ncempy

A comprehensive Python library for electron microscopy data analysis and simulation. ncempy provides algorithms and routines for image processing, file I/O with various microscopy formats, visualization tools, data evaluation, and specialized EDS tomography reconstruction capabilities for electron microscopy research.

Package Information

• Package Name: ncempy
• Language: Python
• Installation: pip install ncempy

Core Imports

import ncempy

Common usage patterns:

import ncempy.io
import ncempy.algo
import ncempy.viz
import ncempy.eval

# Direct access to main functions
from ncempy import read, plot

Basic Usage

import ncempy
import matplotlib.pyplot as plt

# Read electron microscopy data files
data = ncempy.read('microscopy_data.dm3')
print(f"Data shape: {data['data'].shape}")
print(f"Pixel size: {data['pixelSize']}")

# Display the data
ncempy.plot(data)
plt.show()

# Perform image correlation alignment
import ncempy.algo as algo
aligned = algo.image_correlate(data['data'], reference_image)

# Visualize with calibrated axes
ncempy.viz.im_calibrated(aligned, data['pixelSize'])
plt.show()

Architecture

ncempy is organized into modular components for maximum reusability:

• I/O Module: Universal file reader supporting multiple microscopy formats (SER, DM3/DM4, EMD, MRC, SMV)
• Algorithm Module: Core image processing, correlation, peak finding, and mathematical functions
• Visualization Module: Plotting utilities optimized for microscopy data with calibrated axes
• Evaluation Module: Analysis tools for stack alignment, line profiles, and ring diffraction
• EDS Tomography Module: Specialized tools for energy-dispersive X-ray spectroscopy tomography reconstruction

Capabilities

File Input/Output

Universal file reading and format conversion for multiple electron microscopy file formats including Digital Micrograph, SER, EMD/HDF5, MRC, and SMV files.

def read(filename: str) -> dict: ...

File I/O Operations

Image Processing Algorithms

Comprehensive image processing capabilities including correlation-based alignment, peak detection, Fourier operations, distortion correction, and mathematical fitting functions.

def image_correlate(image1, image2, **kwargs): ...
def stack_align(image_stack, **kwargs): ...
def peakFind2D(image, **kwargs): ...
def rebin(array, shape_out, **kwargs): ...

Image Processing Algorithms

Data Visualization

Specialized plotting functions for electron microscopy data with calibrated axes, FFT displays, interactive stack viewing, and scientific visualization tools.

def plot(data_dict, **kwargs): ...
def im_calibrated(image, pixel_size, **kwargs): ...
def imfft(image, **kwargs): ...
class stack_view: ...

Visualization Tools

Data Evaluation

Analysis tools for extracting quantitative information from microscopy data including line profiles, ring diffraction analysis, and multi-correlation techniques.

def line_profile(image, start, end, **kwargs): ...
def multicorr(image_stack, **kwargs): ...

Data Evaluation

EDS Tomography

Specialized functionality for energy-dispersive X-ray spectroscopy tomography including preprocessing, reconstruction interface with GENFIRE, and postprocessing tools.

def ExtractSignalsFromEMD(emd_file, **kwargs): ...
def WriteSignalsToGENFIRE(signals, **kwargs): ...
def ReadGENFIRESignals(results_file, **kwargs): ...

EDS Tomography

Command Line Tools

CLI utilities for common tasks including file format conversion and batch processing operations.

# Console script: ncem2png
def main(): ...

Command Line Tools

Supported File Formats

• SER files (.ser) - FEI/Thermo Fisher TIA format
• Digital Micrograph files (.dm3, .dm4) - Gatan format
• EMD/HDF5 files (.emd, .h5, .hdf5) - Electron Microscopy Dataset format
• MRC files (.mrc, .rec, .st, .ali) - Medical Research Council format
• SMV files (.smv, .img) - Single-image format

Dependencies

• Core: numpy>=2, scipy, matplotlib, h5py>=3
• Optional: glob2, genfire, hyperspy, scikit-image, ipyvolume (for EDS tomography)