Welcome to PySilentSubstitution!
================================
[](https://zenodo.org/badge/latestdoi/390693759) [](https://badge.fury.io/py/pysilsub) [](./CODE_OF_CONDUCT.md) [](https://pypi.com/project/pip/) [](https://pypi.python.org/pypi/ansicolortags/)
<img src="https://github.com/PySilentSubstitution/pysilsub/blob/main/logo/photoreceptor_characters.png?raw=True" alt="photoreceptor-characters" width="200"/>
*PySilSub* is a Python toolbox for performing the method of [silent substitution](https://pysilentsubstitution.github.io/pysilsub/01_background.html) in vision and nonvisual photoreception research.
**Note:** See also, [PyPlr](https://pyplr.github.io/cvd_pupillometry/index.html),
a sister project offering a Python framework for researching the pupillary
light reflex with the Pupil Core eye tracking platform.
With *PySilSub*, observer- and device-specific solutions to silent substitution
problems are found with linear algebra or numerical optimisation via a configurable,
intuitive interface.
```Python
# Example 1 - Target melanopsin with 100% contrast (no background
# specified), whilst ignoring rods and minimizing cone contrast,
# for a 42-year-old observer and field size of 10 degrees. Solved
# with numerical optimization.
from pysilsub import observers, problems
ssp = problems.SilentSubstitutionProblem.from_package_data('STLAB_1_York') # Load example data
ssp.observer = observers.ColorimetricObserver(age=42, field_size=10) # Assign custom observer model
ssp.ignore = ['rh'] # Ignore rod photoreceptors
ssp.silence = ['sc', 'mc', 'lc'] # Minimise cone contrast
ssp.target = ['mel'] # Target melanopsin
ssp.target_contrast = 1.0 # With 100% contrast
solution = ssp.optim_solve() # Solve with optimisation
fig = ssp.plot_solution(solution.x) # Plot the solution
```
<img src="https://raw.githubusercontent.com/PySilentSubstitution/pysilsub/main/img/example_1.svg" alt="Example 1" />
Another example:
```Python
# Example 2 - Target S-cones with 45% contrast against a specified
# background spectrum (all primaries, half max) whilst ignoring rods
# and minimizing contrast on L/M cones and melanopsin, assuming
# 32-year-old observer and 10-degree field size. Solved with linear
# algebra.
from pysilsub import problems
ssp = problems.SilentSubstitutionProblem.from_package_data('STLAB_1_York') # Load example data
ssp.background = [.5] * ssp.nprimaries # Specify background spectrum
ssp.ignore = ['rh'] # Ignore rod photoreceptors
ssp.silence = ['mc', 'lc', 'mel'] # Silence L/M cones and melanopsin
ssp.target = ['sc'] # Target S cones
ssp.target_contrast = .45 # With 45% contrast
solution = ssp.linalg_solve() # Solve with linear algebra
fig = ssp.plot_solution(solution) # Plot the solution
```
<img src="https://raw.githubusercontent.com/PySilentSubstitution/pysilsub/main/img/example_2.svg" alt="Example 2" />
Some features may serve a broader purpose in vision and circadian research. For example, computing and saving a full set of CIEPO06- and CIES026-compliant action spectra for a given observer age and field size.
```python
from pysilsub.observers import ColorimetricObserver
ColorimetricObserver(age=32, field_size=10).save_action_spectra()
```
For more information, check out the code, read the docs, and run `pip install pysilsub` to try out the examples above.
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"description": "Welcome to PySilentSubstitution!\n================================\n\n[](https://zenodo.org/badge/latestdoi/390693759) [](https://badge.fury.io/py/pysilsub) [](./CODE_OF_CONDUCT.md) [](https://pypi.com/project/pip/) [](https://pypi.python.org/pypi/ansicolortags/) \n\n<img src=\"https://github.com/PySilentSubstitution/pysilsub/blob/main/logo/photoreceptor_characters.png?raw=True\" alt=\"photoreceptor-characters\" width=\"200\"/>\n\n*PySilSub* is a Python toolbox for performing the method of [silent substitution](https://pysilentsubstitution.github.io/pysilsub/01_background.html) in vision and nonvisual photoreception research.\n\n**Note:** See also, [PyPlr](https://pyplr.github.io/cvd_pupillometry/index.html),\na sister project offering a Python framework for researching the pupillary \nlight reflex with the Pupil Core eye tracking platform.\n\nWith *PySilSub*, observer- and device-specific solutions to silent substitution \nproblems are found with linear algebra or numerical optimisation via a configurable, \nintuitive interface.\n\n```Python\n# Example 1 - Target melanopsin with 100% contrast (no background \n# specified), whilst ignoring rods and minimizing cone contrast, \n# for a 42-year-old observer and field size of 10 degrees. Solved\n# with numerical optimization.\n\nfrom pysilsub import observers, problems\n\nssp = problems.SilentSubstitutionProblem.from_package_data('STLAB_1_York') # Load example data\nssp.observer = observers.ColorimetricObserver(age=42, field_size=10) # Assign custom observer model\nssp.ignore = ['rh'] # Ignore rod photoreceptors\nssp.silence = ['sc', 'mc', 'lc'] # Minimise cone contrast\nssp.target = ['mel'] # Target melanopsin\nssp.target_contrast = 1.0 # With 100% contrast \nsolution = ssp.optim_solve() # Solve with optimisation\nfig = ssp.plot_solution(solution.x) # Plot the solution\n```\n\n\n<img src=\"https://raw.githubusercontent.com/PySilentSubstitution/pysilsub/main/img/example_1.svg\" alt=\"Example 1\" />\n\nAnother example: \n\n```Python\n# Example 2 - Target S-cones with 45% contrast against a specified \n# background spectrum (all primaries, half max) whilst ignoring rods \n# and minimizing contrast on L/M cones and melanopsin, assuming \n# 32-year-old observer and 10-degree field size. Solved with linear \n# algebra.\n\nfrom pysilsub import problems\n\nssp = problems.SilentSubstitutionProblem.from_package_data('STLAB_1_York') # Load example data\nssp.background = [.5] * ssp.nprimaries # Specify background spectrum\nssp.ignore = ['rh'] # Ignore rod photoreceptors\nssp.silence = ['mc', 'lc', 'mel'] # Silence L/M cones and melanopsin\nssp.target = ['sc'] # Target S cones\nssp.target_contrast = .45 # With 45% contrast \nsolution = ssp.linalg_solve() # Solve with linear algebra\nfig = ssp.plot_solution(solution) # Plot the solution\n```\n\n<img src=\"https://raw.githubusercontent.com/PySilentSubstitution/pysilsub/main/img/example_2.svg\" alt=\"Example 2\" />\n\nSome features may serve a broader purpose in vision and circadian research. For example, computing and saving a full set of CIEPO06- and CIES026-compliant action spectra for a given observer age and field size.\n\n```python\nfrom pysilsub.observers import ColorimetricObserver\n\nColorimetricObserver(age=32, field_size=10).save_action_spectra()\n```\n \nFor more information, check out the code, read the docs, and run `pip install pysilsub` to try out the examples above.\n",
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