packaging

.gitignore

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+# User data
+.DS_Store
+temp*
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+.idea/
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+scratchpaper.*
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# dotenv
+.env
+
+# virtualenv
+.venv
+venv/
+ENV/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+
+# datajoint
+dj_local_conf.json
+dj_local_conf_old.json
+
+# emacs
+**/*~
+**/#*#
+**/.#*

CHANGELOG.md

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+# Changelog
+
+Observes [Semantic Versioning](https://semver.org/spec/v2.0.0.html) standard and [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) convention.
+
+## [0.1.0] - YYYY-MM-DD
++ First release
+
+[0.4.2]: https://github.com/datajoint/compress-multiphoton/releases/tag/0.1.0

CODE_OF_CONDUCT.md

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+
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+We as members, contributors, and leaders pledge to make participation in our
+community a harassment-free experience for everyone, regardless of age, body
+size, visible or invisible disability, ethnicity, sex characteristics, gender
+identity and expression, level of experience, education, socio-economic status,
+nationality, personal appearance, race, caste, color, religion, or sexual
+identity and orientation.
+
+We pledge to act and interact in ways that contribute to an open, welcoming,
+diverse, inclusive, and healthy community.
+
+## Our Standards
+
+Examples of behavior that contributes to a positive environment for our
+community include:
+
+* Demonstrating empathy and kindness toward other people
+* Being respectful of differing opinions, viewpoints, and experiences
+* Giving and gracefully accepting constructive feedback
+* Accepting responsibility and apologizing to those affected by our mistakes,
+  and learning from the experience
+* Focusing on what is best not just for us as individuals, but for the overall
+  community
+
+Examples of unacceptable behavior include:
+
+* The use of sexualized language or imagery, and sexual attention or advances of
+  any kind
+* Trolling, insulting or derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or email address,
+  without their explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Enforcement Responsibilities
+
+Community leaders are responsible for clarifying and enforcing our standards of
+acceptable behavior and will take appropriate and fair corrective action in
+response to any behavior that they deem inappropriate, threatening, offensive,
+or harmful.
+
+Community leaders have the right and responsibility to remove, edit, or reject
+comments, commits, code, wiki edits, issues, and other contributions that are
+not aligned to this Code of Conduct, and will communicate reasons for moderation
+decisions when appropriate.
+
+## Scope
+
+This Code of Conduct applies within all community spaces, and also applies when
+an individual is officially representing the community in public spaces.
+Examples of representing our community include using an official e-mail address,
+posting via an official social media account, or acting as an appointed
+representative at an online or offline event.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported to the community leaders responsible for enforcement at
+[[email protected]](mailto:[email protected]).
+All complaints will be reviewed and investigated promptly and fairly.
+
+All community leaders are obligated to respect the privacy and security of the
+reporter of any incident.
+
+## Enforcement Guidelines
+
+Community leaders will follow these Community Impact Guidelines in determining
+the consequences for any action they deem in violation of this Code of Conduct:
+
+### 1. Correction
+
+**Community Impact**: Use of inappropriate language or other behavior deemed
+unprofessional or unwelcome in the community.
+
+**Consequence**: A private, written warning from community leaders, providing
+clarity around the nature of the violation and an explanation of why the
+behavior was inappropriate. A public apology may be requested.
+
+### 2. Warning
+
+**Community Impact**: A violation through a single incident or series of
+actions.
+
+**Consequence**: A warning with consequences for continued behavior. No
+interaction with the people involved, including unsolicited interaction with
+those enforcing the Code of Conduct, for a specified period of time. This
+includes avoiding interactions in community spaces as well as external channels
+like social media. Violating these terms may lead to a temporary or permanent
+ban.
+
+### 3. Temporary Ban
+
+**Community Impact**: A serious violation of community standards, including
+sustained inappropriate behavior.
+
+**Consequence**: A temporary ban from any sort of interaction or public
+communication with the community for a specified period of time. No public or
+private interaction with the people involved, including unsolicited interaction
+with those enforcing the Code of Conduct, is allowed during this period.
+Violating these terms may lead to a permanent ban.
+
+### 4. Permanent Ban
+
+**Community Impact**: Demonstrating a pattern of violation of community
+standards, including sustained inappropriate behavior, harassment of an
+individual, or aggression toward or disparagement of classes of individuals.
+
+**Consequence**: A permanent ban from any sort of public interaction within the
+community.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage],
+version 2.1, available at
+[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].
+
+Community Impact Guidelines were inspired by
+[Mozilla's code of conduct enforcement ladder][Mozilla CoC].
+
+For answers to common questions about this code of conduct, see the FAQ at
+[https://www.contributor-covenant.org/faq][FAQ]. Translations are available at
+[https://www.contributor-covenant.org/translations][translations].
+
+[homepage]: https://www.contributor-covenant.org
+[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
+[Mozilla CoC]: https://github.com/mozilla/diversity
+[FAQ]: https://www.contributor-covenant.org/faq
+[translations]: https://www.contributor-covenant.org/translations

compress_multiphoton/__init__.py

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+from .compression import compute_quantal_size
+from .analysis import analyze
+
+__all__ = ["compute_quantal_size", "analyze"]

compress_multiphoton/analysis.py

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+import numpy as np
+from time import time
+import plotly.graph_objects as go
+from .compression import compute_quantal_size
+
+
+def timer_func(func):
+    # This function shows the execution time of the function object passed
+    def wrap_func(*args, **kwargs):
+        t1 = time()
+        result = func(*args, **kwargs)
+        t2 = time()
+        print(f"Function {func.__name__!r} executed in {(t2-t1):.4f}s")
+        return result
+
+    return wrap_func
+
+
+def analyze(scan):
+    (
+        model,
+        min_intensity,
+        max_intensity,
+        unique_pixels,
+        unique_variances,
+        quantal_size,
+        zero_level,
+    ) = compute_quantal_size(scan)
+
+    print(f"Quantal size: {quantal_size}")
+    print(f"Intercept: {zero_level}")
+
+    x = np.arange(len(unique_pixels))
+    f = go.Figure(go.Scatter(x=unique_pixels, y=unique_variances, mode="markers"))
+    f.add_trace(go.Scatter(x=x, y=model.predict(x.reshape(-1, 1))))
+    f.update_layout(
+        width=700,
+        height=700,
+        yaxis=dict(title_text="Variance"),
+        xaxis=dict(title_text="Pixel Intensity"),
+        showlegend=False,
+    )
+
+    return f

compress_multiphoton/compression.py

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+import numpy as np
+from sklearn.linear_model import TheilSenRegressor
+
+
+def compute_quantal_size(scan):
+    # Set some params
+    num_frames = scan.shape[2]
+    # min_count = num_frames * 0.1  # pixel values with fewer appearances will be ignored
+    min_count = scan.min()
+    max_acceptable_intensity = 3000  # pixel values higher than this will be ignored
+    # max_acceptable_intensity = 100000
+
+    # Make sure field is at least 32 bytes (int16 overflows if summed to itself)
+    scan = scan.astype(np.float32, copy=False)
+
+    # Create pixel values at each position in field
+    eps = 1e-4  # needed for np.round to not be biased towards even numbers (0.5 -> 1, 1.5 -> 2, 2.5 -> 3, etc.)
+    pixels = np.round((scan[:, :, :-1] + scan[:, :, 1:]) / 2 + eps)
+
+    pixels = pixels.astype(np.int16 if np.max(abs(pixels)) < 2**15 else np.int32)
+
+    # Compute a good range of pixel values (common, not too bright values)
+    unique_pixels, counts = np.unique(pixels, return_counts=True)
+    min_intensity = min(unique_pixels[counts > min_count])
+    max_intensity = max(unique_pixels[counts > min_count])
+    max_acceptable_intensity = min(max_intensity, max_acceptable_intensity)
+    pixels_mask = np.logical_and(pixels >= min_intensity, pixels <= max_acceptable_intensity)
+
+    # Select pixels in good range
+    pixels = pixels[pixels_mask]
+    unique_pixels, counts = np.unique(pixels, return_counts=True)
+
+    # Compute noise variance
+    variances = ((scan[:, :, :-1] - scan[:, :, 1:]) ** 2 / 2)[pixels_mask]
+    pixels -= min_intensity
+    variance_sum = np.zeros(len(unique_pixels))  # sum of variances per pixel value
+    for i in range(0, len(pixels), int(1e8)):  # chunk it for memory efficiency
+        variance_sum += np.bincount(
+            pixels[i : i + int(1e8)], weights=variances[i : i + int(1e8)], minlength=np.ptp(unique_pixels) + 1
+        )[unique_pixels - min_intensity]
+    unique_variances = variance_sum / counts  # average variance per intensity
+
+    # Compute quantal size (by fitting a linear regressor to predict the variance from intensity)
+    X = unique_pixels.reshape(-1, 1)
+    y = unique_variances
+    model = TheilSenRegressor()  # robust regression
+    model.fit(X, y)
+    quantal_size = model.coef_[0]
+    zero_level = -model.intercept_ / model.coef_[0]
+
+    return (model, min_intensity, max_intensity, unique_pixels, unique_variances, quantal_size, zero_level)

compress_multiphoton/version.py

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+"""Package metadata"""
+
+__version__ = "0.1.0"