Useful One-line For Mac
Pyplot tutorial is a collection of command style functions that make matplotlib work like MATLAB. Each pyplot function makes some change to a figure: e.g., creates a figure, creates a plotting area in a figure, plots some lines in a plotting area, decorates the plot with labels, etc.
In various states are preserved across function calls, so that it keeps track of things like the current figure and plotting area, and the plotting functions are directed to the current axes (please note that “axes” here and in most places in the documentation refers to the axes and not the strict mathematical term for more than one axis). See the documentation for a complete list of line styles and format strings. The command in the example above takes a list of xmin, xmax, ymin, ymax and specifies the viewport of the axes. If matplotlib were limited to working with lists, it would be fairly useless for numeric processing. Generally, you will use arrays. In fact, all sequences are converted to numpy arrays internally.
The example below illustrates a plotting several lines with different format styles in one command using arrays. Plot ( x1, y1, x2, y2 ) # use keyword args plt.
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Setp ( lines, color = 'r', linewidth = 2.0 ) # or MATLAB style string value pairs plt. Setp ( lines, 'color', 'r', 'linewidth', 2.0 ) Here are the available properties.
Property Value Type alpha float animated True False antialiased or aa True False clipbox a matplotlib.transform.Bbox instance clipon True False clippath a Path instance and a Transform instance, a Patch color or c any matplotlib color contains the hit testing function dashcapstyle 'butt' 'round' 'projecting' dashjoinstyle 'miter' 'round' 'bevel' dashes sequence of on/off ink in points data (np.array xdata, np.array ydata) figure a matplotlib.figure.Figure instance label any string linestyle or ls '-' '-' '.' ':' 'steps'.
linewidth or lw float value in points lod True False marker '+' ',' '.' The command here is optional because figure(1) will be created by default, just as a subplot(111) will be created by default if you don’t manually specify any axes. The command specifies numrows, numcols, fignum where fignum ranges from 1 to numrows.numcols. The commas in the subplot command are optional if numrows.numcols.
Import matplotlib.pyplot as plt plt. Figure ( 1 ) # the first figure plt. Subplot ( 211 ) # the first subplot in the first figure plt.
Plot ( 1, 2, 3 ) plt. Subplot ( 212 ) # the second subplot in the first figure plt.
Plot ( 4, 5, 6 ) plt. Figure ( 2 ) # a second figure plt. Plot ( 4, 5, 6 ) # creates a subplot(111) by default plt. Figure ( 1 ) # figure 1 current; subplot(212) still current plt. Subplot ( 211 ) # make subplot(211) in figure1 current plt. Title ( 'Easy as 1, 2, 3' ) # subplot 211 title You can clear the current figure with and the current axes with.
If you find it annoying that states (specifically the current image, figure and axes) are being maintained for you behind the scenes, don’t despair: this is just a thin stateful wrapper around an object oriented API, which you can use instead (see ) If you are making lots of figures, you need to be aware of one more thing: the memory required for a figure is not completely released until the figure is explicitly closed with. Deleting all references to the figure, and/or using the window manager to kill the window in which the figure appears on the screen, is not enough, because pyplot maintains internal references until is called.
Import numpy as np import matplotlib.pyplot as plt # Fixing random state for reproducibility np. Seed ( 19680801 ) mu, sigma = 100, 15 x = mu + sigma.
np. Randn ( 10000 ) # the histogram of the data n, bins, patches = plt. Hist ( x, 50, normed = 1, facecolor = 'g', alpha = 0.75 ) plt. Xlabel ( 'Smarts' ) plt. Ylabel ( 'Probability' ) plt. Title ( 'Histogram of IQ' ) plt.
025, r '$ mu=100, sigma=15$' ) plt. Axis ( 40, 160, 0, 0.03 ) plt. Grid ( True ) plt.
Show (, ). Title ( r '$ sigmai=15$' ) The r preceding the title string is important – it signifies that the string is a raw string and not to treat backslashes as python escapes. Matplotlib has a built-in TeX expression parser and layout engine, and ships its own math fonts – for details see. Thus you can use mathematical text across platforms without requiring a TeX installation. For those who have LaTeX and dvipng installed, you can also use LaTeX to format your text and incorporate the output directly into your display figures or saved postscript – see.
The aim for this Wiki is to promote using a command to open up commonly used applications without having to go through many mouse clicks - thus saving time on monitoring and troubleshooting Windows machines. A list I use a lot:. nbtstat - List NetBIOS stats and information. netstat - List TCP/IP stats and information. ipconfig - List TCP/IP configuration for a system. netsh - Network configuration for a system. sc - manage services.
net - whole slew of commands to manage users and groups, shares, connections, etc. ping - makes sure a system is up on the network. tracert - trace the hops between two hosts. Useful to see if there's a break in between and where it is. nslookup - Query DNS for information.
Useful One-line For Mac Os
dcdiag - check health of the domain controller. setspn - check SPNs for Kerberos configuration.