug_log = dials.export.debug.log .help = "The debug log filename" .type = path }


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If you want a div to take up 75% of the width, all you need to do is give it a width of 75%.
If you want a header to take up 75% of the width, you need to play with font-size until it’s roughly the width you want.
(Oh, but the second you resize your window or view the page on any other device, it’s a completely different relative size.)
 When it’s done, you’ll just need to call it, like so:
$(“#main_header”).textPerc(75);
This will find the font-size sweet spot to make that text take up 75% of the width, and it’ll bind an event-listener to make sure it changes when the window size changes.


Hi Ho, Hi Ho, it's off to work we go....
Now that Snow White ran off with her Prince, the house is a mess. The other dwarves need Dopey to sell some gems to cover the house cleaning bills.
The four gems are each worth a different amount of gold (but Dopy can't remember how much!). Click on the gems to sell them
Sell enough of the gems to match the cleaning bill BUT DON'T GO OVER...Doc is a real cheapskate
Each time you pay a bill you'll have to go to another jewler and the price per gem will change
RUBY
EMERALD
SAPHIRE
DIAMOND


Kids can enjoy unlimited free snacks and drinks, including TERRA® Sweets & Blues™ potato chips, Cheez-It® crackers and Skeeter™ Nut-Free chocolate chip cookies


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Read more by clicking "read more" contents.
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@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.govukfrontend.views.html.components._ @import uk.gov.hmrc.govukfrontend.views.html.components.implicits._ @import uk.gov.hmrc.preferencesadminfrontend.config.AppConfig @import uk.gov.hmrc.preferencesadminfrontend.controllers.routes @import uk.gov.hmrc.preferencesadminfrontend.model.AllowlistEntry @this( layout: Layout, form: FormWithCSRF, govukButton: GovukButton, govukTextarea: GovukTextarea, govukBreadcrumbs: GovukBreadcrumbs) @(entryForm: Form[AllowlistEntry])(implicit request: Request[_], messages: Messages, appConfig: AppConfig) @layout(pageTitle = Some("Message Form IDs Allowlist")) { @govukBreadcrumbs(Breadcrumbs( items = Seq( BreadcrumbsItem( content = Text("Home"), href = Some("/paperless/admin/home") ), BreadcrumbsItem( content = Text("Message Brake Allowlist"), href = Some("/paperless/admin/allowlist") ), BreadcrumbsItem( content = Text("Allowlist - Delete"), href = Some("#") ) ) ) )


One of the things a rower always wants to know: how fast am I? In rowing it is quite hard to compare results. Even if you win, how do you know if your crew has been very fast- or the opponents rather slow? How do you compare a lightweight single to a heavyweight eight? And what if a regatta has obviously been influenced by the weather?
This article is about answering some of these questions through visualizations. The data used to draw these graphs is freely available on Time Team. I will exclusively be using 2000m regattas on The Bosbaan - Amsterdam.
For those who do not have a basic knowledge about rowing, this collapsible section will explain more.
About Regattas, Fields, Heats, Boat types etc..
Regatta is the name of a tournament in rowing. Each of these regattas consists of many different categories in which crews can participate. Every race in a category is called a heat. There are many different regattas in The Netherlands: about 10-12 important regattas each year, and many other smaller ones. Most regattas are on a 2000m course- as this is the most important distance in rowing. During world cups and Olympics 2000m is the only distance.
In the following visualizations you'll notice many different codes like N1x or DDev4-. What you need to know: these codes are Dutch abbreviations for the field a crew is in. The abbreviations consist of three parts:
Examples:
A lightweight (L) starter (B) rowing a single (1x): LB1x
Four women (D) rowing a double four (4*) in an "advanced" (O) field: DO4*.
Eight men (-) rowing an eight(8+) in the top (SA) heavyweight class: SA8+.
Other codes (like: ORC, OKE, NER, SKO, TRI, WIL etc.) are abbreviations for rowing clubs.
 This chart allows you to compare them. Hover over the bars to see more details about every crew.
Rowing results differ greatly as races are influenced by various factors. Fair comparison between seasons/years, regattas, races and/or people is very hard. In addition, comparing a lightweight novice to an experienced heavyweight would not make any sense, just like comparing a windy winter regatta to an end-of-season summer regatta. Still, by calculating some correction factors it might be possible to (somehow) compare the data. The goal of this visualizations is trying to achieve this.
Scores (0%-100%) are based on the fastest times in the dataset. Example: if the fastest mens eight would row 2000m in 6min it would mean an average speed of 20kmph. If another mens eight did it in 6m20 that would mean an average speed of 18.95kmph. This results in a score of 94.7%.
The vertical lines represent the averages, one of the regatta day, one of the entire regatta.
Note: By converting every score to a percentage of the quickest time, the scores become relative. Doing this also creates a problem: Which records to compare to? Not all records are set equally competitive as not all boat types are equally popular.
Before viewing this visualization, it is important to know how the race drawing procedure works. From all sign-ups, a random draw decides which crew starts in which lane. In case there are more crews than lanes (often the case), pre-finals will be organized. From the pre-finals, the six quickest teams will promote to the A-Final. In this final, the quickest teams from are lined up in the middle. All slower crews around their lanes.
Example: 6 crews make it to the final, lane [2] to [7] are in use. The quickest crew is lined-up in one of the middle lanes: [4] or [5]. The other crews are aligned based on their times in the heats. The sides lanes thus sporting the slowest crews.]
Due to wind conditions, races might not always be as fair as they seem. In general, the quickest crew in the pre-finals has a right to start in the quickest lane. Often, regatta organisation members tend to ignore lane advantage, although it does not exist - probably because it would involve a lot of hassle and a re-draw.
The following graph attempts to show lane advantage in different regattas. A bigger dot means a better result. Weather data is based on daily averages at Schiphol and will slightly differ from the actual weather. "De Bosbaan" is positioned WSW (start) to ENE (finish), as seen on the map below.
Could not load Bosbaan Map:
An internet connection is required to load Google Maps
Patterns can be seen by looking at the distribution of the bigger and smaller dots. Some regattas (fe. Hollandia 2013) clearly show certain lanes winning all the heats.
Note: Although the lane advantage graph shows average wind factors, these are not the only important factors. Current, water- and air temperature are important as well. The weather stats are merely an indication and should be treated as such.
Website created as part of MPROGs final project. Written in HTML, CSS, Javascript. Data manipulations in JS using: d3js.org and a tiny bit of jQuery. Map by Google, theme by Tanja Lederer.
Thanks to TimeTeam for publishing regatta data. Weather data from KNMI.


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So much awesome in @tenderlove's talk at #cascadiaruby right now. Bring on the 229 slides!
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So much awesome in @tenderlove's talk at #cascadiaruby right now. Bring on the 229 slides!
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FIGLET(6) FIGLET(6) NAME FIGlet - display large characters made up of ordinary screen characters SYNOPSIS figlet [ -cklnoprstvxDELNRSWX ] [ -d fontdirectory ] [ -f fontfile ] [ -m layoutmode ] [ -w outputwidth ] [ -C controlfile ] [ -I infocode ] [ message ] DESCRIPTION FIGlet prints its input using large characters (called ``FIGcharac‐ ters'')made up of ordinary screen characters (called ``sub-characters''). FIGlet output is generally reminiscent of the sort of ``signatures'' many people like to put at the end of e-mail and UseNet messages. It is also reminiscent of the output of some banner programs, although it is ori‐ ented normally, not sideways. FIGlet can print in a variety of fonts, both left-to-right and right-to- left, with adjacent FIGcharacters kerned and ``smushed'' together in var‐ ious ways. FIGlet fonts are stored in separate files, which can be iden‐ tified by the suffix ``.flf''. In systems with UTF-8 support FIGlet may also support TOIlet ``.tlf'' fonts. Most FIGlet font files will be stored in FIGlet's default font directory. FIGlet can also use ``control files'', which tell it to map certain input characters to certain other characters, similar to the Unix tr command. Control files can be identified by the suffix ``.flc''. Most FIGlet con‐ trol files will be stored in FIGlet's default font directory. You can store FIGlet fonts and control files in compressed form. See COMPRESSED FONTS. USAGE Just start up FIGlet (type ``figlet'') and then type whatever you want. Alternatively, pipe a file or the output of another command through FIGlet, or put input on the command line after the options. See EXAMPLES for other things to do. OPTIONS FIGlet reads command line options from left to right, and only the last option that affects a parameter has any effect. Almost every option has an inverse, so that, for example, if FIGlet is customized with a shell alias, all the options are usually still available. Commonly-used options are -f, -c, -k, -t, -p and -v. -f fontfile Select the font. The .flf suffix may be left off of fontfile, in which case FIGlet automatically appends it. FIGlet looks for the file first in the default font directory and then in the current directory, or, if fontfile was given as a full pathname, in the given directory. If the -f option is not specified, FIGlet uses the font that was specified when it was compiled. To find out which font this is, use the -I3 option. -d fontdirectory Change the default font directory. FIGlet looks for fonts first in the default directory and then in the current directory. If the -d option is not specified, FIGlet uses the directory that was specified when it was compiled. To find out which directory this is, use the -I2 option. -c -l -r -x These options handle the justification of FIGlet output. -c cen‐ ters the output horizontally. -l makes the output flush-left. -r makes it flush-right. -x (default) sets the justification accord‐ ing to whether left-to-right or right-to-left text is selected. Left-to-right text will be flush-left, while right-to-left text will be flush-right. (Left-to-right versus right-to-left text is controlled by -L, -R and -X.) -t -w outputwidth These options control the outputwidth, or the screen width FIGlet assumes when formatting its output. FIGlet uses the outputwidth to determine when to break lines and how to center the output. Normally, FIGlet assumes 80 columns so that people with wide ter‐ minals won't annoy the people they e-mail FIGlet output to. -t sets the outputwidth to the terminal width. If the terminal width cannot be determined, the previous outputwidth is retained. -w sets the outputwidth to the given integer. An outputwidth of 1 is a special value that tells FIGlet to print each non-space FIGchar‐ acter, in its entirety, on a separate line, no matter how wide it is. -p -n These options control how FIGlet handles newlines. -p puts FIGlet into ``paragraph mode'', which eliminates some unnecessary line breaks when piping a multi-line file through FIGlet. In paragraph mode, FIGlet treats line breaks within a paragraph as if they were merely blanks between words. (Specifically, -p causes FIGlet to convert any newline which is not preceded by a newline and not followed by a space character into a blank.) -n (default) puts FIGlet back to normal, in which every newline FIGlet reads causes it to produce a line break. -D -E -D switches to the German (ISO 646-DE) character set. Turns `[', `\' and `]' into umlauted A, O and U, respectively. `{', `|' and `}' turn into the respective lower case versions of these. `~' turns into s-z. -E turns off -D processing. These options are deprecated, which means they probably will not appear in the next version of FIGlet. -C controlfile -N These options deal with FIGlet controlfiles. A controlfile is a file containing a list of commands that FIGlet executes each time it reads a character. These commands can map certain input char‐ acters to other characters, similar to the Unix tr command or the FIGlet -D option. FIGlet maintains a list of controlfiles, which is empty when FIGlet starts up. -C adds the given controlfile to the list. -N clears the controlfile list, cancelling the effect of any previous -C. FIGlet executes the commands in all con‐ trolfiles in the list. See the file figfont.txt, provided with FIGlet, for details on how to write a controlfile. -s -S -k -W -o These options control how FIGlet spaces the FIGcharacters that it outputs. -s (default) and -S cause ``smushing''. The FIGcharac‐ ters are displayed as close together as possible, and overlapping sub-characters are removed. Exactly which sub-characters count as ``overlapping'' depends on the font's layoutmode, which is defined by the font's author. -k causes ``kerning''. As many blanks as possible are removed between FIGcharacters, so that they touch, but the FIGcharacters are not smushed. -W makes FIGlet display all FIGcharacters at their full width, which may be fixed or vari‐ able, depending on the font. The difference between -s and -S is that -s will not smush a font whose author specified kerning or full width as the default lay‐ outmode, whereas -S will attempt to do so. If there is no information in the font about how to smush, or if the -o option is specified, then the FIGcharacters are ``over‐ lapped''. This means that after kerning, the first subcharacter of each FIGcharacter is removed. (This is not done if a FIGchar‐ acter contains only one subcharacter.) -m layoutmode Specifies an explicit layoutmode between 1 and 63. Smushmodes are explained in figfont.txt, which also provides complete information on the format of a FIGlet font. For the sake of backward compati‐ bility with versions of FIGlet before 2.2, -m0 is equivalent to -k, -m-1 is equivalent to -W, and -m-2 is equivalent to -s. The -m switch is normally used only by font designers testing the var‐ ious layoutmodes with a new font. -v -I infocode These options print various information about FIGlet, then exit. If several of these options are given on the command line, only the last is executed, and only after all other command-line options have been dealt with. -v prints version and copyright information, as well as a ``Usage: ...'' line. -I prints the information corresponding to the given infocode in a consistent, reliable (i.e., guaranteed to be the same in future releases) format. -I is primarily intended to be used by programs that use FIGlet. infocode can be any of the fol‐ lowing. -1 Normal operation (default). This infocode indicates that FIGlet should operate nor‐ mally, not giving any informational printout, printing its input in the selected font. 0 Version and copyright. This is identical to -v. 1 Version (integer). This will print the version of your copy of FIGlet as a decimal integer. The main version number is multiplied by 10000, the sub-version number is multiplied by 100, and the sub-sub-version number is multiplied by 1. These are added together, and the result is printed out. For example, FIGlet 2.2 will print ``20200'' , version 2.2.1 will print ``20201''. Similarly, version 3.7.2 would print ``30702''. These numbers are guaranteed to be ascending, with later versions having higher numbers. Note that the first major release of FIGlet, version 2.0, did not have the -I option. 2 Default font directory. This will print the default font directory. It is affected by the -d option. 3 Font. This will print the name of the font FIGlet would use. It is affected by the -f option. This is not a filename; the ``.flf'' suffix is not printed. 4 Output width. This will print the value FIGlet would use for outputwidth, the number of columns wide FIGlet assumes the screen is. It is affected by the -w and -t options. 5 Supported font formats. This will list font formats supported by FIGlet . Possible formats are ``flf2'' for FIGfont Version 2 .flf files and ``tlf2'' for TOIlet .tlf files. If infocode is any other positive value, FIGlet will simply exit without printing anything. -L -R -X These options control whether FIGlet prints left-to-right or right-to-left. -L selects left-to-right printing. -R selects right-to-left printing. -X (default) makes FIGlet use whichever is specified in the font file. Once the options are read, if there are any remaining words on the command line, they are used instead of standard input as the source of text. This feature allows shell scripts to generate large letters without having to dummy up standard input files. An empty argument, obtained by two sequential quotes, results in a line break. EXAMPLES To use FIGlet with its default settings, simply type example% figlet and then type whatever you like. To change the font, use the -f option, for example, example% figlet -f script Use the -c option if you would prefer centered output: example% figlet -c We have found that the most common use of FIGlet is making up large text to be placed in e-mail messages. For this reason, FIGlet defaults to 80 column output. If you are using a wider terminal, and would like FIGlet to use the full width of your terminal, use the -t option: example% figlet -t If you don't want FIGlet to smush FIGcharacters into each other, use the -k option: example% figlet -k If figlet gets its input from a file, it is often a good idea to use -p: example% figlet -p < myfile Of course, the above can be combined: example% figlet -ptk -f shadow < anotherfile example% figlet -cf slant Finally, if you want to have FIGlet take the input from the command line instead of a file: example% figlet Hello world Other Things to Try On many systems nice effects can be obtained from the lean font by piping it through tr. Some you might want to try are the following: example% figlet -f lean | tr ' _/' ' ()' example% figlet -f lean | tr ' _/' './\\' example% figlet -f lean | tr ' _/' ' //' example% figlet -f lean | tr ' _/' '/ ' Similar things can be done with the block font and many of the other FIGlet fonts. COMPRESSED FONTS You can compress the fonts and controlfiles using the zip archiving pro‐ gram. Place only one font or controlfile in each archive, and rename the archive file (which will have a name ending in .zip) back to .flf or .flc as the case may be. If you don't rename the file appropriately, FIGlet won't be able to find it. FIGlet does not care what the filename within the .zip archive is, and will process only the first file. The .zip format was chosen because tools to create and manipulate it are widely available for free on many platforms. THE STANDARD FONTS Here are a few notes about some of the fonts provided with FIGlet. You can get many other font from the Web site http://www.figlet.org/ This location should also contain the latest version of FIGlet and other related utilities. The font standard is the basic FIGlet font, used when no other font is specified. (This default can be changed when FIGlet is compiled on your system.) The controlfiles 8859-2, 8859-3, 8859-4, and 8859-9 are pro‐ vided for interpreting those character sets, also known as ISO Latin-2 through Latin-5 respectively. The character set 8859-1 (ISO Latin-1) is FIGlet's default and requires no special controlfile. Closely related are the fonts slant, shadow, small, smslant (both small and slanted), smshadow, (both small and shadowed), and big. These fonts support only Latin-1, except that big supports Greek FIGcharacters as well; the controlfiles frango (for Greek text written in Latin charac‐ ters, so-called ``frangovlakhika''), and 8859-7 (for mixed Latin/Greek text) are provided. The ivrit font is a right-to-left font including both Latin and Hebrew FIGcharacters; the Latin characters are those of the standard font. The available controlfiles are ilhebrew, which maps the letters you get by typing on a U.S. keyboard as if it were a Hebrew keyboard; ushebrew, which makes a reasonable mapping from Latin letters to Hebrew ones; and 8859-8, which supports mixed Latin/Hebrew text. Warning: FIGlet doesn't support bidirectional text, so everything will come out right-to-left, even Latin letters. The fonts terminal, digital, and bubble output the input character with some decoration around it (or no decoration, in the case of terminal). The characters coded 128 to 159, which have varying interpretations, are output as-is. You can use the appropriate controlfiles to process Latin-2, Latin-3, or Latin-4 (but not Latin-5) text, provided your output device has screen or printer fonts that are appropriate for these charac‐ ter sets. Two script fonts are available: script, which is larger than standard, and smscript, which is smaller. The font lean is made up solely of `/' and `_' sub-characters; block is a straight (non-leaning) version of it. The font mini is very small, and especially suitable for e-mail signa‐ tures. The font banner looks like the output of the banner program; it is a cap‐ itals and small capitals font that doesn't support the ISO Latin-1 exten‐ sions to plain ASCII. It does, however, support the Japanese katakana syllabary; the controlfile uskata maps the upper-case and lower-case Latin letters into the 48 basic katakana characters, and the controlfile jis0201 handles JIS 0201X (JIS-Roman) mixed Latin and katakana text. Furthermore, the banner font also supports Cyrillic (Russian) FIGcharac‐ ters; the controlfile 8859-5 supports mixed Latin and Cyrillic text, the controlfile koi8r supports the popular KOI8-R mapping of mixed text, and the controlfile moscow supports a sensible mapping from Latin to Cyril‐ lic, compatible with the moscow font (not supplied). The fonts mnemonic and safemnem support the mnemonic character set docu‐ mented in RFC 1345. They implement a large subset of Unicode (over 1800 characters) very crudely, using ASCII-based mnemonic sequences, and are good for getting a quick look at UTF-8 unicode files, using the con‐ trolfile utf8. ENVIRONMENT FIGLET_FONTDIR If $FIGLET_FONTDIR is set, its value is used as a path to search for font files. FILES file.flf FIGlet font file file.flc FIGlet control file DIAGNOSTICS FIGlet's diagnostics are intended to be self-explanatory. Possible mes‐ sages are Usage: ... Out of memory Unable to open font file Not a FIGlet 2 font file Unable to open control file Not a FIGlet 2 control file "-t" is disabled, since ioctl is not fully implemented. This last message is printed when the -t option is given, but the operat‐ ing system in use does not include the system call FIGlet uses to deter‐ mine the terminal width. FIGlet also prints an explanatory message if the -F option is given on the command line. The earlier version of FIGlet, version 2.0, listed the available fonts when the -F option was given. This option has been removed from FIGlet 2.1. It has been replaced by the figlist script, which is part of the standard FIGlet package. ORIGIN ``FIGlet'' stands for ``Frank, Ian and Glenn's LETters''. Inspired by Frank's .sig, Glenn wrote (most of) it, and Ian helped. Most of the standard FIGlet fonts were inspired by signatures on various UseNet articles. Since typically hundreds of people use the same style of letters in their signatures, it was often not deemed necessary to give credit to any one font designer. BUGS Very little error checking is done on font and control files. While FIGlet tries to be forgiving of errors, and should (hopefully) never actually crash, using an improperly-formatted file with FIGlet will pro‐ duce unpredictable output. FIGlet does not handle format characters in a very intelligent way. A tab character is converted to a blank, and vertical-tab, form-feed and carriage-return are each converted to a newline. On many systems, tabs can be handled better by piping files through expand before piping through FIGlet. FIGlet output is quite ugly if it is displayed in a proportionally-spaced font. I suppose this is to be expected. Please report any errors you find in this man page or the program to<EMAIL_ADDRESS>WEBSITE AND MAILING LIST You can get many fonts which are not in the basic FIGlet package from the Web site http://www.figlet.org/ It should also contain the latest ver‐ sion of FIGlet and other utilities related to FIGlet. There is a mailing list for FIGlet for general discussions about FIGlet and a place where you can ask questions or share ideas with other FIGlet users. It is also the place where we will publish news about new fonts, new software updates etc. To subscribe or unsubscribe from the FIGlet mailing list, please send email to<EMAIL_ADDRESS>or<EMAIL_ADDRESS>or visit the following web page: http://www.figlet.org/mail‐ man/listinfo/figlet AUTHORS Glenn Chappell did most of the work. You can e-mail him but he is not an e-mail fanatic; people who e-mail Glenn will probably get answers, but if you e-mail his best friend: Ian Chai, who is an e-mail fanatic, you'll get answers, endless conversa‐ tion about the mysteries of life, invitations to join some 473 mailing lists and a free toaster. (Well, ok, maybe not the free toaster.) Frank inspired this whole project with his .sig, but don't e-mail him; he's decidedly an un-e-mail-fanatic. Gilbert "The Mad Programmer" Healton added the -A option for version 2.1.1. This option specified input from the command line; it is still allowed, but has no effect. John Cowan added the -o, -s, -k, -S, and -W options, and the support for Unicode mapping tables, ISO 2022/HZ/Shift-JIS/UTF-8 input, and compressed fonts and control files. He also revised this documentation, with a lot of input from Paul Burton. Claudio Matsuoka added the support for .tlf files for version 2.2.4 and performs random hacks and bugfixes. As a fan of FIGlet, Christiaan Keet revised the official FIGlet documen‐ tation and set up the new FIGlet website at http://www.figlet.org/ (and the corresponding ftp://ftp.figlet.org/pub/figlet/) SEE ALSO figlist(6), chkfont(6), showfigfonts(6), toilet(1) v2.2.5 31 May 2012 FIGLET(6)


This is my first webpage
This is my first paragraph
The languages i am going to study:
Java
HTML
Angular


BOYS DON'T CRY (Fox Searchlight) Starring: Hilary Swank, Chloe Sevigny, Peter Sarsgaard, Brendan Sexton III, Alison Folland, Alicia Goranson. Screenplay: Kimberly Peirce and Andy Bienen. Producers: Jeffrey Sharp, John Hart, Eva Kolodner and Christine Vachon. Director: Kimberly Peirce.  Reviewed by Scott Renshaw.
It took five months for BOYS DON'T CRY finally to make its way to Utah. Five months of bumped release dates (at least partially due to an attitude, voiced by an unnamed Fox Searchlight representative, that "gay films don't play there"). Five months of growing hype over the remarkable transformation in the performance of Hilary Swank, who became a Best Actress nominee as expected. Five months of building expectations for one of the best-received independent films of the year, based on a compelling true story. And after five months, plenty of opportunity for the film itself to fall dangerously short of everything I wanted it to be.
BOYS DON'T CRY is not a great piece of film craftsmanship. It's a performance showcase, and a very effective one. The surprise, however, is that the real showcase performance isn't the most talked-about one. Swank stars as Teena Brandon, a native of Lincoln, Nebraska whose sexual identity has always been a source of trouble for her. After numerous run-ins with the law and fellow residents outraged by her behavior, Teena flees Lincoln for the small town of Falls City. There she re-invents herself as Brandon Teena, a young man travelling through town who falls in with a group of aimless young people, including ex-cons John Lotter (Peter Sarsgaard) and Tom Nissen (Brendan Sexton III) and John's sort-of-girlfriend Lana Tisdel (Chloe Sevigny). Brandon instantly becomes attracted to Lana, and finds her receptive to his interest. But secrets have a way of coming out, and when they do, Brandon faces dangerous repercussions.
At the center of the story, of course, is the mystery of Brandon/Teena -- who he was, how so many people were fooled, what Brandon's transformation represented as both threat and promise to the other people involved in the story. Swank's physical performance is superb, made even more effective by co-writer/director Kimberly Peirce's decision to introduce Brandon already in male guise so the switch doesn't become a showy trick. But it's hard not to be more impressed with the physical performance than with what's going underneath it. There are moments when you see the awkwardness of a girl trying to be one of the guys, and moments in the harrowing final half hour when you see her peering in terror through the cracks in her reality. More often, Brandon is an enigmatic catalyst. It seems as though Peirce is more interested in what Brandon stands for than in the person that was Brandon Teena.
The upside to that perspective is that one of those people is Lana, played with unnerving effectiveness by Chloe Sevigny. Lana is in her way a more fascinating character than Brandon -- she engages in just as much self-delusion, but her motivations are more complex. Sevigny plays the small town girl with a dissolute resignation that gradually becomes faint hope for a better life. It's the sort of role most actresses would play initially with hard-edged bluster before unveiling the heart of gold beneath; Sevigny shows a slightly different perspective of Lana every time she turns around.
Sevigny is part of a superb supporting cast, with Sarsgaard and Sexton similarly refusing to play their parts for easy interpretation. The entire milieu of the Falls City youth has a heartbreaking genuineness to it -- particularly noteworthy is how Lana's mother becomes "Mom" to everyone in their desperation for any family relationship -- and Peirce does a fine job of using Brandon to explore the effect of a nonconformist on a place where reality is assumed to be static. It's the idea that Peirce uses Brandon at all that dampens the power of BOYS DON'T CRY, however. The chilling resolution and wonderful supporting performances make it easy to recommend BOYS DON'T CRY. I only wish that five months of focus on Hilary Swank hadn't led me to expect it would be the story of Brandon Teena.
On the Renshaw scale of 0 to 10 gender blenders: 7.
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Entertain Yourself
There are several different web platforms over which people do so. Each platform has a different perceptions all over the world. For example, Facebook is used at a more informal level to stay connected and updated with friends and acquaintances. People post status updates, life events, pictures of events and other things you’d want to talk about with friends and family.
LinkedIn is a social media platforms for professionals, professional organizations and those looking to enter a profession/career. It has a lot of functionality poised towards helping you network, develop professional skills and explore hidden professional opportunities for jobs and careers. It’s free, a means for you to stay connected with former colleagues, stay updated with industry specific news and LinkedIn is used by recruiters to access the hidden job market.
Social Media is a very powerful tool when used properly. It is your personal footprint that you leave on the internet. Everything that you do on the internet leaves a footprint. Hence, you need to be careful with what you put on it.
Word of Caution:
Social Media is a place where anyone can look up and find out about anyone. Therefore, you must be careful as to what information you put on it. Social media platforms are a very powerful tool and can be a big liability if not used properly. What goes on the internet stays on there forever in the form of data somewhere.
With informal platforms like facebook, what you put on there is publically available for anyone and everyone. Hence, your private information (passwords, credit card details, etc) must never be shared over the same.