### Installing Packages with `pip` (Conceptual)

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Conceptual example of installing Python packages using pip. This command is run in the terminal.

```bash
pip install package_name
pip install -r requirements.txt
```

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

### Initialize and Run Bower's Well

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

This snippet shows how to initialize and run Bower's Well. It's a foundational example for starting any process with the tool.

```python
from bower_well import BowerWell

# Initialize BowerWell
bw = BowerWell()

# Run BowerWell
bw.run()
```

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

### Install pyGeoPressure from Downloaded Zip

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/install.rst.txt

Install pyGeoPressure after downloading and unzipping the repository from GitHub. Navigate to the directory and run pip install.

```bash
pip install pyGeoPressure
```

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

### Install Eaton Seis

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Install the Eaton Seis library using pip. This is the first step to using the library.

```bash
pip install "eaton-seis"
```

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

### Install OBP Seis

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

Install the OBP Seis library using pip. This command ensures you have the latest stable version.

```bash
pip install obp-seis
```

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

### Basic Usage Example

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

This snippet demonstrates a fundamental usage pattern. Ensure necessary imports are present.

```python
import numpy as np
import matplotlib.pyplot as plt
from bower.well import Well

# Example data
pressure = np.array([100, 110, 120, 130, 140, 150])
temperature = np.array([30, 35, 40, 45, 50, 55])
depth = np.array([1000, 1200, 1400, 1600, 1800, 2000])

# Create a Well object
well = Well(pressure, temperature, depth)

# Plotting the well data
plt.figure(figsize=(8, 6))
plt.plot(well.pressure, well.depth, label='Pressure')
plt.plot(well.temperature, well.depth, label='Temperature')
plt.xlabel('Value')
plt.ylabel('Depth (m)')
plt.title('Well Data')
plt.legend()
plt.grid(True)
plt.show()
```

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

### Install pyGeoPressure from PyPI

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/install.rst.txt

Install the pyGeoPressure package using pip from the Python Package Index.

```bash
pip install pygeopressure
```

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

### Creating a Simple DataFrame

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Demonstrates the creation of a Pandas DataFrame from a dictionary. Ensure Pandas is installed.

```python
import pandas as pd

data = {
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35],
    'City': ['New York', 'Los Angeles', 'Chicago']
}
df = pd.DataFrame(data)

print(df)
```

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

### Install Bowers Seis

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Install the Bowers Seis library using pip. This is the first step before using any of its functionalities.

```bash
pip install bowers-seis
```

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

### Basic Plotting with Matplotlib

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Provides a simple example of creating a scatter plot using Matplotlib. Requires 'matplotlib' to be installed.

```python
import matplotlib.pyplot as plt

plt.scatter(df['x_axis'], df['y_axis'])
plt.xlabel('X-axis Label')
plt.ylabel('Y-axis Label')
plt.title('Scatter Plot Example')
plt.show()
```

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

### Log.start

Source: https://pygeopressure.readthedocs.io/en/latest/explanation/data_types.html

Retrieves the start depth of available property data.

```APIDOC
## Log.start

### Description
Returns the start depth of available property data.

### Method
Call
```

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

### Basic Data Manipulation (Example)

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Provides a simple example of manipulating seismic data, such as scaling. Ensure the data object is suitable for the operation.

```python
from bowers_seis.segy import read

# Read seismic data
data = read("path/to/your/seismic_data.sgy")

# Example: Scale the amplitude of all traces by a factor of 2
scaled_data = data * 2

# Save the scaled data
write("path/to/your/scaled_data.sgy", scaled_data)
```

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

### Log.start_idx

Source: https://pygeopressure.readthedocs.io/en/latest/explanation/data_types.html

Retrieves the start index of available property data.

```APIDOC
## Log.start_idx

### Description
Returns the start index of available property data.

### Method
Call
```

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

### Well Initializer

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/well.html

Demonstrates how to initialize a Well object. This is the starting point for working with well data.

```python
from pygeopressure.basic.well import Well

# Initialize a Well object
well = Well(name='Well_A', x=1000, y=2000, z=0, md=0, tvd=0, elevation=0)
```

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

### Calculate Pressure Gradients

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

This example calculates pressure gradients for wells. It requires the well data to be loaded first.

```python
from pygeopressure.well import EatonWell

well = EatonWell("path/to/your/eaton_well_data.csv")
well.calculate_pressure_gradients()
print(well.pressure_gradients.head())
```

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

### Import Warnings and System Path Setup

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Configures warning filters and adjusts the system path to include a parent directory for module imports. This is a common setup step for Python scripts that rely on specific project structures.

```python
import warnings
warnings.filterwarnings(action='ignore')
# for python 2 and 3 compatibility
# from builtins import str
# try:
#     from pathlib import Path
# except:
#     from pathlib2 import Path
#--------------------------------------------
import sys
ppath = "../.."

if ppath not in sys.path:
    sys.path.append(ppath)
#--------------------------------------------
```

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

### Install pyGeoPressure from GitHub Develop Branch

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/install.rst.txt

Install the latest development version of pyGeoPressure directly from its GitHub repository using pip.

```bash
pip install -e git://github.com/whimian/pyGeoPressure.git@develop
```

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

### Pressure Prediction Example

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/well.html

Provides an example of how to perform pressure prediction using a Well object. This typically involves using other modules like pygeopressure.pressure.

```python
# This is a placeholder. Actual pressure prediction requires
# adding relevant log curves (e.g., velocity, density) and then
# using specific pressure prediction modules.
# Example: 
# from pygeopressure.pressure import eaton
# pore_pressure = eaton.predict(well, n=1.2) 
print("Pressure prediction functionality is available via other modules.")
```

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

### Eaton Well with Specific Parameters

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

This example initializes EatonWell with specific parameters, demonstrating direct parameter passing during instantiation.

```python
from epyt.well import EatonWell

well = EatonWell(param1="value1", param2=123)
```

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

### Install pyGeoPressure from GitHub (Editable)

Source: https://pygeopressure.readthedocs.io/en/latest/install.html

Install the latest development branch of pyGeoPressure directly from its GitHub repository in editable mode. This is useful for developers.

```bash
pip install -e git://github.com/whimian/pyGeoPressure.git@develop

```

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

### Basic Data Visualization with Matplotlib

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Demonstrates how to create a basic plot using Matplotlib. Ensure Matplotlib is installed.

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

x = np.linspace(0, 10, 100)
y = np.sin(x)

plt.figure(figsize=(8, 6))
plt.plot(x, y, label='sin(x)')
plt.title('Basic Sine Wave Plot')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.legend()
plt.grid(True)
plt.show()
```

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

### Load and Prepare Data for Multivariate Analysis

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/multivariate.ipynb.txt

This snippet shows how to load a dataset using pandas and prepare it for multivariate analysis by handling missing values and selecting relevant columns. Ensure you have pandas installed (`pip install pandas`).

```python
import pandas as pd

# Load the dataset
df = pd.read_csv('your_dataset.csv')

# Handle missing values (e.g., fill with mean)
df.fillna(df.mean(), inplace=True)

# Select relevant columns for analysis
selected_columns = ['col1', 'col2', 'col3']
X = df[selected_columns]
```

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

### Basic NumPy Array Operations

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Illustrates fundamental operations with NumPy arrays. NumPy needs to be installed.

```python
import numpy as np

arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])

print('Array 1:', arr1)
print('Array 2:', arr2)

# Element-wise addition
print('Sum:', arr1 + arr2)

# Element-wise multiplication
print('Product:', arr1 * arr2)
```

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

### Running a Python Script

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Conceptual example of how to run a Python script from the terminal. Assumes the script is named `script.py`.

```bash
python script.py
python script.py arg1 arg2
```

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

### Example of Data Simulation and OLS Regression

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/multivariate.ipynb.txt

Demonstrates simulating data and fitting an Ordinary Least Squares (OLS) regression model. This is a fundamental example for understanding regression analysis.

```python
np.random.seed(0)
X1 = np.random.rand(100)
X2 = np.random.rand(100)
y = 2 * X1 + 3 * X2 + np.random.randn(100)
df_sim = pd.DataFrame({'X1': X1, 'X2': X2, 'y': y})
model_sim = ols('y ~ X1 + X2', data=df_sim).fit()
print(model_sim.summary())

```

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

### Load OBP Well Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Demonstrates how to load well data from OBP. Ensure you have the necessary libraries installed.

```python
from pygeopressure.obp import OBP

# Load well data
well_data = OBP.load_well_data()
```

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

### Get Trace Start Time

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Retrieves the start time of a seismic trace. This is typically 0.0 if the data starts at time zero.

```python
# Get trace start time
trace_start_time = seis.get_trace_start_time()
print(f"Trace start time: {trace_start_time} s")
```

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

### Get Start Index of Available Data

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/well_log.html

Calculates and returns the starting index of the first valid (non-NaN) property data point. Caches the result.

```python
start_index = log.start_idx
```

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

### Creating a NumPy Array with Ones

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Demonstrates creating a NumPy array filled with ones. NumPy must be installed.

```python
import numpy as np

# Create a 2x3 array of ones
ones_array = np.ones((2, 3))
print(ones_array)
```

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

### Basic Data Loading and Preparation

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/multivariate.ipynb.txt

Demonstrates how to load a dataset and prepare it for multivariate analysis. Ensure necessary libraries are imported.

```python
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.preprocessing import StandardScaler
from sklearn.decomposition import PCA
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.compose import ColumnTransformer
from sklearn.manifold import TSNE
from sklearn.cluster import KMeans
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import OneHotEncoder
from sklearn.model_selection import train_test_split
from sklearn.metrics import silhouette_score

# Load the dataset
df = pd.read_csv('data.csv')

# Display the first few rows and basic info
print(df.head())
print(df.info())
print(df.describe())

# Handle missing values (example: imputation with mean)
# Identify numerical and categorical columns
num_cols = df.select_dtypes(include=np.number).columns.tolist()
categorical_cols = df.select_dtypes(include='object').columns.tolist()

# Create imputation pipelines for numerical and categorical features
num_pipeline = Pipeline([
    ('imputer', SimpleImputer(strategy='mean'))
])

categorical_pipeline = Pipeline([
    ('imputer', SimpleImputer(strategy='most_frequent')),
    ('onehot', OneHotEncoder(handle_unknown='ignore'))
])

# Use ColumnTransformer to apply different transformations to different columns
preprocessor = ColumnTransformer([
    ('num', num_pipeline, num_cols),
    ('cat', categorical_pipeline, categorical_cols)
])

# Apply transformations
X = preprocessor.fit_transform(df)

# Get feature names after one-hot encoding
cat_feature_names = preprocessor.named_transformers_['cat']['onehot'].get_feature_names_out(categorical_cols)
feature_names = num_cols + list(cat_feature_names)

X_processed = pd.DataFrame(X, columns=feature_names)

print("\nProcessed Data Head:")
print(X_processed.head())
print("\nProcessed Data Info:")
X_processed.info()

```

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

### Get Start Depth of Available Data

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/well_log.html

Calculates and returns the starting depth where valid (non-NaN) property data is available. Caches the result for efficiency.

```python
start_depth = log.start
```

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

### Generating Random Numbers with NumPy

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Shows how to generate random numbers using NumPy. NumPy must be installed.

```python
import numpy as np

# Generate a random number between 0 and 1
random_num = np.random.rand()
print('Random number:', random_num)

# Generate a random integer between 1 and 10 (inclusive)
random_int = np.random.randint(1, 11)
print('Random integer:', random_int)
```

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

### Perform Factor Analysis

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/multivariate.ipynb.txt

Conducts factor analysis to identify underlying latent factors. This example uses the 'factor_analyzer' library. Ensure it is installed (`pip install factor_analyzer`).

```python
import pandas as pd
from factor_analyzer import FactorAnalyzer

df = pd.read_csv("data.csv")

# Initialize FactorAnalyzer
fa = FactorAnalyzer(n_factors=2, rotation='varimax')

# Fit the model
fa.fit(df)

# Get the factor loadings
loadings = fa.loadings_
print(loadings)

# Get the variance explained by each factor
variance_explained = fa.get_factor_variance()
print(f"Variance explained: {variance_explained}")
```

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

### Basic File Reading

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Shows how to read the content of a text file line by line. The file 'example.txt' must exist.

```python
try:
    with open('example.txt', 'r') as f:
        for line in f:
            print(line.strip())
except FileNotFoundError:
    print('Error: example.txt not found.')
```

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

### Data Manipulation with Pandas

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Illustrates basic data manipulation using Pandas DataFrames. Pandas must be installed.

```python
import pandas as pd

data = {'col1': [1, 2, 3, 4], 'col2': [4, 3, 2, 1]}
df = pd.DataFrame(data)

print('Original DataFrame:')
print(df)

print('\nDataFrame after adding a new column:')
df['col3'] = df['col1'] * 2
print(df)
```

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

### Get Trace Information

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Retrieves information about individual seismic traces, such as their start time and sample interval.

```python
from pygeopressure.seismic import Seismic

seismic_data = Seismic.load("path/to/your/seismic_data.segy")
trace_info = seismic_data.get_trace_info(0)  # Get info for the first trace
print(trace_info)
```

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

### Set Simulation Parameters

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

This example illustrates how to set specific parameters for the simulation. These parameters control various aspects of the simulation's behavior and output.

```python
from pygeopressure.well import EatonWell

# Initialize the EatonWell object
well = EatonWell()

# Set simulation parameters
well.set_params(params=dict(a=1, b=2, c=3))

```

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

### Basic Git Commit

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Conceptual example of adding changes and committing them in Git. These commands are run in the terminal.

```bash
git add .
git commit -m "Your commit message here"
```

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

### Creating a NumPy Array with Zeros

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Demonstrates creating a NumPy array filled with zeros. NumPy must be installed.

```python
import numpy as np

# Create a 3x4 array of zeros
zeros_array = np.zeros((3, 4))
print(zeros_array)
```

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

### Basic Plotting of Seismic Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Provides a simple example of plotting the seismic data. This requires matplotlib to be installed.

```python
import matplotlib.pyplot as plt

data.plot()
```

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

### Eaton Well Configuration Example

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

Shows how to configure the EatonWell object with specific parameters. Configuration should be done before loading or processing data.

```python
from epyt.well import EatonWell

config = {
    "param1": "value1",
    "param2": 123
}
well = EatonWell(config=config)
```

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

### Example: Basic Seismic Inversion Workflow

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

A complete workflow demonstrating the basic steps of seismic inversion using Bowers Seis, from loading data to saving results.

```python
import numpy as np
import pandas as pd
from bowers_seis import SeismicData, seismic_inversion

df = pd.read_csv('seismic_data.csv')
seismic_data = SeismicData(df)
result = seismic_inversion(seismic_data)
print(result)
result.to_csv('inversion_results.csv')
```

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

### Get Trace End Time

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Calculates the end time of a seismic trace. This is the start time plus the trace length.

```python
# Get trace end time
trace_end_time = seis.get_trace_end_time()
print(f"Trace end time: {trace_end_time} s")
```

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

### Log.from_scratch

Source: https://pygeopressure.readthedocs.io/en/latest/explanation/data_types.html

Alternative initializer for creating a Log object from scratch with depth and data.

```APIDOC
## Log.from_scratch

### Description
Alternative initializer to create a Log object from scratch.

### Method
Call

### Parameters
* **depth** - Depth data.
* **data** - Property data.
* **name** (optional) - Log name.
* **units** (optional) - Log units.
* **descr** (optional) - Log description.
* **prop_type** (optional) - Property type.
```

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

### Get Default Parameters

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

This snippet shows how to retrieve the default parameters used by the EatonWell simulation. These defaults can be a starting point for customization.

```python
from pygeopressure.well import EatonWell

# Initialize the EatonWell object
well = EatonWell()

# Get default parameters
default_params = well.get_params()

```

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

### Applying Boundary Conditions

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Demonstrates how to implement absorbing boundary conditions to prevent wave reflections in a simulation. This is crucial for realistic modeling.

```python
# Inside the time-stepping loop, after updating u:

# Absorbing boundary conditions (simple example)
u[0] = u[1]
u[-1] = u[-2]

# More sophisticated absorbing boundary conditions (e.g., PML) would be implemented here.
```

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

### Initialize and Configure Eaton Well

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

Demonstrates basic initialization and configuration of the Eaton Well object. This is a starting point for most operations.

```python
from pygeopressure.well import EatonWell

# Initialize with default parameters
eaton_well = EatonWell()

# Initialize with custom parameters (example)
eaton_well_custom = EatonWell(pressure_unit='Pa', depth_unit='m')
```

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

### Initialize Eaton Seis with Custom Parameters

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Demonstrates initializing Eaton Seis with specific parameters for custom behavior. Adjust these values based on your data and analysis needs.

```python
from pygeopressure.seis import EatonSeis

# Initialize EatonSeis with custom parameters
seis = EatonSeis(n=100, m=100, k=10, l=10, p=10, q=10, r=10, s=10, t=10, u=10, v=10, w=10, x=10, y=10, z=10, a=10, b=10, c=10, d=10, e=10, f=10, g=10, h=10, i=10, j=10, o=10, alpha=10, beta=10, gamma=10, delta=10, epsilon=10, zeta=10, eta=10, theta=10, iota=10, kappa=10, lambda_=10, mu=10, nu=10, xi=10, omicron=10, pi=10, rho=10, sigma=10, tau=10, upsilon=10, phi=10, chi=10, psi=10, omega=10, n_jobs=1, verbose=1)
```

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

### Creating a Seismic Dataset

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Demonstrates how to create a new seismic dataset from scratch using `bowers_seis.create_dataset`. This is useful for generating synthetic data or preparing data for writing.

```python
from bowers_seis import create_dataset
import numpy as np

# Example: Create a dataset with 10 traces, each with 100 samples
num_traces = 10
samples_per_trace = 100

data = create_dataset(num_traces, samples_per_trace)

# Fill with some synthetic data (e.g., random noise)
data.traces = np.random.rand(num_traces, samples_per_trace)
```

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

### Basic Data Loading and Processing

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Demonstrates loading and initial processing of data. This snippet is useful for setting up the data pipeline.

```python
from pygeopressure.well import Well

# Load well data from a file
well = Well.from_file("path/to/your/well_data.csv")

# Perform basic data processing
well.process_data()
```

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

### Basic Data Loading and Display

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Demonstrates how to load data from a CSV file and display the first few rows. Ensure the 'pandas' library is installed.

```python
import pandas as pd

df = pd.read_csv("data.csv")
print(df.head())
```

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

### Advanced Filtering Example

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

An example of applying a more advanced filtering technique, such as a median filter, to seismic data. Ensure correct parameters are used.

```python
from obp_seis.seis import Seis
from obp_seis.processing import median_filter

seis_data = Seis.load("path/to/your/seismic_data.segy")

# Apply a median filter
median_filtered_data = median_filter(seis_data, window_size=5)
```

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

### Getting Trace Statistics

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Demonstrates how to retrieve basic statistics for a seismic trace, such as the number of points and sampling rate.

```python
stats = data[0].stats
print(stats)
```

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

### Initialize Log from Scratch

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/well_log.html

Creates a new Log object with specified depth and data arrays. Useful for manually constructing log data.

```python
log = cls.from_scratch(depth, data, name=None, units=None, descr=None,
                     prop_type=None)
```

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

### Creating a Simple Class

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Illustrates how to define and instantiate a simple class in Python. This is a standard Python feature.

```python
class Dog:
    def __init__(self, name):
        self.name = name

    def bark(self):
        return f'{self.name} says Woof!'

my_dog = Dog('Buddy')
print(my_dog.bark())
```

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

### Get Data Info

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

Shows how to get information about the seismic data, such as the number of samples, sample rate, and data type, using the `info` method.

```python
import obp_seis

# Load seismic data
data = obp_seis.load("path/to/your/seismic_data.segy")

# Get data information
data.info()
```

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

### Setup Development Environment with Conda (Test Env 3)

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/install.rst.txt

Create a conda development environment using the 'test_env_3.yml' file.

```bash
conda env create --file test/test_env_3.yml
```

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

### Log.__init__

Source: https://pygeopressure.readthedocs.io/en/latest/explanation/data_types.html

Initializes a Log object with a file name and log name.

```APIDOC
## Log.__init__

### Description
Initializes a Log object.

### Method
Call

### Parameters
* **file_name** (str) - Pseudo LAS file path.
* **log_name** (str) - Log name to create.
```

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

### Get Data Description

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

Illustrates how to get descriptive statistics of the seismic data, such as count, mean, std, min, max, and quartiles, using the `describe` method.

```python
import obp_seis

# Load seismic data
data = obp_seis.load("path/to/your/seismic_data.segy")

# Get data description
descriptive_stats = data.describe()

# Display the descriptive statistics
print(descriptive_stats)
```

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

### Get Lithostatic Pressure

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/well.html

Property to retrieve the lithostatic (overburden) pressure. It attempts to get the 'Overburden_Pressure' log and returns its data. Handles KeyError if the log is not found.

```python
try:
    temp_log = self.get_log('Overburden_Pressure')
    return np.array(temp_log.data)
except KeyError:
    print("No 'Overburden_Pressure' log found.")
```

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

### Load and Prepare Data for Multivariate Analysis

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/multivariate.ipynb.txt

Demonstrates loading a dataset and performing initial data preparation steps, such as handling missing values and scaling features. Ensure your data is clean and appropriately formatted before proceeding with multivariate analysis.

```python
import pandas as pd
from sklearn.preprocessing import StandardScaler

# Load the dataset
df = pd.read_csv('your_dataset.csv')

# Handle missing values (e.g., fill with mean)
df.fillna(df.mean(), inplace=True)

# Scale numerical features
scaler = StandardScaler()
numerical_cols = df.select_dtypes(include=['float64', 'int64']).columns
df[numerical_cols] = scaler.fit_transform(df[numerical_cols])

print(df.head())
```

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

### Generating Sample Data for Multivariate Analysis (Specific Example)

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/multivariate.ipynb.txt

Creates a specific sample dataset for demonstrating multivariate analysis techniques. This includes generating random data and defining a binary target variable.

```python
np.random.seed(1)
X_specific = np.random.rand(50, 3) * 5
y_specific = (X_specific[:, 0] + X_specific[:, 1] > 5).astype(int)

```

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

### Basic Plotting with Matplotlib

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Shows how to create a basic plot of seismic data using Matplotlib. Requires Matplotlib to be installed.

```python
import matplotlib.pyplot as plt

plt.plot(df["time"], df["amplitude"])
plt.xlabel("Time (s)")
plt.ylabel("Amplitude")
plt.title("Seismic Waveform")
plt.show()
```

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

### Setup Development Environment with Conda (Test Env 2)

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/install.rst.txt

Create a conda development environment using the 'test_env_2.yml' file.

```bash
conda env create --file test/test_env_2.yml
```

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

### Multivariate Plotting Setup

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/plots.html

Initializes axes and plots velocity, porosity, and shale volume logs against depth. Sets axis labels and limits for the velocity plot.

```python
axes[0].plot(np.array(vel_log.data)/1000, vel_log.depth, linewidth=0.5,
                 color='gray')

    axes[0].set(xlabel='Vp (km/s)', ylabel='Depth (m)', ylim=[lower, upper])


    axes[1].plot(por_log.data, por_log.depth, linewidth=0.5, color='gray')
    axes[1].set(xlabel='$\phi$')

    axes[2].plot(vsh_log.data, vsh_log.depth, linewidth=0.5, color='gray')
    axes[2].set(xlabel='$V_{sh}$')

    depth = well.depth
    hydrostatic = well.hydrostatic
    obp = well.lithostatic
```

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

### Get Well Metadata

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Retrieves metadata associated with the OBP Well.

```python
metadata = well.get_well_metadata()
```

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

### Get Trace Headers

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Retrieves the header information for each seismic trace.

```python
trace_headers = seismic_data.get_trace_headers()
```

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

### Get Well Status

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Retrieves the current status of the well. Useful for monitoring.

```python
status = well.get_well_status()
```

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

### K-Means Clustering

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/multivariate.ipynb.txt

Demonstrates the implementation of K-Means clustering algorithm. Ensure data is scaled appropriately before applying.

```python
from sklearn.cluster import KMeans

# Assuming 'data_scaled' is your preprocessed data
k = 3  # Number of clusters

kmeans = KMeans(n_clusters=k, random_state=0, n_init=10)
kmeans.fit(data_scaled)

labels = kmeans.labels_
centroids = kmeans.cluster_centers_
```

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

### Get Well Depth Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Retrieves and prints the depth data for the well.

```python
print(well.depth_data)

```

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

### Get Well Properties

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Retrieves a list of available properties for the OBP Well.

```python
properties = well.get_well_properties()
```

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

### Save Simulation Results

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

This example shows how to save the simulation results to a file. Saving results allows for later retrieval and analysis without re-running the simulation.

```python
from pygeopressure.well import EatonWell

# Initialize the EatonWell object
well = EatonWell()

# Run the simulation
well.run()

# Save the results
well.save("path/to/save/results.csv")

```

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

### Applying a Velocity Model

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

Demonstrates how to apply a velocity model for tasks like migration or velocity analysis. This requires a velocity model file.

```python
from obp_seis.seis import Seis
from obp_seis.processing import apply_velocity_model

seis_data = Seis.load("path/to/your/seismic_data.segy")
velocity_model = Seis.load_velocity_model("path/to/your/velocity_model.csv")

# Apply the velocity model
processed_data = apply_velocity_model(seis_data, velocity_model)
```

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

### Get Velocity Log

Source: https://pygeopressure.readthedocs.io/en/latest/tutorial/bowers_well.html

Extracts the 'Velocity' log data from the specified well.

```python
vel_log = well_cug1.get_log("Velocity")
```

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

### Load Configuration

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Loads configuration settings for the OBP Well. This is essential for customizing behavior.

```python
well.load_config(config_path)
```

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

### Get Bowers Coefficients

Source: https://pygeopressure.readthedocs.io/en/latest/tutorial/bowers_seis.html

Extracts the Bowers coefficients 'A' and 'B' for the specified well.

```python
a = well_cug1.params['bowers']["A"]
b = well_cug1.params['bowers']['B']
```

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

### Plot a Seismic Trace

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Plots the extracted seismic trace. Requires matplotlib to be installed.

```python
trace.plot()
```

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

### Create a Dummy Trace

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Creates a dummy seismic trace for testing or demonstration purposes. This is useful when you don't have actual data available.

```python
from obspy.core.trace import Trace
from obspy.core.util import AttribDict
import numpy as np

# Create a dummy trace
trace_data = np.require(np.arange(1000), dtype=np.int32)
trace = Trace(data=trace_data)
trace.stats.station = "TESTST"
trace.stats.channel = "BHZ"
trace.stats.npts = 1000
trace.stats.sampling_rate = 100
trace.stats.delta = 1.0 / trace.stats.sampling_rate
trace.stats.mseed = AttribDict()
trace.stats.mseed.dataquality = "BEST"
trace.stats.mseed.encoding = "INT32"
trace.stats.mseed.byteorder = "BIG"
```

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

### Get Well Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Retrieves all data stored within the OBP Well object.

```python
well_data = well.get_well_data()
```

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

### Eaton Well Initialization with Configuration Dictionary

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

Shows initializing EatonWell using a configuration dictionary. This is useful for managing complex configurations.

```python
from epyt.well import EatonWell

config = {
    "param1": "value1",
    "param2": 123,
    "flag": True
}
well = EatonWell(config=config)
```

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

### Getting Custom Parameters

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Retrieves the currently set custom parameters for the OBPWell object.

```python
params = well.get_params()
```

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

### Initialize Eaton Well with Custom Parameters

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

Demonstrates initializing an Eaton Well instance with specific geological and fluid parameters. Use this when you have predefined values for your simulation.

```python
from pygeopressure.well import EatonWell

params = {
    "phi": 0.2,
    "rhob": 2.5,
    "rhoc": 2.7,
    "mu": 0.02,
    "cp": 1e-9,
    "rhof": 1.0,
    "mu_f": 0.001,
    "cp_f": 1e-9,
}
well = EatonWell(params=params)
print(well.params)
```

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

### Get Bottom Depth of Log

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/well_log.html

Returns the depth of the last data point in the log.

```python
bottom_depth = log.bottom
```

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

### Get Top Depth of Log

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/well_log.html

Returns the depth of the first data point in the log.

```python
top_depth = log.top
```

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

### Plot Well Curves

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Generates a plot of specified well curves. This requires matplotlib to be installed.

```python
import matplotlib.pyplot as plt

well.plot(['GR', 'RHOB'])
plt.show()

```

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

### Plot Well Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Plots the specified curves for the well. This function requires matplotlib to be installed.

```python
well.plot(["GR", "DEN", "NPHI"])
```

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

### Import Libraries and Configure Environment

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/multivariate.ipynb.txt

Imports necessary libraries and configures the Python environment for pygeopressure. Includes warnings filter and path setup.

```python
import warnings
warnings.filterwarnings(action='ignore')

# for python 2 and 3 compatibility
# from builtins import str
# try:
#     from pathlib import Path
# except:
#     from pathlib2 import Path
#--------------------------------------------
import sys
ppath = "../.."

if ppath not in sys.path:
    sys.path.append(ppath)
#--------------------------------------------
```

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

### Get Trace Information

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

Retrieves specific trace information, such as header values or data samples.

```python
# Get the first trace
first_trace = seismic_data.get_trace(0)

# Get header information for the first trace
header_info = first_trace.header

# Get the data samples for the first trace
data_samples = first_trace.data
```

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

### Initialize and Run Simulation

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

This snippet demonstrates how to initialize and run a simulation using the Eaton Well project. It sets up the necessary parameters and executes the simulation process.

```python
from pygeopressure.well import EatonWell

# Initialize the EatonWell object
well = EatonWell()

# Run the simulation
well.run()

```

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

### Get Geometry

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

Retrieves the geometry information for the seismic survey, including source and receiver locations.

```python
geometry = seismic_data.get_geometry()
```

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

### Loading Data from Different Sources

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Shows how to load well data from various file formats. Ensure your data is in a compatible format before loading.

```python
from pygeopressure.well import Well

# Load data from a different file type (e.g., LAS)
well_las = Well.from_las("path/to/your/well_data.las")

# Load data from a dictionary
well_dict = Well.from_dict(your_data_dictionary)
```

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

### Process Seismic Data (Example)

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

Applies a basic processing step to seismic data. This is a placeholder and should be replaced with specific processing functions.

```python
from obp_seis.processing import Process

# Assuming 'data' is loaded seismic data
processor = Process(data)
processed_data = processor.apply_filter("bandpass", freq_low=10, freq_high=50)
```

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

### Get Survey Headers

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

Retrieves the survey headers, which contain metadata for the entire seismic survey.

```python
survey_headers = seismic_data.get_survey_headers()
```

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

### Get Well Information

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Retrieves and prints basic information about the loaded well, such as its name and depth.

```python
print(well.name)
print(well.depth)

```

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

### Load Data from File

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

This code shows how to load simulation data from a specified file. Ensure the file path is correct and the file format is compatible with the project's data loading mechanism.

```python
from pygeopressure.well import EatonWell

# Initialize the EatonWell object
well = EatonWell()

# Load data from a file
well.load("path/to/your/data.csv")

```

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

### Get All Headers

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Fetches all header information for all traces in the seismic data. This can be memory-intensive for large datasets.

```python
# Get all headers
all_headers = seis.get_all_headers()
print(len(all_headers))
```

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

### Eaton Well Data Loading with Configuration Dictionary

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

Demonstrates loading data into EatonWell using a configuration dictionary. This allows for consistent configuration across different operations.

```python
from epyt.well import EatonWell

config = {
    "param_load": "value_load",
    "flag_load": True
}
well = EatonWell()
well.load_data(data, config=config)
```

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

### Getting the Shape of a DataFrame

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Demonstrates how to retrieve the dimensions (number of rows and columns) of a DataFrame as a tuple.

```python
rows, columns = df.shape
print(f'DataFrame shape: {rows} rows, {columns} columns')
```

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

### Visualize Seismic Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

Visualizes seismic data using a plotting function. Requires matplotlib to be installed.

```python
from obp_seis.plotting import plot_seismic

# Assuming 'data' is loaded seismic data
plot_seismic(data)
```

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

### Initialize and Load Well Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

This snippet shows how to create a Well object and load data from a specified path. Ensure the data file exists at the given location.

```python
from pygeopressure.well import Well

well = Well.from_file("/websites/pygeopressure_readthedocs_io_en/source/tutorial/eaton_well.ipynb.md")
```

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

### Initialize SurveySetting

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/survey_setting.html

Instantiates the SurveySetting class with three reference points to define the survey grid. This process automatically computes basic survey properties and coordinate conversion parameters.

```python
from pygeopressure.basic.survey_setting import SurveySetting

# Assuming 'threepoints' is an object with the necessary attributes
# like startInline, endInline, stepInline, etc.
# survey_setting = SurveySetting(threepoints)
```

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

### Data Visualization - Pressure Over Time

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

Creates a line plot of pressure over time. Requires matplotlib to be installed.

```python
import matplotlib.pyplot as plt

plt.figure(figsize=(12, 6))
plt.plot(filtered_df['date'], filtered_df['pressure'])
plt.title('Pressure Over Time')
plt.xlabel('Date')
plt.ylabel('Pressure')
plt.grid(True)
plt.show()
```

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

### Plotting Well Log Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

Generates a plot of 'GR' and 'NPHI' against depth. Ensure matplotlib is installed.

```python
import matplotlib.pyplot as plt

plt.figure(figsize=(8, 12))
plt.plot(df['GR'], df.index, label='GR')
plt.plot(df['NPHI'], df.index, label='NPHI')
plt.gca().invert_yaxis()
plt.legend()
plt.show()
```

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

### Calculate Pressure using Gateway Method

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

This example calculates pore pressure using the Gateway method. This method might be preferred in specific geological settings or when certain data is available.

```python
from pygeopressure.well import EatonWell

well = EatonWell()
pressure = well.gateway()
print(pressure)
```

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

### Apply Thresholding (Simple)

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Shows how to apply simple thresholding to the seismic data. Pixels above or below a threshold are set to a specific value.

```python
threshold_value = 0.5
seis_thresholded = seis.thresholding(threshold_value=threshold_value)
```

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

### Perform Seismic Data Analysis

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

This example demonstrates performing a specific analysis on the seismic data. Replace `analyze` with the actual analysis method you intend to use.

```python
from pygeopressure.seis import EatonSeis

seis = EatonSeis()
seis.load("path/to/your/seismic/data.segy")
seis.process()

# Perform analysis (replace with actual analysis method)
results = seis.analyze()
```

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

### Advanced Filtering Example

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Demonstrates a more advanced filtering technique, such as a median filter. This can help remove noise.

```python
import seis

data = seis.load("path/to/your/seismic_data.segy")

# Apply a median filter
data = seis.median_filter(data, size=5)
```

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

### OBP Well Initialization

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Initializes the OBP Well with specific parameters. Ensure necessary libraries are imported.

```python
from pygeopressure.well import OBPWell

well = OBPWell(path="/path/to/your/well/data")
```

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

### Save Seismic Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Shows how to save processed seismic data to a file, for example, in SEG-Y format.

```python
seis.save("processed_seismic_data.segy")

```

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

### Filtering Seismic Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

An example of applying a low-pass filter to seismic data. This requires the SciPy library.

```python
from scipy.signal import butter, filtfilt

def butter_lowpass(cutoff, fs, order=5):
    nyq = 0.5 * fs
    normal_cutoff = cutoff / nyq
    b, a = butter(order, normal_cutoff, btype='low', analog=False)
    return b, a

def lowpass_filter(data, cutoff, fs, order=5):
    b, a = butter_lowpass(cutoff, fs, order=order)
    y = filtfilt(b, a, data)
    return y

fs = 100.0  # Sample rate
cutoff = 10.0  # Cutoff frequency
filtered_data = lowpass_filter(df["amplitude"], cutoff, fs)

plt.plot(df["time"], filtered_data)
plt.xlabel("Time (s)")
plt.ylabel("Filtered Amplitude")
plt.title("Low-pass Filtered Seismic Waveform")
plt.show()
```

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

### Eaton Well Initialization with Multiple Parameters

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

Shows initializing EatonWell with multiple configuration parameters. This allows for fine-tuning the library's behavior from the start.

```python
from epyt.well import EatonWell

well = EatonWell(param1="value1", param2=123, flag=True)
```

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

### Get Sample Interval

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Returns the sample interval (in seconds) of the seismic data. This is the inverse of the sample rate.

```python
# Get sample interval
sample_interval = seis.get_sample_interval()
print(f"Sample interval: {sample_interval} s")
```

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

### Basic Data Visualization

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/multivariate.ipynb.txt

Demonstrates how to create basic plots for visualizing multivariate data. Ensure necessary libraries are imported.

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

# Sample data
x = np.random.rand(50)
y = np.random.rand(50)
colors = np.random.rand(50)
areas = 500 * np.random.rand(50)

plt.scatter(x, y, s=areas, c=colors, alpha=0.5)
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.title("Scatter Plot of Random Data")
plt.show()
```

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

### Get Header by Inline and Crossline

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Retrieves the header information for a trace specified by its inline and crossline coordinates.

```python
# Get header by inline and crossline
header_by_coords = seis.get_header_by_inline_crossline(inline=100, crossline=50)
print(header_by_coords)
```

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

### Get Trace Shape

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Determines the shape of an individual seismic trace. This indicates the number of samples in the trace.

```python
print(f"Shape of trace {trace_index}: {selected_trace.shape}")
```

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

### Event Detection

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Shows a basic example of event detection using the `trigger` method. This is a simplified approach and may require tuning.

```python
from seis import read

data = read("path/to/your/seismic/data.sac")

# Detect events using the trigger method
events = data.trigger(threshold=3, window=10)
print(events)
```

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

### Get Well Summary

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Generates and prints a summary of the well data, including basic statistics for each curve.

```python
print(well.summary())
```

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

### Survey Folder Structure Example

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/howtos/survey.rst.txt

Illustrates the standard directory structure for a pyGeoPressure survey, including sub-folders for Seismics, Surfaces, and Wellinfo, along with the root .survey definition file.

```text
+---EXAMPLE_SURVEY
|   .survey
|   |
|   +---Seismics
|   |       velocity.seis
|   |       density.seis
|   |       pressure.seis
|   |
|   +---Surfaces
|   |       T20.hor
|   |       T16.hor
|   |
|   \---Wellinfo
|           .CUG1
|           .CUG2
|           well_data.h5
|
```

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

### Get Curve Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Retrieves and prints the data for a specific curve (e.g., 'GR') from the Well object.

```python
print(well.get_curve("GR"))
```

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

### Get Measured Depth Data

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/well.html

Demonstrates how to retrieve data associated with measured depth from a Well object.

```python
# Assuming 'GR' log curve has been added
md_data = well.get_md_data('GR')
print(f"Retrieved {len(md_data)} data points for GR at measured depth.")
```

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

### Create Development Environment (Python 2.7)

Source: https://pygeopressure.readthedocs.io/en/latest/install.html

Set up a development environment for pyGeoPressure using a conda environment file for Python 2.7. This ensures all necessary dependencies for testing are installed.

```bash
conda env create --file test/test_env_2.yml

```

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

### Get Well Data

Source: https://pygeopressure.readthedocs.io/en/latest/_modules/pygeopressure/basic/well_storage.html

Retrieves the data for a specific well by its name. Raises a KeyError if the well is not found.

```python
well_data = storage.get_well_data('well_name_1')
```

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

### Loading Pressure-Volume Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_well.ipynb.txt

Demonstrates how to load pressure-volume data from a CSV file using the `load_pv_data` utility function. This is a crucial first step for any analysis.

```python
pv_data = load_pv_data("path/to/your/pv_data.csv")
print(pv_data.head())
```

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

### Initialize Bowers Seis

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/bowers_seis.ipynb.txt

Initializes the Bowers Seis object. No specific setup or imports are mentioned as required.

```python
from pygeopressure.bowers_seis import BowersSeis

bowers = BowersSeis()
```

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

### Apply Morphological Operations (Opening)

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_seis.ipynb.txt

Demonstrates applying morphological opening to the seismic data. Opening is erosion followed by dilation, used to remove small objects.

```python
nseis_opened = seis.morphological_opening()
```

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

### Fetch Eaton Well Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/eaton_well.ipynb.txt

Retrieves historical data from the Eaton Well. Ensure you have the necessary libraries installed.

```python
from pygeopressure.well import EatonWell

well = EatonWell("Eaton_Well_1")
data = well.fetch_data()
data.head()
```

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

### Basic Data Visualization

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_seis.ipynb.txt

Shows how to create a basic visualization of the loaded seismic data. This is useful for initial data inspection.

```python
import obp_seis
import matplotlib.pyplot as plt

# Assuming seismic_data is already loaded (e.g., from the previous step)
# seismic_data = obp_seis.load_seismic('path/to/your/seismic_data.segy')

# Plot the seismic data
plt.figure(figsize=(10, 6))
plt.imshow(seismic_data, aspect='auto', cmap='seismic')
plt.title('Seismic Data Visualization')
plt.xlabel('Trace Number')
plt.ylabel('Sample Number')
plt.colorbar(label='Amplitude')
plt.show()

```

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

### Fetch OBP Well Data

Source: https://pygeopressure.readthedocs.io/en/latest/_sources/tutorial/obp_well.ipynb.txt

Retrieves well data from the OBP API. Ensure you have the 'requests' library installed.

```python
import requests

url = "https://api.openbusinesspressure.org/wells/"
params = {
    "format": "json",
    "limit": 1000
}

response = requests.get(url, params=params)
wells_data = response.json()

print(f"Retrieved {len(wells_data)} wells.")
```