Matplotlib Colormaps

import numpy as np
import matplotlib.pyplot as plt

# Sample Data
data = np.random.randn(30, 30)
# Create a heatmap with a sequential colormap
plt.imshow(data, cmap='Blues')
plt.colorbar()  # Adds a color scale legend
plt.title('Sequential Colormap Example')
plt.show()

import numpy as np
import matplotlib.pyplot as plt

# Sample Data
data = np.random.randn(30, 30)
# Heatmap with a diverging colormap
plt.imshow(data, cmap='coolwarm')
plt.colorbar()
plt.title('Diverging Colormap Example')
plt.show()

import numpy as np
import matplotlib.pyplot as plt

# Scatter plot with a qualitative colormap
x = np.random.randn(100)
y = np.random.randn(100)
colors = np.random.randint(0, 5, 100)  # Assigning random categories

plt.scatter(x, y, c=colors, cmap='Set1')
plt.colorbar()
plt.title('Qualitative Colormap Example')
plt.show()

import numpy as np
import matplotlib.pyplot as plt

# Sample Data
data = np.random.randn(30, 30)
# Heatmap with a cyclic colormap
plt.imshow(data, cmap='twilight')
plt.colorbar()
plt.title('Cyclic Colormap Example')
plt.show()

import numpy as np
import matplotlib.pyplot as plt

# Sample Data
data = np.random.randn(30, 30)
plt.imshow(data, cmap='Blues_r')
plt.colorbar()
plt.title('Reversed Colormap')
plt.show()

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap

# Define custom colors
colors = ['#FF0000', '#00FF00', '#0000FF']
custom_cmap = ListedColormap(colors)
# Sample Data
data = np.random.randn(30, 30)
# Apply the custom colormap
plt.imshow(data, cmap=custom_cmap)
plt.colorbar()
plt.title('Custom Colormap')
plt.show()

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors

# Create a new colormap that uses only the first half of the 'Blues' colormap
cmap = plt.get_cmap('Blues', 256)
new_cmap = mcolors.ListedColormap(cmap(np.linspace(0, 0.5, 256)))
# Sample Data
data = np.random.randn(30, 30)
plt.imshow(data, cmap=new_cmap)
plt.colorbar()
plt.title('Subset of a Colormap')
plt.show()