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Programming Articles
Page 2252 of 2547
How to Capture a pick event and use it to activate or deactivate Line Plots in Matplotlib
After enabling the pick event property of artists in Matplotlib, the task is to use the pick event to enable and disable the line plots for a given axis in a set of plots.In order to pick a specific line plot, we use Legend.We will use a Binary classification plot to create the ROC Curve. ROC curve or Receiver Operating Characteristics curve is used for diagnostics, weather prediction and other applications. It contains True Negative Rate (TPR) and False Positive Rate (FPR). Using ROC, we will create multiple plots of the curve.Let us Import the libraries first. Here ‘nbAgg’ is used ...
Read MoreHow to customize spines of Matplotlib figures?
When we plot a figure in Matplotlib, it creates four spines around the figure, top, left, bottom and right. Spines are nothing but a box surrounded with the pictorial representation of the grid which displays some ticks and tickable axes on left(y) and bottom(x).Let us see how to customize the spines in a given figure. We will create six figures to see and customize the spines for it.First import the required libraries for the workbook.import numpy as np import matplotlib.pyplot as pltLet us draw graph for sines, theta = np.linspace(0, 2*np.pi, 128) y = np.sin(theta) fig = plt.figure(figsize=(8, 6))Define the ...
Read MoreHow to customize the color and colormaps of a Plot in Matplotlib
To customize the color and colormaps of a plot, we can use the colormap property from the color library. There are two types of colormap we can create: (a) discrete colormap and (b) continuous colormap.We will first see how to create a discrete colormap followed by continuous colormap.In the example, we will use ‘iris’ dataset to create three plots such that the first plot uses the default colormap and the other two uses RGB map to create a mixed colored plot. However, we can create as many color maps as we have clusters.Exampleimport matplotlib.pyplot as plt import pandas as pd ...
Read MoreHow to manage image resolution of a graph in Matplotlib
An Image contains a 2-D matrix RGB data points which can be defined by the dots point per inch [ DPI ] of the image. The resolution of the image is important because a hi-resolution image will have much more clarity.We have a method ‘plt.savefig()’ in Matplotlib which determines the size of the image in terms of its pixels. Ideally it is having an ‘dpi’ parameter.Let’s see how we can manage the resolution of a graph in Matplotlib.Exampleimport matplotlib.pyplot as plt import numpy as np #Prepare the data for histogram np.random.seed(1961) nd = np.random.normal(13, 5, 1000) #Define the ...
Read MoreHow to provide shadow effect in a Plot using path_effect attribute in Matplotlib
In order to provide path effects like shadow effect in a plot or a graph, we can use the path_effect attribute.For example, let’s see how we can use the path_effect attribute in Matplotlib add a shadow effect to a sigmoid function.import matplotlib.pyplot as plt import numpy as np from matplotlib.patheffects import PathPatchEffect, SimpleLineShadow, NormalNow let us define the size of the figure and plot the sigmoid function, plt.style.use('seaborn-deep') plt.subplots(figsize=(10, 10))Let us define the datapoints for the plot, x = np.linspace(-10, 10, 50) y = 1+ np.exp(-x))Let us define the shadow property in the plot, plt.plot(x, y, linewidth=8, color='blue', path_effects= [SimpleLineShadow(), ...
Read MoreHow to plot with multiple color cycle using cycler property in Matplotlib
Matplotlib has a default color cycle for all the graphs and plots, however, in order to draw plots with multiple color cycles, we can use the cycler property of Matplotlib. It is used to plot repetitive patterns for the axis.First, we will use the Object Oriented APIs such as pyplot to plot the specific visualization.from cycler import cycler import numpy as np from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas from matplotlib.figure import Figure from IPython.core.display import displayIn this example, we will create two objects which will repeat the cycle after every four objects. Thus, after creating two objects, the last two ...
Read MoreHow to plot Exponentially Decaying Function using FuncAnimation in Matplotlib
Let us assume that we want to animate a nature of function which is exponentially decaying like y = a(b)^x where b = growth factor and a = initial value.An exponentially decay function would look like this, However, for now, we want to animate and plot the exponentially decaying tan function.First import the libraries, import numpy as np import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimationDefine the axes, fig, a = plt.subplots()Plotting a blank figure with axes, xdata, ydata = [], [] line, = ax.plot(xdata, ydata)Set the limit of the grids, ax.set_xlim(0, 10) ax.set_ylim(-3.0, 3.0) ax.grid() Define the function to ...
Read MoreHow to create custom markers on a plot in Matplotlib
To create a custom marker on a plot or graph, we use a list where we write the markers we want to see in the plot. The markers are nothing but symbols, emoji, character or any character which we want to see on the figure.In order to create the marker, we will first import the required libraries.import matplotlib.pyplot as plt import numpy as npFor now, we will create a marker on a sine curve. Let us create the grid with size (12, 6), x = np.arange(1, 2.6, 0.1) y = np.sin(2 * np.pi * x) plt.subplots(figsize=(12, 6))Here we will create ...
Read MoreBreadth First Search on Matrix in C++
In a given matrix, there are four objects to analyze the element position: left, right, bottom and top.Breadth First Search is nothing but finding the shortest distance between the two elements of a given 2-D Matrix. Thus in each cell, there are four operations we can perform which can be expressed in four numerals such as, '2' describes that the cell in the matrix is Source.'3' describes that the cell in the matrix is Destination.'1' describes that the cell can be moved further in a direction.'0' describes that the cell in the matrix can not be moved in any direction.On ...
Read MoreHow Tensorflow is used with Estimators to build a linear model to load the titanic dataset?
A linear model can be built with estimators to load the titanic dataset using the ‘read_csv’ method which is present in ‘Pandas’ package. This method takes google APIs that store the titanic dataset. The API is read and the data is stored in the form of a CSV file.Read More: What is TensorFlow and how Keras work with TensorFlow to create Neural Networks?We will use the Keras Sequential API, which is helpful in building a sequential model that is used to work with a plain stack of layers, where every layer has exactly one input tensor and one output tensor.A ...
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