Slider

Komponent, mis kuvab oma lapsi slaidiesituses või karussellis.

Valikud

• title | (string|node): slaidiesitluse / karusselli pealkiri, mis kuvatakse selle ülaosas. Default: none.
• dots | boolean: kuvatakse punkte allosas, et kiiresti liikuda mis tahes slaidi juurde. Default: true.
• fade | boolean: kontrollib, kas slaidide vaheliseks üleminekuks kasutatakse fadingut.. Default: false.
• draggable | boolean: kontrollib, kas kasutajad saavad slaidide vahel navigeerimiseks neid lohistada.. Default: false.
• pagination | string: kas kuvada lehekülgede kaupa kas top, bottom või both.. Default: 'bottom'.
• goto | number: Kui omadust muudetakse, hüppab komponent valitud indeksiga slaidi juurde.. Default: 0.
• infinite | boolean: kontrollib, kas slaidiesitlus kerib ümber oma sisu.. Default: false.
• interval | number: määrab automaatse slaidivahetuse ajaintervalli. Default: none.
• swipe | boolean: võimaldab lohistamise/ pühkimise käitumist. Default: false.
• style | object: CSS inline stiilid. Default: {}.
• onClick | function: callback, mis kutsutakse esile, kui vajutatakse nuppudele next/previous (järgmine/eelmine). Default: onClick() {}.

Näited

• Minimal
• Customize Pagination
• Slideshow
• Custom Styling

Live toimetaja

<Slider title="Questions to explore:" > <p>Try generating new samples of the Normal data. You'll notice that the points don't always lie exactly on the line. This is typical variation. As you generate more random realizations of this plot you'll get better calibrated to the kind of deviation you can expect to see from this large a sample of Normal data.</p> <p>How do the normal qq plots change as you vary the df parameter for the t-distributed data?</p> <p>Can you tell just by looking at the t.data histograms that the data aren't normally distributed? Is it easier to tell from the QQ plots?</p> <p>How do the normal qq plots change as you vary the shape parameter in the gamma-distributed data?</p> </Slider>

<Slider title="Questions to explore:" >
    <p>Try generating new samples of the Normal data. You'll notice that the points don't always lie exactly on the line. This is typical variation. As you generate more random realizations of this plot you'll get better calibrated to the kind of deviation you can expect to see from this large a sample of Normal data.</p>
    <p>How do the normal qq plots change as you vary the df parameter for the t-distributed data?</p>
    <p>Can you tell just by looking at the t.data histograms that the data aren't normally distributed? Is it easier to tell from the QQ plots?</p>
    <p>How do the normal qq plots change as you vary the shape parameter in the gamma-distributed data?</p>
</Slider>

Tulemus

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