psi-io 1.0.0

Readers and writers for data formats used by Predictive Science Inc.

psi-io

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Python utilities for interacting with scientific data formats used by Predictive Science Inc. (PSI).

Primarily this includes the HDF file format used by several of PSI's scientific codes for simulating the solar surface, solar corona, and inner heliosphere, including:

• MAS
• POT3D
• HipFT

Installation

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pip install psi-io

Usage

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Basic Reading

Read the entire dataset from a 3D Br HDF file output by a POT3D solution (spherical r,t,p):

import psi_io
r, t, p, br = psi_io.rdhdf_3d('br.h5')

Here r, t, and p are the 1D coordinate arrays. br is the 3D data array.

There are equivalent routines rdhdf_1d, and rdhdf_2d for 1D and 2D HDF files.

Optimized Reading and Interpolation

One can also read a specific subset of the datasets from disk.

Extract a wedge of data that just spans a range of interest:

r_range = [1.0, 1.2]
t_range = [0.5, 1.0]
p_range = [2.0, 3.0]
brx, rx, tx, px = psi_io.read_hdf_by_value(r_range, t_range, p_range, ifile='br.h5')

Get 2D t,p slice of data interpolated to a specific radius (e.g. 2.0 Rs).

br_slice, t, p = psi_io.np_interpolate_slice_from_hdf(2.5, None, None, ifile='br.h5')

Interpolate the data to specific r, t, p positions (supplied as 1D, 2D, or 3D arrays).

import numpy as np
r_vals = np.array([1.0, 1.1])
t_vals = np.array([0.7, 0.7])
t_vals = np.array([1.5, 1.5])
br_vals = psi_io.interpolate_positions_from_hdf(r_vals, t_vals, t_vals, ifile='br.h5')

Writing

Write a new 3D file:

psi_io.wrhdf_3d('br_mod.h5', r, t, p, br_mod)

As before r, t, and p are the 1D coordinate arrays. br_mod is the 3D data array.

There are equivalent routines wrhdf_1d, and wrhdf_2d for 1D and 2D HDF files.

Requirements

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This package requires the python HDF5 interface, h5py, to work with .h5 files.

If you are working with HDF4 .hdf files then you must also have the optional pyhdf HDF4 python interface installed.

Because these packages require the underlying C HDF libraries to be installed, we generally recommend using conda to install these dependencies. This often makes life much easier than installing from source:

for HDF5

conda install h5py

for HDF4

conda install pyhdf

To isolate these to a specific environment, see environment.yml

Disclaimer

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This package is currently in a pre-release state as we transition from having copies of these routines everywhere to centralizing them in a pip-installable Python package. Although the basic readers are unlikely to change for historical compatibility reasons, some of the newer things like optimized i/o and object oriented hdf reader interface may be more likely to evolve quickly.

Automated tests and basic documentation are coming soon!