Goal: Continue practicing the web design process and familiarizing yourself with Sketch, while also integrating new concepts from last night’s homework into your project.
Warm Up
- What's the difference between a vector image and a raster image? Why do web designers and front end developers often use vectors?
- Revisit the Sketch Shortcuts and Workflow lesson and review available shortcuts. Do you see any you can use to save time today? Discuss. Keep this information handy while you work in Sketch. If you find yourself continually digging deep into a menu, or performing a seemingly-complex series of clicks, check if there's a shortcut!
- What did you think about the Design Thinking lesson in last night's homework? How will you and your partner include aspects of empathic design in this project?
Design
Learn How to Program Makeover (3-Day Project)
Redesign this site you're reading right now; LearnHowToProgram.com! Do you think a more classic "textbook" feel would be more functional and appealing? What about something more modern and sleek? How would you make it easier to navigate? Should it be more richly-featured? More minimal?
Steps
Here is the workflow you will follow to adhere to best practices of The Web Design Process, Mobile-First Design, and Design Thinking simultaneously:
- Target User Personas and Stories. Take time and care at this step! As a student at Epicodus, you're in the target audience for this site. This puts you in a unique position to better understand users' needs, and how they use the interface. But don't forget to consider other types of users too! Identify the application's target audience, and all user personas. Record a full list of user stories in your README before advancing.
- Sketches: Using your user stories as a guide, begin sketching. Create mobile versions of each planned view first, following mobile-first design. Experiment, try different approaches and layouts, discuss thoroughly with your partner, and tweak and rework as necessary. Remember, you should have a fairly finalized layout on paper before wireframing. When you've completed mobile sketches, move on to their desktop equivalents. Then add photographs of paper sketches you're using in the final project to your project repository and README.
- Wireframes: After both mobile and desktop sketches are finalized, create higher-fidelity digital versions of each in Sketch software. Collaborate with your partner to make decisions about interface details that weren't finalized in the sketches (colors, fonts, etc.) Add both mobile and desktop wireframes to your project repository and README.
- Prototypes: Then you'll create both mobile and desktop prototypes of your design. Consider how the application will move and respond. Consider navigation; how does . Tweak and experiment as necessary, until you have a prototype you feel confident with. But don't worry about this yet, we'll cover prototyping in Wednesday's homework!
- Coding: Finalized prototype in hand, you can begin coding an actual site that reflects the design created in your sketches, wireframes, and prototypes!
- Further Exploration: If you complete all steps above before the end of Thursday, restart steps for Admin areas described below. Remember, user stories and personas for admins of the site will likely differ from standard users.


Entries and values
AddService=ServiceName,[flags],service-install-section...
See also the Glossary entry for [DDInstall.Services].


Python Basics, Eratosthenes and Problem 51
At university, I mostly used two programming languages: C and Matlab.
The former was mostly for the first two years and the norm for math
courses, the latter would be much more to the students’ taste, since
it is in a higher level, i.e., easier to work with. From my experience
a hundred-line code in Matlab would easily be more than a thousand
lines in C and that really makes a difference when it comes making
things work first and, only later, worrying about optimization. And
that’s exactly Python’s
For Machine and Deep Learning, the most widely used language is a
seemingly never-ending debate between Python and R. The latter is a
statistical more old school language, an inheritance of a prior
language, S
After deciding what language to focus on, I looked for a systematic
way of adapting my knowledge of other languages to the new one and
also learning its unique properties. And what better way than doing a
course…
Anyway, you can find the notes I’ve taken throughout the course in
This problem comes from a site called Project Euler, which aims at stimulating the practice of programming and mathematics. In it, you will find hundreds of challenging problems that require creativity, logic and a basic (usually) amount of programming.
After looking for a challenge that I could code in one or two days, I bumped into this peculiar problem of replacing digits — it’s actually not really unusual, most of the basic problems there deal with manipulating primes. It goes like this:
By replacing the 1st digit of the 2-digit number *3, it turns out that six of the nine possible values: 13, 23, 43, 53, 73, and 83, are all prime.
By replacing the 3rd and 4th digits of 56**3 with the same digit, this 5-digit number is the first example having seven primes among the ten generated numbers, yielding the family: 56003, 56113, 56333, 56443, 56663, 56773, and 56993. Consequently 56003, being the first member of this family, is the smallest prime with this property.
Find the smallest prime which, by replacing part of the number (not necessarily adjacent digits) with the same digit, is part of an eight prime value family.
 So when I was faced with this problem, my thought was process was to just make a brute force search. The idea would be to simply find all the possible combinations of digits to be replaced, check if the numbers were primes and see if the family size is bigger than 7. Let’s see if it works…
After having the primes, we can finally tackle the problem itself. I chose to first create a list with all the possible combinations of n digits, apply them to the prime being checked and see if it generates a big enough family. So, for example, if the algorithm is checking numbers with 5 digits, it will have to go through:
\[C_{5,5} + C_{5,4} + C_{5,3} + C_{5,2} + C_{5,1} = 1 + 5 + 10 + 10 + 5 = 31\]
I chose to store the combinatios in a list and make the number being
checked a dictionary
comb = []
for L in range(1, len(indexy)):
for subset in itertools.combinations(indexy, L):
comb.append(subset)
comb_list = [list(i) for i in comb]
prime_collection = []
new_numb_dict = {a:b for a,b in
zip(dict_of_number.keys(),
dict_of_number.values())}
This is, admittedly, very dumb. Many combinations will be checked repeatedly, but I had made a decision to have something working first rather than optimizing something I wasn’t sure would work. Now, we go to the main part of the code; we need to replace the digits in the combinations, check if they’re prime and, if so, add them to the family, which will be checked for its size in the end:
for i in range(0,len(comb_list)):
prime_collection = []
# Replacing the numbers according to the combinations
for j in range(0,10):
for k in comb_list[i]:
new_numb_dict[k] = j
# Transform into number
list_new_numb = [i for i in new_numb_dict.values()]
new_numb = int("".join(map(str,list_new_numb)))
# Check if prime
# Need to exclude numbers with leading '0'
if new_numb in primes_N and len(str(new_numb)) == len(str(n)):
prime_collection.append(new_numb)
new_numb_dict = {a:b for a,b in
zip(dict_of_number.keys(),
dict_of_number.values())}
# Need to include the original number and exclude copies
prime_collection = list(set(prime_collection))
# Length of the prime collection searched
if len(prime_collection) >= len_51:
print('\n',n)
print(comb_list)
print(comb_list[i])
print(prime_collection)
return
print("Sad! No numbers found to solve the problem!")
Checking all of the combinations grows very fast as the number of digits increase, thus, even though it takes less than expected, the amount of time needed to find it is a bit absurd compared to solutions mathematicians would come up with: an hour. And that is without computing the primes first. After trying to run the sieve for primes up to 1,000,000 — you need primes up to 10x if you want to work with x digits — and watching my computer almost melt, I chose to download a pre-calculated list on the internet.
It was quite the challenge to solve this problem, not really due to the mathematical difficulty but to my struggles with the language, since I was still too much of a beginner; if you want to check out my complete code, you can go to this Github Repo. And if you would like to see a more optimized and sophisticated approach that only takes 0.25s to find the answer, check this post from the Dreamshire’s blog.
First, we need a way of generating primes. And probably the most efficient way — there are some formulas to get families of primes but they only work for a restricted amount of them — to do it is with the Sieve of Eratosthenes, an ingenious algorithm invented in Ancient Greece by Eratosthenes of Cyrene — he is best known for being the first person to calculate the circumference of the Earth. Essentially, you’re going to use the prime found to sieve out all of its multiples. For example, we first scratch out all of the multiples of 2, then of 3, then of 5, and so on. Naturally, the only numbers left will be primes.
Two classic improvements have also been added to our code: firstly,
you need only to check numbers above and including the square of the
prime being checked, because the numbers below it will either have
been already scratched out by prior primes or are primes; and,
secondly, you only need to check multiples of numbers up to the root
of the biggest number in the list, since the ones above it will be
checked during the algorithm
The core part of the code is very simple, it would look like this in Python:
for j in range(i**2,N+1,i):
try:
numbers.remove(j)
except:
continue


Elton John & Bernie Taupin
50 Years of Music
The power of collaboration can be seen in the 50 year partnership between Elton John and Bernie Taupin.
While Taupin has preferred to stay mostly out of the public eye, John has always acknowledged that without Taupin there very well may not have been Elton John. A chance connection in the late '60s brought the duo together and the magic combination of John's poignant chords and engaging performing along with Taupin's lyrical and relatable storytelling continue to capture fans' hearts. Some of their most-loved hits include:
- Goodbye Yellow Brick Road
- Rocket Man
- Tiny Dancer
- Candle in the Wind
- Daniel
- Your Song
- I'm Still Standing
And so many more. Read more about their inspiring working relationship on Wikipedia.


Join our talents this ramadan and win amazing prizes!
Duration
The competition will start on 08-06-2017 and end on 20-06-2017.
Rules
Every streamer and user will automatically join
the competition 08-06-2017.
Winner will be based upon number of special
Ramadan animated gift sent and received.
1 animated gift sent will be counted as 1 point
on the ranking board.
Any gift sent after 20-06-2017. will
not be counted by the system for this
competition.
Other regular gifts sent to any streamer by any
user will not be counted for this competition
Winners will be announced
on 21-06-2017.
Rewards
Top 3 Streamers on the ranking board as per 20-06-2017 will be given:
- Huawei Smartphone.
- Oppo Smartphone.
- Wireless Bluetooth mini-speaker.
- Super VIP access, slider photo on the homescreen of Streamer application and 50,000 free coins.
- Super VIP access and 25,000 free coins.
- Super VIP access


gdalwarp
Image reprojection and warping utility
Synopsis
gdalwarp [--help-general] [--formats]
[-b|-srcband n]* [-dstband n]*
[-s_srs srs_def] [-t_srs srs_def] [-ct string]
[-to "NAME=VALUE"]* [-vshift | -novshift]
[[-s_coord_epoch epoch] | [-t_coord_epoch epoch]]
[-order n | -tps | -rpc | -geoloc] [-et err_threshold]
[-refine_gcps tolerance [minimum_gcps]]
[-te xmin ymin xmax ymax] [-te_srs srs_def]
[-tr xres yres]|[-tr square] [-tap] [-ts width height]
[-ovr level|AUTO|AUTO-n|NONE] [-wo "NAME=VALUE"] [-ot Byte/Int16/...] [-wt Byte/Int16]
[-srcnodata "value [value...]"] [-dstnodata "value [value...]"]
[-srcalpha|-nosrcalpha] [-dstalpha]
[-r resampling_method] [-wm memory_in_mb] [-multi] [-q]
[-cutline datasource] [-cl layer] [-cwhere expression]
[-csql statement] [-cblend dist_in_pixels] [-crop_to_cutline]
[-if format]* [-of format] [-co "NAME=VALUE"]* [-overwrite]
[-nomd] [-cvmd meta_conflict_value] [-setci] [-oo NAME=VALUE]*
[-doo NAME=VALUE]*
srcfile* dstfile
Description
The gdalwarp utility is an image mosaicing, reprojection and warping utility. The program can reproject to any supported projection, and can also apply GCPs stored with the image if the image is "raw" with control information.
- -b <n>
- -srcband <n>
New in version 3.7.
Specify an input band number to warp (between 1 and the number of bands of the source dataset).
This option is used to warp a subset of the input bands. All input bands are used when it is not specified.
This option may be repeated multiple times to select several input bands. The order in which bands are specified will be the order in which they appear in the output dataset (unless
-dstband
is specified).The alpha band should not be specified in the list, as it will be automatically retrieved (unless
-nosrcalpha
is specified).The following invocation will warp an input datasets with bands ordered as Blue, Green, Red, NearInfraRed in an output dataset with bands ordered as Red, Green, Blue.
gdalwarp in_bgrn.tif out_rgb.tif -b 3 -b 2 -b 1 -overwrite
- -dstband <n>
New in version 3.7.
Specify the output band number in which to warp. In practice, this option is only useful when updating an existing dataset, e.g to warp one band at at time.
gdal_create -if in_red.tif -bands 3 out_rgb.tif gdalwarp in_red.tif out_rgb.tif -srcband 1 -dstband 1 gdalwarp in_green.tif out_rgb.tif -srcband 1 -dstband 2 gdalwarp in_blue.tif out_rgb.tif -srcband 1 -dstband 3
If
-srcband
is specified, there must be as many occurrences of-dstband
as there are of-srcband
.The output alpha band should not be specified, as it will be automatically created if the input dataset has an alpha band, or if
-dstalpha
is specified.If
-dstband
is not specified, then-dstband 1 -dstband 2 ... -dstband N
is assumed where N is the number of input bands (specified explicitly either with-srcband
or implicitly)
- -s_srs <srs def>
Set source spatial reference. If not specified the SRS found in the input dataset will be used.
The coordinate reference systems that can be passed are anything supported by the OGRSpatialReference.SetFromUserInput() call, which includes EPSG Projected, Geographic or Compound CRS (i.e. EPSG:4296), a well known text (WKT) CRS definition, PROJ.4 declarations, or the name of a .prj file containing a WKT CRS definition.
Starting with GDAL 2.2, if the SRS has an explicit vertical datum that points to a PROJ.4 geoidgrids, and the input dataset is a single band dataset, a vertical correction will be applied to the values of the dataset.
- -s_coord_epoch <epoch>
New in version 3.4.
Assign a coordinate epoch, linked with the source SRS. Useful when the source SRS is a dynamic CRS. Only taken into account if
-s_srs
is used.Currently
-s_coord_epoch
and-t_coord_epoch
are mutually exclusive, due to lack of support for transformations between two dynamic CRS.
- -t_srs <srs_def>
Set target spatial reference.
A source SRS must be available for reprojection to occur. The source SRS will be by default the one found in the input dataset when it is available, or as overridden by the user with
-s_srs
The coordinate reference systems that can be passed are anything supported by the OGRSpatialReference.SetFromUserInput() call, which includes EPSG Projected, Geographic or Compound CRS (i.e. EPSG:4296), a well known text (WKT) CRS definition, PROJ.4 declarations, or the name of a .prj file containing a WKT CRS definition.
Starting with GDAL 2.2, if the SRS has an explicit vertical datum that points to a PROJ.4 geoidgrids, and the input dataset is a single band dataset, a vertical correction will be applied to the values of the dataset.
- -t_coord_epoch <epoch>
New in version 3.4.
Assign a coordinate epoch, linked with the target SRS. Useful when the target SRS is a dynamic CRS. Only taken into account if
-t_srs
is used.Currently
-s_coord_epoch
and-t_coord_epoch
are mutually exclusive, due to lack of support for transformations between two dynamic CRS.
- -ct <string>
A PROJ string (single step operation or multiple step string starting with +proj=pipeline), a WKT2 string describing a CoordinateOperation, or a urn:ogc:def:coordinateOperation:EPSG::XXXX URN overriding the default transformation from the source to the target CRS. It must take into account the axis order of the source and target CRS. When creating a new output file, using
-t_srs
is still necessary to have the target CRS written in the metadata of the output file, but the parameters of the CoordinateOperation will override those of the standard transformation.New in version 3.0.
- -to <NAME=VALUE>
Set a transformer option suitable to pass to
GDALCreateGenImgProjTransformer2()
. SeeGDALCreateRPCTransformerV2()
for RPC specific options.
- -vshift
Force the use of vertical shift. This option is generally not necessary, except when using an explicit coordinate transformation (
-ct
), and not specifying an explicit source and target SRS.New in version 3.4.
- -novshift
Disable the use of vertical shift when one of the source or target SRS has an explicit vertical datum, and the input dataset is a single band dataset.
Note
this option was named
-novshiftgrid
in GDAL 2.2 to 3.3.New in version 3.4.
- -order <n>
order of polynomial used for warping (1 to 3). The default is to select a polynomial order based on the number of GCPs.
- -tps
Force use of thin plate spline transformer based on available GCPs.
- -rpc
Force use of RPCs.
- -geoloc
Force use of Geolocation Arrays.
- -et <err_threshold>
Error threshold for transformation approximation (in pixel units - defaults to 0.125, unless, starting with GDAL 2.1, the RPC_DEM transformer option is specified, in which case, an exact transformer, i.e. err_threshold=0, will be used).
- -refine_gcps <tolerance minimum_gcps>
Refines the GCPs by automatically eliminating outliers. Outliers will be eliminated until minimum_gcps are left or when no outliers can be detected. The tolerance is passed to adjust when a GCP will be eliminated. Not that GCP refinement only works with polynomial interpolation. The tolerance is in pixel units if no projection is available, otherwise it is in SRS units. If minimum_gcps is not provided, the minimum GCPs according to the polynomial model is used.
- -te <xmin ymin xmax ymax>
Set georeferenced extents of output file to be created (in target SRS by default, or in the SRS specified with
-te_srs
)
- -te_srs <srs_def>
Specifies the SRS in which to interpret the coordinates given with -te. The <srs_def> may be any of the usual GDAL/OGR forms, complete WKT, PROJ.4, EPSG:n or a file containing the WKT. This must not be confused with -t_srs which is the target SRS of the output dataset.
-te_srs
is a convenience e.g. when knowing the output coordinates in a geodetic long/lat SRS, but still wanting a result in a projected coordinate system.
- -tr <xres> <yres> | -tr square
Set output file resolution (in target georeferenced units).
If not specified (or not deduced from -te and -ts), gdalwarp will, in the general case, generate an output raster with xres=yres.
Starting with GDAL 3.7, if neither
-tr
nor-ts
are specified, that no reprojection is involved (including taking into account geolocation arrays or RPC), the resolution of the source file(s) will be preserved (in previous version, an output raster with xres=yres was always generated). It is possible to ask square pixels to still be generated, by specifyingsquare
as the value for-tr
.
- -tap
(target aligned pixels) align the coordinates of the extent of the output file to the values of the
-tr
, such that the aligned extent includes the minimum extent (edges lines/columns that are detected as blank, before actual warping, will be removed starting with GDAL 3.8). Alignment means that xmin / resx, ymin / resy, xmax / resx and ymax / resy are integer values.
- -ts <width> <height>
Set output file size in pixels and lines. If width or height is set to 0, the other dimension will be guessed from the computed resolution. Note that
-ts
cannot be used with-tr
- -ovr <level|AUTO|AUTO-n|NONE>
To specify which overview level of source files must be used. The default choice, AUTO, will select the overview level whose resolution is the closest to the target resolution. Specify an integer value (0-based, i.e. 0=1st overview level) to select a particular level. Specify AUTO-n where n is an integer greater or equal to 1, to select an overview level below the AUTO one. Or specify NONE to force the base resolution to be used (can be useful if overviews have been generated with a low quality resampling method, and the warping is done using a higher quality resampling method).
- -wo `"NAME=VALUE"`
Set a warp option. The
GDALWarpOptions::papszWarpOptions
docs show all options. Multiple-wo
options may be listed.
- -ot <type>
Force the output image bands to have a specific data type supported by the driver, which may be one of the following:
Byte
,Int8
,UInt16
,Int16
,UInt32
,Int32
,UInt64
,Int64
,Float32
,Float64
,CInt16
,CInt32
,CFloat32
orCFloat64
.
- -wt <type>
Working pixel data type. The data type of pixels in the source image and destination image buffers.
- -r <resampling_method>
Resampling method to use. Available methods are:
near
: nearest neighbour resampling (default, fastest algorithm, worst interpolation quality).bilinear
: bilinear resampling.cubic
: cubic resampling.cubicspline
: cubic spline resampling.lanczos
: Lanczos windowed sinc resampling.average
: average resampling, computes the weighted average of all non-NODATA contributing pixels.rms
root mean square / quadratic mean of all non-NODATA contributing pixels (GDAL >= 3.3)mode
: mode resampling, selects the value which appears most often of all the sampled points. In the case of ties, the first value identified as the mode will be selected.max
: maximum resampling, selects the maximum value from all non-NODATA contributing pixels.min
: minimum resampling, selects the minimum value from all non-NODATA contributing pixels.med
: median resampling, selects the median value of all non-NODATA contributing pixels.q1
: first quartile resampling, selects the first quartile value of all non-NODATA contributing pixels.q3
: third quartile resampling, selects the third quartile value of all non-NODATA contributing pixels.sum
: compute the weighted sum of all non-NODATA contributing pixels (since GDAL 3.1)Note
When downsampling is performed (use of
-tr
or-ts
), existing overviews (either internal/implicit or external ones) on the source image will be used by default by selecting the closest overview to the desired output resolution. The resampling method used to create those overviews is generally not the one you specify through the-r
option. Some formats, like JPEG2000, can contain significant outliers due to wavelet compression works. It might thus be useful in those situations to use the-ovr
NONE
option to prevent existing overviews to be used.
- -srcnodata <value [value...]>
Set nodata masking values for input bands (different values can be supplied for each band). If more than one value is supplied all values should be quoted to keep them together as a single operating system argument. Masked values will not be used in interpolation (details given in Nodata / source validity mask handling)
Use a value of
None
to ignore intrinsic nodata settings on the source dataset.When this option is set to a non-
None
value, it causes theUNIFIED_SRC_NODATA
warping option (seeGDALWarpOptions::papszWarpOptions
) to be set toYES
, if it is not explicitly set.If
-srcnodata
is not explicitly set, but the source dataset has nodata values, they will be taken into account, withUNIFIED_SRC_NODATA
atPARTIAL
by default.
- -dstnodata <value [value...]>
Set nodata values for output bands (different values can be supplied for each band). If more than one value is supplied all values should be quoted to keep them together as a single operating system argument. New files will be initialized to this value and if possible the nodata value will be recorded in the output file. Use a value of
None
to ensure that nodata is not defined. If this argument is not used then nodata values will be copied from the source dataset.
- -srcalpha
Force the last band of a source image to be considered as a source alpha band.
- -nosrcalpha
Prevent the alpha band of a source image to be considered as such (it will be warped as a regular band)
New in version 2.2.
- -dstalpha
Create an output alpha band to identify nodata (unset/transparent) pixels.
- -wm <memory_in_mb>
Set the amount of memory that the warp API is allowed to use for caching. The value is interpreted as being in megabytes if the value is less than 10000. For values >=10000, this is interpreted as bytes.
The warper will total up the memory required to hold the input and output image arrays and any auxiliary masking arrays and if they are larger than the "warp memory" allowed it will subdivide the chunk into smaller chunks and try again.
If the -wm value is very small there is some extra overhead in doing many small chunks so setting it larger is better but it is a matter of diminishing returns.
- -multi
Use multithreaded warping implementation. Two threads will be used to process chunks of image and perform input/output operation simultaneously. Note that computation is not multithreaded itself. To do that, you can use the
-wo
NUM_THREADS=val/ALL_CPUS option, which can be combined with-multi
- -q
Be quiet.
- -if <format>
Format/driver name to be attempted to open the input file(s). It is generally not necessary to specify it, but it can be used to skip automatic driver detection, when it fails to select the appropriate driver. This option can be repeated several times to specify several candidate drivers.
New in version 3.2.
- -of <format>
Select the output format. Starting with GDAL 2.3, if not specified, the format is guessed from the extension (previously was GTiff). Use the short format name.
- -co <NAME=VALUE>
Many formats have one or more optional creation options that can be used to control particulars about the file created. For instance, the GeoTIFF driver supports creation options to control compression, and whether the file should be tiled.
The creation options available vary by format driver, and some simple formats have no creation options at all. A list of options supported for a format can be listed with the --formats command line option but the documentation for the format is the definitive source of information on driver creation options. See Raster drivers format specific documentation for legal creation options for each format.
- -cutline <datasource>
Enable use of a blend cutline from the name OGR support datasource.
- -cl <layername>
Select the named layer from the cutline datasource.
- -cwhere <expression>
Restrict desired cutline features based on attribute query.
- -cblend <distance>
Set a blend distance to use to blend over cutlines (in pixels).
- -crop_to_cutline
Crop the extent of the target dataset to the extent of the cutline.
- -overwrite
Overwrite the target dataset if it already exists. Overwriting must be understood here as deleting and recreating the file from scratch. Note that if this option is not specified and the output file already exists, it will be updated in place.
- -nomd
Do not copy metadata. Without this option, dataset and band metadata (as well as some band information) will be copied from the first source dataset. Items that differ between source datasets will be set to * (see
-cvmd
option).
- -cvmd <meta_conflict_value>
Value to set metadata items that conflict between source datasets (default is "*"). Use "" to remove conflicting items.
- -setci
Set the color interpretation of the bands of the target dataset from the source dataset.
- -oo <NAME=VALUE>
Dataset open option (format specific)
- -doo <NAME=VALUE>
Output dataset open option (format specific)
New in version 2.1.
- <srcfile>
The source file name(s).
- <dstfile>
The destination file name.
Mosaicing into an existing output file is supported if the output file already exists. The spatial extent of the existing file will not be modified to accommodate new data, so you may have to remove it in that case, or use the -overwrite option.
Polygon cutlines may be used as a mask to restrict the area of the destination file that may be updated, including blending. If the OGR layer containing the cutline features has no explicit SRS, the cutline features must be in the SRS of the destination file. When writing to a not yet existing target dataset, its extent will be the one of the original raster unless -te or -crop_to_cutline are specified.
Starting with GDAL 3.1, it is possible to use as output format a driver that only supports the CreateCopy operation. This may internally imply creation of a temporary file.
Nodata / source validity mask handling
Invalid values in source pixels, either identified through a nodata value
metadata set on the source band, a mask band, an alpha band or the use of
-srcnodata
will not be used in interpolation.
The details of how it is taken into account depends on the resampling kernel:
for nearest resampling, for each target pixel, the coordinate of its center is projected back to source coordinates and the source pixel containing that coordinate is identified. If this source pixel is invalid, the target pixel is considered as nodata.
for bilinear, cubic, cubicspline and lanczos, for each target pixel, the coordinate of its center is projected back to source coordinates and a corresponding source pixel is identified. If this source pixel is invalid, the target pixel is considered as nodata. Given that those resampling kernels have a non-null kernel radius, this source pixel is just one among other several source pixels, and it might be possible that there are invalid values in those other contributing source pixels. The weights used to take into account those invalid values will be set to zero to ignore them.
for the other resampling methods, source pixels contributing to the target pixel are ignored if invalid. Only the valid ones are taken into account. If there are none, the target pixel is considered as nodata.
If using -srcnodata
for multiple images with different invalid
values, you need to either (a) pre-process them to have the same to-be-ignored
value, or (b) set the nodata flag for each file. Use (b) if you need to preserve
the original values for some reason, for example:
# for this image we want to ignore black (0)
gdalwarp -srcnodata 0 -dstnodata 0 orig-ignore-black.tif black-nodata.tif
# and now we want to ignore white (0)
gdalwarp -srcnodata 255 -dstnodata 255 orig-ignore-white.tif white-nodata.tif
# and finally ignore a particular blue-grey (RGB 125 125 150)
gdalwarp -srcnodata "125 125 150" -dstnodata "125 125 150" orig-ignore-grey.tif grey-nodata.tif
# now we can mosaic them all and not worry about nodata parameters
gdalwarp black-nodata.tif grey-nodata.tif white-nodata.tif final-mosaic.tif
Approximate transformation
By default gdalwarp uses a linear approximator for the transformations with a permitted error of 0.125 pixels. The approximator basically transforms three points on a scanline: the start, end and middle. Then it compares the linear approximation of the center based on the end points to the real thing and checks the error. If the error is less than the error threshold then the remaining points are approximated (in two chunks utilizing the center point). If the error exceeds the threshold, the scanline is split into two sections, and the approximator is recursively applied to each section until the error is less than the threshold or all points have been exactly computed.
The error threshold (in pixels) can be controlled with the gdalwarp
-et
switch. If you want to compare a true pixel-by-pixel reprojection
use -et 0
which disables this approximator entirely.
Memory usage
Adding RAM will almost certainly increase the speed of gdalwarp.
That's not at all the same as saying that it is worth it, or that the speed
increase will be significant. Disks are the slowest part of the process. By
default gdalwarp won't take much advantage of RAM. Using the flag
-wm 500
will operate on 500MB chunks at a time which is better than
the default. The warp memory specified by -wm
is shared among all
threads, so it is especially beneficial to increase this value when running
gdalwarp with -wo NUM_THREADS
(or its equivalent
GDAL_NUM_THREADS
) greater than 1.
Increasing the I/O block cache size may also help. This can be done by
setting the GDAL_CACHEMAX
configuration like:
gdalwarp --config GDAL_CACHEMAX 500 -wm 500 ...
This uses 500MB of RAM for read/write caching, and 500MB of RAM for working buffers during the warp. Beyond that it is doubtful more memory will make a substantial difference.
Check CPU usage while gdalwarp is running. If it is substantially
less than 100% then you know things are IO bound. Otherwise they are CPU bound.
The --debug
option may also provide useful information. For instance, after
running the following:
gdalwarp --debug on abc.tif def.tif
a message like the following will be output:
GDAL: 224 block reads on 32 block band 1 of utm.tif
In this case it is saying that band 1 of utm.tif
has 32 blocks, but
that 224 block reads were done, implying that lots of data was having to be
re-read, presumably because of a limited IO cache. You will also see messages
like:
GDAL: GDALWarpKernel()::GWKNearestNoMasksByte()
Src=0,0,512x512 Dst=0,0,512x512
The Src/Dst windows show you the "chunk size" being used. In this case my whole
image which is very small. If you find things are being broken into a lot of
chunks increasing -wm
may help somewhat.
But far more important than memory are ensuring you are going through an
optimized path in the warper. If you ever see it reporting
GDALWarpKernel()::GWKGeneralCase()
you know things will be relatively slow.
Basically, the fastest situations are nearest neighbour resampling on 8bit data
without nodata or alpha masking in effect.
Compressed output
In some cases, the output of gdalwarp may be much larger than the original, even if the same compression algorithm is used. By default, gdalwarp operates on chunks that are not necessarily aligned with the boundaries of the blocks/tiles/strips of the output format, so this might cause repeated compression/decompression of partial blocks, leading to lost space in the output format.
The situation can be improved by using the OPTIMIZE_SIZE
warping option
(-wo OPTIMIZE_SIZE=YES
), but note that depending on the source and
target projections, it might also significantly slow down the warping process.
Another possibility is to use gdalwarp without compression and then follow up with gdal_translate with compression:
gdalwarp infile tempfile.tif ...options...
gdal_translate tempfile.tif outfile.tif -co compress=lzw ...etc.
Alternatively, you can use a VRT file as the output format of gdalwarp. The VRT file is just an XML file that will be created immediately. The gdal_translate operations will be of course a bit slower as it will do the real warping operation.
gdalwarp -of VRT infile tempfile.vrt ...options...
gdal_translate tempfile.vrt outfile.tif -co compress=lzw ...etc.
Examples
Basic transformation:
gdalwarp -t_srs EPSG:4326 input.tif output.tif
For instance, an eight bit spot scene stored in GeoTIFF with control points mapping the corners to lat/long could be warped to a UTM projection with a command like this:
gdalwarp -t_srs '+proj=utm +zone=11 +datum=WGS84' -overwrite raw_spot.tif utm11.tif
For instance, the second channel of an ASTER image stored in HDF with control points mapping the corners to lat/long could be warped to a UTM projection with a command like this:
New in version 2.2.
gdalwarp -overwrite HDF4_SDS:ASTER_L1B:"pg-PR1B0000-2002031402_100_001":2 pg-PR1B0000-2002031402_100_001_2.tif
To apply a cutline on a un-georeferenced image and clip from pixel (220,60) to pixel (1160,690):
gdalwarp -overwrite -to SRC_METHOD=NO_GEOTRANSFORM -to DST_METHOD=NO_GEOTRANSFORM -te 220 60 1160 690 -cutline cutline.csv in.png out.tif
where cutline.csv content is like:
id,WKT
1,"POLYGON((....))"
To transform a DEM from geoid elevations (using EGM96) to WGS84 ellipsoidal heights:
New in version 2.2.
gdalwarp -overwrite in_dem.tif out_dem.tif -s_srs EPSG:4326+5773 -t_srs EPSG:4979
C API
This utility is also callable from C with GDALWarp()
.


{% extends "base.html" %} {% block content %}
Footprint is a travel journal app to document your trip. Travelers can use it to create digital logs, which enhance your text with photos and maps marking all of the places you visited, with the option to keep entries private or share them with family and friends. The app also allows users to share their logs and find logs posted by other travelers all over the world. Wanna have a try? Sign up now!
We started Footprint as a course project for 17-637 in 2021 Spring and got a bunch of experience in Django, Ajax and front-end. We took advantage of Codepen, Bootstrap, Stackoverflow, and other useful online resources. Thank you to everyone who selflessly share their programming knowledge. It's already a great journey for us!
Thank you for visiting our website. We hope you find it interesting and would be very glad to answer any questions. We know this project is not perfect. If you'd like to share your ideas or suggestions with us, feel free to contact our team!
Team 21


A few months ago I came across Travis CI.
Travis CI describes itself as
A hosted continuous integration service for the open source community.
It integrates with GitHub via post-receive hooks. So everytime you push to your GitHub repository Travis gets notified and will start building and testing your code.
You have to provide a .travis.yml to configure your build. Although you could customize your build in enormous detail, the defaults provided by Travis CI allow you to start using continous integration easily.
The bare minimum for a .travis.yml
file is the language keyword. For
example, the file below will instruct Travis to build a java project
using maven, gradle or ant depending on which files are
present. I.e. a pom.xml
, build.gradle
or build.xml
file.
1
|
|
Travis CI supports numerous languages, including Java, Ruby, Erlang, Clojure and Haskell. The lanuguage list is growing. To a look on the documentation page for an up-to-date list.
So consider Travis CI for all your open source build.


--- layout: page title: Editing description: Tips and tricks for the editing process background: '/img/t-edit.jpg' --- ##Planning Documentation [**How to build a podcast**](https://drive.google.com/a/uw.edu/file/d/16ZCXoRzc1W90VXlDAutm8Asa5TcCuvwJ/view?usp=sharing) from the makers of **This is Criminal**, Phoebe Judge and Lauren Spohrer.
NPR Storytelling Project Blueprint 2.0 from NPR Training
Imagining the Story by Rod Rosenthal for transom.org
Podcasting Basics: Part 1, Part 2, Part 3, Part 4, and Part 5 from transom.org.
In addition to devices you may already own (smartphones, microphones, and audio recorders), equipment can be reserved through the following locations:
Odegaard Library Sound Studio
UW Libraries Media Arcade
The following are free audio editing programs for all platforms:
Reaper - NOTE: Reaper has a 60-day free trial you can use in the duration of the workshop
Hindenburg - NOTE: Hindenburg has a 30-day free trial you can use in the duration of the workshop
Members of the UW community also have access to the following resources:
UW Libraries Media Arcade - Audition, Audacity, Pro Tools, Reason
Odegaard Library Sound Studio - Ableton Live Suite, ProTools
Odegaard Library Learning Commons - Audacity


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--- layout: post title: "My Week in Review" date: 2016-03-13 10:30:00 +0000 tags: image: https://s3.amazonaws.com/audreywatters/2016-03-13-type.jpg imagecredits: https://www.flickr.com/photos/stevendepolo/4550901923 ---
Image credits: The Noun Project


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In the UK we have started to celebrate π day (the 3rd month's 14th day) every year, even though we don't use the USA's date formatting convention of monthnumber followed by daynumber. But we can't really celebrate the 31st of April (31/4) or the 3rd of Quatember (?) (3/14), so we'll happily celebrate π day on 14/3 along with everyone else!
I set myself a challenge at the beginning of March: make a π-related image using Julia and the Luxor.jl package every day until π day. Some days it worked out well, others didn't, but I've gathered them all here anyway. This post has a fair few images, but not very much code or mathematical content.
The images here are in low-resolution: they should be available on my Flickr page at their full resolution if you want to download or re-use them.
Circle packing may be a well-trodden path, but it always looks neat, and it's a nice easy start. You maintain a list of circles (center point and radius). Then you create a random circle, check it against all the other ones, draw it if it doesn't overlap, or reduce the radius and try again. It's not very efficient but you can set it going and go and make some coffee.
To make the π shape appear, the code creates a path:
fontsize(480)
textoutlines("π", O, :path, halign=:center, valign=:middle)
πoutline = first(pathtopoly())
then checks whether each circle's centerpoint is inside or outside the outline of the π shape:
isinside(pt, πoutline)
and colors it accordingly.
I repeated myself today, thinking I could develop the circles a bit more, and ended up with this glossier wet-look version. The apparently random-looking shapes in the background are Bézier splodges that are supposed to be splashes...
This is π packing rather than circle packing, although the code is again quite similar in outline: choose a point at random, find the largest font size at which the π character fits without overlapping others in the list, and then place it and add it to the list. The colors are a bit murky though.
Combining concentric circles and rainbow colors, this image shows about 350 digits of π.
To generate the digits of π, I use this function:
function pidigits(n)
result = BigInt[]
k, a, b, a1, b1 = big.([2, 4, 1, 12, 4])
while n > 0
p, q, k = k^2, 2k + 1, k + 1
a, b, a1, b1 = a1, b1, p * a + q * a1, p * b + q * b1
d, d1 = a ÷ b, a1 ÷ b1
while d == d1
push!(result, d)
n -= 1
a, a1 = 10(a % b), 10(a1 % b1)
d, d1 = a ÷ b, a1 ÷ b1
end
end
return result
end
It looks like witchcraft to me, but I understand that it's a "spigot" algorithm. I was hoping for a while that it was named after a Professor Spigot, but in fact it's describing the way the digits trickle out one by one like drops of water. It's quick enough for a thousand digits or so, but slows down a lot when you ask for 100_000 or more, probably due to the hard work that the big integer library has to do: even when you're just calculating the first 15 digits of π, the values of a1
and b1
are way over the limits of Int64s.
julia-1.1> @time pidigits(1000);
0.014522 seconds (44.90 k allocations: 9.425 MiB, 28.97% gc time)
The image might work better on white:
Sometimes I wanted to check where certain sequences of digits appeared. I couldn't find a built-in function that looked for a sequence of digits in an array, but this worked well enough for my purposes:
function findsubsequence(needle, haystack)
result = Int64[]
for k in 1:length(haystack) - length(needle)
if needle == view(haystack, k:k + length(needle) - 1)
push!(result, k)
end
end
return result
end
findsubsequence(str::String, digits) =
findsubsequence(map(x -> parse(Int, x), split(str, "")), digits)
findsubsequence("999999", pidigits(2000)) # => [763]
A chunky typeface like the Avenir Heavy I used yesterday is good for masking and clipping. But I wondered how the narrowest typeface would look. I found Briem Akademi, designed by Gunnlaugur Briem at the Royal Academy of Fine Arts in Copenhagen. Adobe's description says:
The most compressed version works best where legibility is less important than dramatic visual effect.
and I like the abstract look even though it's almost illegible... Would this make nice bathroom tiles?
I'm still thinking about using typefaces. I'm a fan of Ed Benguiat's ITC Tiffany font, his nostalgic look back from the 1970s to the age of Edwardian elegance.
It's easy to do this with tables. Like the circle packing, the code checks whether the coordinates of each table cell fall within a given perimeter, and changes the font accordingly.
The excellent Colors.jl package has a function called distinguishable_colors()
(which fortunately tab-completes). The help text says:
This uses a greedy brute-force approach to choose
n
colors that are maximally distinguishable. Givenseed
color(s), and a set of possible hue, chroma, and lightness values (in LCHab space), it repeatedly chooses the next color as the one that maximizes the minimum pairwise distance to any of the colors already in the palette.
Much to do with color depends on the viewer's perception, but I think it works well here. It starts at the top left, and works from left to right. (That pesky decimal point defaults to using the previous color...) You can spot the Feynman point (999999
) halfway down on the left (look for the six consecutive sandy brown squares), or the four purple sevens on the bottom row.
I remembered to try to choose the color for the small labels (probably unreadable in the low-resolution PNG you see here) so that they're either light on dark, or dark on light.
... r, g, b = color of square
gamma = 2.2
luminance = 0.2126 * r^gamma + 0.7152 * g^gamma + 0.0722 * b^gamma
(luminance > 0.5^gamma) ? sethue("black") : sethue("white")
I must have seen an advert for CandyCrush yesterday, or perhaps all that talk of gamma and LCHab spaces caused a reaction, but this sugar rush of an image was the result. The SVG version looks tasty but is too big for this web page.
Arranging the sweets in a spiral looks tidy.
Luxor's polysample()
function takes a polygon and samples it at regular intervals. This allows the following idea, where each point on a shape (here, the outline of the π character) is slowly moved to a matching location on the circular shape around the outside.
For a point on the π border p1
, and a matching point on the circumference polygon p2
, the intermediate point is given by between(p1, p2, n)
, where n
is between 0 and 1.
I like the almost 3D effect you get from this.
Time for a charcoal sketch:
The crinkly edges of the paper are made by the polysample()
function on a rectangle then applying simplex-noise()
-y nudges to the vertices. The paper is textured with rule()
d lines, and there's some very low values for setopacity()
smudges. Shifting the Bézier curve handles slightly for each iteration gives a brushy/sketchy feel. (It's fortunate I can copy and paste some of this code from drawings I've made before: I've learnt the hard way that it's better keep things than throw them away...)
I ran out of time on this one, and there are still some problems with the text spacing. The idea is to have the infinite digits of π spiral into some fiery star with some space-y stuff. Probably not the sort of image I should be attempting at all with simple vector-based 2D graphics tools, but it feels like a challenge. Those wispy trails are the same as yesterday's brush strokes, but using custom setdash()
dashing patterns.
The idea here is to show which digit of π is the current leader, in terms of how many times that digit has appeared already.  Then I couldn't decide on how many digits to show, so it's going to be an animated GIF showing the first 1000 digits. At the 200 digit mark poor old "7" is struggling at the back of the field, but the glory days are ahead - after 1000 digits, it's overtaken 0, 4, and 6.
The animation turned into a video rather than a GIF, because I don't like the low resolution of GIFs today.
And now of course I have to add a suitable audio soundtrack. Luckily I've recently been playing with George Datseris' MIDI interface for Julia, so it was easy enough to make a musical version of the first 1000 digits of π, where the digits from 0 to 9 choose the appropriate note from a reasonably harmonious scale.
using MIDI
function savetrack(track, notes)
file = MIDIFile()
addnotes!(track, notes)
addtrackname!(track, "a track")
push!(file.tracks, track)
writeMIDIFile("/tmp/sound-of-pi.mid", file)
end
scales = [46, 48, 51, 53, 55, 57, 58, 60, 62, 65, 67]
function generatetune!(notes)
pos = 1
dur = 80
k = 1
manypidigits = pidigits(1000)
for i in manypidigits
dur = k * 960
pos += k * 960
n = scales[i + 1]
note = Note(n, 76, pos, dur)
push!(notes, note)
end
end
notes = Notes()
track = MIDITrack()
generatetune!(notes)
savetrack(track, notes)
This "sonification" (or "audification") is just for fun. For a more convincing critique of these sonifications than I can provide, watch the always entertaining Tantacrul's presentation on YouTube.
And while you're on YouTube, the π video is on my YouTube channel, and it's my entry for YouTube's Most Boring Video of 2019 competition, but I suspect it won't do very well—competition in this category is fierce, even if sometimes the contestants are unwilling participants.
Happy π day!
[2019-03-13]
This page was generated using Literate.jl.


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Using Unrestricted allows you to ignore wider constraints. For example, an entire controller may be protected with the Dynamic constraint, but methods in that controller may be freed from constraints by marking them as @@Unrestrcted.
@@Restrictions(@@Group("hurdy") public class UnrestrictedController extends Controller { public static Result index() { return ok(accessOk.render()); } }
@@Restrictions(@@Group("hurdy")) public class UnrestrictedController extends Controller { @@Unrestricted public static Result unrestrictedWithinAConstrainedController() { return ok(accessOk.render()); } }


Chelsea’s €150M war chest, part 1 of 2: Top transfer targets for the Blues
by The Pride of London StaffChelsea will hear about the fate of the January window soon.
The size Chelsea’s supposed war chest has varied but has consistently been in the €150 million range. So we asked our contributors to use CIES Football Observatory values and Transfermarkt values to name their transfer targets using that war chest. Who would we spend that cash on?
Bernardo Silva (€120M) and Alex Telles (€30M) – Varun Dani
Chelsea has two positions that require some upgrading; a winger to replace Pedro and a left back to replace Marcos Alonso. To this extent, Bernardo Silva and Alex Telles would be excellent upgrades.
It is easy to go along the Jadon Sancho hype when it comes to purchasing a new attacker. He is an exquisite talent, but I would want the club to take a more calculated approach and find a player with some unique qualities. Sancho is quite similar to Christian Pulisic and Callum Hudson-Odoi in being a pacey, direct winger but not truly being very different from them.
This Chelsea squad, for all its depth, only has three left footers making them rather predictable at times. If the club was to spend big money on a winger, they should do it to acquire a skill set nobody at the club possess. Enter Bernardo Silva.
A majestic dribbler and massive goal contributor, Silva would thrive on the right side of Chelsea’s attack, which is also his preferred position. He was Manchester City’s best player last season and is criminally underrated. As a wide playmaker, Silva would add the Juan Mata-esque magic touch the squad currently lacks. Aged 25, he would be a player in the prime of his career who would perform instantly to complement the patience required with Pulisic and Hudson-Odoi.
Alex Telles on the other hand comes from a long line of excellent Brazilian left backs, excellent offensively and defensively. He is pacey, skillful and physical, making him the perfect rival for Emerson. His set piece prowess would match that of Alonso’s.
I would prefer the club makes these signings in the summer, rather than the winter, to give them an entire preseason to settle.
| 1 of 3 | Next: 2. The English and the next big Italian wonderkid |


Data Fields | |
| void * | membase |
| RVALUE * | slot |
| size_t | limit |
| struct heaps_slot * | next |
| struct heaps_slot * | prev |
Definition at line 303 of file gc.c.
| size_t heaps_slot::limit |
Definition at line 306 of file gc.c.
Referenced by count_objects(), finalize_list(), free_unused_heaps(), objspace_each_objects(), and slot_sweep().
| void* heaps_slot::membase |
Definition at line 304 of file gc.c.
Referenced by assign_heap_slot(), free_unused_heaps(), and objspace_each_objects().
struct heaps_slot* heaps_slot::next [read] |
Definition at line 307 of file gc.c.
Referenced by gc_sweep(), lazy_sweep(), and unlink_heap_slot().
struct heaps_slot* heaps_slot::prev [read] |
Definition at line 308 of file gc.c.
Referenced by unlink_heap_slot().
Definition at line 305 of file gc.c.
Referenced by assign_heap_slot(), finalize_list(), objspace_each_objects(), and slot_sweep().


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We've put a button online, and want to see what you can make it do.

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button.bind('press', function(data) {
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{{#jsbinLink}}
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Make a virtual button
You're welcome to come and use our button, but if you want to test your creation with your own button, you can create a virtual one below:
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Copyright
2015, 2015 IBM
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.
The IBM Data Merge Utility is accessed via the Merge Servlet which can be accessed at http://yourServer/Merge.html. Parameters passed on the http request are used to initilize the Replace Hash. The Template collection, name and column value can be provided as parameters. The following default values are used if not provided:
- collection: "root"
- name: "default"
- column: empty
The URL: http://www.yourserver.com/Merge.html?collection=MyCollection&name=MyTemplate
will merge the template MyTemplate from the collection MyCollection.
The most fundamental function of the merge process is the replacement of merge tags with data values. The replace "From" values are wrapped in {brackets} and processed globally during the merge process. These replace values are processed as a hash, which implies that adding a duplicate "From" value willreplace the "To" value of the existing hash entry with the new value.
Many Directive Options (SQL Statements, Output Filenames, etc.) are processed by the Template Replace Hash before being used during the merge. Options that are processed by the Replace Hash are listed in the documents with this special mark-up.
The insertion of sub-templates into a target template is the second core feature of the Merge Utility. The Insert Rows directives work with a potentially multi-row data set, and sub-templates are inserted into the target template, at bookmarks for each row of the result set. Bookmarks take the following form
<tkBookmark name="SomeSubTemplate" collection="FromCollection" column="byColumn""/>
The collection and name attributes of the bookmark identify the sub-template to insert. The column attribute if present will insert different sub-templates based on the value in the Column specified here. A template can have multiple bookmarks to insert multiple sub-templates for each row of the result set.
Varying the Sub-Template Inserted
When inserting sub-templates, you can vary the sub-template being inserted based on data in the result set. This is often based on a "Type" field in the result set, and relies on a "Collection" of templates with the same name and a specified column value. If a template for the current column value is not found, the "empty" value is used. If no "empty" value exists for the collection the merge will fail with a "Template Not Found" exception.
The Insert Subtemplate directives have the following Options
- Not Last Tags - Tags that should be empty on the last insertion row
- Only Last Tags - Tags that should be empty on all except the last insertion row
When inserting sub-templates various syntax rules often require that the list separator be different than the list terminator. For example a comma separated list terminated with a period. This can be supported in templates by using static replace tags for the separator/terminator, and then identifying those tags in the "Not Last" and "Only Last" fields of the Insert Directive. Tags identified as "Not Last" are replaced with an empty value on the Last Row of the insert. Tags identified as "Only Last" are replaced with an empty value on all except the last row of the insert.
The following are reserved Replace Tags, that have various effects / meanings:
- DragonFlyCacheReset - The Data Merge Tool will cache all templates, allowing for very fast response
times and high throughput rates. Adding the parameter DragonFlyCacheReset with or without a value will
clear the template cache before executing the merge. This value is not placed on the Replace Hash
- DragonFlySoftFail - If the value {DragonFlySoftFail} is in the replace stack, merge errors are written
as output into the template, rather than throwing exceptions back to a full merge failure.
This can be helpful in debugging problems with nested replace values or invalid sql result sets.
- DragonFlyReplaceValues - The replace tag {DragonFlyReplaceValues} will be replaced with a full
dump of the replace hash, with the From values mangled as {-from} in place of {from}.
This tag can be useful when designing and debugging templates.
- DragonFlyOutputFile - The replace tag {DragonFlyOutputFile} will contain a generated GUID.zip or GUID.tar.gz string.
This is the file name of any additional generated output, and can frequently be used in a javascript
tag to initiate a download. NOTE: This value can be provided as an input parameter, however database
connection caching is associated with the guid during merge execution, so multiple concurrent merges
with the same {DragonFlyOutputFile} value will have unpredictable results. If provided on the replace
stack, you should ensure that this value is unique for the duration of the merge execution.
- DragonFlyTemplateStack - This will print out a / separated list of the current template full-names.
This can be useful when developing and debugging templates.
The Template Editor
The template editor can be accessed at http://yourServer/TemplateEditor.html
A wire frame of the proposed Editor is show below, documentation on the editor will be placed here
A collection is a container for organizing templates. You can create multiple containers that have one or many templates assigned to them.
To access collections, perform the following steps:
1. Navigate to the IDMU application in your browser.
2. Select a collection from the 'Collections' select list.
3. Upon selection of a collection, all the IDMU will display all the available templates in the collection.
4. You may navigate between the templates by clicking on the Left/Right bars in the template editor.
Figure #1 - Collection Page
Figure #2 Navigating Between Templates Using Left and Right Arrows
The template is the core component of the IDMU Template editor. A template provides the ability to create a message, define merge fields, specify directives to drive the retrevial of data, and perform the required inserts of that data. Once the IDMU processes the template, the IDMU can deliver multiple output files from a single merge into a zip or tar archive.
Perform the following steps to create a template:
1. Click on the 'Add' button in the title bar of a template.
2. Upon clicking, the IDMU will launch a dialog box will enabling you to enter the collection, name of template, and columnValue if any.
3. Upon completion of these fields, click on the 'Add' button on the dialog. This will create the new template.
Figure #3 - Creating a new template
You can save a template in any collection. Perform the following steps to save a template:
1. Navigate to the collection and template of interest within that collection.
2. Click on the 'Save' button on the top right of the title bar of the template.
Figure #4 - Saving a template
You can edit the basic template properties like name, output, and description. Perform the following steps to edit template properties:
1. Click on the title of the template from within the collection.
2. The template expand the area and show the basic properties of the template.
3. After making changes, click on the "Save" button of the template.
Figure #5 - Edit template properties
You can add or remove templates in any collection. Perform the following steps to remove a template:
1. Navigate to the collection and template of interest within that collection.
2. Click on the 'Remove' button on the top right of the title bar of the template.
Figure #6 - Removing a template
The IDMU template editor provides multiple merge directives. For a list of available merge directives, click here [link needed]. Once you have identified the merge directive(s) you want to use, perform the following steps:
1. Locate the template you wish to edit.
2. Click on the title of the template, expanding it.
3. Click on the 'Configure' button next to the directives "Select" list. Upon clicking, the IDMU launches the drag and drop directives panel.
4. You can drag the merge directives from the left hand side list onto the right and side. This action will add the selected directive to the template.
5. In addition to the drag and drop of the directives, you can also rearrage the order of the directives.
6. To remove a directive from the template click on the 'red' X button to the right of the merge directive.
*Note* - After adding or changing directives and/or it's properties you must hit the 'Back'
button on this panel, and then press the 'Save' button on the title bar. Otherwise your
changes will not be saved.
Figure #7 - Dragging merge directives
Once you have selected the merge directives for your template, you can edit them to configure the specific data provider information.
To change the properties of a configured template directive, perform the following:
1. Navigate to the directive configuration panel.
2. Click on the directive on the lefthand side of the drag and drop list.
3. Upon clicking, the IDMY will launch the property editor for that particular directive type.
4. Make your edits (for example, update a "WHERE" clause) and press the 'Save' button on the dialog editor.
5. As noted earlier, click the 'Back' button.
6. To complete the edit, click on the "Save" button for the template.
Figure #8 - Editing merge directives
The IDMU allows you to insert sub-templates into templates. The "Insert Subs" directive works with a "Bookmark" to create, process, and insert a sub-template. The IDMU inserts one sub-template for each row of data returned by the data provider specified in the "Insert Subs" directive. From there, the sub-template inherits the full Replace Hash of its parent template, as well as the replace row values of the current record that is driving the insert. Sub-templates can additionally have their own directives to drive additional processing within their own template.
To insert a sub-template you must have configured the template, perform the following:
1. Ensure you have dragged an 'Insert' directive to the left of the template. You will know the "Insert" directive is available because you will see an 'Insert Template' button will appear below the 'Content' area.
2. After clicking on the 'Insert Template' button, the IDMU will present a dialog to create the collection, template name, and column name (optional) for the sub-template.
3. Additionally, when you click on the 'Insert' button, a the IDMU inserts a new bookmark into the content. The IDMU will then refresh the template screen with the new bookmark, expanding it as a sub-template.
Figure #9 - Creating the sub-template
Figure #10 - Creating the bookmark
Any sub-template can be saved as an output file instead of being inserted into the target template, by providing an output file name for the Template. All output files generated in this manner during a merge are added to an archive, and placed in the merge output directory which is specified in the web.xml configuration file.
The archive name is provided in the replace tag {DragonFlyeOutputFile} and a GUID is generated for the file name if needed. If you pass DragonFlyOutputFile as a parameter to the merge you should ensure that the file name provided is unique for the duration of the merge operation. Database connections are cached based on this value, and multiple concurrent merges with the same DragonFlyOutputFile name will have unpredictable results.
 If a required tag is missing the merge process will fail with an exception. If the soft fail indicator is present, the missing values message will be inserted into the template.
The Require directive has the following Options
- Tags - The comma separated list of requried Tags
The Replace Value directive provides for a simple static from/to value pair. The from value is added as-is to the replace stack. This directive is frequently used in conjunction with the Not-Last and Only-Last options of the Insert Rows directives.
For a more flexable way to place static values on the Replace Hash see the Replace from Csv Directives
The Insert Sub-Templates If directive combines the functionality of the
Insert Sub-Templates with the
Tag data provider.
The Insert Sub-Templates from SQL directive combines the functionality of the
Insert Sub-Templates with the
SQL data provider.
The Replace Row from SQL directive combines the functionality of
Replace Row with the
SQL data provider.
The Replace Column from SQL directive combines the functionality of
Replace Col with the
SQL data provider.
The Insert Sub-Templates from CSV directive combines the functionality of the
Insert Sub-Templates with the
CSV data provider.
The Replace Row from CSV directive combines the functionality of
Replace Row with the
CSV data provider.
The Replace Column from CSV directive combines the functionality of
Replace Col with the
CSV data provider.
The Insert Sub-Templates from HTML directive combines the functionality of the
Insert Sub-Templates with the
HTML data provider.
The Replace Row from HTML directive combines the functionality of
Replace Row with the
HTML data provider.
The Replace Column from HTML directive combines the functionality of
Replace Col with the
HTML data provider.
The Replace Column from HTML directive uses the HTML data provider.
to fetch an HTML document, and then find Replace From/To values based on the following options:
By way of example, the following options:
- Element Selector - Input
- From Attribute - ID
- To Attribute - Empty (content of the selected element)
With this HTML Data
will produce the following replace hash
The SQL (JDBC) Data Providers utilize a JDBC data source configured in the IDMU J2EE Context.xml file, and create a SQL SELECT statement based on the options provided. The components of the select statement are each processed by the Replace Hash before being executed.
JDBC Directives
CSV Data Providers fetch their information from either a URL, the data associated with a Replace Tag, or as static data from the directive itself. Once fetched the data is parsed based on the Microsoft Excel CSV formatting standards.
CSV Directives
HTML Data Providers fetch their information from either a URL, the data associated with a Replace Tag, or as static data from the directive itself. Once fetched the data is parsed as HTML, and the HTML <table> elements are selected based on the css selector option and parsed for use. Note that all HTML table elements must specify a table row with table header values. If multiple tables match the selector, they are each parsed and processed in the order they are found in the HTML source.
HTML Directives
Tag Data providers utilize data from the Replace Hash (to support the Insert From Tags directive). If the Tag exists and meets the Condition parameter a data table is constructed with a single column that has the Tag Name. If the "Is List" indicator is set, the tag data is treated as a comma seperated list of values and the data table has multiple rows, one for each value. If the "Is List" indicator is not set the data table will have only a single row.
Tag Data Directives
The Tag Data provider is used to select data that exists in the Replace Hash to use for Directive Processing


https://wordpress.org/plugins/wp-security-audit-log/
Fence background photo by Jason Blackeye on Unsplash
matt@capwebsolutions.com@MattRyan_co


pywinEA.error package¶
pywinEA.error.exceptions module¶
-
exception
pywinEA.error.exceptions.
FeaturesFunctionError
¶ Bases:
Exception
Exception thrown when there is a failure due to the function to evaluate the number of features of a solution.
-
exception
pywinEA.error.exceptions.
FileExists
¶ Bases:
Exception
Exception thrown when trying to overwrite existing files.
-
exception
pywinEA.error.exceptions.
ImpossibleHandleMissing
¶ Bases:
Exception
Exception thrown when data contains missing values and no way has been provided to handle it.
-
exception
pywinEA.error.exceptions.
ImpossibleProcessLabels
¶ Bases:
Exception
Exception thrown when algorithm cannot process class labels.
-
exception
pywinEA.error.exceptions.
InconsistentParameters
¶ Bases:
Exception
Exception thrown when the parameters provided to the algorithm are inconsistent.
-
exception
pywinEA.error.exceptions.
MinimumNumberOfFeaturesAchieved
¶ Bases:
Exception
Exception thrown when the algorithm has converged to less than two features.
-
exception
pywinEA.error.exceptions.
UnfittedAlgorithm
¶ Bases:
Exception
Exception thrown when trying to access parameters or methods with untrained algorithm
-
exception
pywinEA.error.exceptions.
UnsuitableClassifier
¶ Bases:
Exception
Exception thrown when a classifier is not suitable to perform a certain task.


By default, this option is selected. IntelliJ IDEA deduces from project settings when the cross-compilation is needed and automatically applies the --release compiler option for Java 9.
--release


Enables television presenter to see vote counts and announce the winner of the competition. Enables viewers of a popular BBC talent competition to vote for their favourite candidate.


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GenFam: Gene Family based classification and enrichment analysis
Visit GenFamHTSQualC: automated quality control analysis for high-throughput sequencing data (HTS)
Visit HTSQualCbioinfokit: Bioinformatics data analysis and visualization toolkit
Visit bioinfokit


The form you just used was not rendered by anything official PUBG. In fact, it was served from [PLACEHOLDER]. If this were more than just a proof-of-concept, your username/password would be sent back to that server and thus end up in unauthorized hands.
This is a serious problem. Please pressure the PUBG team to fix it ASAP.
Developer? Why not see what you can make happen in this page using a console?


{% include header.html %}
{% include header-inner.html %}
{% include nav-page-menu.html %}
{% include before-content.html %}
{{ page.title }}
{{ content }}
Table of contents
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Connect RSK to Truffle Interact with node
Next: Download SCS
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Butterfly House / Alexis Dornier
- Curated by María Francisca González
- about 13 hours
- version="1.0" encoding="UTF-8"? Architects: Alexis Dornier
- AreaArea of this architecture projectArea: 420.0 m2
- version="1.0" encoding="UTF-8"?YearCompletion year of this architecture project Year: 2019
- version="1.0" encoding="UTF-8"?PhotographsPhotographs: Kiearch
- version="1.0" encoding="UTF-8"?ManufacturersBrands with products used in this architecture project Manufacturers: FRANKE, Grohe, LG Electronics, Sika, Tecnogas, Toto
- Lead Architect Alexis Dornier
- Construction Surya Kembar
- Collaborators Surya Kembar
More Specs Less Specs
Text description provided by the architects. Architecture as an experiment in form of designing a 4 bedroom off the ground structure on stilts. The plan figure of the house is a cross that is surrounded by a circle. The cross is the primary building component, where as the circle is the secondary. This circle holds programs such as the atelier, the pool, the sound studio and back of house program. The living room becomes the continuous landscape brought through the underneath of the sculpture, and is the heart of the circle. The primary building component is the elevated cross, where each of it’s 4 ends hold rooms that point into different directions, framing specific views into the vicinity.
Each of the 4 bedrooms is crowned by a specific roof shape that seamlessly blends into the other extremities of the building. we blend vernacular roof silhouettes into something new, combined and transmuted architecture and visually connected this design to neighboring roofs- not to stand out, but to continue the rhythm of built shapes on the horizon. Bedrooms face towards the inside and can be opened to become visually connected to the inner atrium. The visual relationships of the distinctive building components add to a certain significance and atmosphere and manifest a built, out-of-the-box experiment. The bedrooms can be accessed by 2 central staircases that complete each other in form of a helix. Underneath these staircases a sunken sofa area defines the heart of the home.
The material palette is dominated by the appearance and use of reclaimed wood of different kinds. Intricately textured walls through different patterns, sculptures, artwork and plants create an artistic environment. The oft like character makes a lively, scenic built and curated landscape in the context of tropical modernism.


--- layout: default author_profile: true header: image: /assets/images/Banner.jpg feature_row: - image_path: assets/images/Figure_3.jpg alt: "placeholder image 1" title: "Placeholder 1" excerpt: "This is some sample content that goes here with **Markdown** formatting." - image_path: /assets/images/MSE_Pro_MESO-SCOPE.jpg image_caption: "Image courtesy of [Unsplash](https://unsplash.com/)" alt: "placeholder image 2" title: "Placeholder 2" excerpt: "This is some sample content that goes here with **Markdown** formatting." url: "https://jrcasey.github.io/research/" btn_label: "Read More" btn_class: "btn--primary" - image_path: /assets/images/poster.pdf title: "Placeholder 3" excerpt: "This is some sample content that goes here with **Markdown** formatting." --- {% if page.header.overlay_color or page.header.overlay_image or page.header.image %} {% include page__hero.html %} {% elsif page.header.video.id and page.header.video.provider %} {% include page__hero_video.html %} {% endif %}


Police chief: Gunman at Louisville Kroger shot, killed
LOUISVILLE, Ky. (AP) - Kentucky officers responding to an active shooter at a Louisville supermarket shot and killed a man with a gun, their police chief said.
Louisville Metro Police Chief Steve Conrad said officers arriving at a Kroger Thursday evening found “a man firing a gun and firing shots outside the entrance of the store.”
Conrad says the man shot at the officers, who returned fire, killing him. His name hasn’t been released. No other injuries were reported.
The chief said officers were near the store and “able to respond very very quickly.” He said it apparently began with “an altercation in the store between two men.”
Customers and workers scrambled for safety, he said: “Some were able to flee, others sheltered in place.”
Police brought in buses to keep witnesses out of the weather while they could be interviewed, Conrad said. He planned another press conference Friday and said body camera video would be released.
Kroger said it was “deeply saddened” in a statement obtained by WHAS-TV. The store in Louisville’s Portland neighborhood will remain closed until the investigation concludes.
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CO2 emissions (kg per PPP $ of GDP)
CO2 emissions (kt)
CO2 emissions (metric tons per capita)
CO2 emissions from gaseous fuel consumption (% of total)
CO2 emissions from liquid fuel consumption (% of total)
CO2 emissions from solid fuel consumption (% of total)
CO2 emissions from electricity and heat production, total (% of total fuel combustion)
CO2 emissions from manufacturing industries and construction (% of total fuel combustion)
CO2 emissions from other sectors, excluding residential buildings and commercial and public services (% of total fuel combustion)
CO2 emissions from residential buildings and commercial and public services (% of total fuel combustion)
GDP (current US$)
GDP growth (annual %)
GDP per capita (current US$)
Population, total
Surface area (sq. km)
Selected Countries
Select at least two Countries to compare
CO2 emissions (kg per PPP $ of GDP)
CO2 emissions (kt)
CO2 emissions (metric tons per capita)
CO2 emissions from gaseous fuel consumption (% of total)
CO2 emissions from liquid fuel consumption (% of total)
CO2 emissions from solid fuel consumption (% of total)
CO2 emissions from electricity and heat production, total (% of total fuel combustion)
CO2 emissions from manufacturing industries and construction (% of total fuel combustion)
CO2 emissions from other sectors, excluding residential buildings and commercial and public services (% of total fuel combustion)
CO2 emissions from residential buildings and commercial and public services (% of total fuel combustion)
GDP (current US$)
GDP growth (annual %)
GDP per capita (current US$)
Population, total
Surface area (sq. km)


Usage Details¶
Rake object accepts the following as the constructor parameters, by varying which this implementation of Rake algorithm can be used for several different purposes.
- stopwords : List of words which are considered to break sentences into
phrases. Defaults to
None
. - punctuations : List of punctuations which are considered to break sentences
into phrases. Defaults to
None
. - language : Language to use for tokenization and stopwords. Defaults to
english
. - ranking_metric : Metric to use for ranking of metrics
- Ratio of degree of word to its frequency d(w)/f(w). (Default)
- Degree of word only.
- Frequency of word only.
- max_length : Of phrases to consider. Defaults to
100000
. - min_length : Of phrases to consider. Defaults to
1
.
to use it with a specific language supported by nltk.¶
from rake_nltk import Rake
r = Rake(language=<language>)
Implementation automatically picks up the stopwords
for that language and
default punctuation
set.
to provide your own list of stop words and punctuations¶
from rake_nltk import Rake
r = Rake(
stopwords=<list of stopwords>,
punctuations=<string of puntuations to ignore>
)
to control the metric for ranking¶
from rake_nltk import Metric, Rake
# Paper uses d(w)/f(w) as the final metric. You can use this API with the
# following metrics:
# 1. d(w)/f(w) (Default metric) Ratio of degree of word to its frequency.
r = Rake(ranking_metric=Metric.DEGREE_TO_FREQUENCY_RATIO)
# 2. d(w) Degree of word only.
r = Rake(ranking_metric=Metric.WORD_DEGREE)
# 3. f(w) Frequency of word only.
r = Rake(ranking_metric=Metric.WORD_FREQUENCY)
to control the max or min words in a phrase¶
So that only phrases of specific min and/or max lengthes are considered for ranking
from rake_nltk import Rake
r = Rake(min_length=2, max_length=4)