This is my participation 11 The fourth of the yuegengwen challenge 26 God , Check out the activity details ：2021 One last more challenge

Preface

matplotlib Modules are very powerful ,pyplot Class provides users with the ability to quickly draw polylines 、 Columnar 、 Script methods for common charts such as scatter points . meanwhile ,matplotlib Rely on many underlying renderers, such as Agg Display of image data processing .

In order to draw more beautiful images , We all use matplotlib Apply colors in the image .

In the previous study , There are two main ways to apply colors in charts ：

• Set the color fill attribute keyword ： Such as plot、bar、hist、pi、contour And so on facecolor/color/cmap Attribute keyword
• Rendering numpy data ： Use imshow()/pcolor Method display numpy The data is rendered into an image

In this issue , We will be on matplotlib Draw a color table in the module 、 Chart colors should be learned by applying relevant method attributes ,let's go~

1. imshow() Draw a color table

• imshow() Methods an overview

  pyplot.imshow() Yes, it will numpy The generated data is rendered into 2D Images

  • imshow() take RGBA Data or 2D Rendering scalar data into a color image
  • imshow() Can pass cmap|vmin|vmax Specifies the color level of the output

• imshow() Method to draw a color table

  • Import matplotlib.pyplot library
  • call numpy.random.randint() Generate vector data
  • call pyplot.imshow() Render the data into an image
  • call pylot.show() Show the image

  x = np.random.randint(1,100,size=(3,5))
  plt.imshow(x)
  plt.show()
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• Can pass cmap、vmin、vmax Change the render color level

   plt.imshow(x,cmap="hot",vmin=10,vmax=210)
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• You can call text() Method to fill each color text

  fig,ax = plt.subplots()
  
  x = np.random.randint(1,100,size=(7,7))
  
  ax.imshow(x,cmap="magma_r")
  
  for i in range(7):
      for j in range(7):
          text = ax.text(j,i,x[i,j],ha="center",va="center",color="w")
  
  plt.show()
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2. pcolormesh() Draw a color table

• pcolor() Methods an overview

  • pcolor() Method creates an unconventional color mesh using quadrilateral
  • pcolor() Method for large matrices , Rendering will be slow
  • pcolor（） Method only supports for x,y Mask for processing

• pcolormesh() Methods an overview

  • pcolormesh() Method creates a colored grid using a square
  • pcolormesh() The method is suitable for large matrix data
  • pcolormesh() Method will mask the of the element facecolor Set transparent , You can see the difference using the edge color

• pcolor() Method practice

  x = np.random.rand(6,10)
  
  plt.pcolor(x)
  
  plt.colorbar()
  
  plt.show()
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• pcolormesh() Method practice

  x = np.random.rand(6,10)
  
  plt.pcolormesh(x,edgecolors="k")
  
  plt.colorbar()
  
  plt.show()
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3. hline()、vline() Draw colored lines

• hline()、vline() Methods an overview

  • pyplot.hline(y,xmin,xmax) Method to draw a horizontal line
  • pyplot.vline(x,ymin,ymax) Method to draw a vertical line

• hline()、vline() Method practice

  • call pyplot.rcParams['axes.prop_cycle'].by_key()['color'] obtain Axes The color of the object
  • call pyplot.vline()、pyplot.hline() Method to draw a vertical horizontal line

  prop_cycle = plt.rcParams['axes.prop_cycle']
  colors = prop_cycle.by_key()['color']
  
  for i,color in enumerate(colors):
  
      plt.vlines(i,0,10,color=color)
      plt.hlines(i,0,10,color=color)
  
  plt.show()
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4. colorbar Draw color bars

• colorbar() Methods an overview

  • pylot.colorbar Add a color bar to the chart
  • colorbar It can be applied to scatter、contour、imshow、pcolormesh in
  • colorbar In the chart, the default is vertical display , Can pass orientation Set level

• colorbar() Method practice

  data = np.arange(100).reshape(10,10)
  
  im = plt.imshow(data)
  
  plt.colorbar(im,orientation="horizontal")
  
  plt.show()
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5. Chart color properties

• Color attribute keyword

  • cmap:RGBA Color mapping table , In the form of " Color map table name _r"
  • color: RGBA Color tuples or lists
  • facecolor: Graphic color
  • edgecolor: Graphic border color
  • Color value form ：
    • English words for color ： Like red "red"
    • Abbreviations of words indicating color, such as ： Red "r", yellow "y"
    • RGB Format ： Hexadecimal format, such as "#88c999";(r,g,b) Tuple form
    • You can go to the color list

• List of common chart color attributes

  Method	Chart name	cmap	color	facecolor	edgecolor
  pyplot.hist()	Histogram	×	√	×	√
  pyplot.plot()	Broken line diagram	×	√	×	×
  pyplot.bar()	Histogram	×	√	√	√
  pyplot.pie()	The pie chart	×	√(colors)	×	√
  pyplot.scatter()	Scatter plot	√	√ (c)	×	√(edgecolors)
  pyplot.contour()	Contour map	√	√(colors)	×	×
  pyplot.boxplot()	Box figure	×	×	×	×
  pyplot.violinplot()	Picture of violin	×	×	×	×
  pyplot.imshow()	Exhibition dta For image	√	×	×	×
  pyplot.pcolor()	Color grid	√	√	√	√(edgecolors)

summary

In this issue , We are right. matplotlib When charting in the module , The application methods and properties of color are summarized . How to show the data clearly , Colors are often used in charts to help us distinguish .

The above is the content of this issue , Welcome big guys to praise and comment , See you next time ~