Module Application
Application
class contains the common functions that's
available to the current application.
There is
a global variable application
of type Application
to access these functions.
Type Application
| Application:exit() |
Terminates the application. |
| Application:getAccelerometer() |
This function is obsolete, use Accelerometer class instead. Returns the x, y, z coordinates of the accelerometer. |
| Application:getBackgroundColor() |
Returns the background color (or clear color) of the application in hexadecimal format. |
| Application:getContentHeight() |
If the orientation is portrait, this function returns logical height. |
| Application:getContentWidth() |
If the orientation is portrait, this function returns logical width. |
| Application:getDeviceHeight() |
Returns the physical height of the device in pixels. |
| Application:getDeviceInfo() |
Returns information about device. |
| Application:getDeviceWidth() |
Returns the physical width of the device in pixels. |
| Application:getFps() |
Returns the frame rate of the application. |
| Application:getLanguage() |
Returns the user language in ISO 639-1 format. |
| Application:getLocale() |
Returns the device locale. |
| Application:getLogicalHeight() |
Returns the logical height of the application that is specified at the project properties. |
| Application:getLogicalScaleX() |
Returns the scaling of automatic screen scaling on the x-axis. |
| Application:getLogicalScaleY() |
Returns the scaling of automatic screen scaling on the y-axis. |
| Application:getLogicalTranslateX() |
Returns the translation of automatic screen scaling on the x-axis. |
| Application:getLogicalTranslateY() |
Returns the translation of automatic screen scaling on the y-axis. |
| Application:getLogicalWidth() |
Returns the logical width of the application that is specified at the project properties. |
| Application:getOrientation() |
Returns the orientation of the application. |
| Application:getScaleMode() |
Returns the automatic scale mode of the application. |
| Application:openUrl() |
Opens the given URL (Universal Resource Locator) in the appropriate application. |
| Application:setBackgroundColor(color) |
Sets the background color (or clear color) of the application in hexadecimal format. |
| Application:setFps(fps) |
Sets the frame rate of the application. |
| Application:setKeepAwake(keepAwake) |
Controls the screen dimming and device sleeping of the device. |
| Application:setLogicalDimensions(width, height) |
Sets the logical dimensions of the application. |
| Application:setOrientation(orientation) |
Sets the orientation of the application. |
| Application:setScaleMode(scaleMode) |
Sets the automatic scale mode of the application. |
| Application:vibrate() |
Vibrates the device. |
Type Application
Field(s)
- Application:exit()
-
Terminates the application.
Although this function is available to all platforms, it should be used on Android only.
- Application:getAccelerometer()
-
This function is obsolete, use Accelerometer class instead.
Returns the x, y, z coordinates of the accelerometer.
Return values
-
x coordinate of the accelerometer
-
y coordinate of the accelerometer
-
z coordinate of the accelerometer
-
- Application:getBackgroundColor()
-
Returns the background color (or clear color) of the application in hexadecimal format.
Return value
The background color in hexadecimal format.
- Application:getContentHeight()
-
If the orientation is portrait, this function returns logical height.
If the orientation is landscape, this function returns logical width.
Return value
Logical width or logical height depending on orientation.
- Application:getContentWidth()
-
If the orientation is portrait, this function returns logical width.
If the orientation is landscape, this function returns logical height.
Return value
Logical width or logical height depending on orientation.
- Application:getDeviceHeight()
-
Returns the physical height of the device in pixels.
For example, for iPhone 3GS this function returns 480 and for iPhone 4 (with retina display enabled) this function returns 960.
Return value
The physical height of the device in pixels
- Application:getDeviceInfo()
-
Returns information about device.
- For iOS, returns 5 values: "iOS", iOS version, device type, user interface idiom and device model
- For Android, returns 2 values: "Android", Android version
- For Windows returns 1 value: "Windows"
- For Mac OS X returns 1 value: "Mac OS"
Return value
Information about device
- Application:getDeviceWidth()
-
Returns the physical width of the device in pixels.
For example, for iPhone 3GS this function returns 320 and for iPhone 4 (with retina display enabled) this function returns 640.
Return value
The physical width of the device in pixels
- Application:getFps()
-
Returns the frame rate of the application.
Return value
The frame rate of the application.
- Application:getLanguage()
-
Returns the user language in ISO 639-1 format.
Return value
The the user language
- Application:getLocale()
-
Returns the device locale.
The locale string is a combination of ISO 639-1 and ISO 3166-1. For example, enUS, jaJP.
Return value
The device locale
- Application:getLogicalHeight()
-
Returns the logical height of the application that is specified at the project properties.
Return value
The logical height of the application
- Application:getLogicalScaleX()
-
Returns the scaling of automatic screen scaling on the x-axis.
Return value
The scaling of automatic screen scaling on the x-axis.
- Application:getLogicalScaleY()
-
Returns the scaling of automatic screen scaling on the y-axis.
Return value
The scaling of automatic screen scaling on the y-axis.
- Application:getLogicalTranslateX()
-
Returns the translation of automatic screen scaling on the x-axis.
Return value
The translation of automatic screen scaling on the x-axis.
- Application:getLogicalTranslateY()
-
Returns the translation of automatic screen scaling on the y-axis.
Return value
The translation of automatic screen scaling on the y-axis.
- Application:getLogicalWidth()
-
Returns the logical width of the application that is specified at the project properties.
Return value
The logical width of the application
- Application:getOrientation()
-
Returns the orientation of the application.
Return value
The orientation of the application
- Application:getScaleMode()
-
Returns the automatic scale mode of the application.
Return value
The automatic scale mode of the application
- Application:openUrl()
-
Opens the given URL (Universal Resource Locator) in the appropriate application.
URL can be one of the
http:
,https:
,tel:
, ormailto:
schemes.The following example opens a web page in the browser:
application:openUrl("http://www.giderosmobile.com")
If
mailto:
scheme is specified, the user's e-mail client will be used to open a composer window containing the options specified in the URL. For example, the following URL contains a recipient (user@foo.com), a subject (Test), and a message body (Just a test):application:openUrl("mailto:user@foo.com?subject=Test&body=Just a test")
Or to call a number:
application:openUrl("tel:555-123-4567")
- Application:setBackgroundColor(color)
-
Sets the background color (or clear color) of the application in hexadecimal format.
Default background color is white (0xffffff).
Parameter
-
color
: (number) background color in hexadecimal format
-
- Application:setFps(fps)
-
Sets the frame rate of the application.
Accepted values are
30
and60
.Parameter
-
fps
: (number) the new frame rate of the application
-
- Application:setKeepAwake(keepAwake)
-
Controls the screen dimming and device sleeping of the device.
When the application has no touches as user input for some period, the system puts the device into a sleep state where the screen dims. However some applications have no input and controlled by accelerometer or gyroscope only. For these kind applications, the screen should be kept awake by calling this function with parameter
true
.Note: This function has no effect on desktop.
Parameter
-
keepAwake
: (boolean) if true, screen is kept awake.
-
- Application:setLogicalDimensions(width, height)
-
Sets the logical dimensions of the application.
Parameters
-
width
: (number) logical width -
height
: (number) logical height
-
- Application:setOrientation(orientation)
-
Sets the orientation of the application.
Accepted values are:
- Application.PORTRAIT = "portrait"
- Application.PORTRAITUPSIDEDOWN = "portraitUpsideDown"
- Application.LANDSCAPE_LEFT = "landscapeLeft"
- Application.LANDSCAPE_RIGHT = "landscapeRight"
Parameter
-
orientation
: (string)
- Application:setScaleMode(scaleMode)
-
Sets the automatic scale mode of the application.
Accepted values are:
- Application.NO_SCALE = "noScale"
- Application.CENTER = "center"
- Application.PIXEL_PERFECT = "pixelPerfect"
- Application.LETTERBOX = "letterbox"
- Application.CROP = "crop"
- Application.STRETCH = "stretch"
- Application.FIT_WIDTH = "fitWidth"
- Application.FIT_HEIGHT = "fitHeight"
Parameter
-
scaleMode
: (string)
- Application:vibrate()
-
Vibrates the device.
If the device doesn't support vibration, this function has no effect.


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Goals for today:
Ordinary cumulative sentences feature a transitive verb and two plural arguments: X V’ed Y.
| (1) | The cooks opened the oysters. |
(In some cases,) we can characterize the truth-condition of (1) in terms of what individual cooks did to individual oysters.
| (2) | Cumulative truth-conditions1: Every oyster was opened by a cook. Every cook opened an oyster. \(\forall\exists\land\forall\exists\) |
\(\rightsquigarrow\) simplifying assumption: no collective action occurs.
Lexical analysis: that’s just what “open” means (e.g. Kratzer (2003))2.
| (3) | (With simplifying assumption) |
| \[\textsf{open}(Y)(X) \Leftrightarrow \begin{array}{rl} &\forall x\prec X, \exists y\prec Y, \textsf{open}(y)(x)\\ \land& \forall y\prec Y, \exists x\prec X, \textsf{open}(y)(x) \end{array} \] |
A simplification of Schein (1993) ’s famous video-game examples:
| (4) | a. | The cooks opened every oyster. |
| b. | Truth-conditions: Every cook opened an oyster. Every oyster was opened by a cook. \(\rightsquigarrow\) the cooks opened the oysters. |
If every is a regular universal quantifier, and composition runs as in Heim and Kratzer (1998):
| (5) | a. | |
| b. | The cooks opened every oyster. | |
| c. | By compositional rules: The cooks opened oyster 1 and the cooks opened oyster 2 … \(\forall x\in \textsf{oyster}, \textsf{open}(x)(\iota\textsf{cooks})\) |
|
| d. | By cumulative denotation of open: Every cook opened oyster 1 and oyster 1 was opened by some cook and every cook opened oyster 2 and oyster 2 was opened by some cook … \(\forall x\in \textsf{oyster},\left(\forall y\prec \iota\textsf{cooks}, \textsf{open}(x)(y)\right)\land\left(\exists y\prec \iota\textsf{cooks}, \textsf{open}(x)(y)\right)\) |
|
| e. | Every cook opened oyster 1 and every cook opened oyster 2 … \(\forall x\in \textsf{oyster},\forall y\prec \iota\textsf{cooks}, \textsf{open}(x)(y)\) |
|
| f. | Every cook opened every oyster. |
Puzzle I: how can “every” in object position yield a cumulative reading?
More puzzling even, subject/object asymmetries (Kratzer 2003):
| (6) | a. | ? Every cook opened the oysters |
| b. | Truth-conditions: Every cook opened every oyster |
Puzzle II: why does “every” in subject position not yield a cumulative reading?
Just like every, quantifiers over singularities create challenges.
| (7) | Quantifier over singularities: |
| \(Q(P) \leftrightarrow Q(P \cap \textsf{At})\) |
Supporting cases
The case of non-partitive most. There is a problem of cumulative readings of non-universals as well.
| (8) | Non-partitive most | |
| a. | Most athletes lifted the truck. (Crnič 2010) | |
| b. | Most lawyers7 hired a secretary they7 liked. (Kamp and Reyle 2013) |
This motivates treating non-partitive most as counting singularities:
| (9) | \([\![\text{most athletes}]\!](q) =\#\left\lbrace x\in \textsf{athlete} \middle| \textsf{q}(x)\right\rbrace > \frac12 \#\textsf{athlete}\) |
There is a cumulative-like reading to most:
| (10) | a. | The cooks opened most oysters. |
| b. | Truth-conditions: Most oysters were opened by a cook. Every cook opened an oyster. |
If a) open has a cumulative denotation, b) most means the same as it does in (9), then this reading is unexpected:
| (11) | \(\#\left\lbrace x\in \textsf{oyster} \middle| \textsf{open}(x)(\iota\textsf{cooks})\right\rbrace > \frac12 \#\textsf{oyster}\) \(\Leftrightarrow\#\left\lbrace x\in \textsf{oyster} \middle| \forall y\prec\iota\textsf{cooks}, \textsf{open}(x)(y)\right\rbrace > \frac12 \#\textsf{oyster}\) “More than half the oysters were opened by every cook.” \(\neq\) attested truth-conditions |
There are subjet/object asymmetries here as well:
| (12) | a. | ? Most cooks opened the oysters. |
| b. | Truth-conditions: The proportion of cooks who opened all the oysters was more than half. |
|
| c. | ? Most US voters will vote for two parties. (Crnič 2010) |
The case of Lebanese Arabic3 SAT numerals. Ouwayda (2017) notes that in Lebanese Arabic, numeral DPs above 10 must be headed by singular nouns. When they are, they are either singular-agreeing or plural-agreeing.
| (13) |
Verb agreement
|
| (14) |
Bound pronuns
|
I refer to these two cases as singular-agreeing transdecimal numerals (SAT numerals) and plural-agreeing transdecimal numerals (PAT numerals). We’ll focus on SAT numerals.
| Thirty boy\(_1\)-SG … V-PL … their … | PAT numerals |
| Thirty boy\(_1\)-SG … V-SG … his/her … | SAT numerals |
SAT numerals are what you would expect a singular quantifier to be: they do not yield collective interpretations.
| (15) |
Only distributive interpretations with mixed predicates and singular agreement
|
| (16) |
Only distributive interpretations when binding in the singular
|
| (17) |
SAT numerals don’t combine with collective predicates
|
This points to an analysis in terms of quantification over singularities.
| (18) | \([\![\text{thirty}_{SAT}\text{ child}]\!] = \lambda q. \#\{x | q(x)\land\textsf{child}(x)\} = 30\) |
Just like every and non-partitive most, SAT numerals yield cumulative readings.
| (19) |
Context: each journalist interviewed 10 children, asking them questions about their father.
|
| (20) | Cumulative truth-conditions: Every journalist asked a child about his father. Thirty children was asked by a journalist about his father. |
The presence of this cumulative reading is unexpected if ask has a cumulative denotation.
| (21) | a. | The 3 journalists asked 30 child. |
| b. | The number of boys such that the three journalists asked them about their father is 30. \(\#\{x | \textsf{ask}(x)(\iota\textsf{journalists})\land\textsf{child}(x)\} = 30\) |
|
| c. | The number of boys such that every journalist asked them about their father is 30. \(\#\{x | \forall y\prec \iota\textsf{journalists}, \textsf{ask}(x)(y)\land\textsf{child}(x)\} = 30\) |
Here too, we find subject/object asymmetries.
| (22) |
Context: 10 children asked each journalist questions about their father.
|
Dataset
| Sentence | Reading |
|---|---|
| The cooks opened the oysters. | cumulative |
| The cooks opened every oyster. | cumulative |
| The cooks opened most oysters. | cumulative |
| The cooks opened thirty oyster-\(\varnothing\). | cumulative |
| Every cook opened the oysters. | doubly-distributive |
| Most cooks opened the oysters. | doubly-distributive |
| Thirty cook-\(\varnothing\) opened the oysters. | doubly-distributive |
This paradox has elicited a diverse range of reactions:
Claim: as far as these data points are concerned, there is no need for enriched composition.
Observation: if negative sentences were all that we had to account for, solving the problem of cumulative readings of quantifiers would be extremely simple.
The truth-conditions of negative cumulative sentences sentences are not what we expect: the truth-conditions of (23) are not simply the complement of the cumulative truth-conditions.
| (23) | The cooks didn’t open the oysters. | |
| a. | Attested truth-conditions: \(\neg\exists\exists\) No cook opened any oyster. |
|
| b. | Expected truth-conditions: \(\neg\forall\exists\vee\neg\forall\exists\) Not every cook opened an oyster or not every oyster was opened by a cook. |
There is homogeneity. Homogeneity is also attested in intransitive sentences.
| (24) | Joana and Marius didn’t smile. | |
| a. | Attested truth-conditions: \(\neg\exists\) Neither Joana nor Marius smiled |
|
| b. | Expected truth-conditions: \(\neg\forall\) They didn’t both smile. |
There is also homogeneity in cumulative readings with every:
| (25) | The cooks didn’t open every oyster. | |
| a. | Attested truth-conditions: \(\neg\forall\exists\) Not every oyster was opened by a cook. |
|
| b. | Expected truth-conditions: \(\neg\forall\exists\vee\neg\forall\exists\) Not every oyster was opened by a cook or not every cook opened an oyster. |
Why is this observation important? We now have conflicting evidence regarding the meaning of open
| (26) | a. | The cooks opened the oysters. |
| b. | The cooks didn’t open the oysters. |
Had we started with negative sentences, we would have written the denotation of open differently.
| (27) | a. | The cooks didn’t open the oysters. |
| b. | \(\neg\textsf{opened}(\iota\textsf{cooks})(\iota\textsf{oysters})\) (= expected truth-conditions) \(\Leftrightarrow\) \(\neg\exists x\prec \iota\textsf{cooks}, \exists y \prec \iota\textsf{oysters}, \textsf{opened}(y)(x)\) (= attested truth-conditions) |
Call the meaning in (28 a) is the existential denotation for open.
| (28) | Weak and strong meaning for open | |
| a. | Existential denotation for open \(\textsf{open}(Y)(X) \Leftrightarrow \exists x\prec X, \exists y \prec Y, \textsf{open}(y)(x)\) |
|
| b. | Cumulative denotation for open \(\textsf{open}(Y)(X) \Leftrightarrow \begin{array}{rl} &\forall x\prec X, \exists y\prec Y, \textsf{open}(y)(x)\\ \land& \forall y\prec Y, \exists x\prec X, \textsf{open}(y)(x) \end{array}\) |
Unlike the positive case, the existential denotation works in both negative sentences with and without every.
| (29) | a. | The cooks didn’t open every oyster. |
| b. | ||
| c. | \(\neg\forall y\in \textsf{oyster},\ \textsf{opened}(y)(\iota\textsf{cooks})\) \(\Leftrightarrow \neg\forall y \in \textsf{oyster}, \exists x\prec \iota\textsf{cooks}, \textsf{opened}(y)(x)\) \(=\) attested truth-conditions |
The success of the existential denotation cannot be understated: it covers all other cases considered and more.
The case of most
| (30) | a. | The cooks didn’t open most oysters. |
| b. | Attested truth-conditions: It’s not that the case that most oysters were opened by a cook. |
| (31) | \(\neg\#\left\lbrace x\in \textsf{oyster} \middle| \textsf{open}(x)(\iota\textsf{cooks})\right\rbrace > \frac12 \#\textsf{oyster}\) \(\Leftrightarrow\#\left\lbrace x\in \textsf{oyster} \middle| \exists y\prec\iota\textsf{cooks}, \textsf{open}(x)(y)\right\rbrace \leq \frac12 \#\textsf{oyster}\) “Less than half the oysters were opened by a cook.” = attested truth-conditions |
| (32) | Negative dataset | ||
| a. | \(\checkmark\) | The cooks didn’t open the oysters. \(\rightsquigarrow\) not [some cook opened some oysters] |
|
| b. | \(\checkmark\) | The cooks didn’t open every oyster. \(\rightsquigarrow\) not [every oyster was opened by some cooks] |
|
| c. | \(\checkmark\) | The cooks didn’t open most oysters. \(\rightsquigarrow\) not [most oysters were opened by some cooks] |
|
| d. | \(\checkmark\) | The cooks didn’t open thirty oyster-\(\varnothing\). (Lebanese Arabic) \(\rightsquigarrow\) not [thirty oysters were opened by some cooks] |
|
| e. | \(\checkmark\) | The 3 video-games didn’t teach every quarterback two new plays. (Schein 1993) \(\rightsquigarrow\) not [every quarterback was taught two plays by some video-games] |
Transitive verbs do not have cumulative denotations. They underlyingly have existential denotations. (cf Bayer (2013), Landman (1989))
\[\textsf{open}(Y)(X) \Leftrightarrow \exists x\prec X, \exists y \prec Y, \textsf{open}(y)(x)\]
In positive sentences, adopting the existential denotation misses some inferences of positive sentences (represented in gray).
| (33) | a. | The cooks opened the oysters. |
| b. | Truth-conditions: Some cooks opened some oysters. Every cook opened an oyster. Every oyster was opened by a cook. |
| (34) | a. | The cooks opened every oyster. |
| b. | Truth-conditions: Every oyster was opened by a cook. Every cook opened an oyster. |
| (35) | a. | The cooks opened most oysters. |
| b. | Truth-conditions: Most oysters were opened by a cook. Every cook opened an oyster. |
There is a family resemblance between the gray inferences.
Proposal: derive these inferences as implicatures.
A similar problem arise outside of cumulativity: to account for the truth-contions of (36 a), we may want to posit the existential denotation in (36 b).
| (36) | a. | The children didn’t smile. \(\rightsquigarrow\) no child smiled. |
| b. | \(\textsf{smiled}(X) \Leftrightarrow \exists x\prec X, \textsf{smiled}(x)\) |
| (37) | a. | The children smiled. |
| b. | Truth-conditions:4 Some child smiled. Every child smiled. |
To account for the presense of the gap in the case of (37), Moshe E. Bar-Lev (2018) proposes that a mechanism akin to implicatures, Free Choice implicatures specifically.
Rationale:
Analogy with Free Choice implicatures. (Moshe E. Bar-Lev 2018)
If (38) is a case of implicature, it is a case of an underlying existential (\(\exists\)) being strengthened to a universal (\(\forall\)):
| (38) | a. | The children slept. |
| b. | Truth-conditions: Some child slept. Every child slept. |
| (39) | a. | The children didn’t sleep. |
| b. | Truth-conditions: No child slept. |
In FC implicatures, an underlyingly disjunctive meaning (\(\vee\)) is strengthened in positive sentences to a conjunctive meaning (\(\land\)).
| (40) | a. | You can have ice-cream or cake. |
| b. | Truth-conditions: You either can have ice-cream or can have cake. You can have ice-cream. You can have cake. |
| (41) | a. | You can’t have ice-cream or cake. |
| b. | Truth-conditions: You can neither have ice-cream or cake. |
Analogy with distributive implicatures. The analogy with FC implicatures is not very apt for cumulative sentences. The desired strengthening is not simply converting an existential to a universal.
| (42) | a. | The cooks opened every oyster. |
| b. | Truth-conditions: Every oyster was opened by some cook. Every cook opened an oyster. |
But it does resemble another implicature process: distributive implicatures.
| (43) | a. | Every ambassador speaks Mandarin or Tagalog. |
| b. | Truth-conditions: Every ambassador speaks Mandarin or Tagalog. (\(\forall \gg \vee\)) Some ambassador speaks Mandarin. Some ambassador speaks Tagalog. |
Generalizing \(\vee\) to \(\exists\), this is precisely the type of strengthening observed in positive sentences.
| (44) | a. | The cooks opened every oyster. |
| b. | Truth-conditions: Every oyster was opened by Joana or Marius or Barnaby or … (\(\forall \gg \exists\)) Joana opened some oyster. Marius opened some oyster. Barnaby opened some oyster. … |
Distributive implicatures also arise with other quantifiers than every.
| (45) | a. | Most ambassadors speak Mandarin or Tagalog. |
| b. | Truth-conditions: Most ambassadors speak Mandarin or Tagalog. (most \(\gg \vee\)) Some ambassador speaks Mandarin. Some ambassador speaks Tagalog. |
| (46) | a. | The cooks opened most oysters. |
| b. | Truth-conditions: Most oysters were opened by Joana or Marius or Barnaby or … (most \(\gg \exists\)) Joana opened some oyster. Marius opened some oyster. Barnaby opened some oyster. … |
| Sentence | You can have ice-cream or cake. | The children slept. |
| Underlying meaning | \(\lozenge a \lor\lozenge b\) | \(\exists x\prec\iota\textsf{children}, \textsf{slept}(x)\) |
| Implicature | \(\lozenge a \land\lozenge b\) | \(\forall x\prec\iota\textsf{children}, \textsf{slept}(x)\) |
| Sentence | Everyone speaks Mandarin or Tagalog. | The cooks opened every oyster. |
| Underlying meaning | \(\forall x, m(x)\vee t(x)\) | \(\forall y\in\textsf{oyster}, \exists x\prec\iota\textsf{cooks}, \textsf{opened}(x)(y)\) |
| Implicature | \(\exists x, m(x)\land\exists x, t(x)\) | \(\forall x\prec\iota\textsf{cooks}, \exists y\in\textsf{oyster}, \textsf{opened}(x)(y)\) |
Transitive verbs do not have cumulative denotations. They underlyingly have existential denotations. (cf Bayer (2013), Landman (1989))
\[\textsf{open}(Y)(X) \Leftrightarrow \exists x\prec X, \exists y \prec Y, \textsf{open}(y)(x)\]
In positive sentences, exhaustive participation implicatures arise. They arise through a process of recursive exhaustification.
Canonical implicatures:
| (47) | a. | Some people at my office are nice. |
| b. | Truth-conditions: Some people at my office are nice. Not all people at my office are nice |
In the grammatical tradition (Chierchia, Fox, and Spector 2012), these implicatures are derived by application of a covert operator exh, whose meaning is akin to only:
| (48) | exh some people at my office are nice. Prejacent: some people at my office are nice. Alternatives: \(\circ\) all of them are Strengthened meaning: Some people at my office are nice but not all are. |
These inferences we are interested in are different: they are not simply the negation of an alternative to the sentence
| (49) | a. | You can have ice cream or cake. \(\rightsquigarrow\) you can have both |
| b. | Everyone here speaks Tagalog or Mandarin. (Crnič, Chemla, and Fox 2015) \(\rightsquigarrow\) some speak Tagalog ; some speak Mandarin |
FC implicatures (Fox 2007) and distributive implicatures (Moshe E. Bar-Lev and Fox 2016) are derived via recursive exhaustification.
| (50) | exh exh You can have ice-cream or cake. Prejacent: exh You can have ice-cream or cake. Alternatives: \(\circ\) exh You can have ice-cream. \(\circ\) exh You can have cake. Strengthened meaning: You either can have ice-cream or can have cake. and it’s not the case that you can only have ice-cream. and it’s not the case that you can only have cake. \(\approx\) you can have both |
| (51) | exh exh Every ambassador speaks Mandarin or Tagalog. Prejacent: exh Every ambassador speaks Mandarin or Tagalog.  Strengthened meaning: Every ambassador speaks Mandarin or Tagalog and it’s not the case that every ambassador speaks Mandarin and no ambassador speaks Tagalog. and it’s not the case that every ambassador speaks Tagalog and no ambassador speaks Mandarin. \(\rightsquigarrow\) some ambassador speaks Mandarin ; some ambassador speaks Tagalog. |
By analogy to FC and distributive implicatures:
Assumption: expressions referring to pluralities have their sub-pluralities as their alternatives.
| (52) | exh exh Joana and Marius smiled. Prejacent: Joana or Marius smiled Alternatives: \(\circ\) exh Joana smiled. \(\circ\) exh Marius smiled. Strengthened meaning: Joana or Marius smiled and it’s not the case that only Joana smile and it’s not the case that only Marius smile \(\approx\) both did |
| (53) | exh exh the cooks opened every oyster Prejacent: every oyster was opened by Joana or Marius. Alternatives: \(\circ\) exh every oyster was opened by Joana. \(\approx\) every oyster was opened by Joana and no oysters by Marius. \(\circ\) exh every oyster was opened by Marius. \(\approx\) every oyster was opened by Marius and no oysters by Joana. Strengthened meaning: Every oyster was opened by Joana or Marius. and it’s not the case that every oyster was opened by Joana and no oyster by Marius and it’s not the case that every oyster was opened by Marius and no oyster by Joana. \(\approx\) Joana opened some oysters ; Marius opened some oysters |
Assumption: exh is inserted at any predicative position as much it can be (cf also Magri (2011))
| (54) |
Exception: exh cannot be inserted or is vacuous under negation (FoxSpector?)
Ordinary cumulative readings
| (55) | a. | The cooks opened the oysters. |
| b. | exh exh the cooks exh exh opened the oysters. \(\rightsquigarrow\) exh exh the cooks opened every oyster. |
Cumulative readings of most.
| (56) | a. | The cooks opened most oysters. |
| b. | exh exh the cooks (exh) opened most oysters. \(\rightsquigarrow\) every cook opened an oyster. |
| (57) | Most oysters were opened by Joana or Marius. \(\rightsquigarrow\) Joana opened some oysters \(\rightsquigarrow\) Marius opened some oysters |
Assumption: exh is inserted at any predicative position as much it can be (cf also Magri (2011))
| (58) | a. | Every cook opened the oysters |
| b. | exh exh every cook exh exh opened the oysters. \(\Rightarrow\) every cook opened every oyster |
| (59) | a. | The cooks opened every oyster |
| b. | exh exh the cooks exh exh opened every oyster. \(\Rightarrow\) every cook opened every oyster |
What drives the difference? The low scope of the existential meaning associated with “the cooks”.
Transitive verbs do not have cumulative denotations. They underlyingly have existential denotations. (cf Bayer (2013), Landman (1989))
\[\textsf{open}(Y)(X) \Leftrightarrow \exists x\prec X, \exists y \prec Y, \textsf{open}(y)(x)\]
In positive sentences, exhaustive participation implicatures arise. They arise through a process of recursive exhaustification.
These truth-conditions are inappriopriate when collective action is considered.↩
There is also a compositional analysis: independently of what “open” means, there exists a \(\ast\ast\) operator which generates cumulative readings (e.g. Beck and Sauerland (2000)). This analysis does not help in that respect as well.↩
Some speakers of Lebanese Arabic do not have SAT numerals. Thus, it would be more accurate to say that this is a feature of some sub-dialect of Lebanese Arabic.↩
Because of non-maximality, these truth-conditions may in fact be too strong.↩


Wrapper Functions¶
-
wrapper.
barotropic_eqlat_lwa
(ylat, vort, area, dmu, n_points, planet_radius=6378000.0)[source]¶ Compute equivalent latitude and wave activity on a barotropic sphere.
Parameters: - ylat (numpy.array) – 1-d numpy array of latitude (in degree) with equal spacing in ascending order; dimension = nlat.
- vort (numpy.ndarray) – 2-d numpy array of vorticity values; dimension = (nlat, nlon).
- area (numpy.ndarray) – 2-d numpy array specifying differential areal element of each grid point; dimension = (nlat, nlon).
- dmu (numpy.array) – 1-d numpy array of latitudinal differential length element (e.g. dmu = planet_radius * cos(lat) d(lat)). Size = nlat.
- n_points (int, default None) – Analysis resolution to calculate equivalent latitude. If input as None, it will be initialized as nlat.
- planet_radius (float, default 6.378e+6) – radius of spherical planet of interest consistent with input ‘area’.
Returns: qref (numpy.array) – 1-d numpy array of value Q(y) where latitude y is given by ylat; dimension = (nlat).
lwa_result (numpy.ndarray) –
- 2-d numpy array of local wave activity values;
dimension = [nlat_s x nlon]
-
wrapper.
barotropic_input_qref_to_compute_lwa
(ylat, qref, vort, area, dmu, planet_radius=6378000.0)[source]¶ This function computes LWA based on a prescribed Qref instead of Qref obtained from the vorticity field on a barotropic sphere.
Parameters: - ylat (numpy.array) – 1-d numpy array of latitude (in degree) with equal spacing in ascending order; dimension = nlat.
- qref (numpy.array) – 1-d numpy array of prescribed reference value of vorticity at each latitude; dimension = nlat.
- vort (numpy.ndarray) – 2-d numpy array of vorticity values; dimension = (nlat, nlon).
- area (numpy.ndarray) – 2-d numpy array specifying differential areal element of each grid point; dimension = (nlat, nlon).
- dmu (numpy.array) – 1-d numpy array of latitudinal differential length element (e.g. dmu = planet_radius * cos(lat) d(lat)). Size = nlat.
- planet_radius (float, default 6.378e+6) – radius of spherical planet of interest consistent with input ‘area’.
Returns: lwa_result – 2-d numpy array of local wave activity values; dimension = [nlat_s x nlon]
Return type: numpy.ndarray
-
wrapper.
eqvlat_bracket_hemispheric
(ylat, vort, area, nlat_s=None, n_points=None, planet_radius=6378000.0, vgrad=None)[source]¶ Compute equivalent latitude and <…>_Q in Nakamura and Zhu (2010) in a hemispheric domain.
Parameters: - ylat (numpy.array) – 1-d numpy array of latitude (in degree) with equal spacing in ascending order; dimension = nlat.
- vort (numpy.ndarray) – 2-d numpy array of vorticity values; dimension = (nlat, nlon).
- area (numpy.ndarray) – 2-d numpy array specifying differential areal element of each grid point; dimension = (nlat, nlon).
- nlat_s (int, default None) – The index of grid point that defines the extent of hemispheric domain from the pole. If input as None, it will be initialize as nlat // 2.
- n_points (int, default None) – Analysis resolution to calculate equivalent latitude. If input as None, it will be initialized as nlat_s.
- planet_radius (float, default 6.378e+6) – radius of spherical planet of interest consistent with input ‘area’.
- vgrad (numpy.ndarray, optional) – 2-d numpy array of laplacian (or higher-order laplacian) values; dimension = (nlat, nlon)
Returns: - q_part (numpy.ndarray) – 1-d numpy array of value Q(y) where latitude y is given by ylat; dimension = (nlat).
- brac (numpy.ndarray or None) – 1-d numpy array of averaged vgrad in the square bracket. If vgrad = None, brac = None.
-
wrapper.
eqvlat_hemispheric
(ylat, vort, area, nlat_s=None, n_points=None, planet_radius=6378000.0)[source]¶ Compute equivalent latitude in a hemispheric domain.
Parameters: - ylat (numpy.array) – 1-d numpy array of latitude (in degree) with equal spacing in ascending order; dimension = nlat.
- vort (numpy.ndarray) – 2-d numpy array of vorticity values; dimension = (nlat, nlon).
- area (numpy.ndarray) – 2-d numpy array specifying differential areal element of each grid point; dimension = (nlat, nlon).
- nlat_s (int, default None) – The index of grid point that defines the extent of hemispheric domain from the pole. If input as None, it will be initialize as nlat // 2.
- n_points (int, default None) – Analysis resolution to calculate equivalent latitude. If input as None, it will be initialized as nlat_s.
- planet_radius (float, default 6.378e+6) – radius of spherical planet of interest consistent with input ‘area’.
Returns: q_part – 1-d numpy array of value Q(y) where latitude y is given by ylat; dimension = (nlat).
Return type: numpy.ndarray
-
wrapper.
qgpv_eqlat_lwa
(ylat, vort, area, dmu, nlat_s=None, n_points=None, planet_radius=6378000.0)[source]¶ Compute equivalent latitutde qref and local wave activity lwa_result based on Quasi-geostrophic potential vorticity field vort at a pressure level as outlined in Huang and Nakamura (2017).
Parameters: - ylat (numpy.array) – 1-d numpy array of latitude (in degree) with equal spacing in ascending order; dimension = nlat.
- vort (numpy.ndarray) – 2-d numpy array of Quasi-geostrophic potential vorticity field; dimension = (nlat, nlon).
- area (numpy.ndarray) – 2-d numpy array specifying differential areal element of each grid point; dimension = (nlat, nlon).
- dmu (numpy.array) – 1-d numpy array of latitudinal differential length element (e.g. dmu = planet_radius * cos(lat) d(lat)). Size = nlat.
- nlat_s (int, default None) – The index of grid point that defines the extent of hemispheric domain from the pole. If input as None, it will be initialize as nlat // 2.
- n_points (int, default None) – Analysis resolution to calculate equivalent latitude. If input as None, it will be initialized as nlat_s.
- planet_radius (float, default 6.378e+6) – radius of spherical planet of interest consistent with input ‘area’.
Returns: qref (numpy.ndarray) – 1-d numpy array of value Q(y) where latitude y is given by ylat; dimension = (nlat).
lwa_result (numpy.ndarray) –
- 2-d numpy array of local wave activity values;
dimension = [nlat_s x nlon]
-
wrapper.
qgpv_eqlat_lwa_ncforce
(ylat, vort, ncforce, area, dmu, nlat_s=None, n_points=None, planet_radius=6378000.0)[source]¶ Compute equivalent latitutde qref, local wave activity lwa_result and non-conservative force on wave activity capsigma based on Quasi- geostrophic potential vorticity field vort at a pressure level as outlined in Huang and Nakamura (2017).
Parameters: - ylat (numpy.array) – 1-d numpy array of latitude (in degree) with equal spacing in ascending order; dimension = nlat.
- vort (numpy.ndarray) – 2-d numpy array of Quasi-geostrophic potential vorticity field; dimension = (nlat, nlon).
- ncforce (numpy.ndarray) – 2-d numpy array of non-conservative force field (i.e. theta in NZ10(a) in equation (23a) and (23b)); dimension = (nlat, nlon).
- area (numpy.ndarray) – 2-d numpy array specifying differential areal element of each grid point; dimension = (nlat, nlon).
- dmu (numpy.array) – 1-d numpy array of latitudinal differential length element (e.g. dmu = planet_radius * cos(lat) d(lat)). Size = nlat.
- nlat_s (int, default None) – The index of grid point that defines the extent of hemispheric domain from the pole. If input as None, it will be initialize as nlat // 2.
- n_points (int, default None) – Analysis resolution to calculate equivalent latitude. If input as None, it will be initialized as nlat_s.
- planet_radius (float, default 6.378e+6) – radius of spherical planet of interest consistent with input ‘area’.
Returns: - qref (numpy.ndarray) – 1-d numpy array of value Q(y) where latitude y is given by ylat; dimension = (nlat).
- lwa_result (numpy.ndarray) – 2-d numpy array of local wave activity values; dimension = (nlat, nlon).
- capsigma (numpy.ndarray) – 2-d numpy array of non-conservative force contribution value; dimension = (nlat, nlon).
-
wrapper.
qgpv_eqlat_lwa_options
(ylat, vort, area, dmu, nlat_s=None, n_points=None, vgrad=None, ncforce=None, planet_radius=6378000.0)[source]¶ Compute equivalent latitutde qref, local wave activity lwa_result and non-conservative force on wave activity capsigma based on Quasi- geostrophic potential vorticity field vort at a pressure level as outlined in Huang and Nakamura (2017).
Parameters: - ylat (numpy.array) – 1-d numpy array of latitude (in degree) with equal spacing in ascending order; dimension = nlat.
- vort (numpy.ndarray) – 2-d numpy array of Quasi-geostrophic potential vorticity field; dimension = (nlat, nlon).
- ncforce (numpy.ndarray) – 2-d numpy array of non-conservative force field (i.e. theta in NZ10(a) in equation (23a) and (23b)); dimension = (nlat, nlon).
- area (numpy.ndarray) – 2-d numpy array specifying differential areal element of each grid point; dimension = (nlat, nlon).
- dmu (numpy.array) – 1-d numpy array of latitudinal differential length element (e.g. dmu = planet_radius * cos(lat) d(lat)). Size = nlat.
- nlat_s (int, default None) – The index of grid point that defines the extent of hemispheric domain from the pole. If input as None, it will be initialize as nlat // 2.
- n_points (int, default None) – Analysis resolution to calculate equivalent latitude. If input as None, it will be initialized as nlat_s.
- planet_radius (float, default 6.378e+6) – radius of spherical planet of interest consistent with input ‘area’.
Returns: - return_dict (dictionary) – A dictionary that consist of the 4 computed outputs listed below.
- (1) qref (numpy.ndarray) – 1-d numpy array of value Q(y) where latitude y is given by ylat; dimension = (nlat).
- (2) brac_result (numpy.ndarray) – 1-d numpy array of <…>_Q(y) in NZ10 where latitude y is given by ylat; dimension = (nlat).
- (3) lwa_result (numpy.ndarray) – 2-d numpy array of local wave activity values; dimension = (nlat, nlon).
- (4) capsigma (numpy.ndarray) – 2-d numpy array of non-conservative force contribution value; dimension = (nlat, nlon).
-
wrapper.
qgpv_input_qref_to_compute_lwa
(ylat, qref, vort, area, dmu, nlat_s=None, planet_radius=6378000.0)[source]¶ Compute equivalent latitutde qref and local wave activity lwa_result based on Quasi-geostrophic potential vorticity field vort at a pressure level as outlined in Huang and Nakamura (2017). This function computes lwa based on a prescribed qref instead of qref obtained from the QGPV field.
Parameters: - ylat (numpy.array) – 1-d numpy array of latitude (in degree) with equal spacing in ascending order; dimension = nlat.
- qref (numpy.ndarray) – 1-d numpy array of value Q(y) where latitude y is given by ylat; dimension = (nlat).
- vort (numpy.ndarray) – 2-d numpy array of Quasi-geostrophic potential vorticity field; dimension = (nlat, nlon).
- area (numpy.ndarray) – 2-d numpy array specifying differential areal element of each grid point; dimension = (nlat, nlon).
- dmu (numpy.array) – 1-d numpy array of latitudinal differential length element (e.g. dmu = planet_radius * cos(lat) d(lat)). Size = nlat.
- nlat_s (int, default None) – The index of grid point that defines the extent of hemispheric domain from the pole. If input as None, it will be initialize as nlat // 2.
- planet_radius (float, default 6.378e+6) – radius of spherical planet of interest consistent with input ‘area’.
Returns: lwa_result – 2-d numpy array of local wave activity values; dimension = (nlat, nlon).
Return type: numpy.ndarray
-
wrapper.
theta_lwa
(ylat, theta, area, dmu, nlat_s=None, n_points=None, planet_radius=6378000.0)[source]¶ Compute the surface wave activity B based on surface potential temperature. See Nakamura and Solomon (2010a) for details.
Parameters: - ylat (numpy.array) – 1-d numpy array of latitude (in degree) with equal spacing in ascending order; dimension = nlat.
- theta (numpy.ndarray) – 2-d numpy array of surface potential temperature field; dimension = (nlat, nlon).
- area (numpy.ndarray) – 2-d numpy array specifying differential areal element of each grid point; dimension = (nlat, nlon).
- dmu (numpy.array) – 1-d numpy array of latitudinal differential length element (e.g. dmu = planet_radius * cos(lat) d(lat)). Size = nlat.
- nlat_s (int, default None) – The index of grid point that defines the extent of hemispheric domain from the pole. If input as None, it will be initialize as nlat // 2.
- planet_radius (float, default 6.378e+6) – radius of spherical planet of interest consistent with input ‘area’.
Returns: - qref (numpy.array) – 1-d numpy array of value reference potential temperature Theta(y) approximated by box counting method, where latitude y is given by ylat; dimension = (nlat).
- lwa_result (numpy.ndarray) – 2-d numpy array of local surface wave activity values; dimension = (nlat, nlon).


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Bandwich
A simple 4-track recording interface designed with collaboration in mind
Weather Dashboard
Responsive weather dashboard linked to multiple Openweathermap APIs
Burger Buddy
Keeping a persistent tally of cullinary conquests with MySQL
Play'tSafe
Time-saving app that proposes creative movie and dinner combos
Ciphr
Solve and share algorithms with your peers


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I have a problem with the inline YouTube videos, none is shown correctly.
Only a black background neither a "PLAY" button nor the bar at the botton of the player.
Hope you can help me.
Yours,
BloodDragon1992
Topicstarter
BloodDragon1992
Problem solved:
I used Firefox 8, but I needed to update it


At the beginning of this year, I launched a stock market newsletter called Bullish. I’ve been building this project to be fully autonomous, trying to squeeze as much I can get from free tiers available everywhere, keeping costs close to zero, trying to build a completely automated micro SaaS product.
Bullish is a Ruby app that fetches data from multiple finance API’s and synthesizes that into an email template generated twice a day that gets triggered to MailerLite for delivery.
There are many ways to accomplish this task and the way I initially solved it was to re-purpose a Raspberry Pi that was collecting dust to run the project and set up CRON jobs to trigger emails and other tasks.
Although unusual, this configuration worked great, and the workflow was seamless; all I had to do was ssh into Pi and pull from master to get the latest updates.
Over time a couple of issues started to bother me. First, using Raspberry Pi introduced a single point of failure in the process if power was out, for example, or I was away from home, and something went wrong, there was no way to fix it.
Another problem is that I would forget to run bundle to install or update gems breaking the CRON jobs more often than not.
But the most concerning one was security-related. Bullish stores all of its API keys in an env file, and although not in source control, these keys had to be available in the Raspberry Pi for the service to run and that alone was a big enough reason to look for a better, more scalable and FREE solution.
There are many ways I could have solved this. The most elegant probably being a Lambda function run on a schedule with API keys managed by a service like AWS Secrets Manager, which I still might do at some point, but this time around, I was looking for a quick win.
I’ve been using Github Actions to run tests on every push to master branch, and one day it occurred to me, why not use this to have a workflow to trigger emails and other tasks as well?
Doing some research, I found that Github Actions supports jobs triggered by a scheduled event and has a generous free tier that would work perfectly for my use case.
Github Actions is still pretty new and has some annoying limitations like not sharing common data between jobs, leading to many duplicated steps, but it does allow sharing environment variables across jobs.
Another neat feature is that Github offers managed secrets that get injected in the container when the job executes, so no more API keys are in the open.
Overall I am satisfied with this solution, maybe not definitive, but it addresses most of my concerns like:
And as a bonus, you get notified via email if your job ever fails, giving free visibility that you would otherwise have to put together yourself in services like CRON to figure out if a job ran successfully or not.
Bullish is an open source project on GitHub.
Cheers.


| Name: smt.Vijayalakshmi | Reg No: 8-10smmhc18 |
|---|---|
| Age / Sex:59/f | Contact No: |
| Marital Status:married | Date:9/10/18 |
| Occupation:housewife. Studied upto 10th. | Dr. pjfp |
| Address:native of kadiri. | DIAGNOSIS- |
1.Dm since 7-8 years.
Random check as her dad and, ammamma,her sister and younger bro, husband, mother had dm, on aunt also has dm so simply got checked.no other signs and symptoms.
Pain in the right arm since 7-8 years. Can’t tcarry small weights also. Sleeps on the painful hand side only. because of pressure feels pain is less. Working while she doesn’t feel the pain.
Dust allergy from 37 years. In village stayed fr 10 years there rice husk and all use to create allergy.
Now her symptoms are if she is sleeping on left she feels breathless feels some veil is coming in between then only sweats and feels very uncomfortable.
Tinnitus in right ear since 2 years noticed. Vomiting and motion both same time and fainted. Cant hear keeps hearing like waterfall , insects sound in the night. Husband also deaf ( married to mothers brother). Has an implant in the right ear.
Feet burning , in te nights when wakes up. Must put on fan. Normally doesn’t put fan on. Only in hot season will put fan on.
Cramps on calf got tested vit d and ca deficiency .
f/h:
Dad : died 8 years – don’t know the age. Had had dm, paralysis, ?prostatitis was on catheter, had some rod in the left leg.
Mom: died 4-5 years: tb, asthma, dm,
Mggm: asthma
Husband: tb,
Past h/o:
Abortions – 3.
After that took susten inj fr the 4th then the pregnancy stood.
4th: elder son: 37 years.
5th : son:
6th : daughter.
Tubectomy .
Menopause : had some dub took allo and homoeo then stopped.
Personal h/o:
Diet: veg, vysyas.
Regular.
Crispy must be likes. Likes burnt food.
Thirsty: force as it is good fr health. Also must go to urine lot many times.
Motion: now and then mucus motions . offensive .. bowles normal otherwise. 2 / day. No control must go within 5 min.
Sleeps once wakes doesn’t get sleep. Getting sleep also is difficult.
Mind:
If silent doenst like must have some tv, newspaper, book. Family says do meditation but it doesn’t happen as she hears these sounds.
Rx:
Tuberculinum 1m- weekly doses. – Sunday.morning b/food.
Uran nit 30 – 4-0-4.disc30gm bottle.
antim tart 30 pills 3 pills evening b/food. 2 dram
Lycopodium 200 – 4-0-4. disc
Syphilinum 1m – weekly doses – morning b/food – Wednesday
Rub 30 – 1 dose night b/food.
Merc sol 200 – mucus motions 4 pills sos – 2 dram pills.
Carbo veg 30 – 4 pills sos. Breathlessness.
Calc phos 1m – one dose stat.
1/12/18: same no betterment.
Rx:
Conium 200 – pills 4-4-4. 3 dram.
cocculuc 200/thuja200 – 4-0-4 disc
kalmia 30+guiacum30+sangunaria200 – 4-4-4-4 disc
nux vom 200 – 4 doses – weekly b/food.
Sl 60 doses – 1-0-1
20/7/19:
1.mucous stools reduced
2.shoulder pain reuduced
rx:
1.k iod1m+borax200+nat mur200 4-0-4
2.rub1m 30 tab nt b/food
3.bc 25 4-0-4
r/a 1mnth


Time Management
by Sivan Rahav-MeirHow do we effectively and optimally manage time? Our sages emphasize that both Avraham and Sarah led full lives: “And the life of Sarah was 100 years and 20 years and seven years.”
The commentators stress that this verse’s emphasis on “years” is an indication that Sarah fully lived every one of them. “And Avraham was old, advanced in days” – that is, Avraham would arrive in the next world with each day of his life perfectly intact since each day had been filled with holy, beneficial activity.
This is how Rav Yerucham Levovitz of Mir explains it:
As is known, three angels came to the tent of Avraham and Sarah. One came to inform Sarah about the birth of Yitzchak, one to overturn the city of Sodom, and one to heal Avraham after his brit milah. And Rashi comments: “No angel takes on two missions.”
Each angel has only one mission for which that angel is uniquely qualified and upon which that angel is completely focused. And that should be our guiding principle, to liken ourselves to angels and completely focus on what we are doing at any given moment.
And so with each and every action, Rav Yerucham continues. A person needs to be completely there, exactly like an angel. If now is a moment that demands kindness and generosity, we need to be completely preoccupied with that. If now is a moment meant to study Torah, we need to be completely preoccupied with that.
“No angel takes on two missions.” We need to resist the confusion that comes with taking on many tasks at once. That’s how Avraham and Sarah – exemplars of time management – lived and we should be inspired by them to live that way, too.
- Translation by Yehoshua Siskin


WARNING! Selecting 'Quit GenderMag' below will clear all of your current session's data. Please ensure that you have downloaded the zip file which contains all your screen captures and a file with all of your answers if you wish to have a copy of your current session.


colorado package¶
Submodules¶
colorado.aims_tools module¶
-
class
colorado.aims_tools.
PyMesh
(aims_mesh=None)¶ Bases:
object
-
append
(frame)¶
-
normals
¶
-
polygon
¶
-
polygons
¶
-
to_aims_mesh
(header={})¶ Get the aims mesh version of this mesh.
-
vertices
¶
-
-
class
colorado.aims_tools.
PyMeshFrame
(frame=None)¶ Bases:
object
-
colorado.aims_tools.
add_border
(x, thickness, value)¶ add borders to volume (numpy)
-
colorado.aims_tools.
bucket_aims_to_ndarray
(aims_bucket)¶ Transform an aims bucket into numpy array
Parameters: aims_bucket (soma.aims.BucketMap_VOID.Bucket) – aims bucket object Returns: a Nx3 array of points of the bucket Return type: numpy.ndarray
-
colorado.aims_tools.
bucket_aims_to_volume_aims
(aims_bucket, pad=0)¶ Transform a bucket into a 3d boolean volume. Input and output types are aims objects
-
colorado.aims_tools.
bucket_numpy_to_volume_aims
(bucket_array, pad=0)¶ Transform a bucket into a 3d boolean volume. Input and output types are numpy.ndarray
-
colorado.aims_tools.
bucket_numpy_to_volume_numpy
(bucket_array, pad=0)¶ Transform a bucket into a 3d boolean volume. Input and output types are numpy.ndarray
-
colorado.aims_tools.
bucket_to_mesh
(bucket, gaussian_blur_FWWM=0, threshold_quantile=0, decimation_params={'feature_angle': 180, 'max_clearance': 3, 'max_error': 1, 'reduction_rate': 99}, smoothing_params={'iterations': 30, 'rate': 0.4, 'type': 'lowpass'})¶ Create a mesh from a bucket
Parameters: - bucket (np.ndarray or aims.Volume) – sequence of 3D points.
- gaussian_blur_FWWM (numeric) – the gaussian blur filter’s full with at half maximum.
- threshold_quantile (float in [0,1]) – voxels below this quantile will be set to zero.
- decimation_params (dict, optional) – decimation parameters. reduction_rate : expected % decimation reduction rate max_clearance : maximum clearance of the decimation max_error : maximum error distance from the original mesh (mm) feature_angle : feature angle (degrees), between 0 and 180
- smoothing_params (dict, optional) – smoothing parameters type : smoothing alorithm’s type (laplacian, simplespring, polygonspring or lowpass) iterations : smoothing number of iterations rate : smoothing moving rate at each iteration
Returns: A mesh obtained from the input volume
Return type: aims Mesh
-
colorado.aims_tools.
ndarray_to_aims_volume
(ndarray)¶ Create a new volume from the numpy ndarray. The array is first converted to Fortran ordering, as requested by the Volume constructor
Parameters: ndarray (numpy.ndarray) – the volume data Returns: an Aims Volume object containing the same data as ndarray Return type: aims.Volume
-
colorado.aims_tools.
ndarray_to_volume_aims
(ndarray)¶ Create a new volume from the numpy ndarray. The array is first converted to Fortran ordering, as requested by the Volume constructor
Parameters: ndarray (numpy.ndarray) – the volume data Returns: an Aims Volume object containing the same data as ndarray Return type: aims.Volume
-
colorado.aims_tools.
new_volume_aims_like
(vol)¶ Create a new empty aims.Volume with the same shape as vol
Parameters: vol (np.ndarray) – the volume data Returns: an empty Aims Volume object of the same shape as vol Return type: aims.Volume
-
colorado.aims_tools.
volume_to_bucket_aims
(volume)¶
-
colorado.aims_tools.
volume_to_bucket_numpy
(volume)¶ Transform a binary volume into a bucket. The bucket contains the coordinates of the non-zero voxels in volume.
Parameters: volume (numpy array | aims volume) – 3D image Returns: bucket of non-zero points coordinates Return type: numpy.ndarray
-
colorado.aims_tools.
volume_to_mesh
(volume, gaussian_blur_FWWM=0, threshold_quantile=0, translation=(0, 0, 0), mesh_decimation_params={'feature_angle': 180, 'max_clearance': 3, 'max_error': 1, 'reduction_rate': 99}, mesh_smoothing_params={'iterations': 30, 'rate': 0.4, 'type': 'lowpass'})¶ Create a mesh from a volume.
Before calculating the mesh, the volume is first blurred with a gaussian filter and then thresholded.
Parameters: - volume (np.ndarray or aims.Volume) – 3D binary image (if not binary, all vxels != 0 are set to 1)
- gaussian_blur_FWWM (numeric) – the gaussian blur filter’s full width at half maximum.
- threshold_quantile (float in [0,1]) – voxels below this quantile will be set to zero.
- decimation_params (dict, optional) – decimation parameters. reduction_rate : expected % decimation reduction rate max_clearance : maximum clearance of the decimation max_error : maximum error distance from the original mesh (mm) feature_angle : feature angle (degrees), between 0 and 180
- smoothing_params (dict, optional) – smoothing parameters type : smoothing alorithm’s type (laplacian, simplespring, polygonspring or lowpass) iterations : smoothing number of iterations rate : smoothing moving rate at each iteration
Returns: A mesh obtained from the input volume
Return type: aims Mesh
-
colorado.aims_tools.
volume_to_ndarray
(volume)¶ Transform aims volume in numpy array.
Takes the first element for every dimensions > 3.
Parameters: volume (aims.volume) – aims volume
colorado.anatomist_tools module¶
-
colorado.anatomist_tools.
anatomist_snatpshot
(window)¶ Return a screenshot of an anatomist window as numpy array that can be plotted.
Parameters: (anatomist.cpp.weak_shared_ptr_AWindow (window) – a reference to an open anatpmist window Returns: A snapshot of the window Return type: numpy.ndarray
colorado.bucket module¶
-
colorado.bucket.
draw_numpy_bucket
(bucket)¶ Draw one bucket from numpy array
Parameters: bucket (numpy.ndarray, shape (N,3)) – bucket Returns: a plotly figure representing the bucket Return type: plotly.graphic_objects.Figure
-
colorado.bucket.
draw_numpy_buckets
(buckets, labels=None, transpose=True, shift=(0, 0, 0), fig=None)¶ Draw buckets from numpy arrays.
Parameters: - buckets (Sequence[numpy.ndarray]) – a list of arrays representing the buckets to plot. Each array must be a Nx3 numpy.ndarray containing the coordinates of N points
- transpose (bool, optional) – for plot reasons, transpose each bucket array if True, defaults to True
- x_shift (num, optional) – Amount of x shift to add to each sulcus, defaults to 0
-
colorado.bucket.
get_aims_bucket_g_o
(aims_bucket, name=None, shift=(0, 0, 0), **kwargs)¶ Plot a soma.aims Bucket
-
colorado.bucket.
get_aims_bucket_map_g_o
(aims_bucket_map, name=None, shift=(0, 0, 0), **kwargs)¶ Draw a bucketMap object, which is obtained with aims.read() on .bck files
-
colorado.bucket.
get_bucket_g_o
(bucket, name=None, marker_kwargs={'opacity': 1}, shift=(0, 0, 0), **kwargs)¶
colorado.mesh module¶
-
colorado.mesh.
draw_meshes_in_subplots
(mesh_list, cols=3)¶ Draw meshes in a subplot grid.
Parameters: - mesh_list (list[aims mesh | PyMesh]) – a list of meshes to be drawn
- cols (int, optional) – Number of columns in the subplot. Defaults to 3.
Returns: the complete figure
Return type: plotly.graphic_objects.Figure
-
colorado.mesh.
draw_numpy_meshes
(list_of_vertices, list_of_polygons, labels=None)¶ Draw meshes from the vertices and polygons of the mesh. The meshes are drown in the same figure.
Parameters: - list_of_vertices (list[numpy.array]) – lists of array of points.
- list_of_polygons (list[numpy.array]) – lists of array of points.
- labels (list[str], optional) – list of plots labels. Defaults to None.
Returns: the complete figure
Return type: plotly.graphic_objects.Figure
-
colorado.mesh.
draw_pyMesh
(mesh, shift=(0, 0, 0), **kwargs)¶ Draw a PyMesh object
Parameters: mesh (PyMesh) – The mesh to be drown Returns: graphic object Return type: plotly.graphic_object
-
colorado.mesh.
get_aims_mesh_g_o
(mesh, name=None, shift=(0, 0, 0), **kwargs)¶ Get a plotly graphic object from an aims mesh
-
colorado.mesh.
get_mesh3d_g_o
(vertices, polygons, name=None, shift=(0, 0, 0), **kwargs)¶ Get an plotly graphic object from numpy arrays
Parameters: - vertices (numpy.ndarray) – Nx3 array of points representing the vertices
- polygons (numpy.ndarray) – Nx3 array of points representing the polygons
- name (str, optional) – The plot name. Defaults to None.
Returns: a graphic pbject
Return type: plotly.graph_objects
Module contents¶
-
colorado.
draw
(data, fig=None, labels=None, shift=(0, 0, 0), draw_function=None, draw_f_args={}, **kwargs)¶ Draw objects with plotly
Parameters: - data (soma.aims mesh/volume/bucket) – an object or a list of objects. Object can be an aims bucket, an aims Mesh or a PyMesh
- fig (plotly.graph_objects.Figure, optional) – the plotly figure, if None, one is created, defaults to None
- labels (list[str], optional) – an array of labels for the data if data is a list, defaults to None
- shift (tuple, optional) – shift the plots in data each by (x,y,z), defaults to (0,0,0)
Returns: a plotly figure
Return type: plotly.graph_objects.Figure
-
colorado.
draw_as_mesh
(data, gaussian_blur_FWWM=0, threshold_quantile=0, labels=None, shift=(0, 0, 0), **kwargs)¶


Welcome to the world of
Charles Grealy!
In May 2020 I graduated from the University of Houston with a bachelor’s in mathematics. All through primary school math was both my favorite and strongest subject so it felt fitting to study it in college.
Before attending college, I decided my career plan would be to become a programmer. I came to this decision after discovering certain programming fields require a strong math background. I researched what math graduates were doing in their career and quite a lot had successful careers as a programmer. Including my dad, who was a programmer for 40 years and coincidentally a math major!
In order to gain programming experience, I chose to minor in computer science. Well, after the first introductory to programming course I quickly learned that computer science would be a subject that felt rather natural. The abundance of material (ex: books, articles, StackOverflow, and FreeCodeCamp) available absolutely enriched the education experience. Programming sure does inject serotinin into my veins.
Blog Entries
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{{ post.date|date:"M d, Y" }} - {{ post.title }}
A Calculator on the Web
A mathematical calculator that features keyboard support. HTML/CSS is used to develop the style and layout. JavaScript is used for the overall functionality.
GitHub Live WebsiteOnline Etch A Sketch
Remember Etch A Sketches from your childhood? Here's one online featuring an assortment of colors including a random color generator. Entirely developed with JavaScript and an empty HTML file in order to push to a live website. Option to change the size of the board upon clicking erase.
GitHub Live WebsitePersonal Website
A quarantine project of mine was to create my personal website from scratch. I'll say it's the most fun I have had to date! The goal in the beginning was to only develop a blog, but that later changed when I wanted to expand on the challenge. First I acclimated myself with django (Python). I learned about url mapping, creating views, configuring a database powered by PostgreSQL, and template tagging. Then I created a layout from HTML/CSS and implemented JavaScript to create pleasant features such as smooth scrolling and a drop down menu in the blog posts. Finally, I was able to learn how to push into production via Heroku and transfer to a proper domain.
GitHubStock Portfolio Chatbot
Another quarantine project based upon an interest of mine, the stock market. Yep, I am completely invested in the stock market - pun intended. With Flask (Python) and the help of the Twilio API arose a chat bot used in WhatsApp. Since I became familiar with django by now, Flask felt more natural - in fact maybe quite easy to configure. The program searches for stock prices using a stock market API and stores user data in a PostgreSQL database.
GitHubPython Interpreter in C++
An interpreter reads and executes code. Therefore, a Python interpreter reads and executes Python code. The final project for a class during my undergrad was to build a basic Python interpreter in C++. One of my favorite projects! The objective was to take a Python (.py) file as input, parse each statement, and produce Python-like output. The statements included variables, lists, or a combination of both. Output consisted of the list contents. It's as if you typed 'python' in the terminal, but C++ would become the interpreter.
GitHubIntroduction
Download formal resume (.pdf)I am currently an Instructor at Coder Kids where I teach programming to kids using languages like Scratch and Python. In the last 4 years I focused on my academics at the University of Houston where I obtained a bachelor’s in Mathematics in May 2020.
Education
University of Houston
Houston, TX
Jan 2016 — May 2020
B.Sc in Mathematics
- Overall GPA of 3.26
- Minor in Computer Science
- Noteable coursework: Discrete Mathematics, Data Mining, Introduction to Computer Graphics, Numerical Linear Algebra, Advanced Linear Algebra (1 & 2), Data Structures and Algorithms, Programming Languages, Statistics for the Sciences
- Programming Experience : C++, Python, MATLAB, R
Work Experience
Coder Kids
Instructor
January 2020 — Present
Houston, TX
- Educated 50+ students in first through eigth grade programming fundamentals in Python and Scratch.
- Introduced object oriented programming and other complex topics in a feasible manner
- Provided an open learning environment to increase engagement and encouragement
- Organized free lessons to those absent or for those extra interested
Lennar (formerly Ryland Homes)
IT Technical Support
February 2012 — September 2014
Houston, TX
- Managed new office configurations and ongoing maintenance of the offices for over 150 employees
- Managed technology inventory to ensure surplus available in case of irrepairable devices or onboarding new hires
- Ensured model homes and construction trailers always had internet access by installing wireless 4G devices when necessary or communicating with cable companies
- Troubleshot hardware and software issues at the main office or model homes around Houston and surrounding areas


Please complete the following tutorial and study tasks in order. The current task will be highlighted in blue, tasks you have completed will be in green, and tasks that cannot be started yet are in grey.
During the study, we will ask you to think outloud, which means that you verbally say every question, thought, and observation that you are thinking. This helps us review the study afterwards to understand your thought process.
Thoughout this study, Do Not Use The Browser Back Button!
Please complete this pre-study form before starting
Please complete this post-study form after completing the tasks.


Do You Care About Increasing the Number of Women in Tech?
#gilttech does. To this end, we hosted a roundtable discussion last night featuring more than 25 representatives from some of NYC’s top girls- and women-in-tech organizations. We wanted to hear more about their experiences trying to involve girls and women in tech, and about the challenges they and/or their group members have faced along the way. Other goals:
- To gather organizations working on helping girls and women enter the tech industry by providing coding instruction, mentoring, and other resources/forms of support
- To put like-minded, successful organizers in touch and facilitate networking+brainstorming
- To discuss bias (including the unconscious type) and ways to address/resolve it at different levels (from C- to team-)
- To identify action items for the group to work on
Everyone brought valuable insights and a wealth of experience to the table, which made for a very lively and informative conversation. Participants focused on implementing positive changes that involve and benefit everyone in the tech industry (after all, more women = higher profits). The general consensus is that men need to be a part of our future conversations and our efforts to propose solutions.
Who attended?
Represented groups included:
- Black Girls Code
- Girl Develop It
- RailsBridge
- PyLadies
- NYCTechLatinas
- Girls Who Code
- ClojureBridgeNYC
- Gilt Tech Women
- Gawker Media (starting an internal women-in-tech group)
- NYC Ruby Women
- NYC Lady Project
- Django-NYC
So what comes next?
Participants will be discussing that in our follow-up meetings and conversations.
I want to be a part of the conversation! How can I get involved?
Please tweet at us to let us know what you’d like to contribute. We’re specifically targeting founders and organizers of tech groups, but enthusiastic male allies are also welcome. (For more about male allies and advocates, read this very relevant study by the National Center for Women & Information Technology.)


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Film review by Kevin Patterson
RUN LOLA RUN Rating: ***1/2 (out of four) R, 1999 Director/Screenplay: Tom Tykwer Starring Cast: Franka Potente
RUN LOLA RUN should be required viewing for all Hollywood action-movie directors. Here is a film that is as fast-paced and exciting as anything I've seen the past couple of years, and not only does it establish its breakneck pace without blowing anything up or dropping giant pieces of CGI on the screen, but it even creates a couple of sympathetic characters and offers some clever bits of commentary and insight along the way.
The premise is about as simple as they come. Lola (Franka Potente), a young woman living with her parents, receives a frantic telephone call from her boyfriend Manni, who has misplaced 100,000 deutschmarks of drug money only twenty minutes before he was supposed to deliver it to a gangster. Certain that he will be killed if he shows up without the money, he plans to rob a grocery store. Lola begs him to wait and promises to come up with the money--somehow. Since her bicycle has been stolen, she has to run from one location to the next as she tries to come up with the cash.
All of this exposition occurs in the first ten or fifteen minutes. Following that, writer/director Tom Tykwer shows us three different scenarios for what will happen in the next twenty minutes. Suffice it to say that all of them involve Lola scrambling between several locations, and that in each case it goes right down to the wire before we see whether Lola and Manni will escape their predicament or not. I would estimate that at least five to seven minutes of each scenario are spent on Lola running through the streets, yet these scenes do not grow tiresome in the least. Tykwer has a particularly flamboyant visual style: his camera rarely sits still, and when it does, it's usually watching from an unusual angle. More often, it's following Lola on one of her mad dashes, circling rapidly around a character in crisis, or even taking a swooping dive towards the scene. But his methods are varied enough to avoid overkill, and the combination of his hyperactive camera work and the film's energetic techno score make for a brand of frenetic action that is rare even in today's world of hi-tech filmmaking.
The most interesting aspect of RUN LOLA RUN is the way in which Tykwer uses the differing scenarios to reflect his ideas about fate and chance. In each, there are at first only minor variations, but they soon lead to larger ones. For example, in both the first and second scenarios, Lola goes to her father's bank to try to get the money, but in the second, someone trips her as she runs down the stairs. As a result, the timing of her later collision with a passerby varies by a second or two, and when she gets to the bank, she arrives at a somewhat more uncomfortable moment in her father's conversation with his illicit lover. Thus his reaction to her sudden appearance is much more immediately hostile, which dramatically alters everything that follows. Tykwer also employs a clever gimmick whereby he momentarily cuts away from Lola to someone whom she has just passed, then shows a quick series of photographs that detail the rest of the person's life. These are also sometimes dramatically different between scenarios, depending on what exactly happens when Lola passes the person.
I've grown somewhat tired of movies that establish their hip credentials by making criminals their protagonists, but RUN LOLA RUN gets away with it because it manages to portray its characters sympathetically without whitewashing their actions. It is when Lola and Manni abandon their criminal impulses that they are most successful in escaping their predicament, and in one case divine intervention even seems to play a role. Two wrongs don't make a right in this film, and when Lola or Manni starts threatening violence or attempting robbery, things tend to go even further awry as a result.
This is not to say that RUN LOLA RUN is some sort of philosophical masterpiece, just that it can lay claim to a certain amount of depth underneath its high style. It isn't the most intelligent film of the year, but it might be the most entertaining, and it reaches that plateau without falling into the category of a guilty pleasure.
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Immunity wall/ or extended skin
Project
Final presentation
Theme : Can we recognize the architecture as part of my body?
Design the architectural wall with an immune mechanism by maintaining an ideal microbial flora like our skin microbiome.
Previous studies
1. Biology arena
Nowadays, we sterilize everything we touch to protect ourselves from disease. However, antibiotic resistance bacteria are increasing year by year.
2. Architectural design arena
Jessica Green of the University of Oregon research the building microbiome by metagenome analysis. She argues the machine ventilation system reduce the diversity of bacteria in building.
And some research gropes analyse the microbiome in the architecture.
Hypothesis and the purpose of this project
I think we have to reconsider excessive sterilization and use of antibiotics.
So I'd like to consider architecture with a defense mechanism by microbial flora like our skin.
And I want to ask people through this project: Can we recognize architecture as part of my body?
Project abstract
1. My family's skin microbiome analysis.
2. Selection and culture of bacteria.
3. Designing the architectural wall.
4. Making the future scenario.
5. Evaluation.
Progress of the project
1. My family's skin microbiome analysis.
First, I asked for metagenome analysis to know the bacterial balance of my skin microbiome. I swabed my family's skin and collected samples. I sent these samples to the bioinfomatics company. Few weeks ago, I received the result of metagenom analysis.
This is the result of metagenome analysis of samples.
The samples are my mother, my grandfather and myself.
Because I and my mother are close to lifestyles, the balance of skin microbiome is relatively similar. On the other hand, I can see that my grandfather has different skin microbiome balance.
2. Selection and culture of bacteria.
Ideally, I want to reproduce these skin microbiome balance on the architectural wall. But it's so hard. So in this project, I selected 2 bacteria spp, and cultivate them.
2 spp are Staphylococcus epidermidis and Propionibacterium acnes. Both bacterias produce fatty acids to keep the skin weakly acidic. Weakly acidic skin can protect ourselves from some infection.
Now, I cultivate my skin microbiome and isolate these 2 bacteria spp from it in my house.
3. Designing the architectural wall.
It is difficult to make a big wall in this project. So I plan to create doorknobs or control panels, which are elements of architecture that people frequently contact.
4. Making the future scenario.
I'm wrriting the future scenario that shows how the "wall" is used.
5. Evaluation.
I'm planning a metagenome analysis of my house environmental microbiome. Therefore, I'd like to evaluate from the analysis results how much the target bacteria have become established in the "wall" I made.


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Get ready for fall with cozy staples, luxe bags, more essentials - up to 85% off
Lululemon secretly marked down these 15 favotires - starting at $19
This mini waffle maker made my mornings so much easier - but it's selling out


2 A Brief Note on using Colors
Before we start plotting our data, we need to spend some time to have a closer look at color representation of certain variables. A careful study of color spaces (e.g. Zeileis, Hornik, and Murrell (2009), HCLwizard, Aisch (2011) or Wikipedia) leads to the conclusion that the HCL color space is preferable when mapping a variable to color (be it factorial or continuous).
This color space is readily available in R through the package colorspace and the function of interest is called hcl()
.
In the code chunk that follows we will create a color palette that varies in both color (hue) and also luminance (brightness) so that this can be distinguished even in grey-scale (printed) versions of the plot. As a reference color palette we will use the ‘Spectral’ palette from ColorBrewer which is also a multi-hue palette but represents a diverging color palette. Hence, each end of the palette will look rather similar when converted to greyscale.
library(RColorBrewer)
clrs_spec <- colorRampPalette(rev(brewer.pal(11, "Spectral")))
clrs_hcl <- function(n) {
hcl(h = seq(230, 0, length.out = n),
c = 60, l = seq(10, 90, length.out = n),
fixup = TRUE)
}
### function to plot a color palette
pal <- function(col, border = "transparent", ...)
{
n <- length(col)
plot(0, 0, type="n", xlim = c(0, 1), ylim = c(0, 1),
axes = FALSE, xlab = "", ylab = "", ...)
rect(0:(n-1)/n, 0, 1:n/n, 1, col = col, border = border)
}
So here’s the Spectral palette from ColorBrewer interpolated over 100 colors:
pal(clrs_spec(100))
And this is what it looks like in greyscale:
pal(desaturate(clrs_spec(100)))
We see that this palette varies in lightness from a very bright center to darker ends on each side. Note, that the red end is slightly darker than the blue end.
This is quite ok in case we want to show some diverging data (deviations from a zero point, for example the mean). However, if we are dealing with a sequential measure, such as temperature, or in our case the density of points plotted per some grid cell, we really need to use a sequential color palette. There are two common problems with sequential palettes:
- We need to create a palette that maps the data accurately. This means that the perceived distances between the different hues utilized need to reflect the distances between our data points. AND this distance needs to be constant, no matter between which two point of the palette we want to estimate their distance. Let us consider the following example showing a classic ‘rainbow’ palette (MATLAB refers to this as ‘jet colors’):
pal(rainbow(100))
It becomes obvious that there are several thin bands in this color palette (yellow, aquamarine, purple) which do not map the distances between variable values accurately. That is, the distance between two values located in or around the yellow region of the palette will seem to change faster than, for example, somewhere in the green region (and red and blue).
When converted to greyscale, this palette produces a hell of a mess:
pal(desaturate(rainbow(100)))
Note, that this palette is maybe the most widely used color coding palette for mapping a sequential continuous variable to color. We will see further examples later on… We hope you get the idea that this is not a good way of mapping a sequential variable to color!
hcl()
produces so-called perceptually uniform color palettes and is therefore much better suited to represent sequential data:
pal(clrs_hcl(100))
We see that the different hues are spread constantly over the palette and therefore it is easy to estimate distances between data values from the changes in color. The fact that we also vary luminance here means that we get a very light color at one end (in our case, the red end which is more of a pink tone than red). This might, at first sight, not seem very aesthetically pleasing, yet it enables us to encode our data even in greyscale:
pal(desaturate(clrs_hcl(100)))
As a general suggestion, we encourage you to make use of the HCL color space whenever you can. But most importantly, it is essential to do some thinking before mapping data to color. The most basic question you always need to ask yourself is probably
What is the nature of the data that I want to show? More precisely, is it sequential, diverging, or qualitative?
Once you know this, it is easy to choose the appropriate color palette for the mapping. A good place to start for choosing palettes that are perceptually well thought through is ColorBrewer.
References
Zeileis, Achim, Kurt Hornik, and Paul Murrell. 2009. “Escaping RGBland: Selecting Colors for Statistical Graphics.” Computational Statistics and Data Analysis 53: 3259–70. doi:10.1016/j.csda.2008.11.033.


Elixir is the socio-cultural fest of B.P.PODDAR INSTITUTE OF MANAGEMENT
AND TECHNOLOGY, Kolkata. Over the years, Elixir has established a legacy of fellowship
and pride which fosters cultural diversity and stimulates creativity and imagination.
This spring we unveil a fest which shall witness days of absolute ecstasy, providing the
budding artists a competing platform in diverse fields such as music, dance, theatre,
photography, literature. So get ready to bask in the glory of a magnificence of an
unprecedented scale and embrace all the fun and frolic because ladies and gentlemen,
ELIXIR '19 will be unparalleled! Let 2019 spring bring to you the ’19 edition of Elixir which means
2019 will not just be another year, it will be THE year!
Elixir is the socio-cultural fest of B.P.PODDAR INSTITUTE OF MANAGEMENT
AND TECHNOLOGY, Kolkata. Over the years, Elixir has established a legacy of fellowship
and pride which fosters cultural diversity and stimulates creativity and imagination.
This spring we unveil a fest which shall witness days of absolute ecstasy, providing the
budding artists a competing platform in diverse fields such as music, dance, theatre,
photography, literature. So get ready to bask in the glory of a magnificence of an
unprecedented scale and embrace all the fun and frolic because ladies and gentlemen,
ELIXIR '19 will be unparalleled! Let 2019 spring bring to you the ’19 edition of Elixir which means
2019 will not just be another year, it will be THE year!


I have travelled to the north on numerous occasions, seeing sights such as the giants causeway.Belfast City is a great city with many attractions such as the Titanic Museum.
Another place which i enjoyed visiting was the Ulster-American Folk park, due to my interest in History.
I travelled through wales when i was travelling to Manchester, I admired the beautiful scenery
We arrived in HolyHead and went paintballing
I have been to england 3 times. I have travelled to places such as Devon & Cornwall, St.Ive's, Manchester and London. When i was in First year me and my classmates
travelled to Manchester to see Man United play against Q.P.R . It was a fantastic day made even better when United beat Q.P.R 3 - 1. I also travelled to London With my friends in October 2018. We saw landmarks such as Tower Bridge, The tower of London and Big Ben. We
also went and saw the Los Angeles Chargers play the Tennessee Titans in Wembley Stadium, which was a fantastic experience.
I have been to France twice. My grand aunt owns a house in the south of France, in the town of Colliure. The scenery there is breathtaking, being below the pyrennes mountains
and being situated on the coast, which hosts numerous beautiful beaches. We also visited the castle at Carcassone. It is a perfectly preserved medieval town in the south of France.
We were lucky enough to witness a medieval jousting tournament. Inside the walls of the castle there is many medieval themed shops and restaurant's.
You could also visit the perfectly preserved castle armoury and Throne room.
I have been to Spain on numerous occasions. My family and I usually travel up towards the north of Spain in the Catalan regions. There are many beautiful beaches located there
with breathtaking scenery. It is located on the Costa brava (rocky coast) which gives rise to beautiful sea cliffs and rugged landscapes.
I have also visited Barcelona and Madrid whilst in Spain. Madrid is the most memorable city i have ever visited. It is bursting with culture and has
plenty to see and do such as the Santiago Bernabeau, Madrid Bullring, Toledo, The retiro park and the nighttime atmosphere in the place de sol.
I visited portugal once with my family. We stayed in the town of Villamoura. Portugal is a beautiful country which hosts beautiful weather and scenery.
The Portugese also make beautiful food particulary the meat and steak dishes they prepare. There was a beach near us where we could participate in various
water activities or relax if we felt like it.
I would love to visit the U.S.A in the next few years as it is a vast and beautiful country. I would first like to visit my relatives in Boston and then
proceed to travel around the U.S and see as much as I can. I would love to see the major cities such as New York City, Chicago, Los Angeles and San Fransisco
and of course, Las Vegas. I would also like to travel Route 66, which would give me a chance to take in the beautiful American countryside.
I have a great interest in visiting the nation of Japan. I am fascinated by The samurai and Japan's exciting history. The Samurai are unique and
beautiful works of architecture which i would love to see. Many museums in Japan have a wide display of Samurai weapons
and armour. Japan is also one of the most technologically developed countries in the world, which can be showcased by Japan's
capital city, Tokyo. This is one of the most energetic and futuristic cities in the world.


References
Class Summary
| Static Public Class Summary | ||
| public |
App Class, a container, wires all the components. |
|
| public |
A basic Button Class used for creating html buttons. |
|
| public |
A basic Select Class used for creating html select tags. |
Function Summary
| Static Public Function Summary | ||
| public |
A basic Option class used by the |
|
| public |
ProgressBar(percentage: number): XML ProgressBar constructs the html needed to present a Progress bar. |
|
| public |
A basic Section class used to creating html |
|
| public |
buttonBarsReducer(state: *, action: action): any button and bars Reducer |
|
| public |
Fetch All the buttons and bars from the server. |
|
| public |
Watch for Dispatch ACTIONS.MAKE.INITIATE so the saga can be kicked off. |
|
| public |
|
|
| public |
Initiate the workflow by making request for the button bars data. |
|
| public |
* rootSaga() |
|
| public |
Save the data into the store. |
|
| public |
Update the given Bar by index, adding the given percentage to the value. |
Variable Summary
| Static Public Variable Summary | ||
| public |
store: * A Redux store that lets you read the state, dispatch actions and subscribe to changes. |


{tag_feedback} | Customer comment |
{tag_fullname} | Full name of the person who submitted the comment (anonymous if not available) |
{tag_fullname_nolink} | Full name of the person who submitted the comment without a link (anonymous if not available) |
{tag_rating} | Rating in stars |
{tag_usagedate} | Date when comment was given |
{tag_pendingcomments} | Checks if status of the comment is set to "pending" from admin, in whic case outputs the following message: Your comment is awaiting moderation! |


Use the tool below to declare the appropriate number of drink servings for your event. You can adjust the total number at any time before you submit your application.
The quantity of liquor purchased for the event must not exceed the quantity specified on your permit.
Hosting a liquor tasting? Use the conversion tool below.
According to the information you provided, the number of drinks served at your event should not exceed {{max_servings}}. This is a basic guideline. You may enter your own declared maximum servings, however, please remember that you are responsible for the safety of your guests and are required to prevent over-service and intoxication.


Greetings, my name is Andrew Tocchi and this is my personal bio. To the left you will see a wonderful image of my dog Dalton. Off the bat, I did not name him that was his name already. I apologize, everything after this is essentially going to be a reformatted resume. ENJOY! I have a great interest in technology, it spans the gap between things like SDR to simple networking and website design. I enjoy learning and growing when it comes to emerging tech or new fields of study. I take great pride in my ability to troubleshoot complex issues and to makes sense of chaos.
I recieved two bachelors degrees from UC Berkeley, one in Art Practice and the other in Medieval History. I worked as an educator for several years and then worked as a buisness techinican for a major ISP. Nowadays I am working as an IT Sysadmin in the Transit Industry, and greatly enjoy the large scope of my work. I am constantly learning on the job and in my daily life and I never turn down a chance to expand my wealth of knowledge.
I have worked with a variety of different tech systems. I have worked with SDR when assessing the intergity of vast stretches of coax cable. I have worked with network diagnostic tools like wirehark as well as linux based tool kits. I have exeperience troubleshooting advanced VoIP issues, from physical PBX issues to SIP trunk failures. I have not only worked on as-builts for complex network layouts, but have personally routed, wallfished, and strung physical cables of every variety.


Run Configurations
Clicking the Advanced... button, a new block appears below:
- Initialization Timeout
- Total time (in seconds) to wait for ZAP to initialize.
Warning: If ZAP has not been initialized after the specified time then the program is stopped and the build is marked as a FAILURE.
- Total time (in seconds) to wait for ZAP to initialize.
- Add ZAP command line option
- This fields allows you to add ZAP command line options.
Recommend: If having followed the System Installed guide above, it is recommended to set the
installdir
command line option.Info: Please see HelpCmdline for more information.
Warning: Adding a ZAP command line option can interfere with other UI options of the ZAP Jenkins plugin. Use with caution!
- This fields allows you to add ZAP command line options.
Attachments:
advanced.png (image/png)


Neuroplasticity
Neuroplasticity is the term given to the brains ability to change and adapt over the course of one’s life and through our interactions with our environment. The benefits of neuroplasticity have been seen in stroke victims, people who have lost limbs and brain injury where, as opposed to loosing function, the brain can reconfigure to continue to allow a function that would normally have taken part in the damaged portion of the brain.
This also has an obvious effect on learning. Even just knowing about neuroplasticity can help to overcome some of the mental barriers associated with learning and one’s perception of one’s own intellect. In undertaking this course at EDA, I will be ensuring that I maximise my brains ability to change and ensure permanent learning takes place by:
- Getting good quality sleep
- Continually learning
- Keeping stress levels low
- Engage in projects that I can understand the purpose of to maximise relational connections
- Keep away from negative influences
Check out this site for more info https://bebrainfit.com/brain-plasticity/
Growth Mindset
Having a growth mind-set is to have the understanding that abilities and intelligence can be developed. Our brains are not fixed and the more we learn and practice the smarter we can get. Having a growth mind-set, especially at the outset of learning a new skill, is critical as it breaks down the mental barriers that we put in place that say “we aren’t smart enough to do this”. For me a growth mind-set is nothing new, the idea is highly utilised in the IT sales sector as a way to challenge mental barriers of which there are an unlimited number in sales. I’m undertaking this course in part because I already believe in a growth mind-set and have absolute confidence that I will make a great developer and also love doing it.
From a resource perspective, take a look at Gartner’s piece on growth mind-set in technology leadership roles being critical for the digital business journey. https://www.gartner.com/smarterwithgartner/leadership-practices-to-foster-a-growth-mindset-2/


Settings Environment: Select Service: DUNS# (optional): Advanced Settings Request URL: Application ID: User ID: Password: Payload: Send Service Request


--- layout: post title: no title date: '2014-11-29T07:30:44+01:00' categories: - Sketches picture_url: https://film-Storyboards.tumblr.com/post/103887030113 ---


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SFSU Software Engineering Project CSC 648-848, Fall 2020. For Demonstration Only
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{% extends 'base.html' %} {% block content %}
Back
Snack:
Snack Name: {{ snack.snack }}
Snack Purchaser: {{ snack.purchaser }}
Last Modified: {{ snack.modified }}
Update Snack
DELETE FOREVER


{% load markdown_deux_tags %} {% load static %} {% block content %}
| S.No. | Student | View Response | {% if download_allowed %}Download Response | Download Prompt | {% endif %}Attempt Submission Time | Duration of Attempt | Grades |
| {{forloop.counter}} | {{attempt.student}} | {% if view_download_allowed %} | Download Response | {% endif %}Download Prompt | {{attempt.submission_time}} | {{attempt.duration}} | {{attempt.grade}} |


Cowbest Milk Farm
The Report For Milk Produced Per Shed.
A report on how much you will earn on a weekly basis or even on a yearly basis.
The Report For a Leap Year At a Ksh. 45 rate.


abort
OS/161 Reference Manual
Name
abort - abnormal program termination
Library
Standard C Library (libc, -lc)
Synopsis
#include <abort.h>
void
abort(void);
Description
The abort function causes immediate abnormal program termination.
Cleanup is not performed.
Return Values
abort does not return.