Plots Resolution

• Complete the output from the Plot dialog box Note: The higher the fidelity, the more computer memory is used, so the longer it takes to plot. High fidelity is not necessary for all plots, and a setting between 300 and 600 dpi is generally sufficient for most plots. Was this information helpful?
• How to change the resolution of a plot in base R? In base R, we can save a plot as a png and pass the resolution in the same stage. The procedure to do this is creating the png image with resolution with res argument then creating the plot and using dev.off to create the file. Check out the below examples to understand how it works.

What Is A Plot Diagram?

Plot: The plot consists of the events that happen in the story. In a plot you typically find an introduction, rising action, a climax, the falling action, and a resolution. In a plot you typically find an introduction, rising action, a climax, the falling action, and a resolution.

A plot diagram is a graphical representation of the plot of the story. A story plot diagram is a line graph of story's events, beginning with the story’s start on the left and continuing toward the right, ending with the story’s conclusion.

[insert drawing of plot diagram based entirely on the one from the existing piece; there’s nothing wrong with it]

Whether writing creatively or analyzing another author’s writing, you can study the plot structure and storyline using a plot diagram.

1. Elements of Plot

Elements Of Plot

The plot of a story is the unfolding sequence of events. Just about every story has the same parts of the plot. The six parts of a story are:

1. Exposition
2. Conflict
3. Rising action
4. Climax
5. Falling action
6. Resolution

These six elements break down into three chronological segments. Each segment of the story usually has two elements.

1. Beginning – contains the exposition and establishes the story’s conflict.
2. Middle – contains the rising action and the story’s climax.
3. Conclusion – contains the falling action and resolution.

Exposition

Exposition in a plot introduces of the story’s setting, mood, the main character, supporting characters, and time. Character development happens during this part of the story.

Conflict

Conflict is the problem, crisis, challenge, dilemma, or obstacle presented to the main character.

Rising Action

The rising action is a sequence of solutions to the conflict that the main character tries; it is all the events leading to the turning point of the story. It can be identified by increasing tension, emotion, difficulty, or challenge.

Climax

The climax of the story is the peak of excitement, the moment when the story changes (a turning point), the main character, and the problem is resolved.

Falling Action

The Falling action is all the plot points wrapping up, the consequences of the climax, and reflection on the changes in the main character. It can be identified by decreasing tension, an approaching resolution, and relaxation of emotion.

Resolution Of A Story

The resolution is the plot’s end, whether that resolution is a happy ending or sad ending, fun or frightening, satisfying or unsatisfying. The resolution might tie up loose ends or leave important elements of the story unresolved.

Plot Diagram Example

We can take the simplest of tales, such as Little Miss Muffet, to practice constructing a plot diagram. Here is the original nursery rhyme:

Little Miss MuffetSat on a tuffet,Eating her curds and whey;Along came a spiderWho sat down beside herAnd frightened Miss Muffet away.

What is the story’s beginning? Who is the main character? What is the setting? At the story’s beginning, we are introduced to Miss Muffet, who is sitting on a tuffet (a hassock), eating cottage cheese.

In the rising action, what conflict does our main character face? She must deal with the arrival of a spider. The climax of the story is how our main character solves her problem. Miss Muffet’s solution to her conflict is to run away. The conclusion of the story is abrupt; Miss Muffet left.

Little Miss Muffet is, admittedly, not a complicated or very interesting story. Yet we can diagram its plot:

With this short story, we see that our graph looks like a triangle. The story plot makes a pyramid shape with an even amount of story on either side of the climax.

For pieces more complicated than a simple nursery rhyme, the story’s divisions may not be equal. The rising action may consume much of the story, moving very slowly toward a climax in the story’s middle. The middle part may take up more of the total story; the ending may be very brief. This means the plot diagram is no longer symmetrical.

From Shakespeare to Sci-Fi, just about every work of fiction can be worked out on a plot diagram. Using a plot diagram helps you sort out and identify the plot’s elements, whether you are studying an existing work or writing your own creative fiction.

A plot diagram provides the bare bones of a story. The author’s skill and artistry are in adding depth, detail, supporting characters, and many events up to and after the climax to hold the reader’s attention.

This article describes solutions for preserving semi-transparency when saving a ggplot2-based graphs into a high quality postscript (.eps) file format.

Contents:

Plot Resolution Climax Rising

• Save ggplots with semi-transparent colors

Create a ggplot with semi-transparent color

To illustrate this, we start by creating ggplot2-based survival curves using the function ggsurvplot() in the survminer package. The ggsurvplot() function creates survival curves with the 95% confidence bands in a semi-transparent color.

First install (if needed) survminer as follow:

Then type, this:

In the plot above, the confidence band is semi-transparent. It can be saved to a PDF file without loosing the semi-transparent color.

If you try to export the picture as vector file (EPS ), the 95% confidence interval will disappear and the saved plot looks as follow:

The problem is that EPS in R does not support transparency.

A simple alternative is to export the plot into SVG file format. In the following sections, we’ll describe convenient solutions to save high-quality ggplots by preserving semi-transparency.

Save ggplots with semi-transparent colors

Use cairo-based postscript graphics devices

You can use the ggsave() function in [ggplot2] as follow:

Or use this:

Note that, the argument fallback_resolution is used to control the resolution in dpi at which semi-transparent areas are rasterized (the rest stays as vector format).

Export to powerpoint

You can export the plot to Powerpoint using the ReporteRs package. ReporteRs will give you a fully editable vector format with full support for transparency as well.

We previously described how to Create and format PowerPoint documents from R software using the ReporteRs package. We also described how to export an editable ggplot from R software to powerpoint.

Briefly, to export our survival curves from R to powerpoint, the script looks like this

The output looks like this:

Edit the plot in powerpoint. See the video below: Editing ggplots Exported with ReporteRs into PWPT

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High Resolution Plot Python