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The vascular anatomy of the ovary and the relative contribution of ...
The vascular anatomy of the ovary and the relative contribution of the ovarian and uterine arteries to the blood supply of the ovary in the guinea-pig. M I Hossain .
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1171839/
SEER Training: Anatomy of the Ovaries
Anatomy of the Ovaries. The ovary is a paired organ. Bilateral involvement of ovaries with the same histology is considered a single primary site. The ovaries lie .
http://training.seer.cancer.gov/ovarian/anatomy/
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Anatomy of an ovary | dooce®
Apr 6, 2011 . Monday afternoon I had my annual pelvic exam (HEY-OH! IT'S UTERUS TIME!), and since my regular OBGYN is overbooked for the next ten .
http://dooce.com/2011/04/06/anatomy-of-an-ovary/
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Ovary - Wikipedia, the free encyclopedia
The ovary (for a given side) is located in the lateral wall of the pelvis in a region called the ovarian fossa. The fossa usually lies .
http://en.wikipedia.org/wiki/Ovary
Functional anatomy of the ovaries of wild brush - Cambridge Journals
prolificacy of the brush-tailed porcupine in the wild, the structural and functional anatomy of the ovaries of free-ranging females were studied. Twenty-two female .
http://journals.cambridge.org/production/action/cjoGetFulltext?fulltextid=91748
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Ovary - Anatomy & Physiology - WikiVet
Nov 13, 2012 . 1 Introduction; 2 Anatomical Location; 3 Structure. 3.1 Outer Tunica Albuginea; 3.2 Ovarian Cortex; 3.3 Ovarian Medulla. 3.3.1 The Mare .
http://en.wikivet.net/Ovary_-_Anatomy_%26_Physiology
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Microscopic Anatomy of the Ovary and Uterus
Microscopic Anatomy of the Ovary. copy of 60femalex.jpg (133073 bytes) primordial follicles and secondary follicle. 61femalex.jpg (133991 bytes) mature .
http://science.tjc.edu/images/reproduction/female_anatomy.htm
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Ovary Anatomy
Jun 27, 2011 . Ovary Anatomy. The ovaries are the female pelvic reproductive organs that house the ova and are also responsible for the production of sex .
http://emedicine.medscape.com/article/1949171-overview
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CT Anatomy of the Female Pelvis: A Second Look1 - RadioGraphics
plexus supplying the vagina, ovaries, and uterine body. Ideally, familiarity with variations in the CT appear- ance of normal female pelvic anatomy will enable .
http://radiographics.rsna.org/content/14/1/51.full.pdf
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The Ovaries - Gray's Anatomy of the Human Body - Yahoo! Education
The ovaries are homologous with the testes in the male. They are two nodular bodies, situated one on either side of the uterus in relation to the lateral wall of the .
http://education.yahoo.com/reference/gray/subjects/subject/266
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Uterus and Ovaries
Home · Anatomy Systems . Change View Angle. Uterus and Ovaries, Anterior ( Front) . These tissues build under the influence of hormones from the ovary.
http://www.innerbody.com/image_repo04/repo07.html
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Anatomy of the Ovaries - Ovarian Cancer - HealthCommunities.com
Aug 15, 1999 . Physician developed information about the anatomy of the ovaries. The ovaries are part of the female reproductive system.
http://www.healthcommunities.com/ovarian-cancer/anatomy.shtml
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Anatomy of the Ovary - Women's Cancer Network
Anatomy of the Ovary. An ovary is small and looks like an almond. There are two of them in a woman's pelvis. One is located on either side of the uterus.
http://www.wcn.org/articles/types_of_cancer/ovarian/overview/anatomy.html
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Anatomy & Physiology: The Female Reproduction System
Anatomy and Chemistry Basics. What Is Anatomy . The two ovaries present in each female are held in place by the following ligaments: The broad ligament is .
http://www.cliffsnotes.com/study_guide/The-Female-Reproduction-System.topicArticleId-277792,articleId-277790.html
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Anatomy of Uterus, Fallopian tube & Ovary by ASM - YouTube
Dec 31, 2011 . Anatomy of Uterus, Fallopian tube & Ovary by ASM. Marwan El Sokkary·52 videos. Subscribe Subscribed Unsubscribe 81. 6,217. Like 7 Dislike .
http://www.youtube.com/watch?v=RqNXxBQCQ0A
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Anatomy of the Ovary - Netter Medical Images
Rights-managed illustration of Anatomy of the Ovary from the Netter Collection, drawn by Frank H. Netter.
http://www.netterimages.com/image/7869.htm
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The Human Ovary: Anatomy & Follicular Development | American ...
Dec 2, 2011 . Time flies when you're having fun. And commuting (which is not fun). Well, time flies like an arrow but fruit flies like a banana
(By the way, that .
http://americantransman.com/2011/12/02/the-human-ovary-anatomy-follicular-development/
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Anatomy of the ovaries of the starfish <Emphasis ... - SpringerLink
Anatomy of the Ovaries of the Starfish Asterias rubens (Eehinodermata). A Histological and Ultrastructural Study. H.J.N. Schoenmakers, P.H.J.M. Colenbrander, .
http://www.springerlink.com/index/w03871740850p9u0.pdf
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OVARIAN CANCER: Anatomy and Physiology
Apr 22, 2001 . Anatomy and Physiology. The ovaries are a woman's reproductive organs. There are two ovaries, both located within the pelvis (lower region of .
http://ovariancancer.jhmi.edu/anatphys.cfm
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Clinical Anatomy of the Uterus, Fallopian Tubes, and Ovaries
Sapiens Specialist Publishers of Medical and Environmental Science, GLOWM, Womens Health, Global Library of Womens Medicine, Clinical Anatomy of the .
http://www.glowm.com/index.html?p=glowm.cml/section_view&articleid=1
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ovary (animal and human) -- Britannica Online Encyclopedia
The usually paired ovaries of female vertebrates produce both the sex cells and the hormones necessary for reproduction.... . Ovary function and anatomy .
http://www.britannica.com/EBchecked/topic/435788/ovary
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Anatomy Female Reproductive System- Ovary- Mammary Gland ...
May 26, 2011 . OVARY- Ovarian Ligament UTERINE (FALLOPIAN) TUBE- Infundibulum, Ampulla, Isthmus UTERUS- Body, Fundus, Cervix, Uterine Cavity, .
http://www.youtube.com/watch?v=tyye8uIs3F0
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MDCT of the Ovarian Vein: Normal Anatomy and Pathology
295. Normal Ovarian Vein Anatomy. Ovarian veins originate from the plexus in the broad ligament near the ovary and fallo- pian tube and communicate with the .
http://www.ajronline.org/content/192/1/295.full.pdf
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Functional anatomy of the ovaries of pregnant and lactating Cape ...
ties of the ovary of this species. In the present study we have examined the macro - and microscopic anatomy of the ovary of the female Cape porcupine and the .
http://www.ceru.up.ac.za/downloads/Functional_anatomy_ovaries_porcupines.pdf
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Microscopic anatomy of the ovary of <Emphasis Type ... - SpringerLink
Microscopic Anatomy of the Ovary of Alouatta caraya. JUAN ALBERTO CLAVER, IRENE VON LAWZEWlTSCH. Consejo Nacional de Investigaciones Cientifieas .
http://www.springerlink.com/index/3k84303677435671.pdf
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Reproductive Anatomy and Physiology: The Female Reproductive ...
(2) Location and gross anatomy. The ovaries are about the size and shape of almonds. They lie against the lateral walls of the pelvis, one on each side. They are .
http://www.brooksidepress.org/Products/Obstetric_and_Newborn_Care_1/lesson_1_Section_1A.htm
Gynaecological Anatomy - Gynaecology | Fastbleep
Broad Ligament - The ovaries, uterine tubes, and uterus are enclosed within this . This article will briefly describe the anatomy of each component of the female .
http://www.fastbleep.com/medical-notes/o-g-and-paeds/17/80/495
Human Anatomy & Physiology at Free-Ed.Net
May 21, 2012 . This is an introductory course in human anatomy and physiology. . Ovaries. The primary female reproductive organs, or gonads, are the two .
http://free-ed.net/free-ed/Resources/Sci/Biol/AnatomyPhysiol/Human01_LessonMain.asp?iNum=1208
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1. Include jQuery 1.6+
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That's It. Your code should then be similar to this:
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NOTY is compatible with jQuery 1.6+ for now. But if you are using older version then 1.6 you can add promise.js to your header.
(Thanks to Maksim Pecherskiy)
$ bower install noty
$ npm install noty


BASIC INSTINCT [**Spoilers**] A film review by Michelle L. Zafron Copyright 1992 Michelle L. Zafron
Spoilers follow:
Okay, now maybe it's me, maybe I've just seen too many movies. But, there were no surprises in the plot for me. I knew right off that the shrink was implicated somehow. I came up with two scenarios about fifteen minutes into the film: 1) Catherine did it or 2) the shrink did it. About an hour or so into the film I decided that they were both guilty.
What totally amazed me was the feeling of utter detachment I had during this movie. I was watching carefully but remained completely uninvolved. Occasionally, I got annoyed at blatant attempts at manipulation, but that was about it. But when I left the theater, these incredible feelings of revulsion swept over me. I am ashamed to have paid money to see this movie.
The supporting cast was easily the best thing about the film. But most of them were actors who we've all seen before--they do good solid work and that's it. Michael Douglas was doing the performance from FATAL ATTRACTION. It was essentially the same type of character, but I would have enjoyed seeing some differentiation. Sharon Stone--really didn't impress me too much, but then her character was supposed to be enigmatic so I suppose that explains the lack of depth. The actress playing her lover, Roxy, impressed me far more.
One of the few posts still in the system here about the film mentioned the music favorably. Was it me or did the Jerry Goldsmith score blatantly borrow from Bernard Herrmann?
And let's talk about the Hitchcockian ripoffs...excuse me...homages. It was kind of cute to see Sharon Stone modelling Kim Novak's French twist from VERTIGO, so was the San Francisco setting. I even liked the opening crane shots. But the film didn't just make a couple of inside references to Hitchcock --they borrowed shamelessly and that bugged me.
The film has also given homophobic movements an incredible boost by portraying homosexuality as aberrant and dangerous, but I'm not going to get into this now.
The sex scenes were boring. A lot of you are probably falling off your seats at this, but after the first couple of minutes, I started thinking things like "Man, she must have a great set of boxsprings on that bed." Somehow, I doubt that Mr. Verhoeven intended me to feel that way. The nudity didn't bother me, it just bored me (and by the way, how come we never see male frontal nudity for more than a couple of seconds? I'm not particularly anxious to see this, but I'm curious as to why we don't). Then of course there was the scene in the interrogation room where we learn that like the late Tallulah Bankhead, Catherine does not wear undies. My first thought was "doesn't San Francisco get pretty cold?" Less was definitely not more in this case.
These are all pretty cosmetic criticisms, upon reflection, I think I hated the movie because the character of Catherine was the perverted fantasy of the ice queen who blows hot and cold and remains in control of her emotions throughout. The kind of woman who "deserves" to be hurt. That is wrong.
Every woman in that film came across as either perverted and homicidal. While the only normal, healthy character in the film was the partner, the women came off far worse then the men. The men were portrayed as crude, stupid, sexist authority figures who thought with their primary sex organs, but they were not, for the most part portrayed as being dangerous or deadly. The women were these terrible creatures who looked normal (the ex-con as played by Dorothy Malone--a devoted wife and mother who went crazy) or who occupied positions of wealth and influence (Catherine and the shrink) and who are ultimately deadly creatures.
Sorry for going on so long about the film...
--Michelle L. Zafron<EMAIL_ADDRESS>.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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- ABORTED - Static variable in class openconsensus.trace.Status
-
The operation was aborted, typically due to a concurrency issue like sequencer check failures,
transaction aborts, etc.
- add(double) - Method in interface openconsensus.metrics.DoubleCumulative.DoublePoint
-
Adds the given value to the current value.
- add(double) - Method in interface openconsensus.metrics.DoubleGauge.DoublePoint
-
Adds the given value to the current value.
- add(long) - Method in interface openconsensus.metrics.LongCumulative.LongPoint
-
Adds the given value to the current value.
- add(long) - Method in interface openconsensus.metrics.LongGauge.LongPoint
-
Adds the given value to the current value.
- addEvent(String) - Method in class openconsensus.trace.BlankSpan
-
- addEvent(String, Map<String, AttributeValue>) - Method in class openconsensus.trace.BlankSpan
-
- addEvent(Event) - Method in class openconsensus.trace.BlankSpan
-
- addEvent(String) - Method in interface openconsensus.trace.Span
-
Adds an event to the Span
.
- addEvent(String, Map<String, AttributeValue>) - Method in interface openconsensus.trace.Span
-
Adds an event to the Span
.
- addEvent(Event) - Method in interface openconsensus.trace.Span
-
Adds an event to the Span
.
- addLink(Link) - Method in class openconsensus.trace.BlankSpan
-
- addLink(Link) - Method in interface openconsensus.trace.Span
-
- addLink(Link) - Method in interface openconsensus.trace.Span.Builder
-
Adds a
Link
to the newly created
Span
.
- addLinks(List<Link>) - Method in interface openconsensus.trace.Span.Builder
-
Adds a
List
of
Link
s to the newly created
Span
.
- ALREADY_EXISTS - Static variable in class openconsensus.trace.Status
-
Some entity that we attempted to create (e.g., file or directory) already exists.
- alwaysSample() - Static method in class openconsensus.trace.samplers.Samplers
-
Returns a
Sampler
that always makes a "yes" decision on
Span
sampling.
- applyAsDouble(T) - Method in interface openconsensus.metrics.ToDoubleFunction
-
Applies this function to the given argument.
- applyAsLong(T) - Method in interface openconsensus.metrics.ToLongFunction
-
Applies this function to the given argument.
- asString() - Method in class openconsensus.tags.TagValue
-
Returns the tag value as a String
.
- AttributeValue - Class in openconsensus.trace
-
A class that represents all the possible values for an attribute.
- AttributeValue.Type - Enum in openconsensus.trace
-
An enum that represents all the possible value types for an AttributeValue
.
- CANCELLED - Static variable in class openconsensus.trace.Status
-
The operation was cancelled (typically by the caller).
- clear() - Method in interface openconsensus.metrics.Metric
-
Removes all TimeSeries
from the metric.
- close() - Method in class openconsensus.context.NoopScope
-
- close() - Method in interface openconsensus.context.Scope
-
- compareTo(SpanId) - Method in class openconsensus.trace.SpanId
-
- compareTo(TraceId) - Method in class openconsensus.trace.TraceId
-
- ContextUtils - Class in openconsensus.tags.unsafe
-
Utility methods for accessing the
TagMap
contained in the
Context
.
- ContextUtils - Class in openconsensus.trace.unsafe
-
Util methods/functionality to interact with the Context
.
- copyBytesTo(byte[], int) - Method in class openconsensus.trace.SpanId
-
Copies the byte array representations of the SpanId
into the dest
beginning at
the destOffset
offset.
- copyBytesTo(byte[], int) - Method in class openconsensus.trace.TraceId
-
Copies the byte array representations of the TraceId
into the dest
beginning at
the destOffset
offset.
- copyBytesTo(byte[], int) - Method in class openconsensus.trace.TraceOptions
-
Copies the byte representations of the TraceOptions
into the dest
beginning at
the destOffset
offset.
- copyLowerBase16To(char[], int) - Method in class openconsensus.trace.SpanId
-
Copies the lowercase base16 representations of the SpanId
into the dest
beginning at the destOffset
offset.
- copyLowerBase16To(char[], int) - Method in class openconsensus.trace.TraceId
-
Copies the lowercase base16 representations of the TraceId
into the dest
beginning at the destOffset
offset.
- copyLowerBase16To(char[], int) - Method in class openconsensus.trace.TraceOptions
-
Copies the lowercase base16 representations of the TraceId
into the dest
beginning at the destOffset
offset.
- create(String, String) - Static method in class openconsensus.metrics.LabelKey
-
- create(String) - Static method in class openconsensus.metrics.LabelValue
-
- create(Map<String, String>) - Static method in class openconsensus.resource.Resource
-
- create(Measure, double) - Static method in class openconsensus.stats.Measurement.MeasurementDouble
-
- create(Measure, long) - Static method in class openconsensus.stats.Measurement.MeasurementLong
-
- create(TagKey, TagValue, TagMetadata) - Static method in class openconsensus.tags.Tag
-
Creates a Tag
from the given key, value and metadata.
- create(String) - Static method in class openconsensus.tags.TagKey
-
Constructs a TagKey
with the given name.
- create(TagMetadata.TagTtl) - Static method in class openconsensus.tags.TagMetadata
-
- create(String) - Static method in class openconsensus.tags.TagValue
-
Constructs a TagValue
from the given string.
- create(String) - Static method in class openconsensus.trace.Event
-
Returns a new Event
with the given name.
- create(String, Map<String, AttributeValue>) - Static method in class openconsensus.trace.Event
-
Returns a new Event
with the given name and set of attributes.
- create(SpanContext) - Static method in class openconsensus.trace.Link
-
Returns a new Link
.
- create(SpanContext, Map<String, AttributeValue>) - Static method in class openconsensus.trace.Link
-
Returns a new Link
.
- create(TraceId, SpanId, TraceOptions, Tracestate) - Static method in class openconsensus.trace.SpanContext
-
Creates a new SpanContext
with the given identifiers and options.
- create(SpanContext, SpanId, Resource, String, Span.Kind, SpanData.Timestamp, Map<String, AttributeValue>, List<SpanData.TimedEvent>, List<Link>, Status, SpanData.Timestamp) - Static method in class openconsensus.trace.SpanData
-
Returns a new immutable SpanData
.
- create(SpanData.Timestamp, Event) - Static method in class openconsensus.trace.SpanData.TimedEvent
-
Returns a new immutable TimedEvent<T>
.
- create(long, int) - Static method in class openconsensus.trace.SpanData.Timestamp
-
Creates a new timestamp from given seconds and nanoseconds.
- create(String, String) - Static method in class openconsensus.trace.Tracestate.Entry
-
Creates a new Entry
for the Tracestate
.
- createDoubleMeasurement(double) - Method in interface openconsensus.stats.Measure
-
- createLongMeasurement(long) - Method in interface openconsensus.stats.Measure
-
- createTimeSeries(List<LabelValue>, T, ToDoubleFunction<T>) - Method in interface openconsensus.metrics.DerivedDoubleCumulative
-
Creates a TimeSeries
.
- createTimeSeries(List<LabelValue>, T, ToDoubleFunction<T>) - Method in interface openconsensus.metrics.DerivedDoubleGauge
-
Creates a TimeSeries
.
- createTimeSeries(List<LabelValue>, T, ToLongFunction<T>) - Method in interface openconsensus.metrics.DerivedLongCumulative
-
Creates a TimeSeries
.
- createTimeSeries(List<LabelValue>, T, ToLongFunction<T>) - Method in interface openconsensus.metrics.DerivedLongGauge
-
Creates a TimeSeries
.
- currentBuilder() - Method in interface openconsensus.tags.Tagger
-
Returns a new builder created from the current TagMap
.
- get(C, String) - Method in interface openconsensus.context.propagation.TextFormat.Getter
-
Returns the first value of the given propagation key
or returns null
.
- get(String) - Method in class openconsensus.trace.Tracestate
-
Returns the value to which the specified key is mapped, or null if this map contains no mapping
for the key.
- getAttributes() - Method in class openconsensus.trace.Event
-
Return the attributes of the Event
.
- getAttributes() - Method in class openconsensus.trace.Link
-
Returns the set of attributes.
- getAttributes() - Method in class openconsensus.trace.SpanData
-
Returns the attributes recorded for this Span
.
- getBinaryFormat() - Method in interface openconsensus.tags.Tagger
-
- getBinaryFormat() - Method in interface openconsensus.trace.Tracer
-
- getBooleanValue() - Method in class openconsensus.trace.AttributeValue
-
Returns the boolean value of this AttributeValue
.
- getByte() - Method in class openconsensus.trace.TraceOptions
-
Returns the one byte representation of the TraceOptions
.
- getCanonicalCode() - Method in class openconsensus.trace.Status
-
Returns the canonical status code.
- getContext() - Method in class openconsensus.trace.BlankSpan
-
- getContext() - Method in class openconsensus.trace.Link
-
Returns the TraceId
.
- getContext() - Method in interface openconsensus.trace.Span
-
Returns the SpanContext
associated with this Span
.
- getContext() - Method in class openconsensus.trace.SpanData
-
Returns the SpanContext
associated with this Span
.
- getCurrentSpan() - Method in interface openconsensus.trace.Tracer
-
Gets the current Span from the current Context.
- getCurrentTagMap() - Method in interface openconsensus.tags.Tagger
-
Returns the current TagMap
.
- getDefaultTimeSeries() - Method in interface openconsensus.metrics.DoubleCumulative
-
Returns a DoublePoint
for a cumulative with all labels not set, or default labels.
- getDefaultTimeSeries() - Method in interface openconsensus.metrics.DoubleGauge
-
Returns a DoublePoint
for a gauge with all labels not set, or default labels.
- getDefaultTimeSeries() - Method in interface openconsensus.metrics.LongCumulative
-
Returns a LongPoint
for a cumulative with all labels not set, or default labels.
- getDefaultTimeSeries() - Method in interface openconsensus.metrics.LongGauge
-
Returns a LongPoint
for a gauge with all labels not set, or default labels.
- getDescription() - Method in class openconsensus.metrics.LabelKey
-
Returns the description of this
LabelKey
.
- getDescription() - Method in class openconsensus.trace.Sampler
-
Returns the description of this Sampler
.
- getDescription() - Method in class openconsensus.trace.Status
-
Returns the description of this Status
for human consumption.
- getDoubleValue() - Method in class openconsensus.stats.Measurement
-
- getDoubleValue() - Method in class openconsensus.stats.Measurement.MeasurementDouble
-
- getDoubleValue() - Method in class openconsensus.trace.AttributeValue
-
Returns the double value of this AttributeValue
.
- getEmpty() - Static method in class openconsensus.resource.Resource
-
- getEndTimestamp() - Method in class openconsensus.trace.SpanData
-
Returns the end Timestamp
.
- getEntries() - Method in class openconsensus.trace.Tracestate
-
Returns a
List
view of the mappings contained in this
TraceState
.
- getEvent() - Method in class openconsensus.trace.SpanData.TimedEvent
-
Returns the event.
- getInstance() - Static method in class openconsensus.context.NoopScope
-
Returns a NoopScope
.
- getIterator() - Method in class openconsensus.tags.EmptyTagMap
-
- getIterator() - Method in interface openconsensus.tags.TagMap
-
Returns an iterator over the tags in this TagMap
.
- getKey() - Method in class openconsensus.metrics.LabelKey
-
- getKey() - Method in class openconsensus.tags.Tag
-
Returns the tag's key.
- getKey() - Method in class openconsensus.trace.Tracestate.Entry
-
Returns the key String
.
- getKind() - Method in class openconsensus.trace.SpanData
-
Returns the kind of this Span
.
- getLabels() - Method in class openconsensus.resource.Resource
-
Returns a map of labels that describe the resource.
- getLinks() - Method in class openconsensus.trace.SpanData
-
Returns links recorded for this Span
.
- getLongValue() - Method in class openconsensus.stats.Measurement
-
- getLongValue() - Method in class openconsensus.stats.Measurement.MeasurementLong
-
- getLongValue() - Method in class openconsensus.trace.AttributeValue
-
Returns the long value of this AttributeValue
.
- getLowerLong() - Method in class openconsensus.trace.TraceId
-
Returns the lower 8 bytes of the trace-id as a long value, assuming little-endian order.
- getMeasure() - Method in class openconsensus.stats.Measurement
-
- getMeasure() - Method in class openconsensus.stats.Measurement.MeasurementDouble
-
- getMeasure() - Method in class openconsensus.stats.Measurement.MeasurementLong
-
- getMeter() - Static method in class openconsensus.metrics.Metrics
-
Returns the global
Meter
with the provided implementation.
- getName() - Method in class openconsensus.tags.TagKey
-
Returns the name of the key.
- getName() - Method in class openconsensus.trace.Event
-
Return the name of the Event
.
- getName() - Method in class openconsensus.trace.SpanData
-
Returns the name of this Span
.
- getNanos() - Method in class openconsensus.trace.SpanData.Timestamp
-
Returns the number of nanoseconds after the number of seconds since the Unix Epoch
represented by this timestamp.
- getOrCreateTimeSeries(List<LabelValue>) - Method in interface openconsensus.metrics.DoubleCumulative
-
Creates a TimeSeries
and returns a DoublePoint
if the specified labelValues
is not already associated with this cumulative, else returns an existing DoublePoint
.
- getOrCreateTimeSeries(List<LabelValue>) - Method in interface openconsensus.metrics.DoubleGauge
-
Creates a TimeSeries
and returns a DoublePoint
if the specified labelValues
is not already associated with this gauge, else returns an existing DoublePoint
.
- getOrCreateTimeSeries(List<LabelValue>) - Method in interface openconsensus.metrics.LongCumulative
-
Creates a TimeSeries
and returns a LongPoint
if the specified labelValues
is not already associated with this cumulative, else returns an existing LongPoint
.
- getOrCreateTimeSeries(List<LabelValue>) - Method in interface openconsensus.metrics.LongGauge
-
Creates a TimeSeries
and returns a LongPoint
if the specified labelValues
is not already associated with this gauge, else returns an existing LongPoint
.
- getParentSpanId() - Method in class openconsensus.trace.SpanData
-
Returns the parent SpanId
or null
if the Span
is a root Span
.
- getResource() - Method in class openconsensus.trace.SpanData
-
Returns the resource of this Span
.
- getResource() - Method in interface openconsensus.trace.Tracer
-
- getSeconds() - Method in class openconsensus.trace.SpanData.Timestamp
-
Returns the number of seconds since the Unix Epoch represented by this timestamp.
- getSpanId() - Method in class openconsensus.trace.SpanContext
-
Returns the span identifier associated with this SpanContext
.
- getStartTimestamp() - Method in class openconsensus.trace.SpanData
-
Returns the start Timestamp
of this Span
.
- getStatsRecorder() - Static method in class openconsensus.stats.Stats
-
- getStatus() - Method in class openconsensus.trace.SpanData
-
Returns the Status
.
- getStringValue() - Method in class openconsensus.trace.AttributeValue
-
Returns the string value of this AttributeValue
.
- getTagger() - Static method in class openconsensus.tags.Tags
-
Returns the default Tagger
.
- getTagMetadata() - Method in class openconsensus.tags.Tag
-
- getTagTtl() - Method in class openconsensus.tags.TagMetadata
-
- getTagValue(TagKey) - Method in class openconsensus.tags.EmptyTagMap
-
- getTagValue(TagKey) - Method in interface openconsensus.tags.TagMap
-
Returns the TagValue
associated with the given TagKey
.
- getTextFormat() - Method in interface openconsensus.tags.Tagger
-
- getTextFormat() - Method in interface openconsensus.trace.Tracer
-
- getTimedEvents() - Method in class openconsensus.trace.SpanData
-
Returns the timed events recorded for this Span
.
- getTimestamp() - Method in class openconsensus.trace.SpanData.TimedEvent
-
Returns the Timestamp
of this event.
- getTraceId() - Method in class openconsensus.trace.SpanContext
-
Returns the trace identifier associated with this SpanContext
.
- getTraceOptions() - Method in class openconsensus.trace.SpanContext
-
Returns the TraceOptions
associated with this SpanContext
.
- getTracer() - Static method in class openconsensus.trace.Trace
-
- getTracestate() - Method in class openconsensus.trace.SpanContext
-
Returns the Tracestate
associated with this SpanContext
.
- getType() - Method in class openconsensus.trace.AttributeValue
-
Returns a Type
corresponding to the underlying value of this AttributeValue
.
- getValue() - Method in class openconsensus.metrics.LabelValue
-
- getValue() - Method in class openconsensus.tags.Tag
-
Returns the tag's value.
- getValue(Context) - Static method in class openconsensus.tags.unsafe.ContextUtils
-
Returns the value from the specified Context
.
- getValue() - Method in class openconsensus.trace.Tracestate.Entry
-
Returns the value String
.
- getValue(Context) - Static method in class openconsensus.trace.unsafe.ContextUtils
-
Returns the value from the specified Context
.
- Sampler - Class in openconsensus.trace
-
Sampler is used to make decisions on
Span
sampling.
- Sampler() - Constructor for class openconsensus.trace.Sampler
-
- Samplers - Class in openconsensus.trace.samplers
-
Static class to access a set of pre-defined
Samplers
.
- Scope - Interface in openconsensus.context
-
A
Closeable
that represents a change to the current context over a scope of code.
- set(double) - Method in interface openconsensus.metrics.DoubleGauge.DoublePoint
-
Sets the given value.
- set(long) - Method in interface openconsensus.metrics.LongGauge.LongPoint
-
Sets the given value.
- set(String, String) - Method in class openconsensus.trace.Tracestate.Builder
-
Adds or updates the Entry
that has the given key
if it is present.
- setAttribute(String, String) - Method in class openconsensus.trace.BlankSpan
-
- setAttribute(String, long) - Method in class openconsensus.trace.BlankSpan
-
- setAttribute(String, double) - Method in class openconsensus.trace.BlankSpan
-
- setAttribute(String, boolean) - Method in class openconsensus.trace.BlankSpan
-
- setAttribute(String, AttributeValue) - Method in class openconsensus.trace.BlankSpan
-
- setAttribute(String, String) - Method in interface openconsensus.trace.Span
-
Sets an attribute to the Span
.
- setAttribute(String, long) - Method in interface openconsensus.trace.Span
-
Sets an attribute to the Span
.
- setAttribute(String, double) - Method in interface openconsensus.trace.Span
-
Sets an attribute to the Span
.
- setAttribute(String, boolean) - Method in interface openconsensus.trace.Span
-
Sets an attribute to the Span
.
- setAttribute(String, AttributeValue) - Method in interface openconsensus.trace.Span
-
Sets an attribute to the Span
.
- setComponent(String) - Method in interface openconsensus.metrics.MetricRegistry.Builder
-
Sets the name of the component that reports these metrics.
- setConstantLabels(Map<LabelKey, LabelValue>) - Method in interface openconsensus.metrics.Metric.Builder
-
Sets the map of constant labels (they will be added to all the TimeSeries) for the Metric.
- setDescription(String) - Method in interface openconsensus.metrics.Metric.Builder
-
Sets the description of the Metric.
- setDescription(String) - Method in interface openconsensus.stats.Measure.Builder
-
Sets the detailed description of the measure, used in documentation.
- setIsSampled(boolean) - Method in class openconsensus.trace.TraceOptions.Builder
-
Sets the sampling bit in the options.
- setLabelKeys(List<LabelKey>) - Method in interface openconsensus.metrics.Metric.Builder
-
Sets the list of label keys for the Metric.
- setRecordEvents(boolean) - Method in interface openconsensus.trace.Span.Builder
-
Sets the option to record events even if not sampled for the newly created Span
.
- setResource(Resource) - Method in interface openconsensus.metrics.MetricRegistry.Builder
-
Sets the Resource
associated with the new MetricRegistry
.
- setResource(Resource) - Method in interface openconsensus.trace.Tracer
-
- setSampler(Sampler) - Method in interface openconsensus.trace.Span.Builder
-
- setSpanKind(Span.Kind) - Method in interface openconsensus.trace.Span.Builder
-
Sets the
Span.Kind
for the newly created
Span
.
- setStatus(Status) - Method in class openconsensus.trace.BlankSpan
-
- setStatus(Status) - Method in interface openconsensus.trace.Span
-
- setType(Measure.Type) - Method in interface openconsensus.stats.Measure.Builder
-
Sets the Type
corresponding to the underlying value of this Measure
.
- setUnit(String) - Method in interface openconsensus.metrics.Metric.Builder
-
Sets the unit of the Metric.
- setUnit(String) - Method in interface openconsensus.stats.Measure.Builder
-
Sets the units in which Measure
values are measured.
- shouldSample(SpanContext, Boolean, TraceId, SpanId, String, List<Span>) - Method in class openconsensus.trace.Sampler
-
Called during
Span
creation to make a sampling decision.
- SIZE - Static variable in class openconsensus.trace.SpanId
-
The size in bytes of the SpanId
.
- SIZE - Static variable in class openconsensus.trace.TraceId
-
The size in bytes of the TraceId
.
- SIZE - Static variable in class openconsensus.trace.TraceOptions
-
The size in bytes of the TraceOptions
.
- Span - Interface in openconsensus.trace
-
An interface that represents a span.
- Span.Builder - Interface in openconsensus.trace
-
Span.Builder
is used to construct
Span
instances which define arbitrary scopes of
code that are sampled for distributed tracing as a single atomic unit.
- Span.Kind - Enum in openconsensus.trace
-
Type of span.
- spanBuilder(String) - Method in interface openconsensus.trace.Tracer
-
Returns a
Span.Builder
to create and start a new child
Span
as a child of to
the current
Span
if any, otherwise creates a root
Span
.
- spanBuilderWithExplicitParent(String, Span) - Method in interface openconsensus.trace.Tracer
-
Returns a
Span.Builder
to create and start a new child
Span
(or root if parent
is
null
or has an invalid
SpanContext
), with parent being the designated
Span
.
- spanBuilderWithRemoteParent(String, SpanContext) - Method in interface openconsensus.trace.Tracer
-
- SpanContext - Class in openconsensus.trace
-
A class that represents a span context.
- SpanData - Class in openconsensus.trace
-
Immutable representation of all data collected by the
Span
class.
- SpanData.TimedEvent - Class in openconsensus.trace
-
A timed event representation.
- SpanData.Timestamp - Class in openconsensus.trace
-
A representation of an instant in time.
- SpanId - Class in openconsensus.trace
-
A class that represents a span identifier.
- startSpan() - Method in interface openconsensus.trace.Span.Builder
-
- startSpanAndCall(Callable<V>) - Method in interface openconsensus.trace.Span.Builder
-
Starts a new span and calls the given Callable
with the newly created Span
as
the current Span
, and ends the Span
after the Callable
is called.
- startSpanAndRun(Runnable) - Method in interface openconsensus.trace.Span.Builder
-
Starts a new span and runs the given Runnable
with the newly created Span
as
the current Span
, and ends the Span
after the Runnable
is run.
- Stats - Class in openconsensus.stats
-
- StatsRecorder - Interface in openconsensus.stats
-
Provides methods to record stats against tags.
- Status - Class in openconsensus.trace
-
Defines the status of a
Span
by providing a standard
Status.CanonicalCode
in conjunction
with an optional descriptive message.
- Status.CanonicalCode - Enum in openconsensus.trace
-
The set of canonical status codes.
- stringAttributeValue(String) - Static method in class openconsensus.trace.AttributeValue
-
Returns an AttributeValue
with a string value.
- Tag - Class in openconsensus.tags
-
- Tagger - Interface in openconsensus.tags
-
Object for creating new
TagMap
s and
TagMap
s based on the current context.
- TagKey - Class in openconsensus.tags
-
A key to a value stored in a
TagMap
.
- TagMap - Interface in openconsensus.tags
-
A map from
TagKey
to
TagValue
and
TagMetadata
that can be used to label
anything that is associated with a specific operation.
- TagMapBuilder - Interface in openconsensus.tags
-
- TagMetadata - Class in openconsensus.tags
-
- TagMetadata.TagTtl - Enum in openconsensus.tags
-
- Tags - Class in openconsensus.tags
-
Class to access the global
Tagger
.
- TagValue - Class in openconsensus.tags
-
A validated tag value.
- TextFormat<V> - Interface in openconsensus.context.propagation
-
Injects and extracts a value as text into carriers that travel in-band across process boundaries.
- TextFormat.Getter<C> - Interface in openconsensus.context.propagation
-
Interface that allows a TextFormat
to read propagated fields from a carrier.
- TextFormat.Setter<C> - Interface in openconsensus.context.propagation
-
Class that allows a TextFormat
to set propagated fields into a carrier.
- toBuilder(TagMap) - Method in interface openconsensus.tags.Tagger
-
Returns a builder based on this TagMap
.
- toBuilder() - Method in class openconsensus.trace.Tracestate
-
Returns a Builder
based on this Tracestate
.
- toByteArray(V) - Method in interface openconsensus.context.propagation.BinaryFormat
-
Serializes the value
into the on-the-wire representation.
- ToDoubleFunction<T> - Interface in openconsensus.metrics
-
Represents a function that produces a double-valued result.
- ToLongFunction<T> - Interface in openconsensus.metrics
-
Represents a function that produces a long-valued result.
- toLowerBase16() - Method in class openconsensus.trace.SpanId
-
Returns the lowercase base16 encoding of this SpanId
.
- toLowerBase16() - Method in class openconsensus.trace.TraceId
-
Returns the lowercase base16 encoding of this TraceId
.
- toLowerBase16() - Method in class openconsensus.trace.TraceOptions
-
Returns the lowercase base16 encoding of this TraceOptions
.
- toStatus() - Method in enum openconsensus.trace.Status.CanonicalCode
-
Returns the status that has the current CanonicalCode
..
- toString() - Method in class openconsensus.trace.BlankSpan
-
- toString() - Method in class openconsensus.trace.SpanContext
-
- toString() - Method in class openconsensus.trace.SpanId
-
- toString() - Method in class openconsensus.trace.Status
-
- toString() - Method in class openconsensus.trace.TraceId
-
- toString() - Method in class openconsensus.trace.TraceOptions
-
- Trace - Class in openconsensus.trace
-
Class that manages a global instance of the
Tracer
.
- TraceId - Class in openconsensus.trace
-
A class that represents a trace identifier.
- TraceOptions - Class in openconsensus.trace
-
A class that represents global trace options.
- TraceOptions.Builder - Class in openconsensus.trace
-
- Tracer - Interface in openconsensus.trace
-
Tracer is a simple, interface for
Span
creation and in-process context interaction.
- Tracestate - Class in openconsensus.trace
-
Carries tracing-system specific context in a list of key-value pairs.
- Tracestate.Builder - Class in openconsensus.trace
-
- Tracestate.Entry - Class in openconsensus.trace
-
Immutable key-value pair for Tracestate
.
- value() - Method in enum openconsensus.trace.Status.CanonicalCode
-
Returns the numerical value of the code.
- valueOf(String) - Static method in enum openconsensus.stats.Measure.Type
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum openconsensus.tags.TagMetadata.TagTtl
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum openconsensus.trace.AttributeValue.Type
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum openconsensus.trace.Span.Kind
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum openconsensus.trace.Status.CanonicalCode
-
Returns the enum constant of this type with the specified name.
- values() - Static method in enum openconsensus.stats.Measure.Type
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum openconsensus.tags.TagMetadata.TagTtl
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum openconsensus.trace.AttributeValue.Type
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum openconsensus.trace.Span.Kind
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum openconsensus.trace.Status.CanonicalCode
-
Returns an array containing the constants of this enum type, in
the order they are declared.


Twitter
You can fetch, store and display data about your own Tweets and Liked Tweets for one or more Twitter accounts. By default the included models and templates will link to image and video files at Twitter, but you can also download the original files to store locally. These can then be used to serve different sizes of images locally. See the Fetch Files management command below.
Set-up
Go to https://developer.twitter.com/portal. You’ll need to sign up for a Developer Account, and then create a new App for your Twitter account. Note down the three credentials it says that you should note down.
When viewing your App’s details, click the “Edit” button, then the “Keys and tokens” tab.
In the “Access Token and Secret” section, tap the “Generate” button. Make a note of the Access Token and Access Token Secret.
Django Ditto currently uses the v1.1 Twitter API rather than the latest v2. Unfortunately, accessing v1.1 requires that you apply for “Elevated” access before the API calls used will work. You can do that here: https://developer.twitter.com/en/portal/products/elevated You will then need to wait for approval.
Once you have that, go to the Django admin, and add a new Account
in the Twitter app. Copy the API Key, API Key Secret, Access Token and Access Token Secret from your Twitter App into the Django admin (ignore the other fields), and save the account. A new User
object will be created, reflecting the Twitter user your API credentials are associated with. If it’s worked your Account should have a title like @philgyford instead of a number like 1.
Once this is done you’ll need to import a downloaded archive of Tweets, and/or fetch Tweets from the Twitter API. See Management commands below.
Models
The models available in ditto.twitter.models
are:
Account
Representing a Twitter account that has API credentials and that we fetch Tweets and/or Likes for. It has a one-to-one relationship with a
User
model.Media
A photo, video or Animated GIF that was attached to one or more Tweets. Its
media_type
property differentiates between'photo'
,'video'
and'animated_gif'
. (Yes, the plural model name is a bit confusing, sorry.) The files for photos and animated GIFs can be fetched from Twitter and used locally, although this isn’t the default. See the Fetch Files management command below.Tweet
A Tweet. It may have been posted by one of the Users with an
Account
that we fetch Twets for. Or it might have been posted by a differentUser
and favorited/liked by one of the Users with anAccount
.User
A Twitter user. Every time a Tweet is fetched a new
User
object is created/updated for the person who posted it. One or more of these Users will have an associatedAccount
, as these are the user(s) we fetch data for.
So, you will end up with many User
objects in the system. But only one (or a few) will be associated with Account
objects – these are the Users for which you fetch Tweets or favorited/liked Tweets.
Managers
Media
For Media
objects there is only the standard manager available:
Media.objects.all()
Fetches all
Media
objects, attached to Tweets by anyone, whether public or private.
There is no concept in Twitter of a ‘private’ photo or video. The same photo
could be posted by different public and private Twitter users. Exercise caution
when displaying Media
objects to public webpages.
Tweet
Tweet
models have several managers. There are two main differentiators we want to restrict things by:
Public vs private: Whether a Tweet was posted by a public or private Twitter user.
Posted Tweet vs Favorited Tweet: Sometimes we’ll want to only fetch Tweets posted by one of the Users with an API-credentialed Account. Sometimes we’ll want to only fetch Tweets those Accounts have favorited/liked. Sometimes we’ll want to fetch ALL Tweets, whether posted or favorited.
On public-facing web pages you should only use the managers starting Tweet.public_
as these will filter out all Tweets posted by private Twitter users.
Tweet.objects.all()
The default manager fetches all Tweets in the system, posted by all Users, whether they’re public or private, and whether posted by an Account’s User or favorited by them.
Tweet.public_objects.all()
Only gets Tweets posted by any Users who are not private. This includes Tweets that have simply been favorited/liked by one of your Accounts.
Tweet.tweet_objects.all()
Only gets Tweets posted by a User with an Account, not favorited by them. And from both public and private Users.
Tweet.public_tweet_objects.all()
Only gets Tweets posted by a User with an Account, not favorited by them, but only for Users who aren’t private. For use on public pages.
Tweet.favorite_objects.all()
Only gets Tweets favorited by a User with an Account, whether those Tweets are posted by public or private Users.
Tweet.public_favorite_objects.all()
Only gets Tweets favorited by a User with an Account, and only Tweets posted by Users who aren’t private.
Of course, these can all be filtered as usual. So, if you wanted to get all the public Tweets posted by a particular User
:
from ditto.twitter.models import User, Tweet
user = User.objects.get(screen_name='philgyford')
tweets = Tweet.public_tweet_objects.filter(user=user)
And to get public Tweets that user has favorited:
favorites = Tweet.public_favorite_objects.filter(user=user)
Management commands
Import Tweets
If you have more than 3,200 Tweets, you can only include older Tweets by downloading your archive and importing it. To do so, request your archive at https://twitter.com/settings/download_your_data . When you’ve downloaded it, do:
$ ./manage.py import_twitter_tweets --path=/path/to/twitter-2022-01-31-123456abcdef
using the correct path to the directory you’ve downloaded and unzipped (in this case, the unzipped directory is twitter-2022-01-031-123456abcdef
). This will import all of the Tweets found in the archive and all of the images and animated GIFs’ MP4 files (other videos aren’t currently imported).
NOTE: If you have an archive of data you downloaded before sometime in early 2019 it will be a different format. You can tell because the folder will contain five directories, and three files: index.html
, README.txt
, and tweets.csv
. If you want to import an archive in this format add the –archive-version=v1 argument:
$ ./manage.py import_twitter_tweets --archive-version=v1 --path=/path/to/123456_abcdef
using the correct path to the directory (in this case, the unzipped directory is 123456_abcdef
). This will import Tweet data but no images etc, because these files weren’t included in the older archive format.
 To fully-populate those Tweets you should run this (replacing philgyford
with your Twitter screen name):
$ ./manage.py update_twitter_tweets --account=philgyford
This will fetch data for up to 6,000 Tweets. If you have more than that in your archive, run it every 15 minutes to avoid rate limiting, until you’ve fetched all of the Tweets. This command will fetch data for the least-recently fetched. It’s worth running every so often in the future, to fetch the latest data (such as Retweet and Like counts).
Fetch Tweets
Periodically you’ll want to fetch the latest Tweets. This will fetch only those Tweets posted since you last fetched any:
$ ./manage.py fetch_twitter_tweets --account=philgyford --recent=new
You might also, or instead, want to fetch more than that. Here we fetch the most recent 200:
$ ./manage.py fetch_twitter_tweets --account=philgyford --recent=200
This would update data such as the Retweet and Like counts for all of the 200 fetched Tweets, even if they’re older than your last fetch. It’s fine to fetch data about Tweets you’ve already fetched; their data will be updated.
If you have more than one Twitter Account in Ditto, the above commands can be run across all of them by omitting the --account
option. eg:
$ ./manage.py fetch_twitter_tweets --recent=new
Fetch Favorites
To fetch recent Tweets that all your Accounts have favorited/liked, run one of these:
$ ./manage.py fetch_twitter_favorites --recent=new
$ ./manage.py fetch_twitter_favorites --recent=200
Or restrict to Tweets favorited/liked by a single Account:
$ ./manage.py fetch_twitter_favorites --account=philgyford --recent=new
$ ./manage.py fetch_twitter_favorites --account=philgyford --recent=200
Update Users
When a Tweet of any kind is fetched, its User data is also stored, and the User’s profile photo (avatar) is downloaded and stored in your project’s MEDIA_ROOT
directory. You can optionally set the DITTO_TWITTER_DIR_BASE
setting to change the location. The default is:
DITTO_TWITTER_DIR_BASE = 'twitter'
If your MEDIA_ROOT
was set to /var/www/example.com/media/
then the above setting would save the profile image for the user with a Twitter ID 12345678
to something like this:
/var/www/example.com/media/twitter/avatars/56/78/12345678/my_avatar.jpg
You may periodically want to update the stored data about all the Twitter users stored in Ditto. (quantity of Tweets, descriptions, etc). Do it like this:
$ ./manage.py update_twitter_users --account=philgyford
This requires an account
as the data is fetched from that Twitter user’s point of view, when it comes to privacy etc.
Fetch Files (Media)
Fetching Tweets (whether your own or your favorites/likes) fetches all the data about them, but does not fetch any media files uploaded with them. There’s a separate command for fetching images and the MP4 video files created from animated GIFs. (There’s no way to fetch the videos, or original GIF files.)
You must first download the Tweet data (above), and then you can fetch the files for all those Tweets:
$ ./manage.py fetch_twitter_files
This will fetch the files for all Tweets whose files haven’t already been fetched. So, the first time, it’s all the Tweets’ files, which can take a while.
If you want to force a re-fetching of all files, whether they’ve already been downloaded or not:
$ ./manage.py fetch_twitter_files --all
Each image/MP4 is associated with the relevant Tweet(s) and saved within your project’s MEDIA_ROOT
directory, as defined in settings.py
. There’s one optional setting to customise the directory in which the files are saved. Its default value is as shown here:
DITTO_TWITTER_DIR_BASE = 'twitter'
Files are organised into separate directories according to the final characters of their file names (so as not to have too many in one directory). eg, an image might be saved in:
/var/www/example.com/media/twitter/media/6T/ay/CRXEfBEWUAA6Tay.png
Every uploaded image, animated GIF and video should have a single image. Animated GIFs will also have an MP4 file.
Once you’ve downloaded the original files, you can use these to generate all the different sizes of image required for your site, instead of linking direct to the image files on Twitter. To do this, ensure imagekit
is in your INSTALLED_APPS
setting:
INSTALLED_APPS = (
# ...
'imagekit',
# ...
)
And add this to your settings.py (its default value is False
):
DITTO_TWITTER_USE_LOCAL_MEDIA = True
Any requests in your templates for the URLs of photo files of any size will now use resized versions of your downloaded original files, generated by Imagekit. The first time you load a page (especially if it lists many images) it will be slow, but the images are cached (in a CACHE
directory in your media folder).
For example, before changing this setting, the URL of small image (Media.small_url
) would be something like this:
https://pbs.twimg.com/media/CjuCDVLXIAALhYz.jpg:small
After choosing to use local photos, it would be something like this:
/media/CACHE/images/twitter/media/Lh/Yz/CjuCDVLXIAALhYz/5a726ea25d3bbd1b35b21b8b61b98c4c.jpg
If you change your mind you can switch back to using the images hosted on Twitter by removing the DITTO_TWITTER_USE_LOCAL_MEDIA
setting or changing it to False
.
Animated GIFs are converted into MP4 videos when first uploaded to Twitter. Ditto downloads and uses these in a similar way to images. ie, by default the video_url
property of a Media
object that’s an Animated GIF would be like:
https://pbs.twimg.com/tweet_video/CRXEfBEWUAA6Tay.mp4
If it’s been downloaded and DITTO_TWITTER_USE_LOCAL_MEDIA
is True
then
calling video_url
would return a URL like:
/media/twitter/media/6T/ay/CRXEfBEWUAA6Tay.mp4
However, there’s no way to download actual videos that were uploaded to Twitter, and so Ditto will always try to use videos hosted on Twitter, no matter what the value of DITTO_TWITTER_USE_LOCAL_MEDIA
.
Fetch Accounts
Deprecated: This only needs to be used whenever a new Account
is added to the system. It fetches the User
data for each Account
that has API credentials, and associates the two objects.
$ ./manage.py fetch_twitter_accounts
I don’t think this is needed now.


Guidelines about how to install and use the Google Maps Draw Module
Google Maps Draw Module is a useful tool for web developers who want to build web apps for creating maps and draw shapes in the front end. It is based on modern tools such as Google API v3, jQuery, Javascript, Bootstrap, HTML5 and CSS3.
This module provides a responsive web interface to users for adding markers and drawing polygons, rectangles, polylines and circles in order to create maps online. Users are able to add/edit/delete objects on Google Maps. Also users can enter title and description for all objects they create.
Basic information of all objects added (title, coords) are located in HTML input elements, so developers can use them in any way by submitting the form.
The module has a geocoding tool for searching an area and center map on this location.
For a full demonstration of Google Maps Draw Module, PHP and Mysql was used for storing maps created in database, for loading objects to display on map, editing and deletings maps.
Current Google Maps Draw Module demonstration can work on any web server which support PHP (at least v5.4) and MySQL (at least .5.3).
In order to start using this module, you have to follow steps below for installation:
Google Maps Draw Module provides a responsive web interface to users for adding markers and drawing polygons, rectangles, polylines and circles in order to create maps online.
The module has a geocoding tool for searching an area by name or coordinates and center map on this location.
When click on Create Map, an interactive map is displayed so users can select various shapes for adding to this map. The available shapes are:
If select markers, then user has just click on the map to locate each marker having also the option to move it on the desired location. By clicking on "Change icon" button, the user can change the icon of marker to add.
If select polylines or polygons or rectangles or circles, when click on "Add" button a corresponding editable shape is added on the map. So the user is able to modify the shape and also move it to the desired location. By clicking on "Save" button, the shape becomes not editable and the user can add another shape.
For each shape added on the map, the user can also enter a title/description. Finally the user can enter title and description for the map created.
For each shape added, there are buttons for editing and removing before saving. Also when click an "Clear All" button, all objects from the map will be removed.
When finish editing the map, user must click on "Submit" button, so the map and all connected shapes will be stored on database.
For retrieving any map stored, click on "Browse Maps" and then click on a map title from the list displayed.
The zip file contains the following files and directories:
For any customization required on creating maps and drawing objects on map, the following files have to be modified:
For any customizations on HTML views, modifications could be made in files at "view" folder.
For translating more languages, is required to add the appropriate file in folder "languages" (e.g. copy from en.php). Also the new language must be added in file "includes/config.php.".
1.4 (17 Aug 2015)
------------------------------------------
- Added the option of displaying a global map which contains all objects created by all users
- Added full page map view, so it's possible to use a map on other pages or sites using iframe
- Added option for admin to select which types of map objects will be available for users (e.g. enable only markers and polygons)
- Added option for admin to enable/disable the list of check boxes with available objects on each map
- Added multilanguage support
- Several code improvements
1.3 (13 May 2015)
------------------------------------------
- Added OpenStreetMap layer
- Added calculation of area for polygons, rectangles and circles
- Added option to change icon on markers
- Added checkboxes for each group of objects to show/hide on map
- Added option to add marker on current user's location
- Map options (center, zoom, type) are stored now in database
- New objects are automatically resized depending on the zoom level
- Added config file for setting basic options of the application
- Fixed issue when viewing a map, so the markers are not draggable
- Several code improvements
1.2 (20 Mar 2015)
------------------------------------------
- Fixed bug when editing markers
1.1 (2 Jan 2015)
------------------------------------------
- Added option for editing existing maps
- Code improvements
1.0 (28 Dec 2014)
------------------------------------------
Initial release


Dogs needed to star in opera at Wolverhampton Grand
Dogs with star quality are wanted to appear on the Wolverhampton Grand stage.
by James VukmirovicIf you're dog is well behaved, small, used to being around people and quiet then award-winning director and producer Ellen Kent wants to hear from you.
Ms Kent is directing opera La Boheme at the Grand Theatre in Wolverhampton on January 26.
She said: "People say never work with children or animals, but I love to do both. The first time was 20 years ago when my pet cat Holly Go-Lightly was in one of my productions and was an instant hit.
"Since then, we’ve had horses, dogs, goldfish and even a golden eagle with a 6ft wingspan on stage. Many years ago, when we last did La Boheme and asked local people to volunteer their pets it was a huge success.
"We even used a rescue dog once and found him dozens of new owners. We’re a nation of animal lovers after all. I’m sure there is plenty of doggie talent out there."
Puccini's opera is based on Henri Murger’s novel Scenes de la vie de Boheme and focuses on the tragic love between seamstress Mimi and penniless poet Rodolfo.
Anyone wishing to audition their dog should send a photograph to Angela Klappa by email to<EMAIL_ADDRESS>Please include a contact number and address as well as the breed, height, weight, age and name of the dog.
Tickets for La Boheme on January 26 2020 are on sale now at grandtheatre.co.uk, by calling 01902 42 92 12 or by visiting the Lichfield Street Box Office in person.


Jazz is a genre that originated in the late nineteenth and early twenty century
Country music is an american popular that originated in...
Rock is popular american music that....
Each day we have free song selected especially for you


WaMDaM_v1.05 [WaMDaM_DBWrench_Schema_v1.05.xml]
| Table Name | Comment |
| AttributeCategories | Organizes attributes under a group as in their original data source (e.g., hydropower attributes) |
| Attributes | It is a bridge tables that allow associating many Object Types with many attributes. Users also can share the same native attribute across different object types like Capital Cost attribute that is shared for all the WEAP Objects |
| ObjectCategories | Organizes objects under a group as in their original data source (e.g., small and big reservoirs) |
| ObjectTypes | An Object Type is the building element of a dataset that modelers customize its attributes to represent a distinct water system component (e.g., reservoir or a river) in their models (data structures). An Object Type may represent physical and existing water components or to represent conceptual objects like representing water gains and losses in a river though a virtual node object at a point on a river. |
| ResourceTypes | A ResourceType Structure is a particular configuration and arrangement of Object Types and their Attributes in a dataset (e.g., model) for a specific domain (e.g., water supply, wastewater collection, storm water). |
| WaMDaMVersion | Stores the version of WaMDaM database to keep track of changes and help validate the database when used in the Wizard |
(none)
(none)
(none)


Here’s some showable/hideable content.
details
You know that’s right.
Yes yes y’all.
It does not stop, no.


This site is based on an algorithm that learns about your consumption of different products and tell you when you will be running out in advance.
Useful for item such as :
Your hub is where you can get all the information on your consumption and your items.
It is were you can :
The more data you give us, the more accurate the models for you and newcomers should become.
However, we feel that you should not be forced to give us data that you do not want to give.
We take your privacy seriously. Your data will be kept to update your current predictions.
If we use your data in any other way, it will be done by removing anything that could identify you.


Fun Learning Project
Flarn
Design & Development
Flarn is a Fun Learning platform where people can sign up and solve simple fun questions.
It is built with Spring Boot with a Postgres database and VueJS. It is hosted on Heroku and Netlify.
Flarn follows good design patterns and practices.
Users are able to view their timeline using their own activities and stories (activities from users they follow).
Users can then attempt problems, view people on the platform and subscribe to other users.
Users can then vie the various ranking of other users. People gain points as they solve more problems. Users can
also edit their profile by uploading new profile pictures.
Different (learners, moderators, admin) have a different views of the user interface.
Project GitHub


SURVOL USE CASES
This
page summarizes very different use cases, on various platforms. They
share a common scenario:
- Choosing a running process or an application
- Then trying to have as much information as possible, by
trial and error.
The
results are presented as commented images, and some hypothesis based on
them. Several successive Survol versions might be used in these
explorations, because the software
evolves based on these use cases. Still, the core
functionalities and general interface behaviour are stable.
Return to Survol, or see
the FAQs, architecture, the installation notes,
or Doxygen-generated
pages here.


{{=T("This form allows the administrator to remove a duplicate location.")}}
{{=T("Select 2 potential locations from the dropdowns.")}}
{{=T("Load the details to help decide which is the best one to keep out of the 2.")}}
{{=T("Copy any data from the one to be deleted into the one to keep")}}
{{=T("Save any Changes in the one you wish to keep")}}
{{=T("Press the 'Delete Old' button to have all records which reference this one be repointed at the new one & then the old record will be deleted.")}}


Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Serves 8
Little lamb chops are coated in breadcrumbs and simply fried. Serve with braised red cabbage and buttered potatoes for an easy dinner party dish.
For the red cabbage, melt the butter in a large saucepan and gently fry the onion until soft. Add the red cabbage and cook for 2 minutes. Add the apple, vinegar, blueberries, brown sugar, bramble jelly, cloves, cinnamon stick and 125ml/4fl oz water. Season with 20 turns of a black pepper mill and the salt. Cover with a tight-fitting lid and cook for 45 minutes, then check the liquid, if drying out add a splash more water; if there is a lot of liquid in the pan, remove the lid so any excess evaporates. Cook for another 15 minutes.
For the lamb, season the chops with salt and pepper. Put the flour, beaten eggs and breadcrumbs in separate shallow bowls. Toss the chops in the flour, then dip in the beaten egg and coat with the breadcrumbs.
Heat the butter and oil in a large frying pan. Once hot, fry the chops until golden-brown all over and cooked through (about 7–8 minutes on each side).
To serve, remove the cinnamon stick and cloves from the cabbage. Serve the cabbage and chops with boiled new potatoes rolled in melted butter and sprinkled with chopped parsley.


Snack Foods
Items made daily!
Fruit Salsa
Sides
Vegetables
Salads
Chicken Salads
Pimento Cheese
Breads
Desserts
Home
Snack Foods
Weekly Menus
Place an Order
Contact


This low-level module reads data from a visit connection.
module VisitReader<src_file="VisitReader.c"> { int+IPort2 SockID = -1; int+IPort2 Trigger = 0; omethod+notify_inst VisitReader_inst( TimeStamp+write, n1+read+write, n2+read+write, n3+read+write, n4+read+write, DataIntSize+write, DataInt+write, DataShortSize+write, DataShort+write, DataByteSize+write, DataByte+write, DataDoubleSize+write, DataDouble+write, DataString+write, DataIntScalar+write, DataByteScalar+write, DataShortScalar+write, DataDoubleScalar+write ) = "VisitReader_inst"; omethod+req VisitReader_read( SockID+read+req, Trigger+read+notify+req, TimeStamp+write, n1+write, n2+write, n3+write, n4+write, DataIntSize+write, DataInt+write, DataByteSize+write, DataByte+write, DataShortSize+write, DataShort+write, DataDoubleSize+write, DataDouble+write, DataString+write, DataIntScalar+write, DataShortScalar+write, DataByteScalar+write, DataDoubleScalar+write ) = "VisitReader_read"; double+OPort2 TimeStamp; int+OPort2 n1 = -1; int+OPort2 n2 = -1; int+OPort2 n3 = -1; int+OPort2 n4 = -1; int o1 = -1; int o2 = -1; int o3 = -1; int o4 = -1; int s1 = -1; int s2 = -1; int s3 = -1; int s4 = -1; int DataIntSize = 0; int+OPort2 DataInt[DataIntSize]; int DataByteSize = 0; byte+OPort2 DataByte[DataByteSize]; int DataShortSize = 0; short+OPort2 DataShort[DataShortSize]; int DataDoubleSize = 0; double+OPort2 DataDouble[DataDoubleSize]; string+OPort2 DataString; int+OPort2 DataIntScalar; byte+OPort2 DataByteScalar; short+OPort2 DataShortScalar; double+OPort2 DataDoubleScalar; };
This module reads data from a remote application. The remote application it should connect to is specified by the SockID input. This input will normally be provided by the VisitServer module that has created the connection. The module is triggered whenever data arrives at the Trigger port. The Trigger input can be connected directly to the Trigger output port of a VisitServer if only one VisitReader or VisitWriter module is being used. If more than one VisitReader or VisitWriter is connected to a VisitServer it is necessary to use a Multiplexer in order to select a VisitReader or VisitWriter module for each request. There is no implicit distinction between read and write requests. Therefore the user is responsible for using different IDs for read and write requests.
Whenever the module is triggered data is read from the remote application and presented on the output ports. The output values TimeStamp and n1 ... n4 contain the header-information that has been sent by the remote application (using the
visit_send_4d
orvisit_send_string
function calls). The Data... output ports contain the data values that have been sent by the remote application. Depending on the type of data that has been sent the data will be presented on the appropriate Data output port. With a field of length n1=n2=n3=n4=1 the data is presented at both a vector and a scalar output port.The VisitReader module should be used in conjunction with the modules Multiplexer, VisitServer and VisitWriter.
Before this module can be compiled and used the VISIT library must be installed. For information on how to install this library please see the VISIT library(http://www.fz-juelich.de/zam/visit) home page. A complete set of documentation for the VISIT-library can also be found at this URL.
The Visit IAC project assumes that the VISIT library has been installed into the default directory i.e.
/usr/local/visit/
If this is not the case then the references to that directory in the visit_mods.v file will have to be modified.
SockID
Integer input port that contains a socket descriptor. This socket descriptor specifies the data-connection to the remote application. This input port should be connected to the SockID output port of the VisitServer module.
Trigger
When this input is triggered the VisitReader module will attempt to read a message from the remote application. Normally this port should be connected to the Trigger output port of the VisitServer module. This should be done by either making a direct connection or making an indirect connection through a Multiplexer module.
Timestamp, n1, n2, n3, n4
Contain the header-information that has been sent by the remote application (using the visit_send_4d or visit_send_string function calls).
DataString
If the datatype of the read message is STRING this output port will present the data contained in the message.
DataInt, DataShort, DataByte, DataDouble
If the read message contains numerical data the values will be presented at one of these array outputs. The output used depends upon the datatype of the read message. If the message only contains a single value the value will also be presented at the appropriate scalar output.
DataIntScalar, DataShortScalar, DataByteScalar, DataDoubleScalar
If the read message contains a single numerical value the value will be presented at one of these scalar outputs. The output used depends upon the datatype of the read message. If the message contains more than one value these outputs will not used.
The low-level module VisitReader is used in the Functional Macro visitreader.
Examples of the use of this module can be found in the VisitSimpleEg and VisitGoLEg example applications.
xp_comm_proj/visit/visit_mods.v contains the V definition of the VisitReader module.
By default the low-level library VisitMods, which needs to be compiled, has the process set to express. Therefore express must not be running while this project is compiled.
Before the Visit project can be compiled the VISIT library must be installed, configured and compiled. For full instructions please see the VISIT library web-site.
The Visit IAC project assumes that the VISIT library has been installed into the default directory i.e.
/usr/local/visit/
If this is not the case then the references to that directory in the visit_mods.v file will have to be modified.
Wolfgang Frings Central Institute for Applied Mathematics Research Center Juelich D-52425 Juelich Germany
Ma YingLiang, Manchester Visualization Centre Andrew Dodd, International AVS Centre


Inspired by the evolution of Text Adventures and 8-Bit computer games The Arcade de Bruno, is a way of playing games that illustrate biological mechanisms that are established and falsified enough to become the Black Boxes Bruno Latour talks about; established ready-made science much in common with the kits I'm thinking about.
These games illustrate biological mechanisms that are established and falsified enough to become Black Boxes
Use the red and green buttons to tab through links and white to select and the black button to return here. blue and yellow move up and down through links
Black Box Phage is a game made in html5
& bitsy
showing how Bacteriophage interact with cells. This Black Box has helped humans to end things like Tuberculosis and Smallpox and without it the structure of DNA may never have been found.


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GimmeMotifs documentation
Simon van Heeringen
Jun 24, 2010
Contents
1 Introduction
2 Installation
2.1 Prerequisites
2.1.1 Required packages (Python)
2.1.2 Other required packages
2.1.3 Motif prediction programs
2.1.4 Data sources
2.2 Building from source
2.3 Configuration
2.3.1 Indexing the genomes
2.3.2 Adding gene files
2.3.3 The easy way: add_organism.py
2.3.4 MotifSampler configuration
2.3.5 Other configuration options
3 Usage
3.1 Quick GimmeMotifs example
3.2 Detailed options
3.3 Other scripts
4 Acknowledgements
1 Introduction
GimmeMotifs is a de novo motif prediction pipeline, especially suited for ChIP-seq datasets. It incorporates several existing motif prediction algorithms in an ensemble method to predict motifs and clusters these motifs using the WIC similarity scoring metric. It is freely available for download and use under the MIT license. If you find GimmeMotifs useful, please cite:
- van Heeringen SJ and Veenstra GJC, GimmeMotifs: a de novo motif prediction pipeline for ChIP-sequencing experiments, in preparation.
This document describes how to install and use GimmeMotifs, for theoretical details, please see our publication .
Hopefully this document explains at least the basics of installation and usage, but it's probably far from complete. If you have any further question, please don't hesistate to contact me<EMAIL_ADDRESS>2 Installation
I have tried to make installation of GimmeMotifs as easy as possible. However, as it depends on quite some external packages (motif prediction tools!), it's still not quite a single-click install. Please make sure all prerequisites are installed before installing GimmeMotifs.
2.1 Prerequisites
GimmeMotifs runs on Linux. Definitely not on Windows, sorry. Mac OS X should work in theory, but as I don't have the option to test this, I'm not completely sure.
Before you can install GimmeMotifs you'll need:
- some Python modules and other packages
- genomic sequences
- motif prediction tools
2.1.1 Required packages (Python)
2.1.2 Other required packages
2.1.3 Motif prediction programs
In addition to all the basics you need to get GimmeMotifs up and running you will also need the motif prediction tools, which can be used by GimmeMotifs to predict motifs. You can use any or all of these according to your preference. The following tools are supported by GimmeMotifs:
Please consult the respective manuals regarding installation of these tools. As mentioned, you can install any or all of them, according to your needs. However, we recommend installing at least several to leverage the ensemble approach of GimmeMotifs. The top performing tools in our ChIP-seq benchmarks were MEME, MotifSampler and Weeder, but all other tools find motifs that are not found by other tools. In fact, it's because there is no single all-round top performing method that GimmeMotifs exists.
It's always possible to install these programs after installation of GimmeMotifs and update the configuration files to include the new tools. However, during installation, GimmeMotifs will try to find any installed tools and add them automatically, so that's the easiest option.
After installation of MotifSampler, one additional configuration step is necessary, described in section 2.3.4.
2.1.4 Data sources
You will need some genome fasta files for any motif-prediction. Currently GimmeMotifs uses BED files as input (as that's the data-format ChIP-seq pipelines commonly produce), so the genomic fasta files are absolutely required to get the sequence information. These files should be organized in one directory with one file per chromosome or scaffold, with the filename being the chromosome name with an extension of .fa, .fsa or .fasta. No exceptions, no different layouts. A good source is the UCSC Genome Browser database [8]. For instance, the human hg18 files needed to run the examples included with GimmeMotifs can be downloaded here:
ftp://hgdownload.cse.ucsc.edu/goldenPath/hg18/bigZips/chromFa.zip.
All fasta files need to be indexed before GimmeMotifs can use them, see section 2.3.1.
2.2 Building from source
You can download the lastest version of GimmeMotifs at:
http://www.ncmls.eu/bioinfo/gimmemotifs/.
Start by unpacking the source archive
tar xvzf gimmemotifs-1.00.tar.gz
cd gimmemotifs-1.00
You can build GimmeMotifs with the following command:
python setup.py build
Run the tests to check if the basics work correctly:
python run_tests.py
If you encounter no errors, go ahead with installing GimmeMotifs (root privileges required):
sudo python setup.py install
During installation GimmeMotifs will try to locate the tools you have installed. If you have recently installed them, running an updatedb will be necessary. Using this option GimmeMotifs will create a configuration file /usr/share/gimmemotifs/gimmemotifs.cfg by default. This is a system-wide configuration that can be used by all users.
It is also possible to run the setup.py install command with the -prefix, -home, or -install-data options, to install in GimmeMotifs in a different location (for instance, in your own home directory). In this case a configuration file /.gimmemotifs.cfg will be created. However, these alternative methods of installing GimmeMotifs have not been extensively tested. Let me know if you run into problems.
2.3 Configuration
2.3.1 Indexing the genomes
All the genomes that you want to use with GimmeMotifs will need to be indexed for (relatively) fast retrieval of sequences. You can do this, once you have installed GimmeMotifs, by running the following command (as root or with sudo):
create_genome_index.py -f /dir/to/fasta/files/ -n genome_name
For instance, if I wanted to index the human genome (version hg18) on my computer, where all fasta files are located in the directory /usr/share/genome/ I would run the following command:
sudo create_genome_index.py -f /usr/share/genome/hg18/ -n hg18
Repeat this step for every additional genome or organism that you want to use GimmeMotifs with.
Please note: for Weeder, currently only hg18, hg19, mm9, sacCer2 and xenTro2 are supported as organism names (following the UCSC naming convention). This will be fixed as a configuration file in a later release.
2.3.2 Adding gene files
When using the genomic_matched background setting (which is the default), there needs to be a file describing genes in BED format in the /usr/share/gimmemotifs/genes/ directory. The file needs to be named <index_name>.bed, so for instance hg18.bed. By default hg18.bed, mm9.bed and xenTro2.bed are included.
2.3.3 The easy way: add_organism.py
The script add_organism.py combines the previous two steps (indexing the fasta files, and adding a gene file), and makes sure the gene BED file is in the correct place with the correct name. This is the easiest way to add a new genome/organism for use with GimmeMotifs.
2.3.4 MotifSampler configuration
If you want to use MotifSampler there is one more step that you'll have to take after installation of GimmeMotifs. For every organism, you'll need a MotifSampler background. These can be obtained from http://homes.esat.kuleuven.be/~thijs/Work/BackgroundModel.html or, alternatively, be created with CreateBackgroundModel (which can be downloaded from the same site as MotifSampler). The background model file needs to be saved in the directory /usr/share/gimmemotifs/MotifSampler and it should be named <organism_index_name>.bg. So, for instance, if I downloaded the human epd background (epd_homo_sapiens_499_chromgenes_non_split_3.bg), this file should be saved as /usr/share/gimmemotifs/MotifSampler/hg18.bg.
2.3.5 Other configuration options
All of GimmeMotifs configuration is stored in /usr/share/gimmemotifs/gimmemotifs.cfg or /.gimmemotifs.cfg. If the file /.gimmemotifs.cfg exists in your home directory this will always have precedence over the system-wide configuration.
The configuraton file is created at installation time with all defaults set, but you can always edit it afterwards. It contains two sections main and params that take care of paths, file locations, parameter settings etc. Additionally, every motif tool has it's own section.
Let's have a look at the options.
[main]
index_dir = /usr/share/gimmemotifs/genome_index
template_dir = /usr/share/gimmemotifs/templates
seqlogo = /usr/local/bin/seqlogo
score_dir = /usr/share/gimmemotifs/score_dists
motif_databases = /usr/share/gimmemotifs/motif_databases
gene_dir = /usr/share/gimmemotifs/genes
- index_dir The location of the indeces of the genome fasta-files.
- template_dir The location of the KID html templates, used to generate the reports.
- seqlogo The seqlogo executable.
- score_dir To generate p-values, a pre-calculated file with mean and sd of score distributions is needed. These are located here.
- motif_databases For now contains only the JASPAR motifs.
- gene_dir A bed-file containing gene locations for every indexed organism. This is needed to create the matched genomic background.
[params]
background = genomic_matched,random
use_strand = False
tools = MDmodule,Weeder,MotifSampler
analysis = medium
pvalue = 0.001
width = 200
fraction = 0.2
genome = hg18
lwidth = 500
cluster_threshold = 0.95
available_tools = Weeder,MDmodule,MotifSampler,gadem,meme,trawler
abs_max = 1000
enrichment = 1.5
This section specifies all the default GimmeMotifs parameters. Most of these can also be specified at the command-line when running GimmeMotifs, in which case they will override the parameters specified here.
3 Usage
3.1 Quick GimmeMotifs example
You can try GimmeMotifs with two example datasets included in the examples directory. This example does require you to have hg18 present and indexed.
Change to the examples directory and run the following command:
gimme_motifs.py -i TAp73alpha.fa -n p73
The -n or -name option defines the name of the output directory that is created. All output files are stored in this directory.
Depending on your computer you may have to wait some minutes for your results. Once GimmeMotifs is finished you can open p73/p73_motif_report.html in your browser.
3.2 Detailed options
- -i or -inputfile
This is the only mandatory option. The inputfile needs to be in BED format: at least three tab-seperated columns describing chromosome name, start and end. The fourth column is optional, if specified it will be used by MDmodule to sort the features before motif prediction. GimmeMotifs will take the middle of these features, and subsequently extend those to the width specified by the width parameter (see below).
-
-n or -name
The name of your analysis. All outputfiles will be stored in a directory named as given by this parameter. By default this will be gimmemotifs_dd_mm_yyyy, where d,m and y are the current day, month and year respectively.
-
-a or -analysis
The size of motifs to look for: small (5-8), medium (5-12) or large (5-15). The larger the motifs, the longer GimmeMotifs will run.
-
-g or -genome
Name of the genome (index) to use. For instance, for the example in section 2.3.1 this would be hg18.
-
-s or -singlestrand
Only use the + strand for prediction (off by default).
-
-f or -fraction
This parameter controls the fraction of the sequences used for prediction. This 0.2 by default, so in this case a randomly chosen 20% of the sequences will be used for prediction. The remaining sequences will be used for validation (enrichment, ROC curves etc.). If you have a large set of sequences (ie. most ChIP-seq peak sets), this is fine. However, if your set is smaller, it might be worthwile to increase this prediction fraction.
-
-w or -width
This is the width of the sequences used for motif prediction. Smaller sequences will result in a faster analysis, but you are of course limited by the accuracy of your data. For the tested ChIP-seq data sets 200 performs fine.
-
-e or -enrichment
All motifs should have an absolute enrichment of at least this parameter compared to background to be called significant.
-
-p or -pvalue
All motifs should have a pvalue of at most this parameter (hypergeometric enrichment compared to background) to be called significant.
-
-b or -background
Type of background to use. By default random (1st order Markov model, similar dinucleotide frequencies as your sequences) and matched_genomic (randomly chosen from the genome with a similar distribution respective to the TSS of genes) are used.
-
-l or -localization_width
Width used in the positional preference plots.
-
-t or -tools
A comma-seperated list of all the motif prediction tools to use. By default all installed tools that are specified in the GimmeMotifs configuration file are used.
3.3 Other scripts
In addition to gimme_motifs.py the GimmeMotifs package contains several other tools that can perform the various substeps of GimmeMotifs, as well as other useful tools. Run them to see the options.
closest_motif_match.py
create_genome_index.py
generate_sequences.py
motif_cluster.py
motif_localization_plots.py
motif_roc.py
motif_roc_metrics.py
pwm2logo.py
pwmscan.py
track2fasta.py
4 Acknowledgements
We are grateful to Waseem Akhtar, Robert Akkers, Max Koeppel, Evelyn Kouwenhoven, Leonie Smeenk and Jo Zhou for providing data and feedback during GimmeMotifs development. Also we would like to thank Stefanie Bartels, Adalberto Costessi, Joost Martens and Nagesha Rao for testing and helpful discussion.
Of course GimmeMotifs by itself wouldn't be able to do anything, if there wasn't such a number of excellent tools available. Therefore, thanks to all the authors of the motif prediction programs for making their software publicly available!
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Dominic Thiem dethrones Alexander Zverev to set up Stefanos Tsitsipas final
by FSA EditorThere will be a first-time ATP Finals champion on Sunday after Dominic Thiem ended Alexander Zverev’s reign in London.
Dominic Thiem will face Stefanos Tsitsipas for the ATP Finals title after dethroning Alexander Zverev in straight sets.
Thiem beat Roger Federer and Novak Djokovic to reach the last four of the season-ending tournament for the first time and dispatched Zverev 7-5 6-3 at the O2 Arena in London on Saturday.
Zverev was unable to break the fifth seed, who was more composed than the defending champion and broke once in each set to set up a showdown with Tsitsipas – conqueror of Federer earlier in the day.
Thiem has won five titles in a stellar season and the two-time French Open runner-up will claim the biggest of his career if he gets the better of Tsitsipas on Sunday, having struck 21 winners in his sixth victory in eight meetings with Zverev.
The first break point came for Zverev, but Thiem denied his close friend to level at 2-2 after unleashing one of a number of blistering backhands.
Zverev saw another break point pass him by and it was his opponent – wearing exactly the same attire – who got the decisive break of a tight opening set.
A couple of sloppy errors from Zverev gave Thiem two set points and the German thrashed his racket into the ground after returning to his chair following a costly double fault.
Zverev headed off court after watching his racket fly up in the air when he drilled it against the hard court in fury and the seventh seed was a break down at 4-2 in the second following a string of unforced errors.
Thiem got himself out of trouble when Zverev forced two break points in the next game and sealed victory with a forehand winner.