Part of a series of articles on |
Psychoanalysis |
---|
|
- Totally Rad Photoshop Actions
- Totally Rad Definition
- Totally Rad Actions Photoshop
- Totally Rad Actions Coupon Code
Psychological projection is a defence mechanism in which the human ego defends itself against unconscious impulses or qualities (both positive and negative) by denying their existence in themselves while attributing them to others.[1] For example, a person who is habitually rude may constantly accuse other people of being rude. It incorporates blame shifting.
Historical precursors[edit]
A prominent precursor in the formulation of the projection principle was Giambattista Vico.[2][3] In 1841, Ludwig Feuerbach was the first enlightenment thinker to employ this concept as the basis for a systematic critique of religion.[4][5][6] The Babylonian Talmud (500 AD) notes the human tendency toward projection and warns against it: 'Do not taunt your neighbour with the blemish you yourself have.'[7] In the New Testament, Jesus also warned against projection: 'Why do you look at the speck of sawdust in your brother’s eye and pay no attention to the plank in your own eye? How can you say to your brother, ‘Let me take the speck out of your eye,’ when all the time there is a plank in your own eye? You hypocrite, first take the plank out of your own eye, and then you will see clearly to remove the speck from your brother’s eye.' [8]
Psychoanalytic developments[edit]
Matplotlib comes with a set of default settings that allow customizing all kinds of properties. You can control the defaults of almost every property in matplotlib: figure size and dpi, line width, color and style, axes, axis and grid properties, text and font properties and so on. Photo editing tools that are fast, fun, and simple. The United Nations Human Rights Council (UNHRC; French: Conseil des droits de l'homme des Nations unies, CDH) is a United Nations body whose mission is to promote and protect human rights around the world.
Projection (German: Projektion) was conceptualised by Sigmund Freud in his letters to Wilhelm Fliess,[9] and further refined by Karl Abraham and Anna Freud. Freud considered that, in projection, thoughts, motivations, desires, and feelings that cannot be accepted as one's own are dealt with by being placed in the outside world and attributed to someone else.[10] What the ego repudiates is split off and placed in another.[11]
Freud would later come to believe that projection did not take place arbitrarily, but rather seized on and exaggerated an element that already existed on a small scale in the other person.[12] (The related defence of projective identification differs from projection in that there the other person is expected to become identified with the impulse or desire projected outside,[13] so that the self maintains a connection with what is projected, in contrast to the total repudiation of projection proper.)[14]
Melanie Klein saw the projection of good parts of the self as leading potentially to over-idealisation of the object.[15] Equally, it may be one's conscience that is projected, in an attempt to escape its control: a more benign version of this allows one to come to terms with outside authority.[16]
Theoretical examples[edit]
Projection tends to come to the fore in normal people at times of personal or political crisis[17] but is more commonly found in personalities functioning at a primitive level as in narcissistic personality disorder or borderline personality disorder.[18]
Carl Jung considered that the unacceptable parts of the personality represented by the Shadow archetype were particularly likely to give rise to projection, both small-scale and on a national/international basis.[19]Marie-Louise Von Franz extended her view of projection, stating that 'wherever known reality stops, where we touch the unknown, there we project an archetypal image'.[20]
Psychological projection is one of the medical explanations of bewitchment used to explain the behavior of the afflicted children at Salem in 1692. The historian John Demos asserts that the symptoms of bewitchment experienced by the afflicted girls were due to the girls undergoing psychological projection of repressed aggression.[21]
Practical examples[edit]
- Victim blaming: The victim of someone else's actions or bad luck may be offered criticism, the theory being that the victim may be at fault for having attracted the other person's hostility.[22]
- Projection of marital guilt: Thoughts of infidelity to a partner may be unconsciously projected in self-defence on to the partner in question, so that the guilt attached to the thoughts can be repudiated or turned to blame instead, in a process linked to denial.[23]
- Bullying: A bully may project his/her own feelings of vulnerability onto the target(s) of the bullying activity. Despite the fact that a bully's typically denigrating activities are aimed at the bully's targets, the true source of such negativity is ultimately almost always found in the bully's own sense of personal insecurity or vulnerability.[24] Such aggressive projections of displaced negative emotions can occur anywhere from the micro-level of interpersonal relationships, all the way up through to the macro-level of international politics, or even international armed conflict.[19]
- Projection of general guilt: Projection of a severe conscience[25] is another form of defense, one which may be linked to the making of false accusations, personal or political.[19]
- Projection of hope: Also, in a more positive light, a patient may sometimes project his or her feelings of hope onto the therapist.[26]
Counter-projection[edit]
Jung wrote, 'All projections provoke counter-projection when the object is unconscious of the quality projected upon it by the subject.'[27] Thus, what is unconscious in the recipient will be projected back onto the projector, precipitating a form of mutual acting out.[28]
In a rather different usage, Harry Stack Sullivan saw counter-projection in the therapeutic context as a way of warding off the compulsive re-enactment of a psychological trauma, by emphasizing the difference between the current situation and the projected obsession with the perceived perpetrator of the original trauma.[29]
Clinical approaches[edit]
Drawing on Gordon Allport's idea of the expression of self onto activities and objects, projective techniques have been devised to aid personality assessment, including the Rorschach ink-blots and the Thematic Apperception Test (TAT).[30]
Projection may help a fragile ego reduce anxiety, but at the cost of a certain dissociation, as in dissociative identity disorder.[31] In extreme cases, an individual's personality may end up becoming critically depleted.[32] In such cases, therapy may be required which would include the slow rebuilding of the personality through the 'taking back' of such projections.[33]
The method of managed projection is a type of projective techniques. The basic principle of the method is that a subject is presented with his own verbal portrait named by the name of another person, as well as with a portrait of his fictional opposition (V. V. Stolin, 1981).
The technique is suitable for application in psychological counseling and might provide valuable information about the form and nature of his or her self-esteem Bodalev, A (2000). 'General psychodiagnostics'.
Criticism[edit]
Some studies were critical of Freud's theory. Research supports the existence of a false-consensus effect whereby humans have a broad tendency to believe that others are similar to themselves, and thus 'project' their personal traits onto others. This applies to good traits as well as bad traits and is not a defense mechanism for denying the existence of the trait within the self.[34]
Instead, Newman, Duff, and Baumeister (1997) proposed a new model of defensive projection. In this view, repressors try to suppress thoughts of their undesirable traits, and these efforts make those trait categories highly accessible—so that they are then used all the more often when forming impressions of others. The projection is then only a by-product of the real defensive mechanism.[35]
See also[edit]
References[edit]
- ^Sigmund Freud, Case Histories II (PFL 9) p. 132
- ^Harvey, Van A. (1997). Feuerbach and the interpretation of religion. Cambridge University Press. p. 4. ISBN0521470498.
- ^Cotrupi, Caterina Nella (2000). Northrop Frye and the poetics of process. University of Toronto Press, Scholarly Publishing Division. p. 21. ISBN978-0802081414.
- ^Harvey, Van A. (1997). Feuerbach and the interpretation of religion. University of cambridge. p. 4. ISBN978-0521586306.
- ^Mackey, James patrick (2000). The Critique of Theological Reason. Cambridge University press. pp. 41–42. ISBN978-0521169233.
- ^Nelson, John K. (1990). 'A Field Statement on the Anthropology of Religion'. Ejournalofpoliticalscience.
- ^Babylonian Talmud. pp. Baba Metsiya 59b, Kiddushin 70a.
And he who [continually] declares [others] unfit is [himself] unfit and never speaks in praise [of people]. And Samuel said: All who defame others, with their own blemish they stigmatize [these others].
- ^Matthew 7:3-5 (NIV)
- ^Jean-Michel Quinodoz, Reading Freud (London 2005) p. 24
- ^Case Studies II p. 210.
- ^Otto Fenichel, The Psychoanalytic Theory of Neurosis (London 1946) p. 146.
- ^Sigmund Freud, On Psychopathology (PFL 10) pp. 200–01.
- ^Patrick Casement, Further Learning from the Patient (1997) p. 177.
- ^Otto F. Kernberg, Borderline Conditions and Pathological Narcissism (London 1990) p. 56.
- ^Hanna Segal, Klein (1979) p. 118.
- ^R. Wollheim, On the Emotions (1999) pp. 217–18.
- ^Erik Erikson, Childhood and Society (1973) p. 241.
- ^Glen O. Gabbard, Long-Term Psychodynamic Psychotherapy (London 2010) p. 33.
- ^ abcCarl G. Jung ed., Man and his Symbols (London 1978) pp. 181–82.
- ^Franz, Marie-Louise von (September 1972). Patterns of Creativity Mirrored in Creation Myths (Seminar series). Spring Publications. ISBN978-0-88214-106-0.found in: Gray, Richard M. (1996). Archetypal explorations: an integrative approach to human behavior. Routledge. p. 201. ISBN978-0-415-12117-0.
- ^Demos, John (1970). 'Underlying Themes in the Witchcraft of Seventeenth-Century New England'. American Historical Review. 75 (5): 1311–26 [p. 1322]. JSTOR1844480.
- ^The Pursuit of Health, June Bingham & Norman Tamarkin, M.D., Walker Press.
- ^Sigmund Freud, On Psychopathology (Middlesex 1987) p. 198.
- ^Paul Gilbert, Overcoming Depression (1999) pp. 185–86.
- ^Patrick Casement, Further Learning from the Patient (1990) p. 142.
- ^Patrick Casement, Further Learning from the Patient (1990) p. 122.
- ^General Aspects of Dream Psychology, CW 8, par. 519.
- ^Ann Casement, Carl Gustav Jung (2001) p. 87.
- ^F. S. Anderson ed., Bodies in Treatment (2007) p. 160.
- ^Semeonoff, B. (1987). 'Projective Techniques'. In Gregory, Richard (ed.). The Oxford Companion to the Mind. New York: Oxford University Press. p. 646. ISBN0-19-866124-X.
- ^Trauma and Projection(subscription required)
- ^R. Appignanesi ed., Introducing Melanie Klein (Cambridge 2006) pp. 115, 126.
- ^Mario Jacoby, The Analytic Encounter (1984) pp. 10, 108.
- ^Baumeister, Roy F.; Dale, Karen; Sommer, Kristin L. (1998). 'Freudian Defense Mechanisms and Empirical Findings in Modern Social Psychology: Reaction Formation, Projection, Displacement, Undoing, Isolation, Sublimation, and Denial'. Journal of Personality. 66 (6): 1090–92. doi:10.1111/1467-6494.00043.
- ^Newman, Leonard S.; Duff, Kimberley J.; Baumeister, Roy F. (1997). 'A new look at defensive projection: Thought suppression, accessibility, and biased person perception'. Journal of Personality and Social Psychology. 72 (5): 980–1001. doi:10.1037/0022-3514.72.5.980. PMID9150580.
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Psychological_projection&oldid=915059288'
Nicolas P. Rougier
Table of Contents
Sources are available fromgithub
All code and material is licensed under a Creative CommonsAttribution-ShareAlike 4.0.
You can test your installation before the tutorial using the check-installation.py script.
See also:
matplotlib is probably the single most used Python package for 2D-graphics. Itprovides both a very quick way to visualize data from Python andpublication-quality figures in many formats. We are going to explorematplotlib in interactive mode covering most common cases.
IPython and the pylab mode
IPython is an enhanced interactive Python shell thathas lots of interesting features including named inputs and outputs, access toshell commands, improved debugging and much more. When we start it with thecommand line argument -pylab (--pylab since IPython version 0.12), it allowsinteractive matplotlib sessions that have Matlab/Mathematica-like functionality.
pyplot
pyplot provides a convenient interface to the matplotlib object-orientedplotting library. It is modeled closely after Matlab(TM). Therefore, themajority of plotting commands in pyplot have Matlab(TM) analogs with similararguments. Important commands are explained with interactive examples.
In this section, we want to draw the cosine and sine functions on the sameplot. Starting from the default settings, we'll enrich the figure step by stepto make it nicer.
The first step is to get the data for the sine and cosine functions:
X is now a NumPy array with 256 values ranging from -π to +π (included). C isthe cosine (256 values) and S is the sine (256 values).
To run the example, you can download each of the examples and run it using:
You can get source for each step by clicking on the corresponding figure.
Using defaults
Matplotlib comes with a set of default settings that allow customizing allkinds of properties. You can control the defaults of almost every property inmatplotlib: figure size and dpi, line width, color and style, axes, axis andgrid properties, text and font properties and so on. While matplotlib defaultsare rather good in most cases, you may want to modify some properties forspecific cases.
Instantiating defaults
Documentation
In the script below, we've instantiated (and commented) all the figure settingsthat influence the appearance of the plot. The settings have been explicitlyset to their default values, but now you can interactively play with the valuesto explore their affect (see Line properties and Line styles below).
Changing colors and line widths
As a first step, we want to have the cosine in blue and the sine in red and aslightly thicker line for both of them. We'll also slightly alter the figuresize to make it more horizontal.
Setting limits
Documentation
Current limits of the figure are a bit too tight and we want to make some spacein order to clearly see all data points.
Setting ticks
Documentation
Current ticks are not ideal because they do not show the interesting values(+/-π,+/-π/2) for sine and cosine. We'll change them such that they show onlythese values.
Setting tick labels
Documentation
Ticks are now properly placed but their label is not very explicit. We couldguess that 3.142 is π but it would be better to make it explicit. When we settick values, we can also provide a corresponding label in the second argumentlist. Note that we'll use latex to allow for nice rendering of the label.
Moving spines
Documentation
Spines are the lines connecting the axis tick marks and noting the boundariesof the data area. They can be placed at arbitrary positions and until now, theywere on the border of the axis. We'll change that since we want to have them inthe middle. Since there are four of them (top/bottom/left/right), we'll discardthe top and right by setting their color to none and we'll move the bottom andleft ones to coordinate 0 in data space coordinates.
Adding a legend
Documentation
Let's add a legend in the upper left corner. This only requires adding thekeyword argument label (that will be used in the legend box) to the plotcommands.
Annotate some points
Let's annotate some interesting points using the annotate command. We choose the2π/3 value and we want to annotate both the sine and the cosine. We'll firstdraw a marker on the curve as well as a straight dotted line. Then, we'll usethe annotate command to display some text with an arrow.
Devil is in the details
Documentation
The tick labels are now hardly visible because of the blue and red lines. We canmake them bigger and we can also adjust their properties such that they'll berendered on a semi-transparent white background. This will allow us to see boththe data and the labels.
So far we have used implicit figure and axes creation. This is handy for fastplots. We can have more control over the display using figure, subplot, andaxes explicitly. A figure in matplotlib means the whole window in the userinterface. Within this figure there can be subplots. While subplot positionsthe plots in a regular grid, axes allows free placement within the figure. Bothcan be useful depending on your intention. We've already worked with figuresand subplots without explicitly calling them. When we call plot, matplotlibcalls gca() to get the current axes and gca in turn calls gcf() to get thecurrent figure. If there is none it calls figure() to make one, strictlyspeaking, to make a subplot(111). Let's look at the details.
Figures
A figure is the windows in the GUI that has 'Figure #' as title. Figuresare numbered starting from 1 as opposed to the normal Python way startingfrom 0. This is clearly MATLAB-style. There are several parameters thatdetermine what the figure looks like:
Argument | Default | Description |
---|---|---|
num | 1 | number of figure |
figsize | figure.figsize | figure size in in inches (width, height) |
dpi | figure.dpi | resolution in dots per inch |
facecolor | figure.facecolor | color of the drawing background |
edgecolor | figure.edgecolor | color of edge around the drawing background |
frameon | True | draw figure frame or not |
The defaults can be specified in the resource file and will be used most of thetime. Only the number of the figure is frequently changed.
When you work with the GUI you can close a figure by clicking on the x in theupper right corner. You can also close a figure programmatically by callingclose. Depending on the argument it closes (1) the current figure (noargument), (2) a specific figure (figure number or figure instance asargument), or (3) all figures (all as argument).
As with other objects, you can set figure properties with the set_something methods.
Subplots
With subplot you can arrange plots in a regular grid. You need to specify thenumber of rows and columns and the number of the plot. Note that the gridspec command is a morepowerful alternative.
Axes
Axes are very similar to subplots but allow placement of plots at any locationin the figure. So if we want to put a smaller plot inside a bigger one we doso with axes.
Ticks
Well formatted ticks are an important part of publishing-readyfigures. Matplotlib provides a totally configurable system for ticks. There aretick locators to specify where ticks should appear and tick formatters to giveticks the appearance you want. Major and minor ticks can be located andformatted independently from each other. By default minor ticks are not shown,i.e. there is only an empty list for them because it is as NullLocator (seebelow).
Tick Locators
There are several locators for different kind of requirements:
Class | Description |
---|---|
NullLocator | No ticks. |
IndexLocator | Place a tick on every multiple of some base number of points plotted. |
FixedLocator | Tick locations are fixed. |
LinearLocator | Determine the tick locations. |
MultipleLocator | Set a tick on every integer that is multiple of some base. |
AutoLocator | Select no more than n intervals at nice locations. |
LogLocator | Determine the tick locations for log axes. |
All of these locators derive from the base class matplotlib.ticker.Locator.You can make your own locator deriving from it. Handling dates as ticks can beespecially tricky. Therefore, matplotlib provides special locators inmatplotlib.dates.
For quite a long time, animation in matplotlib was not an easy task and wasdone mainly through clever hacks. However, things have started to change sinceversion 1.1 and the introduction of tools for creating animation veryintuitively, with the possibility to save them in all kind of formats (but don'texpect to be able to run very complex animations at 60 fps though).
The most easy way to make an animation in matplotlib is to declare aFuncAnimation object that specifies to matplotlib what is the figure toupdate, what is the update function and what is the delay between frames.
Drip drop
A very simple rain effect can be obtained by having small growing ringsrandomly positioned over a figure. Of course, they won't grow forever since thewave is supposed to damp with time. To simulate that, we can use a more andmore transparent color as the ring is growing, up to the point where it is nomore visible. At this point, we remove the ring and create a new one.
First step is to create a blank figure:
Next, we need to create several rings. For this, we can use the scatter plotobject that is generally used to visualize points cloud, but we can also use itto draw rings by specifying we don't have a facecolor. We also have to takecare of initial size and color for each ring such that we have all sizes betweena minimum and a maximum size. In addition, we need to make sure the largest ringis almost transparent.
Now, we need to write the update function for our animation. We know that ateach time step each ring should grow and become more transparent while thelargest ring should be totally transparent and thus removed. Of course, we won'tactually remove the largest ring but re-use it to set a new ring at a new randomposition, with nominal size and color. Hence, we keep the number of ringsconstant.
Last step is to tell matplotlib to use this function as an update function forthe animation and display the result or save it as a movie:
Earthquakes
We'll now use the rain animation to visualize earthquakes on the planet fromthe last 30 days. The USGS Earthquake Hazards Program is part of the NationalEarthquake Hazards Reduction Program (NEHRP) and provides several data on theirwebsite. Those data are sorted according toearthquakes magnitude, ranging from significant only down to all earthquakes,major or minor. You would be surprised by the number of minor earthquakeshappening every hour on the planet. Since this would represent too much datafor us, we'll stick to earthquakes with magnitude > 4.5. At the time of writing,this already represent more than 300 earthquakes in the last 30 days.
First step is to read and convert data. We'll use the urllib library thatallows us to open and read remote data. Data on the website use the CSV formatwhose content is given by the first line:
We are only interested in latitude, longitude and magnitude and we won't parsetime of event (ok, that's bad, feel free to send me a PR).
Now, we need to draw the earth on a figure to show precisely where the earthquakecenter is and to translate latitude/longitude in some coordinates matplotlibcan handle. Fortunately, there is the basemap project (that tends to be replaced by themore complete cartopy) that is reallysimple to install and to use. First step is to define a projection to draw theearth onto a screen (there exists many different projections) and we'll stickto the mill projection which is rather standard for non-specialist like me.
Next, we request to draw coastline and fill continents:
The earth object will also be used to translate coordinates quiteautomatically. We are almost finished. Last step is to adapt the rain code andput some eye candy:
If everything went well, you should obtain something like this (with animation):
Regular Plots
Hints
You need to use the fill_betweencommand.
Starting from the code below, try to reproduce the graphic on the right takingcare of filled areas.
Click on figure for solution.
Scatter Plots
Starting from the code below, try to reproduce the graphic on the right takingcare of marker size, color and transparency.
Click on figure for solution.
Bar Plots
Hints
You need to take care of text alignment.
Starting from the code below, try to reproduce the graphic on the right byadding labels for red bars.
Click on figure for solution.
Contour Plots
Starting from the code below, try to reproduce the graphic on the right takingcare of the colormap (see Colormaps below).
Click on figure for solution.
Imshow
Hints
You need to take care of the
origin
of the image in the imshow command anduse a colorbar.Starting from the code below, try to reproduce the graphic on the right takingcare of colormap, image interpolation and origin.
Click on figure for solution.
Pie Charts
Starting from the code below, try to reproduce the graphic on the right takingcare of colors and slices size.
Click on figure for solution.
Quiver Plots
Hints
You need to draw arrows twice.
Starting from the code above, try to reproduce the graphic on the right takingcare of colors and orientations.
Click on figure for solution.
Grids
Starting from the code below, try to reproduce the graphic on the right takingcare of line styles.
Click on figure for solution.
Multi Plots
Hints
You can use several subplots with different partition.
Starting from the code below, try to reproduce the graphic on the right.
Click on figure for solution.
Polar Axis
Starting from the code below, try to reproduce the graphic on the right.
Click on figure for solution.
3D Plots
Hints
You need to use contourf.
![Totally Totally](/uploads/1/2/4/8/124860660/148056711.jpg)
Starting from the code below, try to reproduce the graphic on the right.
Click on figure for solution.
Text
Try to do the same from scratch!
Click on figure for solution.
Matplotlib benefits from extensive documentation as well as a largecommunity of users and developpers. Here are some links of interest:
Tutorials
- Pyplot tutorial
- Introduction
- Controlling line properties
- Working with multiple figures and axes
- Working with text
- Image tutorial
- Startup commands
- Importing image data into Numpy arrays
- Plotting numpy arrays as images
- Text tutorial
- Text introduction
- Basic text commands
- Text properties and layout
- Writing mathematical expressions
- Text rendering With LaTeX
- Annotating text
- Artist tutorial
- Introduction
- Customizing your objects
- Object containers
- Figure container
- Axes container
- Axis containers
- Tick containers
- Path tutorial
- Introduction
- Bézier example
- Compound paths
- Transforms tutorial
- Introduction
- Data coordinates
- Axes coordinates
- Blended transformations
- Using offset transforms to create a shadow effect
- The transformation pipeline
Matplotlib documentation
- FAQ
- Installation
- Usage
- How-To
- Troubleshooting
- Environment Variables
Code documentation
The code is fairly well documented and you can quickly access a specificcommand from within a python session:
Galleries
The matplotlib gallery isalso incredibly useful when you search how to render a given graphic. Eachexample comes with its source.
A smaller gallery is also available here.
Mailing lists
Finally, there is a user mailing list where you canask for help and a developers mailing list that is moretechnical.
Here is a set of tables that show main properties and styles.
Line properties
Property | Description | Appearance |
---|---|---|
alpha (or a) | alpha transparency on 0-1 scale | |
antialiased | True or False - use antialised rendering | |
color (or c) | matplotlib color arg | |
linestyle (or ls) | see Line properties | |
linewidth (or lw) | float, the line width in points | |
solid_capstyle | Cap style for solid lines | |
solid_joinstyle | Join style for solid lines | |
dash_capstyle | Cap style for dashes | |
dash_joinstyle | Join style for dashes | |
marker | see Markers | |
markeredgewidth (mew) | line width around the marker symbol | |
markeredgecolor (mec) | edge color if a marker is used | |
markerfacecolor (mfc) | face color if a marker is used | |
markersize (ms) | size of the marker in points |
Line styles
Symbol | Description | Appearance |
---|---|---|
- | solid line | |
-- | dashed line | |
-. | dash-dot line | |
: | dotted line | |
. | points | |
, | pixels | |
o | circle | |
^ | triangle up | |
v | triangle down | |
< | triangle left | |
> | triangle right | .png'> |
s | square | |
+ | plus | |
x | cross | |
D | diamond | |
d | thin diamond | |
1 | tripod down | |
2 | tripod up | |
3 | tripod left | |
4 | tripod right | |
h | hexagon | |
H | rotated hexagon | |
p | pentagon | |
| | vertical line | |
_ | horizontal line |
Markers
Symbol | Description | Appearance |
---|---|---|
0 | tick left | |
1 | tick right | |
2 | tick up | |
3 | tick down | |
4 | caret left | |
5 | caret right | |
6 | caret up | |
7 | caret down | |
o | circle | |
D | diamond | |
h | hexagon 1 | |
H | hexagon 2 | |
_ | horizontal line | |
1 | tripod down | |
2 | tripod up | |
3 | tripod left | |
4 | tripod right | |
8 | octagon | |
p | pentagon | |
^ | triangle up | |
v | triangle down | |
< | triangle left | |
> | triangle right | .png'> |
d | thin diamond | |
, | pixel | |
+ | plus | |
. | point | |
s | square | |
* | star | |
| | vertical line | |
x | cross | |
r'$sqrt{2}$' | any latex expression |
Colormaps
All colormaps can be reversed by appending
_r
. For instance, gray_r
isthe reverse of gray
.If you want to know more about colormaps, see Documenting the matplotlibcolormaps.
Base
Name | Appearance |
---|---|
autumn | |
bone | |
cool | |
copper | |
flag | |
gray | |
hot | |
hsv | |
jet | |
pink | |
prism | |
spectral | |
spring | |
summer | |
winter |
GIST
Name | Appearance |
---|---|
gist_earth | |
gist_gray | |
gist_heat | |
gist_ncar | |
gist_rainbow | |
gist_stern | |
gist_yarg |
Sequential
Name | Appearance |
---|---|
BrBG | |
PiYG | |
PRGn | |
PuOr | |
RdBu | |
RdGy | |
RdYlBu | |
RdYlGn | |
Spectral |
Diverging
Totally Rad Photoshop Actions
Name | Appearance |
---|---|
Blues | |
BuGn | |
BuPu | |
GnBu | |
Greens | |
Greys | |
Oranges | |
OrRd | |
PuBu | |
PuBuGn | |
PuRd | |
Purples | |
RdPu | |
Reds | |
YlGn | |
YlGnBu | |
YlOrBr | |
YlOrRd |
Qualitative
Totally Rad Definition
Name | Appearance |
---|---|
Accent | |
Dark2 | |
Paired | |
Pastel1 | |
Pastel2 | |
Set1 | |
Set2 | |
Set3 |
Totally Rad Actions Photoshop
Miscellaneous
Totally Rad Actions Coupon Code
Name | Appearance |
---|---|
afmhot | |
binary | |
brg | |
bwr | |
coolwarm | |
CMRmap | |
cubehelix | |
gnuplot | |
gnuplot2 | |
ocean | |
rainbow | |
seismic | |
terrain |