Randy  Stanton

Randy Stanton

1633765200

Draw Tree in C - Brownian Tree

Tutorial to simulate Diffusion-limited aggregation in C language, resulting in fractal, called as Brownian Tree, where diffusion is the primary means of transport.

Sine Waveform without Graphics in C : https://youtu.be/JUx4Id2NJF8

#c 

 

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Draw Tree in C - Brownian Tree
Dylan  Iqbal

Dylan Iqbal

1561523460

Matplotlib Cheat Sheet: Plotting in Python

This Matplotlib cheat sheet introduces you to the basics that you need to plot your data with Python and includes code samples.

Data visualization and storytelling with your data are essential skills that every data scientist needs to communicate insights gained from analyses effectively to any audience out there. 

For most beginners, the first package that they use to get in touch with data visualization and storytelling is, naturally, Matplotlib: it is a Python 2D plotting library that enables users to make publication-quality figures. But, what might be even more convincing is the fact that other packages, such as Pandas, intend to build more plotting integration with Matplotlib as time goes on.

However, what might slow down beginners is the fact that this package is pretty extensive. There is so much that you can do with it and it might be hard to still keep a structure when you're learning how to work with Matplotlib.   

DataCamp has created a Matplotlib cheat sheet for those who might already know how to use the package to their advantage to make beautiful plots in Python, but that still want to keep a one-page reference handy. Of course, for those who don't know how to work with Matplotlib, this might be the extra push be convinced and to finally get started with data visualization in Python. 

You'll see that this cheat sheet presents you with the six basic steps that you can go through to make beautiful plots. 

Check out the infographic by clicking on the button below:

Python Matplotlib cheat sheet

With this handy reference, you'll familiarize yourself in no time with the basics of Matplotlib: you'll learn how you can prepare your data, create a new plot, use some basic plotting routines to your advantage, add customizations to your plots, and save, show and close the plots that you make.

What might have looked difficult before will definitely be more clear once you start using this cheat sheet! Use it in combination with the Matplotlib Gallery, the documentation.

Matplotlib 

Matplotlib is a Python 2D plotting library which produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms.

Prepare the Data 

1D Data 

>>> import numpy as np
>>> x = np.linspace(0, 10, 100)
>>> y = np.cos(x)
>>> z = np.sin(x)

2D Data or Images 

>>> data = 2 * np.random.random((10, 10))
>>> data2 = 3 * np.random.random((10, 10))
>>> Y, X = np.mgrid[-3:3:100j, -3:3:100j]
>>> U = 1 X** 2 + Y
>>> V = 1 + X Y**2
>>> from matplotlib.cbook import get_sample_data
>>> img = np.load(get_sample_data('axes_grid/bivariate_normal.npy'))

Create Plot

>>> import matplotlib.pyplot as plt

Figure 

>>> fig = plt.figure()
>>> fig2 = plt.figure(figsize=plt.figaspect(2.0))

Axes 

>>> fig.add_axes()
>>> ax1 = fig.add_subplot(221) #row-col-num
>>> ax3 = fig.add_subplot(212)
>>> fig3, axes = plt.subplots(nrows=2,ncols=2)
>>> fig4, axes2 = plt.subplots(ncols=3)

Save Plot 

>>> plt.savefig('foo.png') #Save figures
>>> plt.savefig('foo.png',  transparent=True) #Save transparent figures

Show Plot

>>> plt.show()

Plotting Routines 

1D Data 

>>> fig, ax = plt.subplots()
>>> lines = ax.plot(x,y) #Draw points with lines or markers connecting them
>>> ax.scatter(x,y) #Draw unconnected points, scaled or colored
>>> axes[0,0].bar([1,2,3],[3,4,5]) #Plot vertical rectangles (constant width)
>>> axes[1,0].barh([0.5,1,2.5],[0,1,2]) #Plot horiontal rectangles (constant height)
>>> axes[1,1].axhline(0.45) #Draw a horizontal line across axes
>>> axes[0,1].axvline(0.65) #Draw a vertical line across axes
>>> ax.fill(x,y,color='blue') #Draw filled polygons
>>> ax.fill_between(x,y,color='yellow') #Fill between y values and 0

2D Data 

>>> fig, ax = plt.subplots()
>>> im = ax.imshow(img, #Colormapped or RGB arrays
      cmap= 'gist_earth', 
      interpolation= 'nearest',
      vmin=-2,
      vmax=2)
>>> axes2[0].pcolor(data2) #Pseudocolor plot of 2D array
>>> axes2[0].pcolormesh(data) #Pseudocolor plot of 2D array
>>> CS = plt.contour(Y,X,U) #Plot contours
>>> axes2[2].contourf(data1) #Plot filled contours
>>> axes2[2]= ax.clabel(CS) #Label a contour plot

Vector Fields 

>>> axes[0,1].arrow(0,0,0.5,0.5) #Add an arrow to the axes
>>> axes[1,1].quiver(y,z) #Plot a 2D field of arrows
>>> axes[0,1].streamplot(X,Y,U,V) #Plot a 2D field of arrows

Data Distributions 

>>> ax1.hist(y) #Plot a histogram
>>> ax3.boxplot(y) #Make a box and whisker plot
>>> ax3.violinplot(z)  #Make a violin plot

Plot Anatomy & Workflow 

Plot Anatomy 

 y-axis      

                           x-axis 

Workflow 

The basic steps to creating plots with matplotlib are:

1 Prepare Data
2 Create Plot
3 Plot
4 Customized Plot
5 Save Plot
6 Show Plot

>>> import matplotlib.pyplot as plt
>>> x = [1,2,3,4]  #Step 1
>>> y = [10,20,25,30] 
>>> fig = plt.figure() #Step 2
>>> ax = fig.add_subplot(111) #Step 3
>>> ax.plot(x, y, color= 'lightblue', linewidth=3)  #Step 3, 4
>>> ax.scatter([2,4,6],
          [5,15,25],
          color= 'darkgreen',
          marker= '^' )
>>> ax.set_xlim(1, 6.5)
>>> plt.savefig('foo.png' ) #Step 5
>>> plt.show() #Step 6

Close and Clear 

>>> plt.cla()  #Clear an axis
>>> plt.clf(). #Clear the entire figure
>>> plt.close(). #Close a window

Plotting Customize Plot 

Colors, Color Bars & Color Maps 

>>> plt.plot(x, x, x, x**2, x, x** 3)
>>> ax.plot(x, y, alpha = 0.4)
>>> ax.plot(x, y, c= 'k')
>>> fig.colorbar(im, orientation= 'horizontal')
>>> im = ax.imshow(img,
            cmap= 'seismic' )

Markers 

>>> fig, ax = plt.subplots()
>>> ax.scatter(x,y,marker= ".")
>>> ax.plot(x,y,marker= "o")

Linestyles 

>>> plt.plot(x,y,linewidth=4.0)
>>> plt.plot(x,y,ls= 'solid') 
>>> plt.plot(x,y,ls= '--') 
>>> plt.plot(x,y,'--' ,x**2,y**2,'-.' ) 
>>> plt.setp(lines,color= 'r',linewidth=4.0)

Text & Annotations 

>>> ax.text(1,
           -2.1, 
           'Example Graph', 
            style= 'italic' )
>>> ax.annotate("Sine", 
xy=(8, 0),
xycoords= 'data', 
xytext=(10.5, 0),
textcoords= 'data', 
arrowprops=dict(arrowstyle= "->", 
connectionstyle="arc3"),)

Mathtext 

>>> plt.title(r '$sigma_i=15$', fontsize=20)

Limits, Legends and Layouts 

Limits & Autoscaling 

>>> ax.margins(x=0.0,y=0.1) #Add padding to a plot
>>> ax.axis('equal')  #Set the aspect ratio of the plot to 1
>>> ax.set(xlim=[0,10.5],ylim=[-1.5,1.5])  #Set limits for x-and y-axis
>>> ax.set_xlim(0,10.5) #Set limits for x-axis

Legends 

>>> ax.set(title= 'An Example Axes',  #Set a title and x-and y-axis labels
            ylabel= 'Y-Axis', 
            xlabel= 'X-Axis')
>>> ax.legend(loc= 'best')  #No overlapping plot elements

Ticks 

>>> ax.xaxis.set(ticks=range(1,5),  #Manually set x-ticks
             ticklabels=[3,100, 12,"foo" ])
>>> ax.tick_params(axis= 'y', #Make y-ticks longer and go in and out
             direction= 'inout', 
              length=10)

Subplot Spacing 

>>> fig3.subplots_adjust(wspace=0.5,   #Adjust the spacing between subplots
             hspace=0.3,
             left=0.125,
             right=0.9,
             top=0.9,
             bottom=0.1)
>>> fig.tight_layout() #Fit subplot(s) in to the figure area

Axis Spines 

>>> ax1.spines[ 'top'].set_visible(False) #Make the top axis line for a plot invisible
>>> ax1.spines['bottom' ].set_position(( 'outward',10))  #Move the bottom axis line outward

Have this Cheat Sheet at your fingertips

Original article source at https://www.datacamp.com

#matplotlib #cheatsheet #python

Represent Tree using graphics in C/C++

Prerequisite: graphics.hHow to include graphics.h?

In C/C++ there is graphics.h header file which is used to create the object like line, circle, etc.

Given an array arr[] of N integers, the task is to write C++ program to create the Tree using graphics.h.

Approach: To run the program we have the include the below header file:

#include 

We will create a Tree with the help below functions:

  1. setcolor(color): This function present in graphic.h header file which is used to set the current drawing color to the new color.
  2. floodfill(pattern, color): function is used to fill an enclosed area. The current fill pattern and fill color is used to fill the area.
  3. circle(x, y, radius): The header file graphics.h contains circle() function which draws a circle with center at (x, y) and given radius.
  4. outtextxy(): The header file graphics.h contains outtextxy() function which displays the text or string at a specified point (x, y) on the screen.

#computer-graphics #trees #c #c++ #cplusplus #programming-c

Tamale  Moses

Tamale Moses

1624240146

How to Run C/C++ in Sublime Text?

C and C++ are the most powerful programming language in the world. Most of the super fast and complex libraries and algorithms are written in C or C++. Most powerful Kernel programs are also written in C. So, there is no way to skip it.

In programming competitions, most programmers prefer to write code in C or C++. Tourist is considered the worlds top programming contestant of all ages who write code in C++.

During programming competitions, programmers prefer to use a lightweight editor to focus on coding and algorithm designing. VimSublime Text, and Notepad++ are the most common editors for us. Apart from the competition, many software developers and professionals love to use Sublime Text just because of its flexibility.

I have discussed the steps we need to complete in this blog post before running a C/C++ code in Sublime Text. We will take the inputs from an input file and print outputs to an output file without using freopen file related functions in C/C++.

#cpp #c #c-programming #sublimetext #c++ #c/c++

Dicey Issues in C/C++

If you are familiar with C/C++then you must have come across some unusual things and if you haven’t, then you are about to. The below codes are checked twice before adding, so feel free to share this article with your friends. The following displays some of the issues:

  1. Using multiple variables in the print function
  2. Comparing Signed integer with unsigned integer
  3. Putting a semicolon at the end of the loop statement
  4. C preprocessor doesn’t need a semicolon
  5. Size of the string matters
  6. Macros and equations aren’t good friends
  7. Never compare Floating data type with double data type
  8. Arrays have a boundary
  9. Character constants are different from string literals
  10. Difference between single(=) and double(==) equal signs.

The below code generates no error since a print function can take any number of inputs but creates a mismatch with the variables. The print function is used to display characters, strings, integers, float, octal, and hexadecimal values onto the output screen. The format specifier is used to display the value of a variable.

  1. %d indicates Integer Format Specifier
  2. %f indicates Float Format Specifier
  3. %c indicates Character Format Specifier
  4. %s indicates String Format Specifier
  5. %u indicates Unsigned Integer Format Specifier
  6. %ld indicates Long Int Format Specifier

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A signed integer is a 32-bit datum that encodes an integer in the range [-2147483648 to 2147483647]. An unsigned integer is a 32-bit datum that encodes a non-negative integer in the range [0 to 4294967295]. The signed integer is represented in twos-complement notation. In the below code the signed integer will be converted to the maximum unsigned integer then compared with the unsigned integer.

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#problems-with-c #dicey-issues-in-c #c-programming #c++ #c #cplusplus

Ari  Bogisich

Ari Bogisich

1590587580

Loops in C++ | For, While, and Do While Loops in C++

In this Video We are going to see how to use Loops in C++. We will see How to use For, While, and Do While Loops in C++.
C++ is general purpose, compiled, object-oriented programming language and its concepts served as the basis for several other languages such as Java, Python, Ruby, Perl etc.

#c #c# #c++ #programming-c