Plotting Examples

Linear and SemiLog plots

import sys
import numpy as np
import matplotlib.pyplot as plt

# If using it with pypi, the following line can be removed
sys.path.insert(1, '../src')
import chrispytools.plot as cpy

# Create sample data
x = np.linspace(0, 10, 100)
y1 = np.sin(x)
y2 = np.cos(x)
y3 = np.sin(x) * np.cos(x)


# Create plot data
# [ [ X-Data, Y-Data, Label, kwargs for matplotlib ] ]
plot_data = [
    [x, y1, "sin(x)"],
    [x, y2, "cos(x)", 'linestyle=dashed,color=red'],
    [x, y3, "sin(x)*cos(x)", 'linestyle=:,color=green,marker=o,markersize=2']
]

plot_data2 = [ [x, y1, "sin(x)"] ]

# Create labels with units
x_label = ["Time", "s", 1e-3]  # Label, unit, scaling factor (converts to ms)
y_label = ["Amplitude", "V"]

# Example 1: LinearPlot
fig = plt.figure(figsize=(3.5, 2.2), dpi=300)
ax = plt.subplot(111)

cpy.LinearPlot(ax, plot_data, x_label, y_label)

plt.show()

# Example 2: SemiLogXPlot
fig = plt.figure(figsize=(3.5, 2.2), dpi=300)
ax = plt.subplot(111)

cpy.SemiLogXPlot(ax, plot_data, x_label, y_label)

plt.show()

# Example 3: SemiLogYPlot
fig = plt.figure(figsize=(3.5, 2.2), dpi=300)
ax = plt.subplot(111)

cpy.SemiLogYPlot(ax, plot_data, x_label, y_label)

plt.show()

# Example 4: Complex Plot
fig = plt.figure(figsize=(3.5, 2.2), dpi=300)
ax = plt.subplot(111)

cpy.LinearPlot(ax, plot_data2, x_label, y_label)

# Adding a horizontal and vertical lines
cpy.HLinePlot(ax, 0.75, "750 mV", xDistance=0.5, color="C2", lw=1, fontsize=7)
cpy.VLinePlot(ax, 2e-3, "2 ms", yDistance=0.25, color="C1", lw=1, fontsize=7)

# Adding a rectangle to highlight some area
cpy.RectanglePlot(ax, 5e-3, 3e-3, 0, 0.75, color="darksalmon")

plt.show()

Histogram and Box plots

import sys
import numpy as np
import matplotlib.pyplot as plt

# If using it with pypi, the following line can be removed
sys.path.insert(1, '../src')
import chrispytools.plot as cpy

data1 = np.random.normal(loc=0, scale=1, size=1000)
data2 = np.random.normal(loc=0.5, scale=2, size=1000) + 2


Y_label = [r'Hits', '']
X_label = [r'Value', '']

# Example 1: Histogram
Data_Histo = [ [data1, data1, "Data"] ]

fig = plt.figure(figsize=(3.5, 2.2), dpi=300)
ax = plt.subplot(111)

cpy.HistogramPlot(ax, Data_Histo, X_label, Y_label, Legend=False)

plt.show()

# Example 2: Histogram
# Dataset 
Data_Box = [[[1, 2], [data1, data2], "Data"] ]

# Labels (customize as needed)
X_label = ["Category", ""]
Y_label = ["Value", ""]

fig = plt.figure(figsize=(3.5, 2.2), dpi=300)
ax = plt.subplot(111)

# Use your BoxPlot function
cpy.BoxPlot(ax, Data_Box, X_label, Y_label)

plt.show()

Special plots

import sys
import numpy as np
import matplotlib.pyplot as plt

# If using from local source during development
sys.path.insert(1, '../src')
import chrispytools.plot as cpy

# Create example grid data
x = np.linspace(0, 10, 200)
y = np.linspace(0, 5, 100)
X, Y = np.meshgrid(x, y)

# 2D function with clear valleys (e.g., interference pattern)
Z = np.sin(0.5 * X) * np.cos(2 * Y)

# Plot data for PseudoColorPlot
plot_map = [[X, Y, Z, "2D Function", "cmap=viridis, rasterized=True"]]

# Get Y-position of minimum Z for each X
y_min = y[ np.argmin(Z, axis=0) ]
x_min = x

# Compute minima along axis 1 (X-min for each Y)
x_min2 = x[ np.argmin(Z, axis=1) ]
y_min2 = y

minima_line = [ [x_min, y_min, "Min along Y", "color=red, linewidth=1"],
                [x_min2, y_min2, "Min along X", "color=red, linewidth=1, linestyle=--"]
            ]


# Define labels
x_label = ["X Axis", "", 1]
y_label = ["Y Axis", "", 1]

# Plotting
fig = plt.figure(figsize=(5, 3.5), dpi=300)
ax = plt.subplot(111)

# Pseudocolor background
cpy.PseudoColorPlot(ax, plot_map, x_label, y_label, Legend=False)

# Overlay minima as a red contour-like line
cpy.LinearPlot(ax, minima_line, x_label, y_label)

plt.tight_layout()
plt.show()