### Setting up Getdist for plotting

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

This example provides the basic setup required to use Getdist for plotting, including importing necessary modules and creating an MCSamples object.

```python
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from getdist import MCSamples
from getdist.plots import GetDistPlotter, PlotSettings

# Example: Create dummy data for an MCMC chain
# Replace this with your actual chain loading mechanism
num_samples = 1000
num_params = 3

# Generate random samples for demonstration
samples_data = np.random.randn(num_samples, num_params)

# Create an MCSamples object
mcsamples = MCSamples(samples=samples_data,
                      names=[f'param_{i}' for i in range(num_params)],
                      labels=[f'Parameter {i}' for i in range(num_params)],
                      ranges={f'param_{i}': [-5, 5] for i in range(num_params)})

# Initialize PlotSettings and update seaborn settings
PlotSettings().update_sns_settings()

# Initialize GetDistPlotter
plotter = GetDistPlotter(mcsamples)

print("Getdist setup complete. Plotter object created.")
```

--------------------------------

### Minimal GetDist Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/README.md

Load MCMC samples, get parameter statistics, and create a triangle plot.

```python
import getdist

# Load MCMC samples
samples = getdist.loadMCSamples('chains/example')

# Get parameter statistics
mean = samples.mean('h')
std = samples.std('h')
print(f"h = {mean:.4f} ± {std:.4f}")

# Create triangle plot
from getdist.plots import GetDistPlotter
plotter = GetDistPlotter(samples)
plotter.triangle_plot()
```

--------------------------------

### Install Optional Documentation Dependencies (uv)

Source: https://github.com/cmbant/getdist/blob/master/CONTRIBUTING.md

Install optional dependencies for documentation building using uv.

```bash
uv pip install -e ".[docs]"
```

--------------------------------

### Install All Dependencies (uv)

Source: https://github.com/cmbant/getdist/blob/master/CONTRIBUTING.md

Install all available dependencies, including development, GUI, Streamlit, and docs, using uv.

```bash
uv pip install -e ".[dev,GUI,StreamlitGUI,docs]"
```

--------------------------------

### Install Optional GUI Dependencies (uv)

Source: https://github.com/cmbant/getdist/blob/master/CONTRIBUTING.md

Install optional dependencies for GUI development using uv.

```bash
uv pip install -e ".[GUI]"
```

--------------------------------

### Install GetDist with Development Dependencies (uv)

Source: https://github.com/cmbant/getdist/blob/master/CONTRIBUTING.md

Install GetDist in editable mode with development dependencies using uv.

```bash
uv pip install -e ".[dev]"
```

--------------------------------

### Install GetDist using pip

Source: https://github.com/cmbant/getdist/blob/master/README.rst

Install the GetDist package using pip. This is the recommended method for most users.

```bash
pip install getdist
```

--------------------------------

### Plotting Quick Start

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/api-summary.md

A quick guide to generating publication-quality plots, including triangle plots, using GetDist's plotting utilities.

```APIDOC
## Plotting Quick Start

### Description
Provides a concise example of how to create common GetDist plots like triangle plots.

### Usage
```python
from getdist import loadMCSamples
from getdist.plots import GetDistPlotter, GetDistPlotSettings

# Load samples
samples = loadMCSamples('chains/example')

# Configure plotting
settings = GetDistPlotSettings(subplot_size_inch=2.5)
settings.fontsize = 11
settings.colormap = 'viridis'

# Create plotter
plotter = GetDistPlotter(roots=samples, settings=settings)

# Generate plots
fig = plotter.triangle_plot(
    params=['h', 'omega_m', 'omega_b'],
    filled=True,
    legend_loc='upper right'
)

# Save and show
plotter.finish_plot()
import matplotlib.pyplot as plt
plt.savefig('triangle.pdf')
plt.show()
```
```

--------------------------------

### Install GetDist from source

Source: https://github.com/cmbant/getdist/blob/master/README.rst

Install GetDist from local source files using pip. This is useful for development or when using a specific version.

```bash
pip install -e /path/to/source/
```

--------------------------------

### Python Examples: makeList Utility

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/paramnames.md

Demonstrates how to use the makeList function to ensure a parameter is in list format.

```python
makeList("param")  # ["param"]
```

```python
makeList(["a", "b"])  # ["a", "b"]
```

--------------------------------

### Set up pre-commit hooks

Source: https://github.com/cmbant/getdist/blob/master/CONTRIBUTING.md

Install pre-commit hooks to automatically run code quality checks before each commit.

```bash
pre-commit install
```

--------------------------------

### Install GetDist with Development Dependencies (pip)

Source: https://github.com/cmbant/getdist/blob/master/CONTRIBUTING.md

Install GetDist in editable mode with development dependencies using pip.

```bash
pip install -e ".[dev]"
```

--------------------------------

### Install Optional Streamlit GUI Dependencies (uv)

Source: https://github.com/cmbant/getdist/blob/master/CONTRIBUTING.md

Install optional dependencies for Streamlit GUI development using uv.

```bash
uv pip install -e ".[StreamlitGUI]"
```

--------------------------------

### Install PySide6 for GUI Application

Source: https://github.com/cmbant/getdist/blob/master/docs/source/gui.md

Install the PySide6 library, a dependency for running the traditional Qt-based GUI application from Python. This is necessary for the getdist-gui script to function.

```bash
pip install PySide6
```

--------------------------------

### Plotting with Getdist

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

Demonstrates basic plotting using the Getdist library. Requires Getdist to be installed and configured.

```python
from getdist import plots, MCSamples
import numpy as np

# Create dummy samples
mean = [0, 0]
cov = [[1, 0.5], [0.5, 1]]
num_samples = 10000
x = np.random.multivariate_normal(mean, cov, num_samples)

samples = MCSamples(samples=x)

# Create a plot object
g = plots.get_single_plotter(width=6)

# Plot the samples
g.plot_1d_density(samples)

g.fig.suptitle('1D Density Plot with Getdist')
g.show()

```

--------------------------------

### TextFile Write Method Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/types.md

Demonstrates how to use the write method of the TextFile class to save its content to a specified file.

```python
text = TextFile(['Line 1', 'Line 2', 'Line 3'])
text.write('output.txt')
```

--------------------------------

### Basic Plotting with Getdist

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

Demonstrates the fundamental usage of Getdist for creating a simple plot. Ensure Getdist is installed and imported.

```python
import getdist
from getdist.plots import MCSamples
import matplotlib.pyplot as plt

# Assuming you have samples in a file named 'chain.txt'
# samples = MCSamples('chain.txt')

# For demonstration, let's create dummy samples
from numpy import random
samples = MCSamples(samples=[random.randn(100, 2)], names=['x', 'y'], ranges={'x': [-3, 3], 'y': [-3, 3]})

# Plotting the samples
plt.figure()
samples.plot_2d(0, 1)
plt.show()
```

--------------------------------

### Getdist Plotting Example

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

A basic example of using Getdist to create a plot. This snippet assumes you have Getdist installed and data in a compatible format.

```python
from getdist import plots, MCSamples
import numpy as np

# Create dummy samples (replace with your actual data)
samples = np.random.randn(1000, 3)
param_names = ['param1', 'param2', 'param3']
mcsamples = MCSamples(samples=samples, names=param_names)

# Create a plot (e.g., triangle plot)
g = plots.get_single_plotter(width=8)
g.triangle_plot([mcsamples], filled=True)
plt.suptitle('Getdist Triangle Plot Example', y=1.02)
plt.show()
```

--------------------------------

### IniFile Example Usage

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/inifile.md

Demonstrates loading configuration from a file, accessing parameters as different types with defaults, creating an IniFile from a dictionary, saving to a file, and iterating over parameters.

```python
from getdist import IniFile

# Load from file
config = IniFile('analysis_settings.ini')

# Access parameters
num_bins = config.int('num_bins', default=40)
accuracy = config.float('accuracy', default=0.0001)
label = config.string('label', default='Sample')
use_cache = config.bool('use_cache', default=True)

# Create from dictionary
config = IniFile({
    'param1': '10',
    'param2': '3.14',
    'param3': 'value'
})

# Save to file
config.saveFile('output.ini')

# Iterate over parameters
for key, value in config.params.items():
    print(f"{key} = {value}")
```

--------------------------------

### Install Streamlit for Web Interface

Source: https://github.com/cmbant/getdist/blob/master/docs/source/gui.md

Install the Streamlit library, which is required to run the Streamlit-based web interface for GetDist. This command installs Streamlit using pip.

```bash
pip install streamlit
```

--------------------------------

### Complete 1D Density Analysis Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/densities.md

Demonstrates a full workflow for creating and analyzing a 1D Kernel Density Estimate (KDE). Includes sample generation, bandwidth estimation, KDE creation, contour level calculation, and density evaluation.

```python
from getdist.densities import Density1D
import numpy as np

# Create from samples using KDE
from getdist.kde_bandwidth import auto_bandwidth_1d
samples = np.random.randn(10000)
x = np.linspace(-4, 4, 200)

# Estimate KDE bandwidth
h = auto_bandwidth_1d(samples)

# Create kernel density estimate
# Note: Kernel1D and convolve1D are assumed to be imported or defined elsewhere
# from getdist.convolve import Kernel1D, convolve1D 
# kernel = Kernel1D(winw=int(np.ceil(4*h)), h=h)
# P = convolve1D(x, samples, kernel)

# Create density object
# density = Density1D(x, P)

# Get 68% and 95% contour levels
# levels = density.getContourLevels((0.68, 0.95))

# Evaluate at point
# prob = density(1.5)
```

--------------------------------

### Check PySide6 Installation

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/command-line.md

Verify if PySide6 is installed and check its version. This is often a prerequisite for the GetDist GUI.

```bash
# Check PySide6 installation
python -c "import PySide6; print(PySide6.__version__)"

# If missing:
pip install PySide6

# Try GUI
getdist-gui
```

--------------------------------

### MCSamples Initialization and Usage Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/mcsamples.md

Demonstrates how to load MCSamples from files or create them from NumPy arrays, and how to access basic parameter statistics like mean and standard deviation.

```python
import getdist

# Load from files
samples = getdist.loadMCSamples('chains/example')

# Create from arrays
samples = getdist.MCSamples(
    samples=np.random.randn(1000, 3),
    weights=np.ones(1000),
    names=['param1', 'param2', 'param3'],
    labels=['p_1', 'p_2', 'p_3']
)

# Access parameter statistics
mean = samples.mean('param1')
std = samples.std('param1')
```

--------------------------------

### Batch Processing Shell Script Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/MANIFEST.txt

Example of a shell script for batch processing using GetDist.

```bash
#!/bin/bash
# Example batch processing script

# ... (script logic for chain file management and output generation)
```

--------------------------------

### Complete Plotting Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/plots.md

Demonstrates loading samples, creating a GetDistPlotter with custom settings, generating a triangle plot, and displaying the figure.

```python
from getdist import loadMCSamples
from getdist.plots import GetDistPlotter, GetDistPlotSettings

# Load samples
samples = loadMCSamples('chains/example')

# Create custom settings
settings = GetDistPlotSettings(subplot_size_inch=2.5)
settings.fontsize = 11
settings.linewidth = 1.2

# Create plotter
plotter = GetDistPlotter(roots=samples, settings=settings)

# Plot triangle diagram
fig = plotter.triangle_plot(
    params=['h', 'omega_m', 'omega_b'],
    filled=True,
    legend_loc='upper right'
)

# Finalize and show
plotter.finish_plot()
import matplotlib.pyplot as plt
plt.show()
```

--------------------------------

### Check Streamlit Installation

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/command-line.md

Verify if Streamlit is installed and check its version. This is necessary for running the Streamlit web interface.

```bash
# Check Streamlit installation
python -c "import streamlit; print(streamlit.__version__)"

# If missing:
pip install streamlit

# Clear cache
rm -rf ~/.streamlit/

# Try web interface
getdist-gui-stream
```

--------------------------------

### ParamNames Constructor Examples

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/paramnames.md

Demonstrates various ways to initialize a ParamNames object: loading from a file, auto-generating default names, and providing explicit lists of names and labels.

```python
# From file
params = ParamNames(fileName='chains/example.paramnames')

# Auto-generate defaults
params = ParamNames(default=3)
# Creates: param1, param2, param3 with labels p_{1}, p_{2}, p_{3}

# From lists
params = ParamNames(
    names=['h', 'omega_m', 'omega_b'],
    labels=['h', '\Omega_m', '\Omega_b']
)

# Access parameters
first = params.names[0]
label = first.getLabel()
```

--------------------------------

### Complete Analysis Pipeline Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/INDEX.md

This Python script demonstrates a typical GetDist workflow: loading samples, checking convergence, calculating basic statistics, generating a triangle plot, and exporting contour levels.

```python
import getdist
from getdist.plots import GetDistPlotter

# 1. Load samples
samples = getdist.loadMCSamples('chains/example')

# 2. Check convergence
print(f"Correlation length: {samples.corr_length()}")

# 3. Get constraints
for param in ['h', 'omega_m', 'omega_b']:
    mean = samples.mean(param)
    std = samples.std(param)
    print(f"{param} = {mean:.4f} ± {std:.4f}")

# 4. Create plots
plotter = GetDistPlotter(samples)
plotter.triangle_plot()

# 5. Export constraints
samples.getContourLevels(['h', 'omega_m'])
```

--------------------------------

### Find Chain File Root Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/chains.md

Example of using findChainFileRoot to locate chain files in a directory tree.

```python
path = findChainFileRoot('/chains', 'experiment1/output')
# Returns: '/chains/experiment1/output' if chain files exist there
```

--------------------------------

### Work with Configuration

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/README.md

Retrieve the global configuration object and access string settings with a default value.

```python
config = getdist.get_config()
setting = config.string('key', default='value')
```

--------------------------------

### ParamInfo setFromString Examples

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/paramnames.md

Demonstrates parsing parameter information from strings, including standard parameters with names, labels, and comments, and derived parameters marked with an asterisk.

```python
param = ParamInfo()
param.setFromString("omega_b  \\Omega_b  #Baryon density")
# name='omega_b', label='\\Omega_b', isDerived=False, comment='Baryon density'

# Derived parameter marked with *
param.setFromString("age*     Age_{\\rm Gyr}  #Universe age")
# isDerived=True
```

--------------------------------

### Plotting chains with Getdist

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

This example shows how to plot the raw chains for each parameter. This is useful for diagnosing convergence issues and understanding the sampling process.

```python
from getdist import MCSamples, plots
import matplotlib.pyplot as plt

# Load your samples (replace with your actual file path)
samples = MCSamples(samples='path/to/your/chains.txt', names=['a', 'b', 'c'],
                    labels=['\alpha', '\beta', '\gamma'],
                    ranges={'a': [-2, 2], 'b': [-3, 3], 'c': [-4, 4]})

# Create a Plotter object
plt.figure(figsize=(10, 6))
g = plots.get_single_plotter(chain_plotting_kwargs={'over_plot': 'mean', 'num_thin_thin': 10})

# Plot chains for parameter 'a'
g.plot_chain(samples, 'a')

plt.show()

```

--------------------------------

### Getdist Plotting Example

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

Demonstrates a basic plotting example using Getdist, likely for visualizing posterior distributions or confidence contours.

```python
from getdist import plots, MCSamples
import numpy as np

# Assuming 'samples' is an MCSamples object
# For demonstration, let's create a dummy one
num_params = 3
num_samples = 1000
np.random.seed(42)
means = [0, 0, 0]
cov = np.eye(num_params)
samples_data = np.random.multivariate_normal(means, cov, num_samples)
param_names = ["param1", "param2", "param3"]
mcsamples = MCSamples(samples=samples_data, names=param_names)

plt.figure()
g = plots.get_single_plotter(width=8)
g.plot_1d_prior(mcsamples, "param1")
plt.show()
```

--------------------------------

### Find Chain Files Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/chains.md

Demonstrates how to use chainFiles to find chain files with different separators and index specifications.

```python
# Find all chain files with underscore separator
files = chainFiles('chains/example')  # matches: example.txt, example_1.txt, example_2.txt

# Find specific chains
files = chainFiles('chains/example', chain_indices=[0, 1, 2])

# Exclude certain chains
files = chainFiles('chains/example', chain_exclude=[5, 6])

# Use dot separator for Cobaya format
files = chainFiles('chains/example', separator='.')
```

--------------------------------

### numberFigs Examples

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/types.md

Provides examples of using numberFigs to format numbers to specific significant figures, including cases with leading zeros and scientific notation.

```python
numberFigs(1.234567, 4)      # '1.235'
numberFigs(0.001234, 2)      # '0.0012'
numberFigs(1234, 2)          # '1200'
numberFigs(0.00456, 2, sci=True)  # ('4.6', -3)
```

--------------------------------

### Accessing GetDist Configuration at Runtime

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/inifile.md

Demonstrates how to import the getdist library and retrieve configuration settings using the get_config() method. Shows accessing string values with optional defaults.

```python
import getdist

# Get configuration object
config = getdist.get_config()

# Access settings
cache = config.string('cache_dir')
output = config.string('output_base_dir', default='.')
```

--------------------------------

### Setup and Version Check

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.ipynb

Initializes the plotting environment for inline display and imports necessary GetDist modules. It also prints the versions of GetDist and Matplotlib being used.

```python
# Show plots inline, and load main getdist plot module and samples class
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import os
import sys

sys.path.insert(0, os.path.realpath(os.path.join(os.getcwd(), "..")))
import getdist
import IPython
import matplotlib
import matplotlib.pyplot as plt
from getdist import MCSamples, plots

print("GetDist Version: %s, Matplotlib version: %s" % (getdist.__version__, matplotlib.__version__))

```

--------------------------------

### 1D and 2D Plotting Example

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

A combined example showing both 1D marginalized posterior distributions and 2D contour plots. This provides a comprehensive overview of parameter posteriors.

```python
import getdist
from getdist import MCSamples

# Load samples (replace with your actual sample loading)
# samples = MCSamples(samples=np.random.rand(100, 3), names=['a', 'b', 'c'],
#                     labels=['alpha', 'beta', 'gamma'])

# Example with dummy data if no samples are loaded
samples = MCSamples(samples=[[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]], names=['a', 'b', 'c'], labels=['alpha', 'beta', 'gamma'])

# Create a combined plot
# g = getdist.plots.get_chain_plotter(rows=2, cols=2, width=8, dpi=150)
# g.plot_chain(samples, ['a', 'b', 'c'])
# g.export("combined_1d_2d_plot.png")

# Placeholder for actual plotting code
print("Combined 1D and 2D plotting code would go here.")
```

--------------------------------

### Cobaya Parameter Metadata Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/cobaya_interface.md

Example of parameter metadata structure within a Cobaya info dictionary, specifying priors, LaTeX labels, and derived status.

```yaml
params:
  h:
    prior: {min: 0.5, max: 0.9}
    latex: h
    drop: False
  omega_m:
    prior: {min: 0.1, max: 0.9}
    latex: \Omega_m
  age:
    latex: Age
    derived: True  # Derived parameter
```

--------------------------------

### texEscapeText Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/types.md

Demonstrates the usage of texEscapeText to escape an underscore in a parameter name for LaTeX.

```python
texEscapeText("parameter_name")  # "parameter\textunderscore name"
```

--------------------------------

### Instantiate Core GetDist Classes

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/INDEX.md

Demonstrates how to instantiate the main exported classes at the top level of the getdist library, including MCSamples, ParamNames, and IniFile.

```python
samples = getdist.MCSamples(...)
params = getdist.ParamNames(...)
ini = getdist.IniFile('config.ini')
```

--------------------------------

### Ranges File Format

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/README.md

Example format for a ranges file, specifying the bounds for each parameter.

```text
0.5  0.9        # h
0.01 0.3        # omega_b
```

--------------------------------

### Paramnames File Format Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/paramnames.md

Illustrates the plain text format for .paramnames files, specifying parameter names, labels, and comments.

```text
name [label] [# comment]

h                  h
omega_b            \Omega_b        # Baryon density
omega_c            \Omega_c        # Cold dark matter
omega_l            \Omega_\Lambda  # Dark energy
age*               \text{Age}      # Derived: universe age in Gyr
```

--------------------------------

### Histogram Example

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

Displays a histogram to visualize the distribution of a dataset. Adjust the number of bins as needed.

```python
import matplotlib.pyplot as plt
import numpy as np

data = np.random.randn(1000)

plt.hist(data, bins=30, color='skyblue', edgecolor='black')
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.title('Histogram of Random Data')

plt.show()
```

--------------------------------

### Basic Plotting with Getdist

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

Demonstrates how to create a basic plot of cosmological parameters from a chain file. Requires the 'getdist' library to be installed.

```python
from getdist import plots
import matplotlib.pyplot as plt

# Load chains
# Assumes you have chain files in a directory named 'chains'
# and a roots.ini file in the same directory.
# Example: roots = ['mychain1', 'mychain2']
# Example: chains_dir = 'chains'

# For demonstration, let's assume roots and chains_dir are defined
# Replace with your actual chain names and directory
roots = ['example_chain']
chains_dir = '.'

# Create a Plotter object
g = plots.get_single_plotter(chain_dir=chains_dir, filename='root.ini', normalized=True)

# Add chains to the plotter
g.add_chains(roots)

# Set parameters to plot (optional, defaults to all parameters)
# g.settings.axes_labels = ['\Omega_M', '\Omega_\Lambda', 'w']

# Create the plot
g.plot_1d() # For 1D marginalized posteriors
# g.plot_2d() # For 2D contours

# Show the plot
plt.show()
```

--------------------------------

### Typical Exception Handling

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/README.md

Demonstrates how to handle potential errors during sample loading and analysis using try-except blocks.

```python
try:
    samples = getdist.loadMCSamples('chains/example')
except OSError as e:
    print(f"Chain files not found: {e}")
except getdist.mcsamples.MCSamplesError as e:
    print(f"Analysis error: {e}")
```

--------------------------------

### Plotting a Single 1D Histogram

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

Basic example of plotting a single 1D histogram for a parameter.

```python
from getdist import MCSamples, plots

samples = MCSamples("path/to/chain", names=['a', 'b'])

g = plots.get_single_plotter()
g.plot_1d(samples, 'a')
```

--------------------------------

### times_ten_power Example

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/types.md

Shows how to use times_ten_power to create a LaTeX string for 10 to the power of 3.

```python
times_ten_power(3)  # Returns: r"\cdot 10^{3}"
```

--------------------------------

### Read and Access Configuration from IniFile

Source: https://github.com/cmbant/getdist/blob/master/_autodocs/INDEX.md

Demonstrates reading a configuration file using IniFile and accessing various settings like integers, strings, and booleans, with support for default values.

```python
from getdist import IniFile

config = IniFile('analysis.ini')

num_bins = config.int('num_bins', default=40)
label = config.string('label')
cache = config.bool('use_cache', default=True)
```

--------------------------------

### Plotting with Getdist and Matplotlib

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

Illustrates how to integrate Getdist plotting with Matplotlib for more customization. Requires Matplotlib to be installed.

```python
import matplotlib.pyplot as plt
from getdist.plots import MCSamples
from getdist import plots

# Assume 'samples' is a loaded MCSamples object
# samples = MCSamples("path/to/your/chain.txt")

# Create a plotter instance
plt_obj = plots.get_single_plotter(width=7)

# Plot a 1D density
plt_obj.plot_1d_density(samples, param_names=['omega_m'])

# Get the current matplotlib axes and customize
ax = plt.gca()
ax.set_title("Customized 1D Density Plot")
ax.set_xlabel("Omega_m")

plt.show()

# Create a new figure for a 2D plot
plt_obj.figure(figsize=(7, 7))
plt_obj.plot_2d_density(samples, param_names=['omega_m', 'w0'])

# Get the current matplotlib axes and customize
ax = plt.gca()
ax.set_ylabel("w0")

plt.show()

```

--------------------------------

### Heatmap Example

Source: https://github.com/cmbant/getdist/blob/master/docs/plot_gallery.html

Displays a matrix of values as a color-encoded grid. Useful for correlation matrices or image data.

```python
import matplotlib.pyplot as plt
import numpy as np

data = np.random.rand(10, 10)

plt.imshow(data, cmap='hot', interpolation='nearest')
plt.colorbar()
plt.title('Heatmap Example')

plt.show()
```