photompy 0.0.3

A library for reading, writing, and viewing photometric files.

PhotomPy: Photometric Python

A library for reading, writing, and viewing photometric files.

Installation

1. Clone the repo

   git clone https://github.com/jvbelenky/photompy.git
   

   or

   git clone [e-mail]:jvbelenky/photompy.git
   

2. Install locally

   cd photompy
   python setup.py sdist
   pip install .
   

3. Test, if you like

   python3 tests/example_usage.py tests/ies_files/LLIA001477-003.ies
   

4. If on Linux/MacOS, after cloning:

   cd photompy
   make all
   

Usage

Read files

Most of the core functionality of the library is in read_ies_data :

from photompy import *
lampdict = read_ies_data(filename)

By default, an ies file will be read in its original form, the angle values formatted in accordance with its photometry type, and interpolated to achieve a value for vertical angles (0,180) and horizontal angles (0,360). They are stored in dictionaries with keys phis,thetas, and values. They can be accessed like so:

original_dict = lampdict["original_vals"]
full_dict = lampdict["full_vals"]
interp_dict = lampdict["interp_vals"]

Extending the angles and interpolation between them can be disabled if desired:

lampdict = read_ies_data(filename, extend=False, interpolate=False)

Simple calculations

If finer interpolation is desired, the interp_vals dictionary can be overwritten:

interpolate_values(lampdict, overwrite=True, num_thetas=361, num_phis=721)
finer_interp_dict = lampdict["interp_vals"]

Simple calculations are performed at the filename level:

power = total_optical_power(filename)
luminous_area = lamp_area(filename, units="meters")

Visualization

Some plotting functions are provided for quickly visualizing a file. The default is a standard polar plot:

plot_ies(filename)

An alternative cartesian plotting function is provided and maybe be useful for those less familiar with polar plots to quickly gut-check any changes made to a file:

plot_ies(filename, type="cartesian", "original")
plot_ies(filename, type="cartesian", "full", elev=90, azim=45)
plot_ies(filename, type="cartesian", "interpolated", title="Interpolated", show_cbar=True)

Any dictionary that has keys thetas, phis, and values, where values contains a numpy array of shape ( len(phis), len(thetas) ) can also be quickly plotted with plot_valdict_cartesian or plot_valdict_polar

full_dict = lampdict["full_vals"]
new_dict = full_dict.copy()
new_dict["values"] = full_dict["values"] * 5
fig, ax = plot_valdict_cartesian(new_dict)
fig, ax = plot_valdict_polar(new_dict)

Writing files

To write a new ies file, you must pass a lampdict object and a key pointing to the dictionary where the theta, phi, and candela values are stored. You may want to save the extended or interpolated versions of the original file:

lampdict = read_ies_data(filename)
outfile = "full_vals.ies"
write_ies_data(outfile, lampdict, valkey="full_vals")
outfile = "interp_vals.ies"
write_ies_data(outfile, lampdict, valkey="interp_vals")

If you wish to save a different array of candela values, you can either manipulate the 3 provided value dictionary, or you must create a new dictionary and add it to the lampdict object before writing it to a new file.

# read 
lampdict = read_ies_data(filename)
interp_dict = lampdict["interp_vals"]

# copy and manipulate new dictionary
new_dict = interp_dict.copy()
new_dict["values"] = interp_dict["values"] * 5

# save in lampdict object
lampdict["scaled_vals"] = newdict

# write new value dictionary 
outfile = "scaled_interp_vals.ies"
write_ies_data(outfile, lampdict, valkey="scaled_vals")

Note that header data is not automatically updated in the latter case. Verify that all information is correct before writing.

Roadmap

• PyPi distribution
• More flexibility in function inputs - pass either filename, or dict object, etc
• Matrix manipulations - aim and rearrange input files
• Dialux file (.ldt) support
• More extensive write support

License

Distributed under the MIT License. See LICENSE.txt for more information.

Contact

Vivian Belenky - [e-mail] - @vivian_belenky

Project Link: https://github.com/jvbelenky/photompy/