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Articles on Trending Technologies
Technical articles with clear explanations and examples
How can I get the color of the last figure in Matplotlib?
In Matplotlib, you can retrieve the color of any plotted line using the get_color() method. This is particularly useful when you want to identify the automatically assigned colors or when working with multiple plots in the same figure. Basic Example Let's start with a simple example to understand how get_color() works ? import numpy as np import matplotlib.pyplot as plt # Set figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Create data points x = np.arange(10) # Plot multiple lines p = plt.plot(x, x, x, x ** 2, x, x ** ...
Read MoreHow to plot contourf and log color scale in Matplotlib?
In Matplotlib, you can create contour plots with logarithmic color scaling using contourf() combined with LogLocator(). This is particularly useful when your data spans several orders of magnitude. Basic Setup First, let's understand the key components needed for logarithmic contour plots − Use contourf() method for filled contour plots Apply ticker.LogLocator() for logarithmic color scale Handle negative or zero values with masked arrays Add a colorbar to visualize the scale Example Here's how to create a contour plot with logarithmic color scaling − import matplotlib.pyplot as plt import numpy as np ...
Read MoreHow do I customize the display of edge labels using networkx in Matplotlib?
Customizing edge labels in NetworkX with Matplotlib allows you to control the appearance and positioning of text displayed along graph edges. You can adjust label position, font properties, and styling to create clear, professional network visualizations. Basic Edge Label Display First, let's create a simple graph with edge labels ? import matplotlib.pyplot as plt import networkx as nx # Create a directed graph G = nx.DiGraph() G.add_nodes_from([1, 2, 3, 4]) G.add_edges_from([(1, 2), (2, 3), (3, 4), (4, 1), (1, 3)]) # Position nodes using spring layout pos = nx.spring_layout(G, seed=42) # Draw the ...
Read MoreHow to independently set horizontal and vertical, major and minor gridlines of a plot?
Matplotlib allows you to independently control horizontal and vertical, major and minor gridlines using the grid() method along with axis-specific methods. This provides fine-grained control over plot appearance. Basic Syntax The grid() method can be applied to specific axes: ax.xaxis.grid(which="major", color='color', linestyle='style', linewidth=width) ax.yaxis.grid(which="minor", color='color', linestyle='style', linewidth=width) Parameters which − Specifies "major" or "minor" gridlines color − Sets the gridline color linestyle − Defines line style ('-', '--', '-.', ':') linewidth − Controls line thickness Complete Example Here's how to create independent horizontal and vertical gridlines with different styles ...
Read MoreContour hatching in Matplotlib plot
Contour hatching in Matplotlib allows you to add visual patterns to filled contour plots, making it easier to distinguish between different regions. This is particularly useful for creating publication-ready plots or when working with grayscale images. Basic Contour Hatching Here's how to create a contour plot with different hatch patterns ? import matplotlib.pyplot as plt import numpy as np # Set figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Create coordinate arrays x = np.linspace(-3, 5, 150) y = np.linspace(-3, 5, 120) X, Y = np.meshgrid(x, y) # Generate sample data ...
Read MoreHow can I move a tick label without moving corresponding tick in Matplotlib?
In Matplotlib, you can move tick labels independently from their corresponding ticks using the set_xticklabels() or set_yticklabels() methods, or by creating custom annotations. This is useful when you need to adjust label positioning for better readability without affecting the tick marks themselves. Method 1: Using set_xticklabels() with Custom Positions The most straightforward approach is to get existing tick positions and create custom labels ? import matplotlib.pyplot as plt import numpy as np # Create sample data x = np.linspace(0, 10, 100) y = np.sin(x) plt.figure(figsize=(10, 6)) plt.plot(x, y) # Get current tick positions ...
Read MoreHow to access axis label object in Matplotlib?
To access axis label objects in Matplotlib, you can use the get_label() method on the axis object, which returns the label text object. This is useful when you need to retrieve or manipulate axis labels programmatically. Basic Syntax The main methods for accessing axis labels are ? # Get X-axis label text x_label_text = ax.xaxis.get_label().get_text() # Get Y-axis label text y_label_text = ax.yaxis.get_label().get_text() # Get the label object itself x_label_obj = ax.xaxis.get_label() y_label_obj = ax.yaxis.get_label() Example: Accessing Axis Label Objects Here's a complete example showing how to set and ...
Read MoreAdjust one subplot's height in absolute way (not relative) in Matplotlib
When creating subplots in Matplotlib, you sometimes need precise control over their positioning and dimensions. The Axes() class allows you to specify absolute positions and sizes instead of using relative grid layouts. Understanding Axes Parameters The Axes() class takes parameters [left, bottom, width, height] where all values are in figure coordinates (0 to 1) ? left − horizontal position of the left edge bottom − vertical position of the bottom edge width − width of the subplot height − height of the subplot Example Here's how to create two subplots with different absolute ...
Read MoreCalculate the curl of a vector field in Python and plot it with Matplotlib
To calculate the curl of a vector field in Python and plot it with Matplotlib, we can use the quiver() method to visualize the vector field and its curl components in 3D space. What is Curl? The curl of a vector field F = (u, v, w) measures the rotation or circulation of the field at each point. For a 3D vector field, the curl is calculated as: curl F = (∂w/∂y - ∂v/∂z, ∂u/∂z - ∂w/∂x, ∂v/∂x - ∂u/∂y) Example: Calculating and Plotting Curl Let's create a vector field and visualize its curl using ...
Read MoreHow to assign specific colors to specific cells in a Matplotlib table?
Matplotlib allows you to assign specific colors to individual cells in a table using the cellColours parameter. This is useful for highlighting data, creating color-coded reports, or improving table readability. Basic Syntax The ax.table() method accepts a cellColours parameter that takes a 2D list where each element corresponds to a cell color ? ax.table(cellText=data, cellColours=colors, colLabels=columns, loc='center') Example Let's create a table with employee data and assign specific colors to each cell ? import matplotlib.pyplot as plt # Set figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # ...
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