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If not, please open a new issue. +If you have a feature request, please open a new issue with the label `enhancement`. + +## Development + +Follow this [Development Guide](https://github.com/inscopix/pyisx?tab=readme-ov-file#development-guide) for instructions on how to setup a development environment and build the package from source. diff --git a/_sources/examples.md.txt b/_sources/examples.md.txt new file mode 100644 index 0000000..b29a7a0 --- /dev/null +++ b/_sources/examples.md.txt @@ -0,0 +1,9 @@ + +# Examples + +This sections contains examples of how to use the `isx` package to process Inscopix data. + +::: {toctree} +examples/readData +examples/writeData +::: diff --git a/_sources/examples/readData.md.txt b/_sources/examples/readData.md.txt new file mode 100644 index 0000000..61566de --- /dev/null +++ b/_sources/examples/readData.md.txt @@ -0,0 +1,264 @@ + +# Reading Data + +This section demonstrates how the `isx` package can be used to read data from Inscopix files. +Refer to the [file types](../overview) table for reference on the Inscopix file types and read support. + +:::{note} +The following sections assume the `isx` package has been imported, i.e., `import isx` +::: + +## Microscope & Behavior Movies + +`Microscope Movie` and `Behavior Movie` file types can be read using the `isx.Movie` class. + +```python + # Open the movie for reading + movie = isx.Movie.read("movie.isxd") +``` + +Movie objects have timing and spacing properties which can be accessed: + + +```python + # Timing information can be accessed using: + movie.timing + + # The number of frames can be accessed using: + movie.timing.num_samples + + # The time period can be accessed using: + movie.timing.period.secs_float + + # Spacing information can be accessed using: + movie.spacing + + # The dimensions of the frame can be accessed using: + # which will return a 2-tuple containing the dimensions of the frame + # (num_rows, num_cols), or (height, width) + movie.spacing.num_pixels +``` + +Frames from movies can be read into memory: + +```python + # The pixel data type can accessed using: + movie.data_type + + # Read every frame of the movie, and process it + for i in range(movie.timing.num_samples): + # Dimensions of the frame are (num_rows, num_cols), or (height, width) + frame = movie.get_frame_data(i) + + # Process frame + ... +``` + +::: {warning} +It's recommended to read one frame into memory at a time to prevent out of memory errors. +::: + +::: {note} +Python indexes by 0, so the first frame is at index 0, and the the second frame is at index 1, and so on. +::: + +## Cell Sets + +`Cell Set` file types can be read using the `isx.CellSet` class. + +```python + # Open the cell set for reading + cell_set = isx.CellSet.read("cell_set.isxd") +``` + +Similar to movies, cell sets have timing and spacing properties which can be accessed. +These properties are derived from the parent movie which generated the cell set. + +```python + # Timing information can be accessed using: + cell_set.timing + + # The number of frames can be accessed using: + cell_set.timing.num_samples + + # The time period can be accessed using: + cell_set.timing.period.secs_float + + # Spacing information can be accessed using: + cell_set.spacing + + # The dimensions of the frame can be accessed using: + # which will return a 2-tuple containing the dimensions of the frame + # (num_rows, num_cols), or (height, width) + cell_set.spacing.num_pixels +``` + +Cell data from cell sets can be read into memory: + +```python + # The number of cells in the cell set can accessed using: + cell_set.num_cells + + # Read data of every cell in the cell set, and process it + for i in range(cell_set.num_cells): + # Get the cell name + name = cell_set.get_cell_name(i) + + # Get the temporal activity trace of a cell + trace = cell_set.get_cell_trace(i) + + # Get the spatial footprint of a cell + footprint = cell_set.get_cell_image_data(i) + + # Process cell data + ... +``` + +## Event Sets + +`Event Set` file types can be read using the `isx.EventSet` class. + +```python + # open the event set for reading + event_set = isx.EventSet.read("event_set.isxd") +``` + +Similar to cell sets, event sets have timing properties which can be accessed. +These properties are derived from the parent cell set which generated the event set. + +```python + # Timing information can be accessed using: + event_set.timing + + # The number of frames can be accessed using: + event_set.timing.num_samples + + # The time period can be accessed using: + event_set.timing.period.secs_float +``` + +Cell data from event sets can be read into memory: + +```python + # Read data of every cell in the event set, and process it + for i in range(event_set.timing.num_samples): + # Get the cell name + name = event_set.get_cell_name(i) + + # Get the event timestamps and amplitudes of a cell + offsets, amplitudes = event_set.get_cell_data(i) + + # Process cell data + ... +``` + +## Vessel Sets + +`Vessel Set` file types can be read using the `isx.VesselSet` class. + +```python + # Open the vessel set for reading + vessel_set = isx.VesselSet.read("vessel_set.isxd") +``` + +Similar to movies, vessel sets have timing and spacing properties which can be accessed. +These properties are derived from the parent movie which generated the vessel set. + +```python + # Timing information can be accessed using: + vessel_set.timing + + # The number of frames can be accessed using: + vessel_set.timing.num_samples + + # The time period can be accessed using: + vessel_set.timing.period.secs_float + + # Spacing information can be accessed using: + vessel_set.spacing + + # The dimensions of the frame can be accessed using: + # which will return a 2-tuple containing the dimensions of the frame + # (num_rows, num_cols), or (height, width) + vessel_set.spacing.num_pixels +``` + +Vessel data from vessel sets can be read into memory: + +```python + # The number of vessels in the vessel set can be accessed using: + vessel_set.num_vessels + + # The standard deviation projection image of the parent movie + # This is the same for every vessel + image = vessel_set.get_vessel_image_data(0) + + # Read data of every vessel in the vessel set, and process it + for i in range(vessel_set.num_vessels): + # Get the vessel name + name = vessel_set.get_vessel_name(i) + + # Get the vessel status + status = vessel_set.get_vessel_status(i) + + # For vessel diameter vessel sets, get the following data: + # The vessel diameter trace + trace = vessel_set.get_vessel_trace_data(i) + # The direction of rbc velocity trace + center_trace = vessel_set.get_vessel_center_trace_data(i) + # The vessel line points + line = vessel_set.get_vessel_line_data(i) + + # For rbc velocity vessel sets, get the following data: + # The rbc velocity trace + trace = vessel_set.get_vessel_trace_data(i) + # The direction of rbc velocity trace + direction_trace = vessel_set.get_vessel_direction_trace_data(i) + # The first correlation heatmap of the vessel + corr = vessel_set.get_vessel_correlations_data(i, 0) + # The vessel box points + box = vessel_set.get_vessel_line_data(i) + + # Process vessel data + ... +``` + +## GPIO & IMU + +`GPIO` and `IMU` file types can be read using the `isx.GpioSet` class. + +```python + # open the gpio set for reading + gpio_set = isx.GpioSet.read("signals.gpio") +``` + +Gpio sets have timing properties which can be accessed. + +```python + # Timing information can be accessed using: + gpio_set.timing + + # The number of frames can be accessed using: + gpio_set.timing.num_samples + + # The time period can be accessed using: + gpio_set.timing.period.secs_float +``` + +Signal data from gpio sets can be read into memory: + +```python + # Number of channels (i.e., signals) can be accessed using: + gpio_set.num_channels + + # Read data of every cell in the cell set, and process it + for i in range(gpio_set.num_channels): + # Get the channel name + name = gpio_set.get_channel_name(i) + + # Get the signal timestamps and amplitudes of a channel + offsets, amplitudes = gpio_set.get_channel_data(i) + + # Process signal data + ... +``` diff --git a/_sources/examples/writeData.md.txt b/_sources/examples/writeData.md.txt new file mode 100644 index 0000000..fd25eef --- /dev/null +++ b/_sources/examples/writeData.md.txt @@ -0,0 +1,142 @@ + +# Writing Data + +This section demonstrates how the `isx` package can be used to write data to Inscopix files. +Refer to [file types](../overview) for reference on the Inscopix file types and write support. + +::: {note} +The following sections assume the `isx` package has been imported, i.e., `import isx` +::: + +## Microscope Movies + +The `Microscope Movie` file type can be written using the `isx.Movie` class. + +```python + # Define timing, spacing, data_type properties + timing = isx.Timing(num_samples=200, period=isx.Duration.from_msecs(10)) + spacing = isx.Spacing(num_pixels=(300, 400)) + data_type = numpy.float32 + + # Open the movie for writing + movie = isx.Movie.write('movie.isxd', timing, spacing, data_type) + + for i in range(timing.num_samples): + # Generate frame to write + frame = ... + + # Write to file + movie.set_frame_data(i, frame) + + # Flush to disk + movie.flush() +``` + +::: {note} +Python indexes by 0, so the first frame is at index 0, and the the second frame is at index 1, and so on. +::: + +## Cell Sets + +The `Cell Set` file type can be written using the `isx.CellSet` class. + +```python + # Define timing, spacing properties + timing = isx.Timing(num_samples=200, period=isx.Duration.from_msecs(10)) + spacing = isx.Spacing(num_pixels=(300, 400)) + + # Open the cell set for writing + cell_set = isx.CellSet.write('cell_set.isxd', timing, spacing) + + for i in range(timing.num_samples): + # Generate cell footprint and trace to write + image = ... + trace = ... + + # Write to file + cell_set.set_cell_data(i, image, trace, 'C{}'.format(i)) + + # Flush to disk + cell_set.flush() +``` + +## Event Sets + +The `Event Set` file type can be written using the `isx.EventSet` class. + +```python + # Define timing properties + timing = isx.Timing(num_samples=200, period=isx.Duration.from_msecs(10)) + + # Open the event set for writing + cell_names = ['C00', 'C01', ...] + event_set = isx.EventSet.write('event_set.isxd', timing, cell_names) + + for i in range(cell_set.num_cells): + # Generate event offsets and amplitudes + offsets = ... + amplitudes = ... + + # Write to file + event_set.set_cell_data(c, offsets, amplitudes) + + # Flush to disk + event_set.flush() +``` + +## Vessel Sets + +The `Vessel Set` file type can be written using the `isx.VesselSet` class. + +For vessel diameter vessel sets: + +```python + # Define timing, spacing, vessel type properties + timing = isx.Timing(num_samples=200, period=isx.Duration.from_msecs(10)) + spacing = isx.Spacing(num_pixels=(300, 400)) + vessel_type = "vessel diameter" + + # Open the vessel set for writing + vessel_set = isx.VesselSet.write('vessel_set.isxd', timing, spacing, vessel_type) + + # Generate a projection image of the parent movie + image = ... + for i in range(timing.num_samples): + # Generate vessel diameter line, trace, and center trace to write + line = .. + trace = ... + center_trace = ... + + # Write to file + vessel_set.set_vessel_diameter_data(i, image, line, trace, center_trace, 'V{}'.format(i)) + + # Flush to disk + vessel_set.flush() +``` + +For RBC velocity vessel sets: + +```python + # Define timing, spacing, vessel type properties + timing = isx.Timing(num_samples=200, period=isx.Duration.from_msecs(10)) + spacing = isx.Spacing(num_pixels=(300, 400)) + vessel_type = "rbc velocity" + + # Open the vessel set for writing + vessel_set = isx.VesselSet.write('vessel_set.isxd', timing, spacing, vessel_type) + + # Generate a projection image of the parent movie + image = ... + for i in range(timing.num_samples): + # Generate rbc velocity line, trace, and direction trace, and correlation heatmaps to write + line = ... + trace = ... + direction_trace = ... + correlations_trace = ... + + # Write to file + vessel_set.set_rbc_velocity_data(i, image, line, trace, direction_trace, correlations_trace, 'V{}'.format(i)) + + # Flush to disk + vessel_set.flush() +``` diff --git a/_sources/faq.md.txt b/_sources/faq.md.txt new file mode 100644 index 0000000..72f7fd7 --- /dev/null +++ b/_sources/faq.md.txt @@ -0,0 +1,14 @@ +# FAQ + +* What's the difference between the [IDPS Python API](https://inscopix.com/software-analysis-miniscope-imaging/) and `pyisx`? + * The IDPS (Inscopix Data Processing Software) Python API is a python package included with the IDPS GUI application. `pyisx` is an open-source version of this package, which contains the exact same functionality (excluding any algorithms), and can be installed without installing the entire IDPS application. +* Does this package include algorithms from the IDPS Python API? + * No, currently the algorithms from the IDPS Python API are not included in `pyisx` +* What's the difference between `pyisx` and `isx`? + * [pyisx](https://github.com/inscopix/pyisx) project is a python binding for [isxcore](https://github.com/inscopix/isxcore), a C++ API for interacting with Inscopix data. + * `isx` is the python package for this project, with pre-built binaries available on [pypi](https://pypi.org/project/isx/). +* How do I file a bug report or a feature request? + * If you have found a bug, we recommend searching the [issues page](https://github.com/inscopix/pyisx/issues) to see if it has already been reported. If not, please open a new issue. + * If you have a feature request, please open a new issue with the label `enhancement`. +* Can I use this in my own projects? + * Absolutely! `pyisx` is an open-source project and free to use. Please refer to the (license)[#license] for more details on usage guidelines. diff --git a/_sources/index.md.txt b/_sources/index.md.txt new file mode 100644 index 0000000..b785281 --- /dev/null +++ b/_sources/index.md.txt @@ -0,0 +1,50 @@ + +# pyisx documentation + +`isx` is a python package for interacting with Inscopix data. +This package encapsulates the following I/O functionality: + +* Reading Inscopix files (`.isxd`, `.isxb`, `.gpio`, `.imu`) +* Writing Inscopix files (`.isxd`) +* Exporting Inscopix files to third-party formats (`.mp4`, `.tiff`, `.csv`) + +::: {toctree} +:maxdepth: 1 +:caption: Contents: + +overview +installation +reference +examples +contributing +faq +::: + +## Links + +* [Github](https://github.com/inscopix/pyisx) +* [isxcore Github](https://github.com/inscopix/isxcore) +* [Inscopix](https://inscopix.com/) + +## Quick Start + +To install `isx`, run the following command in a python environment: + +```python +pip install isx +``` + +## License + +This project has been released under a [CC BY-NC license](https://creativecommons.org/licenses/by-nc/4.0). This means that you are free to: + +* Share — copy and redistribute the material in any medium or format +* Adapt — remix, transform, and build upon the material + + * The licensor cannot revoke these freedoms as long as you follow the license terms. + +Under the following terms: + +* Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. +* NonCommercial — You may not use the material for commercial purposes . +* No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. diff --git a/_sources/installation.md.txt b/_sources/installation.md.txt new file mode 100644 index 0000000..7c0d7f7 --- /dev/null +++ b/_sources/installation.md.txt @@ -0,0 +1,35 @@ + +# Installation + +Pre-built binaries of this API can be installed from [PyPi](https://pypi.org/project/isx) for the supported platforms. + +```bash +pip install isx +``` + +::: {attention} +For Apple Silicon (i.e., macOS with arm64 architecture), the package is currently not natively supported. However, it's possible to use [anaconda](https://www.anaconda.com/) to configure an x86 environment and use the project. +::: + +```bash +CONDA_SUBDIR=osx-64 conda create -n python= +conda activate +conda config --env --set subdir osx-64 +pip install isx +``` + +Replace `` with a name for the conda environment, and `` with the python version to use. + +## Supported Platforms + +This package has been built and tested on the following operating systems, for python versions `3.9 - 3.12`: + +| OS | Version | Architecture | +| --------- | ------- | ----- | +| macOS | 13 | x86_64 | +| Ubuntu (Linux) | 20.04 | x86_64 | +| Windows | 11 | amd64 | + +## Development (advanced) + +In order to build the package locally, follow this [Development Guide](https://github.com/inscopix/pyisx?tab=readme-ov-file#development-guide). diff --git a/_sources/overview.md.txt b/_sources/overview.md.txt new file mode 100644 index 0000000..8a3a2ae --- /dev/null +++ b/_sources/overview.md.txt @@ -0,0 +1,56 @@ + +# Overview + +`isx` is a python package for interacting with Inscopix data. +This package encapsulates the following I/O functionality: +* Reading Inscopix files (`.isxd`, `.isxb`, `.gpio`, `.imu`) +* Writing Inscopix files (`.isxd`) +* Exporting Inscopix files to third-party formats (`.mp4`, `.tiff`, `.csv`) + +The [pyisx](https://github.com/inscopix/pyisx) project is a python binding for [isxcore](https://github.com/inscopix/isxcore), a C++ API for interacting with Inscopix data. + +## Install + + +This package is available on [pypi](https://pypi.org/project/isx/). +To install `isx`, run the following command in a python environment: + +```python +pip install isx +``` + +::: {attention} +For Apple Silicon (i.e., macOS with arm64 architecture), the package is currently not natively supported. However, it's possible to use [anaconda](https://www.anaconda.com/) to configure an x86 environment and use the project. +::: + +```bash +CONDA_SUBDIR=osx-64 conda create -n python= +conda activate +conda config --env --set subdir osx-64 +pip install isx +``` + +Please refer to the [Installation](#installation) guide for more details. + +## File Types + +This package encapsulates the following I/O functionality: + + +The following table summarizes all Inscopix file types and the functionality supported by this package: + +| File Type | File Format | Read | Write | Export | Description | +| --------- | ----------- | ---- | ----- | ------ | ----------- | +| `Microscope Movie` | `.isxd` | Yes | Yes | `.mp4`, `.tiff`, `.csv` | Recording acquired from a microscope | +| `Microscope Image` | `.isxd` | Yes | Yes | `.tiff` | Image acquired from a microscope | +| `Behavior Movie` | `.isxb` | Yes | No | `.mp4` | Compressed recording acquired from a behavior camera | +| `Cell Set` | `.isxd` | Yes | Yes | `.tiff`, `.csv` | Neural cells represented as a set of temporal activity traces and spatial footprints. A `Cell Set` is generated from a `Microscope Movie` | +| `Event Set` | `.isxd` | Yes | Yes | `.csv` | Neural events (e.g., calcium events) represented as a set of discrete signal traces. An `Event Set` is generated from a `Cell Set` | +| `Vessel Set` | `.isxd` | Yes | Yes | `.tiff`, `.csv` | Vessels represented as a set of vessel diameter or red blood cell (rbc) velocity traces. A `Vessel Set` is generated from a blood flow `Microscope Movie` | +| `GPIO` | `.gpio`, `.isxd` | Yes | No | `.isxd`, `.csv` | General purpose input/output signals recorded from an acquisition device | +| `IMU` | `.imu` | Yes | No | `.isxd`, `.csv` | Inertial measurement unit (accelerometer, magnetometer, orientation​) recorded from an acquisition device | +| `Compressed Microscope Movie` | `.isxc` | No | No | N/A | Compressed recording acquired from a microscope. A `Compressed Microscope Movie` is decompressed into a `Microscope Movie` | + +## Next Steps + +To learn more about how to use the `isx` package, refer to the [Examples](#examples) guide and the [API Reference](#reference). diff --git a/_sources/reference.rst.txt b/_sources/reference.rst.txt new file mode 100644 index 0000000..5157890 --- /dev/null +++ b/_sources/reference.rst.txt @@ -0,0 +1,16 @@ +.. _reference: + +API Reference +============= + +.. warning:: + + All hidden modules, classes, functions and members (i.e. those starting with \_) + are hidden because they are not part of the public API and their behavior + may change in future versions. + We recommend you do not use them and will not provide support for them. + This includes the ``_internal`` module. + +.. automodule:: isx + :members: + :imported-members: diff --git a/_static/_sphinx_javascript_frameworks_compat.js b/_static/_sphinx_javascript_frameworks_compat.js new file mode 100644 index 0000000..8141580 --- /dev/null +++ b/_static/_sphinx_javascript_frameworks_compat.js @@ -0,0 +1,123 @@ +/* Compatability shim for jQuery and underscores.js. + * + * Copyright Sphinx contributors + * Released under the two clause BSD licence + */ + +/** + * small helper function to urldecode strings + * + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL + */ +jQuery.urldecode = function(x) { + if (!x) { + return x + } + return decodeURIComponent(x.replace(/\+/g, ' ')); +}; + +/** + * small helper function to urlencode strings + */ +jQuery.urlencode = encodeURIComponent; + +/** + * This function returns the parsed url parameters of the + * current request. Multiple values per key are supported, + * it will always return arrays of strings for the value parts. + */ +jQuery.getQueryParameters = function(s) { + if (typeof s === 'undefined') + s = document.location.search; + var parts = s.substr(s.indexOf('?') + 1).split('&'); + var result = {}; + for (var i = 0; i < parts.length; i++) { + var tmp = parts[i].split('=', 2); + var key = jQuery.urldecode(tmp[0]); + var value = jQuery.urldecode(tmp[1]); + if (key in result) + result[key].push(value); + else + result[key] = [value]; + } + return result; +}; + +/** + * highlight a given string on a jquery object by wrapping it in + * span elements with the given class name. + */ +jQuery.fn.highlightText = function(text, className) { + function highlight(node, addItems) { + if (node.nodeType === 3) { + var val = node.nodeValue; + var pos = val.toLowerCase().indexOf(text); + if (pos >= 0 && + !jQuery(node.parentNode).hasClass(className) && + !jQuery(node.parentNode).hasClass("nohighlight")) { + var span; + var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.className = className; + } + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + node.parentNode.insertBefore(span, node.parentNode.insertBefore( + document.createTextNode(val.substr(pos + text.length)), + node.nextSibling)); + node.nodeValue = val.substr(0, pos); + if (isInSVG) { + var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect"); + var bbox = node.parentElement.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute('class', className); + addItems.push({ + "parent": node.parentNode, + "target": rect}); + } + } + } + else if (!jQuery(node).is("button, select, textarea")) { + jQuery.each(node.childNodes, function() { + highlight(this, addItems); 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+ margin-left: auto; + margin-right: auto; +} + +table.contentstable p.biglink { + line-height: 150%; +} + +a.biglink { + font-size: 1.3em; +} + +span.linkdescr { + font-style: italic; + padding-top: 5px; + font-size: 90%; +} + +/* -- general index --------------------------------------------------------- */ + +table.indextable { + width: 100%; +} + +table.indextable td { + text-align: left; + vertical-align: top; +} + +table.indextable ul { + margin-top: 0; + margin-bottom: 0; + list-style-type: none; +} + +table.indextable > tbody > tr > td > ul { + padding-left: 0em; +} + +table.indextable tr.pcap { + height: 10px; +} + +table.indextable tr.cap { + margin-top: 10px; + background-color: #f2f2f2; +} + +img.toggler { + margin-right: 3px; + margin-top: 3px; + cursor: pointer; +} + +div.modindex-jumpbox { + border-top: 1px solid #ddd; + border-bottom: 1px solid #ddd; + margin: 1em 0 1em 0; + padding: 0.4em; +} + +div.genindex-jumpbox { + border-top: 1px solid #ddd; + border-bottom: 1px solid #ddd; + margin: 1em 0 1em 0; + padding: 0.4em; +} + +/* -- domain module index --------------------------------------------------- */ + +table.modindextable td { + padding: 2px; + border-collapse: collapse; +} + +/* -- general body styles --------------------------------------------------- */ + +div.body { + min-width: 360px; + max-width: 800px; +} + +div.body p, div.body dd, div.body li, div.body blockquote { + -moz-hyphens: auto; + -ms-hyphens: auto; + -webkit-hyphens: auto; + hyphens: auto; +} + +a.headerlink { + visibility: hidden; +} + +a:visited { + color: #551A8B; +} + +h1:hover > a.headerlink, +h2:hover > a.headerlink, +h3:hover > a.headerlink, +h4:hover > a.headerlink, +h5:hover > a.headerlink, +h6:hover > a.headerlink, +dt:hover > a.headerlink, +caption:hover > a.headerlink, +p.caption:hover > a.headerlink, +div.code-block-caption:hover > a.headerlink { + visibility: visible; +} + +div.body p.caption { + text-align: inherit; +} + +div.body td { + text-align: left; +} + +.first { + margin-top: 0 !important; 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+ float: right; + clear: right; + overflow-x: auto; +} + +p.sidebar-title { + font-weight: bold; +} + +nav.contents, +aside.topic, +div.admonition, div.topic, blockquote { + clear: left; +} + +/* -- topics ---------------------------------------------------------------- */ + +nav.contents, +aside.topic, +div.topic { + border: 1px solid #ccc; + padding: 7px; + margin: 10px 0 10px 0; +} + +p.topic-title { + font-size: 1.1em; + font-weight: bold; + margin-top: 10px; +} + +/* -- admonitions ----------------------------------------------------------- */ + +div.admonition { + margin-top: 10px; + margin-bottom: 10px; + padding: 7px; +} + +div.admonition dt { + font-weight: bold; +} + +p.admonition-title { + margin: 0px 10px 5px 0px; + font-weight: bold; +} + +div.body p.centered { + text-align: center; + margin-top: 25px; +} + +/* -- content of sidebars/topics/admonitions -------------------------------- */ + +div.sidebar > :last-child, +aside.sidebar > :last-child, +nav.contents > :last-child, +aside.topic > :last-child, +div.topic > :last-child, +div.admonition > :last-child { + margin-bottom: 0; +} + +div.sidebar::after, +aside.sidebar::after, +nav.contents::after, +aside.topic::after, +div.topic::after, +div.admonition::after, +blockquote::after { + display: block; + content: ''; + clear: both; +} + +/* -- tables ---------------------------------------------------------------- */ + +table.docutils { + margin-top: 10px; + margin-bottom: 10px; + border: 0; + border-collapse: collapse; +} + +table.align-center { + margin-left: auto; + margin-right: auto; +} + +table.align-default { + margin-left: auto; + margin-right: auto; +} + +table caption span.caption-number { + font-style: italic; +} + +table caption span.caption-text { +} + +table.docutils td, table.docutils th { + padding: 1px 8px 1px 5px; + border-top: 0; + border-left: 0; + border-right: 0; + border-bottom: 1px solid #aaa; +} + +th { + text-align: left; + padding-right: 5px; +} + +table.citation { + border-left: solid 1px gray; + margin-left: 1px; +} + +table.citation td { + border-bottom: none; +} + +th > :first-child, +td > :first-child { + margin-top: 0px; +} + +th > :last-child, +td > :last-child { + margin-bottom: 0px; +} + +/* -- figures --------------------------------------------------------------- */ + +div.figure, figure { + margin: 0.5em; + padding: 0.5em; +} + +div.figure p.caption, figcaption { + padding: 0.3em; +} + +div.figure p.caption span.caption-number, +figcaption span.caption-number { + font-style: italic; +} + +div.figure p.caption span.caption-text, +figcaption span.caption-text { +} + +/* -- field list styles ----------------------------------------------------- */ + +table.field-list td, table.field-list th { + border: 0 !important; +} + +.field-list ul { + margin: 0; + padding-left: 1em; +} + +.field-list p { + margin: 0; +} + +.field-name { + -moz-hyphens: manual; + -ms-hyphens: manual; + -webkit-hyphens: manual; + hyphens: manual; +} + +/* -- hlist styles ---------------------------------------------------------- */ + +table.hlist { + margin: 1em 0; +} + +table.hlist td { + vertical-align: top; +} + +/* -- object description styles --------------------------------------------- */ + +.sig { + font-family: 'Consolas', 'Menlo', 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', monospace; 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+ +/** + * Simple result scoring code. + */ +if (typeof Scorer === "undefined") { + var Scorer = { + // Implement the following function to further tweak the score for each result + // The function takes a result array [docname, title, anchor, descr, score, filename] + // and returns the new score. + /* + score: result => { + const [docname, title, anchor, descr, score, filename] = result + return score + }, + */ + + // query matches the full name of an object + objNameMatch: 11, + // or matches in the last dotted part of the object name + objPartialMatch: 6, + // Additive scores depending on the priority of the object + objPrio: { + 0: 15, // used to be importantResults + 1: 5, // used to be objectResults + 2: -5, // used to be unimportantResults + }, + // Used when the priority is not in the mapping. + objPrioDefault: 0, + + // query found in title + title: 15, + partialTitle: 7, + // query found in terms + term: 5, + partialTerm: 2, + }; +} + +const _removeChildren = (element) => { + while (element && element.lastChild) element.removeChild(element.lastChild); +}; + +/** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping + */ +const _escapeRegExp = (string) => + string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string + +const _displayItem = (item, searchTerms, highlightTerms) => { + const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; + const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; + const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; + const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + const contentRoot = document.documentElement.dataset.content_root; + + const [docName, title, anchor, descr, score, _filename] = item; + + let listItem = document.createElement("li"); + let requestUrl; + let linkUrl; + if (docBuilder === "dirhtml") { + // dirhtml builder + let dirname = docName + "/"; + if (dirname.match(/\/index\/$/)) + dirname = dirname.substring(0, dirname.length - 6); + else if (dirname === "index/") dirname = ""; + requestUrl = contentRoot + dirname; + linkUrl = requestUrl; + } else { + // normal html builders + requestUrl = contentRoot + docName + docFileSuffix; + linkUrl = docName + docLinkSuffix; + } + let linkEl = listItem.appendChild(document.createElement("a")); + linkEl.href = linkUrl + anchor; + linkEl.dataset.score = score; + linkEl.innerHTML = title; + if (descr) { + listItem.appendChild(document.createElement("span")).innerHTML = + " (" + descr + ")"; + // highlight search terms in the description + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + } + else if (showSearchSummary) + fetch(requestUrl) + .then((responseData) => responseData.text()) + .then((data) => { + if (data) + listItem.appendChild( + Search.makeSearchSummary(data, searchTerms, anchor) + ); + // highlight search terms in the summary + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + }); + Search.output.appendChild(listItem); +}; +const _finishSearch = (resultCount) => { + Search.stopPulse(); + Search.title.innerText = _("Search Results"); + if (!resultCount) + Search.status.innerText = Documentation.gettext( + "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories." + ); + else + Search.status.innerText = _( + "Search finished, found ${resultCount} page(s) matching the search query." + ).replace('${resultCount}', resultCount); +}; +const _displayNextItem = ( + results, + resultCount, + searchTerms, + highlightTerms, +) => { + // results left, load the summary and display it + // this is intended to be dynamic (don't sub resultsCount) + if (results.length) { + _displayItem(results.pop(), searchTerms, highlightTerms); + setTimeout( + () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), + 5 + ); + } + // search finished, update title and status message + else _finishSearch(resultCount); +}; +// Helper function used by query() to order search results. +// Each input is an array of [docname, title, anchor, descr, score, filename]. +// Order the results by score (in opposite order of appearance, since the +// `_displayNextItem` function uses pop() to retrieve items) and then alphabetically. +const _orderResultsByScoreThenName = (a, b) => { + const leftScore = a[4]; + const rightScore = b[4]; + if (leftScore === rightScore) { + // same score: sort alphabetically + const leftTitle = a[1].toLowerCase(); + const rightTitle = b[1].toLowerCase(); + if (leftTitle === rightTitle) return 0; + return leftTitle > rightTitle ? -1 : 1; // inverted is intentional + } + return leftScore > rightScore ? 1 : -1; +}; + +/** + * Default splitQuery function. Can be overridden in ``sphinx.search`` with a + * custom function per language. + * + * The regular expression works by splitting the string on consecutive characters + * that are not Unicode letters, numbers, underscores, or emoji characters. + * This is the same as ``\W+`` in Python, preserving the surrogate pair area. + */ +if (typeof splitQuery === "undefined") { + var splitQuery = (query) => query + .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) + .filter(term => term) // remove remaining empty strings +} + +/** + * Search Module + */ +const Search = { + _index: null, + _queued_query: null, + _pulse_status: -1, + + htmlToText: (htmlString, anchor) => { + const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); + for (const removalQuery of [".headerlink", "script", "style"]) { + htmlElement.querySelectorAll(removalQuery).forEach((el) => { el.remove() }); + } + if (anchor) { + const anchorContent = htmlElement.querySelector(`[role="main"] ${anchor}`); + if (anchorContent) return anchorContent.textContent; + + console.warn( + `Anchored content block not found. Sphinx search tries to obtain it via DOM query '[role=main] ${anchor}'. Check your theme or template.` + ); + } + + // if anchor not specified or not found, fall back to main content + const docContent = htmlElement.querySelector('[role="main"]'); + if (docContent) return docContent.textContent; + + console.warn( + "Content block not found. Sphinx search tries to obtain it via DOM query '[role=main]'. Check your theme or template." + ); + return ""; + }, + + init: () => { + const query = new URLSearchParams(window.location.search).get("q"); + document + .querySelectorAll('input[name="q"]') + .forEach((el) => (el.value = query)); + if (query) Search.performSearch(query); + }, + + loadIndex: (url) => + (document.body.appendChild(document.createElement("script")).src = url), + + setIndex: (index) => { + Search._index = index; + if (Search._queued_query !== null) { + const query = Search._queued_query; + Search._queued_query = null; + Search.query(query); + } + }, + + hasIndex: () => Search._index !== null, + + deferQuery: (query) => (Search._queued_query = query), + + stopPulse: () => (Search._pulse_status = -1), + + startPulse: () => { + if (Search._pulse_status >= 0) return; + + const pulse = () => { + Search._pulse_status = (Search._pulse_status + 1) % 4; + Search.dots.innerText = ".".repeat(Search._pulse_status); + if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); + }; + pulse(); + }, + + /** + * perform a search for something (or wait until index is loaded) + */ + performSearch: (query) => { + // create the required interface elements + const searchText = document.createElement("h2"); + searchText.textContent = _("Searching"); + const searchSummary = document.createElement("p"); + searchSummary.classList.add("search-summary"); + searchSummary.innerText = ""; + const searchList = document.createElement("ul"); + searchList.classList.add("search"); + + const out = document.getElementById("search-results"); + Search.title = out.appendChild(searchText); + Search.dots = Search.title.appendChild(document.createElement("span")); + Search.status = out.appendChild(searchSummary); + Search.output = out.appendChild(searchList); + + const searchProgress = document.getElementById("search-progress"); + // Some themes don't use the search progress node + if (searchProgress) { + searchProgress.innerText = _("Preparing search..."); + } + Search.startPulse(); + + // index already loaded, the browser was quick! + if (Search.hasIndex()) Search.query(query); + else Search.deferQuery(query); + }, + + _parseQuery: (query) => { + // stem the search terms and add them to the correct list + const stemmer = new Stemmer(); + const searchTerms = new Set(); + const excludedTerms = new Set(); + const highlightTerms = new Set(); + const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); + splitQuery(query.trim()).forEach((queryTerm) => { + const queryTermLower = queryTerm.toLowerCase(); + + // maybe skip this "word" + // stopwords array is from language_data.js + if ( + stopwords.indexOf(queryTermLower) !== -1 || + queryTerm.match(/^\d+$/) + ) + return; + + // stem the word + let word = stemmer.stemWord(queryTermLower); + // select the correct list + if (word[0] === "-") excludedTerms.add(word.substr(1)); + else { + searchTerms.add(word); + highlightTerms.add(queryTermLower); + } + }); + + if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js + localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) + } + + // console.debug("SEARCH: searching for:"); + // console.info("required: ", [...searchTerms]); + // console.info("excluded: ", [...excludedTerms]); + + return [query, searchTerms, excludedTerms, highlightTerms, objectTerms]; + }, + + /** + * execute search (requires search index to be loaded) + */ + _performSearch: (query, searchTerms, excludedTerms, highlightTerms, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + const allTitles = Search._index.alltitles; + const indexEntries = Search._index.indexentries; + + // Collect multiple result groups to be sorted separately and then ordered. + // Each is an array of [docname, title, anchor, descr, score, filename]. + const normalResults = []; + const nonMainIndexResults = []; + + _removeChildren(document.getElementById("search-progress")); + + const queryLower = query.toLowerCase().trim(); + for (const [title, foundTitles] of Object.entries(allTitles)) { + if (title.toLowerCase().trim().includes(queryLower) && (queryLower.length >= title.length/2)) { + for (const [file, id] of foundTitles) { + const score = Math.round(Scorer.title * queryLower.length / title.length); + const boost = titles[file] === title ? 1 : 0; // add a boost for document titles + normalResults.push([ + docNames[file], + titles[file] !== title ? `${titles[file]} > ${title}` : title, + id !== null ? "#" + id : "", + null, + score + boost, + filenames[file], + ]); + } + } + } + + // search for explicit entries in index directives + for (const [entry, foundEntries] of Object.entries(indexEntries)) { + if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { + for (const [file, id, isMain] of foundEntries) { + const score = Math.round(100 * queryLower.length / entry.length); + const result = [ + docNames[file], + titles[file], + id ? "#" + id : "", + null, + score, + filenames[file], + ]; + if (isMain) { + normalResults.push(result); + } else { + nonMainIndexResults.push(result); + } + } + } + } + + // lookup as object + objectTerms.forEach((term) => + normalResults.push(...Search.performObjectSearch(term, objectTerms)) + ); + + // lookup as search terms in fulltext + normalResults.push(...Search.performTermsSearch(searchTerms, excludedTerms)); + + // let the scorer override scores with a custom scoring function + if (Scorer.score) { + normalResults.forEach((item) => (item[4] = Scorer.score(item))); + nonMainIndexResults.forEach((item) => (item[4] = Scorer.score(item))); + } + + // Sort each group of results by score and then alphabetically by name. + normalResults.sort(_orderResultsByScoreThenName); + nonMainIndexResults.sort(_orderResultsByScoreThenName); + + // Combine the result groups in (reverse) order. + // Non-main index entries are typically arbitrary cross-references, + // so display them after other results. + let results = [...nonMainIndexResults, ...normalResults]; + + // remove duplicate search results + // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept + let seen = new Set(); + results = results.reverse().reduce((acc, result) => { + let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(','); + if (!seen.has(resultStr)) { + acc.push(result); + seen.add(resultStr); + } + return acc; + }, []); + + return results.reverse(); + }, + + query: (query) => { + const [searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms] = Search._parseQuery(query); + const results = Search._performSearch(searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms); + + // for debugging + //Search.lastresults = results.slice(); // a copy + // console.info("search results:", Search.lastresults); + + // print the results + _displayNextItem(results, results.length, searchTerms, highlightTerms); + }, + + /** + * search for object names + */ + performObjectSearch: (object, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const objects = Search._index.objects; + const objNames = Search._index.objnames; + const titles = Search._index.titles; + + const results = []; + + const objectSearchCallback = (prefix, match) => { + const name = match[4] + const fullname = (prefix ? prefix + "." : "") + name; + const fullnameLower = fullname.toLowerCase(); + if (fullnameLower.indexOf(object) < 0) return; + + let score = 0; + const parts = fullnameLower.split("."); + + // check for different match types: exact matches of full name or + // "last name" (i.e. last dotted part) + if (fullnameLower === object || parts.slice(-1)[0] === object) + score += Scorer.objNameMatch; + else if (parts.slice(-1)[0].indexOf(object) > -1) + score += Scorer.objPartialMatch; // matches in last name + + const objName = objNames[match[1]][2]; + const title = titles[match[0]]; + + // If more than one term searched for, we require other words to be + // found in the name/title/description + const otherTerms = new Set(objectTerms); + otherTerms.delete(object); + if (otherTerms.size > 0) { + const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); + if ( + [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) + ) + return; + } + + let anchor = match[3]; + if (anchor === "") anchor = fullname; + else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; + + const descr = objName + _(", in ") + title; + + // add custom score for some objects according to scorer + if (Scorer.objPrio.hasOwnProperty(match[2])) + score += Scorer.objPrio[match[2]]; + else score += Scorer.objPrioDefault; + + results.push([ + docNames[match[0]], + fullname, + "#" + anchor, + descr, + score, + filenames[match[0]], + ]); + }; + Object.keys(objects).forEach((prefix) => + objects[prefix].forEach((array) => + objectSearchCallback(prefix, array) + ) + ); + return results; + }, + + /** + * search for full-text terms in the index + */ + performTermsSearch: (searchTerms, excludedTerms) => { + // prepare search + const terms = Search._index.terms; + const titleTerms = Search._index.titleterms; + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + + const scoreMap = new Map(); + const fileMap = new Map(); + + // perform the search on the required terms + searchTerms.forEach((word) => { + const files = []; + const arr = [ + { files: terms[word], score: Scorer.term }, + { files: titleTerms[word], score: Scorer.title }, + ]; + // add support for partial matches + if (word.length > 2) { + const escapedWord = _escapeRegExp(word); + if (!terms.hasOwnProperty(word)) { + Object.keys(terms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: terms[term], score: Scorer.partialTerm }); + }); + } + if (!titleTerms.hasOwnProperty(word)) { + Object.keys(titleTerms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: titleTerms[term], score: Scorer.partialTitle }); + }); + } + } + + // no match but word was a required one + if (arr.every((record) => record.files === undefined)) return; + + // found search word in contents + arr.forEach((record) => { + if (record.files === undefined) return; + + let recordFiles = record.files; + if (recordFiles.length === undefined) recordFiles = [recordFiles]; + files.push(...recordFiles); + + // set score for the word in each file + recordFiles.forEach((file) => { + if (!scoreMap.has(file)) scoreMap.set(file, {}); + scoreMap.get(file)[word] = record.score; + }); + }); + + // create the mapping + files.forEach((file) => { + if (!fileMap.has(file)) fileMap.set(file, [word]); + else if (fileMap.get(file).indexOf(word) === -1) fileMap.get(file).push(word); + }); + }); + + // now check if the files don't contain excluded terms + const results = []; + for (const [file, wordList] of fileMap) { + // check if all requirements are matched + + // as search terms with length < 3 are discarded + const filteredTermCount = [...searchTerms].filter( + (term) => term.length > 2 + ).length; + if ( + wordList.length !== searchTerms.size && + wordList.length !== filteredTermCount + ) + continue; + + // ensure that none of the excluded terms is in the search result + if ( + [...excludedTerms].some( + (term) => + terms[term] === file || + titleTerms[term] === file || + (terms[term] || []).includes(file) || + (titleTerms[term] || []).includes(file) + ) + ) + break; + + // select one (max) score for the file. + const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w])); + // add result to the result list + results.push([ + docNames[file], + titles[file], + "", + null, + score, + filenames[file], + ]); + } + return results; + }, + + /** + * helper function to return a node containing the + * search summary for a given text. keywords is a list + * of stemmed words. + */ + makeSearchSummary: (htmlText, keywords, anchor) => { + const text = Search.htmlToText(htmlText, anchor); + if (text === "") return null; + + const textLower = text.toLowerCase(); + const actualStartPosition = [...keywords] + .map((k) => textLower.indexOf(k.toLowerCase())) + .filter((i) => i > -1) + .slice(-1)[0]; + const startWithContext = Math.max(actualStartPosition - 120, 0); + + const top = startWithContext === 0 ? "" : "..."; + const tail = startWithContext + 240 < text.length ? "..." : ""; + + let summary = document.createElement("p"); + summary.classList.add("context"); + summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; + + return summary; + }, +}; + +_ready(Search.init); diff --git a/_static/sphinx_highlight.js b/_static/sphinx_highlight.js new file mode 100644 index 0000000..8a96c69 --- /dev/null +++ b/_static/sphinx_highlight.js @@ -0,0 +1,154 @@ +/* Highlighting utilities for Sphinx HTML documentation. */ +"use strict"; + +const SPHINX_HIGHLIGHT_ENABLED = true + +/** + * highlight a given string on a node by wrapping it in + * span elements with the given class name. + */ +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 && + !parent.classList.contains(className) && + !parent.classList.contains("nohighlight") + ) { + let span; + + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } + + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + const rest = document.createTextNode(val.substr(pos + text.length)); + parent.insertBefore( + span, + parent.insertBefore( + rest, + node.nextSibling + ) + ); + node.nodeValue = val.substr(0, pos); + /* There may be more occurrences of search term in this node. So call this + * function recursively on the remaining fragment. + */ + _highlight(rest, addItems, text, className); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect" + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); + } + } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); + } +}; +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target) + ); +}; + +/** + * Small JavaScript module for the documentation. + */ +const SphinxHighlight = { + + /** + * highlight the search words provided in localstorage in the text + */ + highlightSearchWords: () => { + if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight + + // get and clear terms from localstorage + const url = new URL(window.location); + const highlight = + localStorage.getItem("sphinx_highlight_terms") + || url.searchParams.get("highlight") + || ""; + localStorage.removeItem("sphinx_highlight_terms") + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); + + // get individual terms from highlight string + const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); + if (terms.length === 0) return; // nothing to do + + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '

' + + '' + + _("Hide Search Matches") + + "

" + ) + ); + }, + + /** + * helper function to hide the search marks again + */ + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + localStorage.removeItem("sphinx_highlight_terms") + }, + + initEscapeListener: () => { + // only install a listener if it is really needed + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; + if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { + SphinxHighlight.hideSearchWords(); + event.preventDefault(); + } + }); + }, +}; + +_ready(() => { + /* Do not call highlightSearchWords() when we are on the search page. + * It will highlight words from the *previous* search query. + */ + if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); + SphinxHighlight.initEscapeListener(); +}); diff --git a/_static/theme.css b/_static/theme.css new file mode 100644 index 0000000..00a18c9 --- /dev/null +++ b/_static/theme.css @@ -0,0 +1,3 @@ +.wy-nav-content { + max-width: 1200px !important; +} \ No newline at end of file diff --git a/contributing.html b/contributing.html new file mode 100644 index 0000000..d4ec793 --- /dev/null +++ b/contributing.html @@ -0,0 +1,132 @@ + + + + + + + Contributing — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Contributing

+

Contributions to pyisx are welcome from anyone! +In order to contribute, please open a pull request on Github and fill out the required information in the pull request description.

+
+

Reporting Bugs

+

If you have found a bug, we recommend searching the issues page to see if it has already been reported. If not, please open a new issue. +If you have a feature request, please open a new issue with the label enhancement.

+
+
+

Development

+

Follow this Development Guide for instructions on how to setup a development environment and build the package from source.

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/examples.html b/examples.html new file mode 100644 index 0000000..b74443e --- /dev/null +++ b/examples.html @@ -0,0 +1,141 @@ + + + + + + + Examples — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Examples

+

This sections contains examples of how to use the isx package to process Inscopix data.

+
+ +
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/examples/readData.html b/examples/readData.html new file mode 100644 index 0000000..61c65a9 --- /dev/null +++ b/examples/readData.html @@ -0,0 +1,364 @@ + + + + + + + Reading Data — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Reading Data

+

This section demonstrates how the isx package can be used to read data from Inscopix files. +Refer to the file types table for reference on the Inscopix file types and read support.

+
+

Note

+

The following sections assume the isx package has been imported, i.e., import isx

+
+
+

Microscope & Behavior Movies

+

Microscope Movie and Behavior Movie file types can be read using the isx.Movie class.

+
    # Open the movie for reading
+    movie = isx.Movie.read("movie.isxd")
+
+
+

Movie objects have timing and spacing properties which can be accessed:

+
    # Timing information can be accessed using:
+    movie.timing
+
+    # The number of frames can be accessed using:
+    movie.timing.num_samples
+
+    # The time period can be accessed using:
+    movie.timing.period.secs_float
+
+    # Spacing information can be accessed using:
+    movie.spacing
+
+    # The dimensions of the frame can be accessed using:
+    # which will return a 2-tuple containing the dimensions of the frame
+    # (num_rows, num_cols), or (height, width)
+    movie.spacing.num_pixels
+
+
+

Frames from movies can be read into memory:

+
    # The pixel data type can accessed using:
+    movie.data_type
+
+    # Read every frame of the movie, and process it
+    for i in range(movie.timing.num_samples):
+        # Dimensions of the frame are (num_rows, num_cols), or (height, width)
+        frame = movie.get_frame_data(i)
+        
+        # Process frame
+        ...
+
+
+
+

Warning

+

It’s recommended to read one frame into memory at a time to prevent out of memory errors.

+
+
+

Note

+

Python indexes by 0, so the first frame is at index 0, and the the second frame is at index 1, and so on.

+
+
+
+

Cell Sets

+

Cell Set file types can be read using the isx.CellSet class.

+
    # Open the cell set for reading
+    cell_set = isx.CellSet.read("cell_set.isxd")
+
+
+

Similar to movies, cell sets have timing and spacing properties which can be accessed. +These properties are derived from the parent movie which generated the cell set.

+
    # Timing information can be accessed using:
+    cell_set.timing
+
+    # The number of frames can be accessed using:
+    cell_set.timing.num_samples
+
+    # The time period can be accessed using:
+    cell_set.timing.period.secs_float
+
+    # Spacing information can be accessed using:
+    cell_set.spacing
+
+    # The dimensions of the frame can be accessed using:
+    # which will return a 2-tuple containing the dimensions of the frame
+    # (num_rows, num_cols), or (height, width)
+    cell_set.spacing.num_pixels
+
+
+

Cell data from cell sets can be read into memory:

+
    # The number of cells in the cell set can accessed using:
+    cell_set.num_cells
+
+    # Read data of every cell in the cell set, and process it
+    for i in range(cell_set.num_cells):
+        # Get the cell name
+        name = cell_set.get_cell_name(i)
+
+        # Get the temporal activity trace of a cell
+        trace = cell_set.get_cell_trace(i)
+
+        # Get the spatial footprint of a cell
+        footprint = cell_set.get_cell_image_data(i)
+        
+        # Process cell data
+        ...
+
+
+
+
+

Event Sets

+

Event Set file types can be read using the isx.EventSet class.

+
    # open the event set for reading
+    event_set = isx.EventSet.read("event_set.isxd")
+
+
+

Similar to cell sets, event sets have timing properties which can be accessed. +These properties are derived from the parent cell set which generated the event set.

+
    # Timing information can be accessed using:
+    event_set.timing
+
+    # The number of frames can be accessed using:
+    event_set.timing.num_samples
+
+    # The time period can be accessed using:
+    event_set.timing.period.secs_float
+
+
+

Cell data from event sets can be read into memory:

+
    # Read data of every cell in the event set, and process it
+    for i in range(event_set.timing.num_samples):
+        # Get the cell name
+        name = event_set.get_cell_name(i)
+
+        # Get the event timestamps and amplitudes of a cell
+        offsets, amplitudes = event_set.get_cell_data(i)
+
+        # Process cell data
+        ...
+
+
+
+
+

Vessel Sets

+

Vessel Set file types can be read using the isx.VesselSet class.

+
    # Open the vessel set for reading
+    vessel_set = isx.VesselSet.read("vessel_set.isxd")
+
+
+

Similar to movies, vessel sets have timing and spacing properties which can be accessed. +These properties are derived from the parent movie which generated the vessel set.

+
    # Timing information can be accessed using:
+    vessel_set.timing
+
+    # The number of frames can be accessed using:
+    vessel_set.timing.num_samples
+
+    # The time period can be accessed using:
+    vessel_set.timing.period.secs_float
+
+    # Spacing information can be accessed using:
+    vessel_set.spacing
+
+    # The dimensions of the frame can be accessed using:
+    # which will return a 2-tuple containing the dimensions of the frame
+    # (num_rows, num_cols), or (height, width)
+    vessel_set.spacing.num_pixels
+
+
+

Vessel data from vessel sets can be read into memory:

+
    # The number of vessels in the vessel set can be accessed using:
+    vessel_set.num_vessels
+
+    # The standard deviation projection image of the parent movie
+    # This is the same for every vessel
+    image = vessel_set.get_vessel_image_data(0)
+
+    # Read data of every vessel in the vessel set, and process it
+    for i in range(vessel_set.num_vessels):
+        # Get the vessel name
+        name = vessel_set.get_vessel_name(i)
+
+        # Get the vessel status
+        status = vessel_set.get_vessel_status(i)
+
+        # For vessel diameter vessel sets, get the following data:
+        # The vessel diameter trace
+        trace = vessel_set.get_vessel_trace_data(i)
+        # The direction of rbc velocity trace
+        center_trace = vessel_set.get_vessel_center_trace_data(i)
+        # The vessel line points
+        line = vessel_set.get_vessel_line_data(i)
+
+        # For rbc velocity vessel sets, get the following data:
+        # The rbc velocity trace
+        trace = vessel_set.get_vessel_trace_data(i)
+        # The direction of rbc velocity trace
+        direction_trace = vessel_set.get_vessel_direction_trace_data(i)
+        # The first correlation heatmap of the vessel
+        corr = vessel_set.get_vessel_correlations_data(i, 0)
+        # The vessel box points
+        box = vessel_set.get_vessel_line_data(i)
+
+        # Process vessel data
+        ...
+
+
+
+
+

GPIO & IMU

+

GPIO and IMU file types can be read using the isx.GpioSet class.

+
    # open the gpio set for reading
+    gpio_set = isx.GpioSet.read("signals.gpio")
+
+
+

Gpio sets have timing properties which can be accessed.

+
    # Timing information can be accessed using:
+    gpio_set.timing
+
+    # The number of frames can be accessed using:
+    gpio_set.timing.num_samples
+
+    # The time period can be accessed using:
+    gpio_set.timing.period.secs_float
+
+
+

Signal data from gpio sets can be read into memory:

+
    # Number of channels (i.e., signals) can be accessed using:
+    gpio_set.num_channels
+
+    # Read data of every cell in the cell set, and process it
+    for i in range(gpio_set.num_channels):
+        # Get the channel name
+        name = gpio_set.get_channel_name(i)
+
+        # Get the signal timestamps and amplitudes of a channel
+        offsets, amplitudes = gpio_set.get_channel_data(i)
+
+        # Process signal data
+        ...
+
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/examples/writeData.html b/examples/writeData.html new file mode 100644 index 0000000..499be2e --- /dev/null +++ b/examples/writeData.html @@ -0,0 +1,260 @@ + + + + + + + Writing Data — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Writing Data

+

This section demonstrates how the isx package can be used to write data to Inscopix files. +Refer to file types for reference on the Inscopix file types and write support.

+
+

Note

+

The following sections assume the isx package has been imported, i.e., import isx

+
+
+

Microscope Movies

+

The Microscope Movie file type can be written using the isx.Movie class.

+
    # Define timing, spacing, data_type properties
+    timing = isx.Timing(num_samples=200, period=isx.Duration.from_msecs(10))
+    spacing = isx.Spacing(num_pixels=(300, 400))
+    data_type = numpy.float32
+
+    # Open the movie for writing
+    movie = isx.Movie.write('movie.isxd', timing, spacing, data_type)
+
+    for i in range(timing.num_samples):
+        # Generate frame to write
+        frame = ...
+
+        # Write to file
+        movie.set_frame_data(i, frame)
+    
+    # Flush to disk
+    movie.flush()
+
+
+
+

Note

+

Python indexes by 0, so the first frame is at index 0, and the the second frame is at index 1, and so on.

+
+
+
+

Cell Sets

+

The Cell Set file type can be written using the isx.CellSet class.

+
    # Define timing, spacing properties
+    timing = isx.Timing(num_samples=200, period=isx.Duration.from_msecs(10))
+    spacing = isx.Spacing(num_pixels=(300, 400))
+    
+    # Open the cell set for writing
+    cell_set = isx.CellSet.write('cell_set.isxd', timing, spacing)
+
+    for i in range(timing.num_samples):
+        # Generate cell footprint and trace to write
+        image = ...
+        trace = ...
+
+        # Write to file
+        cell_set.set_cell_data(i, image, trace, 'C{}'.format(i))
+    
+    # Flush to disk
+    cell_set.flush()
+
+
+
+
+

Event Sets

+

The Event Set file type can be written using the isx.EventSet class.

+
    # Define timing properties
+    timing = isx.Timing(num_samples=200, period=isx.Duration.from_msecs(10))
+
+    # Open the event set for writing
+    cell_names = ['C00', 'C01', ...]
+    event_set = isx.EventSet.write('event_set.isxd', timing, cell_names)
+
+    for i in range(cell_set.num_cells):
+        # Generate event offsets and amplitudes
+        offsets = ...
+        amplitudes = ...
+
+        # Write to file
+        event_set.set_cell_data(c, offsets, amplitudes)
+    
+    # Flush to disk
+    event_set.flush()
+
+
+
+
+

Vessel Sets

+

The Vessel Set file type can be written using the isx.VesselSet class.

+

For vessel diameter vessel sets:

+
    # Define timing, spacing, vessel type properties
+    timing = isx.Timing(num_samples=200, period=isx.Duration.from_msecs(10))
+    spacing = isx.Spacing(num_pixels=(300, 400))
+    vessel_type = "vessel diameter"
+
+    # Open the vessel set for writing
+    vessel_set = isx.VesselSet.write('vessel_set.isxd', timing, spacing, vessel_type)
+
+    # Generate a projection image of the parent movie
+    image = ...
+    for i in range(timing.num_samples):
+        # Generate vessel diameter line, trace, and center trace to write
+        line = ..
+        trace = ...
+        center_trace = ...
+
+        # Write to file
+        vessel_set.set_vessel_diameter_data(i, image, line, trace, center_trace, 'V{}'.format(i))
+    
+    # Flush to disk
+    vessel_set.flush()
+
+
+

For RBC velocity vessel sets:

+
    # Define timing, spacing, vessel type properties
+    timing = isx.Timing(num_samples=200, period=isx.Duration.from_msecs(10))
+    spacing = isx.Spacing(num_pixels=(300, 400))
+    vessel_type = "rbc velocity"
+
+    # Open the vessel set for writing
+    vessel_set = isx.VesselSet.write('vessel_set.isxd', timing, spacing, vessel_type)
+
+    # Generate a projection image of the parent movie
+    image = ...
+    for i in range(timing.num_samples):
+        # Generate rbc velocity line, trace, and direction trace, and correlation heatmaps to write
+        line = ...
+        trace = ...
+        direction_trace = ...
+        correlations_trace = ...
+
+        # Write to file
+        vessel_set.set_rbc_velocity_data(i, image, line, trace, direction_trace, correlations_trace, 'V{}'.format(i))
+    
+    # Flush to disk
+    vessel_set.flush()
+
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/faq.html b/faq.html new file mode 100644 index 0000000..5d9586c --- /dev/null +++ b/faq.html @@ -0,0 +1,144 @@ + + + + + + + FAQ — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

FAQ

+
    +

  • What’s the difference between the IDPS Python API and pyisx?

    +
      +

    • The IDPS (Inscopix Data Processing Software) Python API is a python package included with the IDPS GUI application. pyisx is an open-source version of this package, which contains the exact same functionality (excluding any algorithms), and can be installed without installing the entire IDPS application.

      • +
    +
    • +

  • Does this package include algorithms from the IDPS Python API?

    +
      +

    • No, currently the algorithms from the IDPS Python API are not included in pyisx

      • +
    +
    • +

  • What’s the difference between pyisx and isx?

    +
      +

    • pyisx project is a python binding for isxcore, a C++ API for interacting with Inscopix data.

      • +

    • isx is the python package for this project, with pre-built binaries available on pypi.

      • +
    +
    • +

  • How do I file a bug report or a feature request?

    +
      +

    • If you have found a bug, we recommend searching the issues page to see if it has already been reported. If not, please open a new issue.

      • +

    • If you have a feature request, please open a new issue with the label enhancement.

      • +
    +
    • +

  • Can I use this in my own projects?

    +
      +

    • Absolutely! pyisx is an open-source project and free to use. Please refer to the (license)[#license] for more details on usage guidelines.

      • +
    +
    • +
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/genindex.html b/genindex.html new file mode 100644 index 0000000..f458453 --- /dev/null +++ b/genindex.html @@ -0,0 +1,481 @@ + + + + + + Index — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • Index
    • +
  • +
    • +
+
+
+
+
+ + +

Index

+ +
+ A + | C + | D + | E + | F + | G + | H + | I + | L + | M + | O + | R + | S + | T + | V + | W + +
+

A

+ + + +
+ +

C

+ + + +
+ +

D

+ + +
+ +

E

+ + + +
+ +

F

+ + + +
+ +

G

+ + + +
+ +

H

+ + +
+ +

I

+ + + +
+ +

L

+ + +
+ +

M

+ + + +
+ +

O

+ + + +
+ +

R

+ + +
+ +

S

+ + + +
+ +

T

+ + + +
+ +

V

+ + + +
+ +

W

+ + +
+ + + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/index.html b/index.html new file mode 100644 index 0000000..3f3da5f --- /dev/null +++ b/index.html @@ -0,0 +1,166 @@ + + + + + + + pyisx documentation — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

pyisx documentation

+

isx is a python package for interacting with Inscopix data. +This package encapsulates the following I/O functionality:

+
    +

  • Reading Inscopix files (.isxd, .isxb, .gpio, .imu)

    • +

  • Writing Inscopix files (.isxd)

    • +

  • Exporting Inscopix files to third-party formats (.mp4, .tiff, .csv)

    • +
+
+

Contents:

+ +
+ +
+

Quick Start

+

To install isx, run the following command in a python environment:

+
pip install isx
+
+
+
+
+

License

+

This project has been released under a CC BY-NC license. This means that you are free to:

+
    +

  • Share — copy and redistribute the material in any medium or format

    • +

  • Adapt — remix, transform, and build upon the material

    +
      +

    • The licensor cannot revoke these freedoms as long as you follow the license terms.

      • +
    +
    • +
+

Under the following terms:

+
    +

  • Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

    • +

  • NonCommercial — You may not use the material for commercial purposes .

    • +

  • No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

    • +
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/installation.html b/installation.html new file mode 100644 index 0000000..433681d --- /dev/null +++ b/installation.html @@ -0,0 +1,166 @@ + + + + + + + Installation — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Installation

+

Pre-built binaries of this API can be installed from PyPi for the supported platforms.

+
pip install isx
+
+
+
+

Attention

+

For Apple Silicon (i.e., macOS with arm64 architecture), the package is currently not natively supported. However, it’s possible to use anaconda to configure an x86 environment and use the project.

+
+
CONDA_SUBDIR=osx-64 conda create -n <name> python=<python>
+conda activate <name>
+conda config --env --set subdir osx-64
+pip install isx
+
+
+

Replace <name> with a name for the conda environment, and <python> with the python version to use.

+
+

Supported Platforms

+

This package has been built and tested on the following operating systems, for python versions 3.9 - 3.12:

+ + + + + + + + + + + + + + + + + + + + + +

OS

Version

Architecture

macOS

13

x86_64

Ubuntu (Linux)

20.04

x86_64

Windows

11

amd64

+
+
+

Development (advanced)

+

In order to build the package locally, follow this Development Guide.

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/objects.inv b/objects.inv new file mode 100644 index 0000000..9e92225 Binary files /dev/null and b/objects.inv differ diff --git a/overview.html b/overview.html new file mode 100644 index 0000000..29eafc9 --- /dev/null +++ b/overview.html @@ -0,0 +1,234 @@ + + + + + + + Overview — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Overview

+

isx is a python package for interacting with Inscopix data. +This package encapsulates the following I/O functionality:

+
    +

  • Reading Inscopix files (.isxd, .isxb, .gpio, .imu)

    • +

  • Writing Inscopix files (.isxd)

    • +

  • Exporting Inscopix files to third-party formats (.mp4, .tiff, .csv)

    • +
+

The pyisx project is a python binding for isxcore, a C++ API for interacting with Inscopix data.

+
+

Install

+

This package is available on pypi. +To install isx, run the following command in a python environment:

+
pip install isx
+
+
+
+

Attention

+

For Apple Silicon (i.e., macOS with arm64 architecture), the package is currently not natively supported. However, it’s possible to use anaconda to configure an x86 environment and use the project.

+
+
CONDA_SUBDIR=osx-64 conda create -n <name> python=<python>
+conda activate <name>
+conda config --env --set subdir osx-64
+pip install isx
+
+
+

Please refer to the Installation guide for more details.

+
+
+

File Types

+

This package encapsulates the following I/O functionality:

+

The following table summarizes all Inscopix file types and the functionality supported by this package:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

File Type

File Format

Read

Write

Export

Description

Microscope Movie

.isxd

Yes

Yes

.mp4, .tiff, .csv

Recording acquired from a microscope

Microscope Image

.isxd

Yes

Yes

.tiff

Image acquired from a microscope

Behavior Movie

.isxb

Yes

No

.mp4

Compressed recording acquired from a behavior camera

Cell Set

.isxd

Yes

Yes

.tiff, .csv

Neural cells represented as a set of temporal activity traces and spatial footprints. A Cell Set is generated from a Microscope Movie

Event Set

.isxd

Yes

Yes

.csv

Neural events (e.g., calcium events) represented as a set of discrete signal traces. An Event Set is generated from a Cell Set

Vessel Set

.isxd

Yes

Yes

.tiff, .csv

Vessels represented as a set of vessel diameter or red blood cell (rbc) velocity traces. A Vessel Set is generated from a blood flow Microscope Movie

GPIO

.gpio, .isxd

Yes

No

.isxd, .csv

General purpose input/output signals recorded from an acquisition device

IMU

.imu

Yes

No

.isxd, .csv

Inertial measurement unit (accelerometer, magnetometer, orientation​) recorded from an acquisition device

Compressed Microscope Movie

.isxc

No

No

N/A

Compressed recording acquired from a microscope. A Compressed Microscope Movie is decompressed into a Microscope Movie

+
+
+

Next Steps

+

To learn more about how to use the isx package, refer to the Examples guide and the API Reference.

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/py-modindex.html b/py-modindex.html new file mode 100644 index 0000000..989debb --- /dev/null +++ b/py-modindex.html @@ -0,0 +1,131 @@ + + + + + + Python Module Index — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • Python Module Index
    • +
  • +
    • +
+
+
+
+
+ + +

Python Module Index

+ +
+ i +
+ + + + + + + +
 
+ i
+ isx +
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/reference.html b/reference.html new file mode 100644 index 0000000..976da6d --- /dev/null +++ b/reference.html @@ -0,0 +1,2381 @@ + + + + + + + API Reference — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

API Reference

+
+

Warning

+

All hidden modules, classes, functions and members (i.e. those starting with _) +are hidden because they are not part of the public API and their behavior +may change in future versions. +We recommend you do not use them and will not provide support for them. +This includes the _internal module.

+
+

The Inscopix Python API package.

+
+
+class isx.CellSet
+

A cell set contains the image and trace data associated with components in +a movie, such as cells or regions of interest.

+

It is always backed by a file in the native .isxd format.

+
+

Examples

+

Read an existing cell set from a file and get the image and trace data of +the first cell.

+
>>> cell_set = isx.CellSet.read('recording_20160613_105808-PP-PP-BP-MC-DFF-PCA-ICA.isxd')
+>>> image_0 = cell_set.get_cell_image_data(0)
+>>> trace_0 = cell_set.get_cell_trace_data(0)
+
+
+

Write a new cell set to a file with the same timing and spacing as an +existing movie, with 3 random cell images and traces.

+
>>> movie = isx.Movie.read('recording_20160613_105808-PP-PP.isxd')
+>>> cell_set = isx.CellSet.write('cell_set.isxd', movie.timing, movie.spacing)
+>>> for i in range(3):
+>>>     image = numpy.random.random(cell_set.spacing.num_pixels).astype(numpy.float32)
+>>>     trace = numpy.random.random(cell_set.timing.num_samples).astype(numpy.float32)
+>>>     cell_set.set_cell_data(i, image, trace, 'C{}'.format(i))
+>>> cell_set.flush()
+
+
+
+
+

Attributes

+
+
file_pathstr

The path of the file that stores this.

+
+
mode{‘r’, ‘w’}

The mode the file was opened with.

+
+
timingisx.Timing

The timing of the samples in each cell trace.

+
+
spacingisx.Spacing

The spacing of the pixels in each cell image.

+
+
num_cellsint

The number of cells or components.

+
+
+
+
+flush()
+

Flush all meta-data and cell data to the file.

+

This should be called after setting all cell data of a cell set opened with isx.CellSet.write().

+
+ +
+
+get_acquisition_info()
+

Get information about acquisition that may be stored in some files, +such as nVista 3 movies and data derived from those.

+
+

Returns

+
+
dict

A dictionary likely parsed from JSON that maps from string keys to variant values.

+
+
+
+
+ +
+
+get_cell_image_data(index)
+

Get the image data associated with a cell.

+
+

Arguments

+
+
indexint >= 0

The index of a cell.

+
+
+
+
+

Returns

+
+
numpy.ndarray

The image data in a 2D array.

+
+
+
+
+ +
+
+get_cell_name(index)
+
+

Arguments

+
+
indexint >= 0

The index of a cell.

+
+
+
+
+

Returns

+
+
str

The name of the indexed cell.

+
+
+
+
+ +
+
+get_cell_status(index)
+
+

Arguments

+
+
indexint >= 0

The index of a cell.

+
+
+
+
+

Returns

+
+
{‘accepted’, ‘undecided’, ‘rejected’}

The status of the indexed cell as a string.

+
+
+
+
+ +
+
+get_cell_trace_data(index)
+

Get the trace data associated with a cell.

+
+

Arguments

+
+
indexint >= 0

The index of a cell.

+
+
+
+
+

Returns

+
+
numpy.ndarray

The trace data in a 1D array.

+
+
+
+
+ +
+
+classmethod read(file_path, read_only=True)
+

Open an existing cell set from a file for reading.

+

This is a light weight operation that simply reads the meta-data from the cell set, +and does not read any image or trace data.

+
+

Arguments

+
+
file_pathstr

The path of the file to read.

+
+
read_onlybool

If true, only allow meta-data and data to be read, otherwise allow some meta-data +to be written (e.g. cell status).

+
+
+
+
+

Returns

+
+
isx.CellSet

The cell set that was read. Meta-data is immediately available. +Image and trace data must be read using isx.CellSet.get_cell_image_data() +and isx.CellSet.get_cell_trace_data() respectively.

+
+
+
+
+ +
+
+set_cell_data(index, image, trace, name)
+

Set the image and trace data of a cell.

+

Cells must be set in increasing order, otherwise this will error.

+
+

Arguments

+
+
indexint >= 0

The index of a cell.

+
+
imagenumpy.ndarray

The image data in a 2D array.

+
+
tracenumpy.ndarray

The trace data in a 1D array.

+
+
namestr

The name of the cell.

+
+
+
+
+ +
+
+set_cell_status(index, status)
+

Set the status of cell. This will also flush the file.

+
+

Warning

+

As this flushes the file, only use this after all cells have been +written using isx.CellSet.set_cell_data().

+
+
+

Arguments

+
+
indexint >= 0

The index of a cell.

+
+
status{‘accepted’, ‘undecided’, ‘rejected’}

The desired status of the indexed cell.

+
+
+
+
+ +
+
+classmethod write(file_path, timing, spacing)
+

Open a new cell set to a file for writing.

+

This is a light weight operation. It does not write any image or trace data immediately.

+
+

Arguments

+
+
file_pathstr

The path of the file to write. If it already exists, this will error.

+
+
timingisx.Timing

The timing of the cell set to write. Typically this comes from the movie this +is derived from.

+
+
spacingisx.Spacing

The spacing of the movie to write. Typically this comes from the movie this is +derived from.

+
+
+
+
+

Returns

+
+
isx.CellSet

The empty cell set that was written. +Image and trace data must be written with isx.CellSet.set_cell_data().

+
+
+
+
+ +
+
+ +
+
+class isx.Duration
+

A duration of time.

+
+

Examples

+

Make a period of 50 milliseconds

+
>>> period = isx.Duration.from_msecs(50)
+
+
+
+
+

Attributes

+
+
secs_floatfloat

The duration in seconds as a floating point number.

+
+
+
+
+classmethod from_msecs(msecs)
+

Make a duration from a number of milliseconds.

+
+ +
+
+classmethod from_secs(secs)
+

Make a duration from a number of seconds.

+
+ +
+
+classmethod from_usecs(usecs)
+

Make a duration from a number of microseconds.

+
+ +
+
+to_msecs()
+

Convert to an integer number of whole milliseconds.

+
+ +
+
+to_secs()
+

Convert to an integer number of whole seconds.

+
+ +
+
+to_usecs()
+

Convert to an integer number of whole microseconds.

+
+ +
+
+ +
+
+class isx.Enum(value)
+

Generic enumeration.

+

Derive from this class to define new enumerations.

+
+ +
+
+class isx.EventSet
+

An event set contains the event data of a number of components or cells.

+

It is typically derived from a cell set after applying an event detection +algorithm. +Each event of a cell is comprised of a time stamp offset and a value or amplitude.

+
+

Examples

+

Read an existing event set from a file and get the event data associated with the +first cell.

+
>>> event_set = isx.EventSet.read('recording_20160613_105808-PP-PP-BP-MC-DFF-PCA-ICA-ED.isxd')
+>>> [offsets, amplitudes] = event_set.get_cell_data(0)
+
+
+

Write a new event set to a file by applying a threshold to the traces of an existing +cell set.

+
>>> cell_set = isx.CellSet.read('recording_20160613_105808-PP-PP-BP-MC-DFF-PCA-ICA.isxd')
+>>> cell_names = ['C{}'.format(c) for c in range(cell_set.num_cells)]
+>>> event_set = isx.EventSet.write('recording_20160613_105808-PP-PP-BP-MC-DFF-PCA-ICA-custom_ED.isxd', cell_set.timing, cell_names)
+>>> offsets = numpy.array([x.to_usecs() for x in cell_set.timing.get_offsets_since_start()], numpy.uint64)
+>>> for c in range(cell_set.num_cells):
+>>>     trace = cell_set.get_cell_trace_data(c)
+>>>     above_thresh = trace > 500
+>>>     event_set.set_cell_data(c, offsets[above_thresh], trace[above_thresh])
+>>> event_set.flush()
+
+
+
+
+

Attributes

+
+
file_pathstr

The path of the file that stores this.

+
+
mode{‘r’, ‘w’}

The mode the file was opened with.

+
+
timingisx.Timing

The timing of the samples in each event trace.

+
+
num_cellsint

The number of cells or components.

+
+
cell_dictdict

Dictionary mapping cell names to cell indices

+
+
+
+
+flush()
+

Flush all meta-data and cell data to the file.

+

This should be called after setting all cell data of an event set opened with isx.EventSet.write().

+
+ +
+
+get_acquisition_info()
+

Get information about acquisition that may be stored in some files, +such as nVista 3 movies and data derived from those.

+
+

Returns

+
+
dict

A dictionary likely parsed from JSON that maps from string keys to variant values.

+
+
+
+
+ +
+
+get_cell_data(index)
+

Get the event data associated with a cell.

+
+

Arguments

+
+
indexint >= 0

The index of a cell.

+
+
+
+
+

Returns

+
+
offsetsnumpy.ndarray

The 1D array of time stamps offsets from the start in microseconds.

+
+
amplitudesnumpy.ndarray

The 1D array of event amplitudes.

+
+
+
+
+ +
+
+get_cell_index(name)
+
+

Arguments

+
+
nameint >= 0

The name of a cell.

+
+
+
+
+

Returns

+
+
str

The index of the named cell.

+
+
+
+
+ +
+
+get_cell_name(index)
+
+

Arguments

+
+
indexint >= 0

The index of a cell.

+
+
+
+
+

Returns

+
+
str

The name of the indexed cell.

+
+
+
+
+ +
+
+classmethod read(file_path)
+

Open an existing event set from a file for reading.

+

This is a light weight operation that simply reads the meta-data from the event set, +and does not read any event data.

+
+

Arguments

+
+
file_pathstr

The path of the file to read.

+
+
+
+
+

Returns

+
+
isx.EventSet

The event set that was read. Meta-data is immediately available. +Event data must be read using isx.EventSet.get_cell_data().

+
+
+
+
+ +
+
+set_cell_data(index, offsets, amplitudes)
+

Set the event data of a cell.

+
+

Arguments

+
+
indexint >= 0

The index of a cell.

+
+
offsetsnumpy.ndarray

The 1D array of time stamps offsets from the start in microseconds.

+
+
amplitudesnumpy.ndarray

The 1D array of event amplitudes.

+
+
+
+
+ +
+
+classmethod write(file_path, timing, cell_names)
+

Open a new event set to a file for writing.

+

This is a light weight operation. It does not write any event data immediately.

+
+

Arguments

+
+
file_pathstr

The path of the file to write. If it already exists, this will error.

+
+
timingisx.Timing

The timing of the event set to write. Typically this comes from the cell set this +is derived from.

+
+
cell_nameslist<str>

The names of the cells that will be written. Typically these come from the cell set +this is derived from.

+
+
+
+
+

Returns

+
+
isx.EventSet

The empty event set that was written. +Image and trace data must be written with isx.EventSet.set_cell_data().

+
+
+
+
+ +
+
+ +
+
+class isx.Fraction(numerator=0, denominator=None, *, _normalize=True)
+

This class implements rational numbers.

+

In the two-argument form of the constructor, Fraction(8, 6) will +produce a rational number equivalent to 4/3. Both arguments must +be Rational. The numerator defaults to 0 and the denominator +defaults to 1 so that Fraction(3) == 3 and Fraction() == 0.

+

Fractions can also be constructed from:

+
+
    +

  • numeric strings similar to those accepted by the +float constructor (for example, ‘-2.3’ or ‘1e10’)

    • +

  • strings of the form ‘123/456’

    • +

  • float and Decimal instances

    • +

  • other Rational instances (including integers)

    • +
+
+
+
+as_integer_ratio()
+

Return the integer ratio as a tuple.

+

Return a tuple of two integers, whose ratio is equal to the +Fraction and with a positive denominator.

+
+ +
+
+classmethod from_decimal(dec)
+

Converts a finite Decimal instance to a rational number, exactly.

+
+ +
+
+classmethod from_float(f)
+

Converts a finite float to a rational number, exactly.

+

Beware that Fraction.from_float(0.3) != Fraction(3, 10).

+
+ +
+
+limit_denominator(max_denominator=1000000)
+

Closest Fraction to self with denominator at most max_denominator.

+
>>> Fraction('3.141592653589793').limit_denominator(10)
+Fraction(22, 7)
+>>> Fraction('3.141592653589793').limit_denominator(100)
+Fraction(311, 99)
+>>> Fraction(4321, 8765).limit_denominator(10000)
+Fraction(4321, 8765)
+
+
+
+ +
+ +
+
+class isx.GpioSet
+

A GPIO set contains the data recorded across a number of channels.

+

Each data point is comprised of a time stamp offset and a value or amplitude.

+
+

Examples

+

Read an existing gpio set from a file and get the data associated with the first channel.

+
>>> gpio_set = isx.GpioSet.read('2020-05-20-10-33-22_video.gpio')
+>>> [offsets, amplitudes] = gpio_set.get_channel_data(0)
+
+
+
+
+

Attributes

+
+
file_pathstr

The path of the file that stores this.

+
+
mode{‘r’, ‘w’}

The mode the file was opened with.

+
+
timingisx.Timing

The timing of the samples.

+
+
num_channelsint

The number of channels.

+
+
channel_dictdict

Dictionary mapping channel names to channel indices

+
+
+
+
+get_acquisition_info()
+

Get information about acquisition that may be stored in some files, +such as nVista 3 movies and data derived from those.

+
+

Returns

+
+
dict

A dictionary likely parsed from JSON that maps from string keys to variant values.

+
+
+
+
+ +
+
+get_channel_data(index)
+

Get the data associated with a channel.

+
+

Arguments

+
+
indexint >= 0

The index of a channel.

+
+
+
+
+

Returns

+
+
offsetsnumpy.ndarray

The 1D array of time stamps offsets from the start in microseconds.

+
+
amplitudesnumpy.ndarray

The 1D array of amplitudes.

+
+
+
+
+ +
+
+get_channel_index(name)
+
+

Arguments

+
+
nameint >= 0

The name of a channel.

+
+
+
+
+

Returns

+
+
str

The index of the named channel.

+
+
+
+
+ +
+
+get_channel_name(index)
+
+

Arguments

+
+
indexint >= 0

The index of a channel.

+
+
+
+
+

Returns

+
+
str

The name of the indexed channel.

+
+
+
+
+ +
+
+classmethod read(file_path)
+

Open an existing GPIO set from a file for reading.

+

This is a light weight operation that simply reads the meta-data from the GPIO set, +and does not read any GPIO data.

+
+

Arguments

+
+
file_pathstr

The path of the file to read.

+
+
+
+
+

Returns

+
+
isx.GpioSet

The GPIO set that was read. Meta-data is immediately available. +GPIO data must be read using isx.GpioSet.get_channel_data().

+
+
+
+
+ +
+
+ +
+
+class isx.Image
+

An image is effectively a movie with one frame and no timing.

+

It is always backed by a file, which can be read or written using this class. +See importMovie for details on what formats are supported for read. +Only the native .isxd format is supported for write.

+
+

Examples

+

Read an existing image and get its data.

+
>>> image = isx.Image.read('recording_20160613_105808-PP-PP-BP-Mean Image.isxd')
+>>> image_data = image.get_data()
+
+
+

Calculate the minimum image from an existing movie and write it.

+
>>> movie = isx.Movie.read('recording_20160613_105808-PP-PP.isxd')
+>>> min_image = 4095 * numpy.ones(movie.spacing.num_pixels, dtype=movie.data_type)
+>>> for i in range(movie.timing.num_samples):
+>>>     min_image = numpy.minimum(min_image, movie.get_frame_data(i))
+>>> isx.Image.write('recording_20160613_105808-PP-PP-min.isxd', movie.spacing, movie.data_type, min_image)
+
+
+
+
+

Attributes

+
+
file_pathstr

The path of the file that stores this.

+
+
mode{‘r’, ‘w’}

The mode the file was opened with.

+
+
spacingisx.Spacing

The spacing of the pixels in the image.

+
+
data_type{numpy.uint16, numpy.float32}

The data type of each pixel.

+
+
+
+
+get_data()
+

Get the data stored in the image.

+
+

Returns

+
+
numpy.ndarray

The image data.

+
+
+
+
+ +
+
+classmethod read(file_path)
+

Read an existing image from a file.

+
+

Arguments

+
+
file_pathstr

The path of the image file to read.

+
+
+
+
+

Returns

+
+
isx.Image

The image that was read.

+
+
+
+
+ +
+
+classmethod write(file_path, spacing, data_type, data)
+

Write an image to a file.

+
+

Arguments

+
+
file_pathstr

The path of the file to write. If it already exists, this will error.

+
+
spacingisx.Spacing

The spacing of the image to write.

+
+
data_type{numpy.uint16, numpy.float32}

The data type of each pixel.

+
+
datanumpy.array

The 2D array of data to write.

+
+
+
+
+

Returns

+
+
isx.Image

The image that was written.

+
+
+
+
+ +
+
+ +
+
+class isx.Movie
+

A movie contains a number of frames with timing and spacing information.

+

It is always backed by a file, which can be read or written using this class. +See importMovie for details on what formats are supported for read. +Only the native .isxd format is supported for write.

+
+

Examples

+

Read an existing movie and get its first frame as a numpy array.

+
>>> movie = isx.Movie.read('recording_20160613_105808-PP-PP.isxd')
+>>> frame_data = movie.get_frame_data(0)
+
+
+

Write a 400x300 movie with 200 random frames of float32 values.

+
>>> timing = isx.Timing(num_samples=200)
+>>> spacing = isx.Spacing(num_pixels=(300, 400))
+>>> movie = isx.Movie.write('movie-400x300x200.isxd', timing, spacing, numpy.float32)
+>>> for i in range(timing.num_samples):
+>>>     movie.set_frame_data(i, numpy.random.random(spacing.num_pixels).astype(numpy.float32))
+>>> movie.flush()
+
+
+
+
+

Attributes

+
+
file_pathstr

The path of the file that stores this.

+
+
mode{‘r’, ‘w’}

The mode the file was opened with.

+
+
timingisx.Timing

The timing of the frames.

+
+
spacingisx.Spacing

The spacing of the pixels in each frame.

+
+
data_type{numpy.uint16, numpy.float32}

The data type of each pixel.

+
+
+
+
+flush()
+

Flush all meta-data and frame data to the file.

+

This should be called after setting all frames of a movie opened with isx.Movie.write().

+
+ +
+
+get_acquisition_info()
+

Get information about acquisition that may be stored in some files, +such as nVista 3 movies and data derived from those.

+
+

Returns

+
+
dict

A dictionary likely parsed from JSON that maps from string keys to variant values.

+
+
+
+
+ +
+
+get_frame_data(index)
+

Get a frame from the movie by index.

+
+

Arguments

+
+
indexint >= 0

The index of the frame. If this is out of range, this should error.

+
+
+
+
+

Returns

+
+
numpy.ndarray

The retrieved frame data.

+
+
+
+
+ +
+
+get_frame_timestamp(index)
+

Get a frame timestamp from the movie by index.

+

The timestamps are in units of microseconds. +This is a TSC (time stamp counter) value which is saved during acquisition. +These values come from a hardware counter on a particular acquisition box. +As a result, they can only be used to compare to other values that originate from the same hardware counter (e.g., paired recordings).

+

To get timestamps relative to the start of the movie, +simply subtract each timestamp with the timestamp of the first frame in the movie. +To get timestamps relative to Unix epoch time, add the timestamps computed relative +to the start of the movie with the Unix epoch start timestamp of the movie, accessible through the timing member of this class. +Alternatively, the timestamps of a movie can be exported relative to the start of the movie, +or relative to the Unix epoch time, using the function isx.export_movie_timestamps_to_csv.

+
+

Arguments

+
+
indexint >= 0

The index of the frame. If this is out of range, this should error.

+
+
+
+
+

Returns

+
+
int

The retreived frame timestamp. +If the movie has no frame timestamps, the function will throw an error,

+
+
+
+
+ +
+
+classmethod read(file_path)
+

Open an existing movie from a file for reading.

+

This is a light weight operation that simply reads the meta-data from the movie, +and does not read any frame data.

+
+

Arguments

+
+
file_pathstr

The path of the file to read.

+
+
+
+
+

Returns

+
+
isx.Movie

The movie that was read. Meta-data is immediately available. +Frames must be read using isx.Movie.get_frame().

+
+
+
+
+ +
+
+set_frame_data(index, frame)
+

Set frame data in a writable movie.

+

Frames must be set in increasing order, otherwise this will error.

+
+

Arguments

+
+
indexint >= 0

The index of the frame.

+
+
framenumpy.ndarray

The frame data.

+
+
+
+
+ +
+
+classmethod write(file_path, timing, spacing, data_type)
+

Open a new movie to a file for writing.

+

This is a light weight operation. It does not write any frame data immediately.

+
+

Arguments

+
+
file_pathstr

The path of the file to write. If it already exists, this will error.

+
+
timingisx.Timing

The timing of the movie to write.

+
+
spacingisx.Spacing

The spacing of the movie to write.

+
+
data_type{numpy.uint16, numpy.float32}

The data type of each pixel.

+
+
+
+
+

Returns

+
+
isx.Movie

The empty movie that was written. +Frame data must be written with isx.Movie.set_frame_data().

+
+
+
+
+ +
+
+ +
+
+class isx.Spacing(num_pixels=(0, 0))
+

The spacing associated with a set of pixels.

+
+

Examples

+

Make spacing for a 1440x1080 image.

+
>>> spacing = isx.Spacing(num_pixels=(1080, 1440))
+
+
+
+
+

Attributes

+
+
num_pixels2-tuple<int>

The number of pixels as (num_rows, num_cols).

+
+
+
+
+ +
+
+class isx.Time
+

A time stamp that defines a calendar date and wall time.

+
+
+to_datetime()
+
+

Returns

+
+
datetime.datetime

The nearest Python datetime.

+
+
+
+
+ +
+ +
+
+class isx.Timing(num_samples=0, period=<isx.core.Duration object>, start=<isx.core.Time object>, dropped=[], cropped=[], blank=[])
+

The timing associated with a set of samples, such as the frames of a movie or the +values of a trace.

+

Some samples are described as invalid, meaning that the sample is missing. +These include dropped samples, which could arise due to an error at acquisition time, +and cropped samples, which are likely due to processing.

+
+

Examples

+

Make timing for 9 samples, every 10 milliseconds.

+
>>> timing = isx.Timing(num_samples=9, period=isx.Duration.from_msecs(10))
+
+
+
+
+

Attributes

+
+
num_samplesint >= 0

The number of samples, including invalid (dropped, cropped, or blank) ones.

+
+
periodisx.Duration

The period or duration of one sample.

+
+
startisx.Time

The time stamp associated with the start of the first sample.

+
+
droppedlist<int>

The indices of the dropped samples.

+
+
croppedlist<2-tuple>

The index ranges of the cropped samples. +Each element specifies the inclusive lower and upper bounds of a range +of indices.

+
+
blanklist<int>

The indices of the blank samples.

+
+
+
+
+get_offsets_since_start()
+

Get the offsets from the start of the timing.

+
+

Returns

+
+
list<isx.Duration>

Each element is the offset from the start to a sample.

+
+
+
+
+ +
+
+get_valid_samples()
+
+

Returns

+
+
numpy.ndarray

The valid sample indices.

+
+
+
+
+ +
+
+get_valid_samples_mask()
+

Get a 1D array mask indicating whether each sample is valid.

+
+

Returns

+
+
numpy.ndarray

Each element indicates whether the corresponding sample is valid.

+
+
+
+
+ +
+
+ +
+
+class isx.VesselSet
+

A vessel set contains the image, line and trace data associated with components in +a movie, such as vessels or regions of interest.

+

It is always backed by a file in the native .isxd format.

+

A vessel set can represent two types of data: vessel diameter and rbc velocity. +Depending on the vessel type, different information will be stored to disk.

+

Note: Since blood flow algorithms apply a sliding window over input movies, +the timing of a vessel trace is different from the timing of its input movie. +Each frame of a vessel trace represents a measurement for a particular window sampled from its input movie. +Relative to the input movie, each frame maps to the start of the corresponding window sampled. +The duration of a frame is equal to the time increment of the sliding window.

+

The following examples will demonstrate the types of data accessible for both types of vessel sets.

+
+

Examples

+

Vessel Diameter +Read an existing vessel set from a file and get the image, line and diameter trace data of +the first vessel.

+
>>> vessel_set = isx.VesselSet.read('bloodflow_movie_10s-VD.isxd')
+>>> image_0 = vessel_set.get_vessel_image_data(0)
+>>> line_0 = vessel_set.get_vessel_line_data(0)
+>>> trace_0 = vessel_set.get_vessel_trace_data(0)
+>>> center_trace_0 = vessel_set.get_vessel_center_trace_data(0)
+
+
+

Write a new vessel set to a file with the same timing and spacing as an +existing movie, with 3 random vessel images, lines and diameter traces.

+
>>> movie = isx.Movie.read('recording_20160613_105808-PP-PP.isxd')
+>>> vessel_set = isx.VesselSet.write('vessel_set.isxd', movie.timing, movie.spacing, 'vessel diameter')
+>>> for i in range(3):
+>>>     image = numpy.random.random(vessel_set.spacing.num_pixels).astype(numpy.float32)
+>>>     lines = numpy.random.randint(0, min(spacing.num_pixels), (num_vessels, 2, 2))
+>>>     trace = numpy.random.random(vessel_set.timing.num_samples).astype(numpy.float32)
+>>>     center_trace = numpy.random.random(vessel_set.timing.num_samples).astype(numpy.float32)
+>>>     vessel_set.set_vessel_diameter_data(i, image, lines, trace, center_trace, 'V{}'.format(i))
+>>> vessel_set.flush()
+
+
+

RBC Velocity +Read an existing vessel set from a file and get the image, line and rbc velocity trace data of +the first vessel.

+
>>> vessel_set = isx.VesselSet.read('bloodflow_movie_10s-RBCV.isxd')
+>>> image_0 = vessel_set.get_vessel_image_data(0)
+>>> line_0 = vessel_set.get_vessel_line_data(0)
+>>> trace_0 = vessel_set.get_vessel_trace_data(0)
+>>> direction_trace_0 = vessel_set.get_vessel_direction_trace_data(0)
+>>> corr_0 = vessel_set.get_vessel_correlations_data(0, 0) # look at first frame of correlation data for the first vessel
+
+
+

Write a new vessel set to a file with the same timing and spacing as an +existing movie, with 3 random vessel images, lines and rbc velocity traces.

+
>>> movie = isx.Movie.read('recording_20160613_105808-PP-PP.isxd')
+>>> vessel_set = isx.VesselSet.write('vessel_set.isxd', movie.timing, movie.spacing, 'rbc velocity')
+>>> for i in range(3):
+>>>     image = numpy.random.random(vessel_set.spacing.num_pixels).astype(numpy.float32)
+>>>     lines = numpy.random.randint(0, min(spacing.num_pixels), (num_vessels, 2, 2))
+>>>     trace = numpy.random.random(vessel_set.timing.num_samples).astype(numpy.float32)
+>>>     direction_trace = numpy.random.random(vessel_set.timing.num_samples).astype(numpy.float32)
+>>>     correlation_size = np.random.randint(2, 5, size=(2,))
+>>>     correlations_trace = numpy.random.random([vessel_set.timing.num_samples, 3, correlation_size[0], correlation_size[1]]).astype(numpy.float32)
+>>>     vessel_set.set_rbc_velocity_data(i, image, lines, trace, direction_trace, correlations_trace, 'V{}'.format(i))
+>>> vessel_set.flush()
+
+
+
+
+

Attributes

+
+
file_pathstr

The path of the file that stores this.

+
+
mode{‘r’, ‘w’}

The mode the file was opened with.

+
+
timingisx.Timing

The timing of the samples in each vessel trace.

+
+
spacingisx.Spacing

The spacing of the pixels in each vessel image.

+
+
num_vesselsint

The number of vessels or components.

+
+
+
+
+class VesselSetType(value)
+

An enumeration.

+
+ +
+
+flush()
+

Flush all meta-data and vessel data to the file.

+

This should be called after setting all vessel data of a vessel set opened with isx.VesselSet.write().

+
+ +
+
+get_acquisition_info()
+

Get information about acquisition that may be stored in some files, +such as nVista 3 movies and data derived from those.

+
+

Returns

+
+
dict

A dictionary likely parsed from JSON that maps from string keys to variant values.

+
+
+
+
+ +
+
+get_vessel_center_trace_data(index)
+

Get the center trace data associated with a vessel. +This represents an index on the user drawn line where the center of the diamter was estimated to be.

+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
+
+
+

Returns

+
+
numpy.ndarray

The center trace data in a 1D array. +If no center traces are stored in the file, the function will throw an error

+
+
+
+
+ +
+
+get_vessel_correlations_data(index, frame)
+

Get the correlation trace data associated with a vessel at a certain frame.

+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
frameint >= 0

The frame index of the time-series trace.

+
+
+
+
+

Returns

+
+
numpy.ndarray

The correlations data in a 3D array of size (3, width, height) +Each slice of the ndarray is a correlation heatmap for a particular temporal offset +The mapping of temporal offsets is (slice 0 -> t = -1, slice 1 -> t = 0, slice 2 = t = 1) +If no correlations are stored in the file, the function will throw an error

+
+
+
+
+ +
+
+get_vessel_direction_trace_data(index)
+

Get the direction trace data associated with a vessel +This is the direction component of each velocity measurement reported in degrees relative to positive x-axis.

+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
+
+
+

Returns

+
+
numpy.ndarray

The direction trace data in a 1D array. +If no direction traces are stored in the file, the function will throw an error

+
+
+
+
+ +
+
+get_vessel_image_data(index)
+

Get the image data associated with a vessel.

+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
+
+
+

Returns

+
+
numpy.ndarray

The image data in a 2D array.

+
+
+
+
+ +
+
+get_vessel_line_data(index)
+

Get the line data associated with a vessel.

+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
+
+
+

Returns

+
+
numpy.ndarray

The line data in a 2D array.

+
+
+
+
+ +
+
+get_vessel_name(index)
+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
+
+
+

Returns

+
+
str

The name of the indexed vessel.

+
+
+
+
+ +
+
+get_vessel_set_type()
+

Get the type of the vessel set.

+
+

Returns

+
+
VesselSetType Enum

An enum representation of the different vessel set types. +either VesselSetType.VESSEL_DIAMETER or VesselSetType.RBC_VELOCITY

+
+
+
+
+ +
+
+get_vessel_status(index)
+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
+
+
+

Returns

+
+
{‘accepted’, ‘undecided’, ‘rejected’}

The status of the indexed vessel as a string.

+
+
+
+
+ +
+
+get_vessel_trace_data(index)
+

Get the trace data associated with a vessel.

+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
+
+
+

Returns

+
+
numpy.ndarray

The trace data in a 1D array.

+
+
+
+
+ +
+
+has_correlation_heatmaps()
+

If true, cross-correlation heatmaps for rbc velocity measurements are stored in this file.

+
+

Returns

+
+
bool

Flag indicating whether heatmaps were saved.

+
+
+
+
+ +
+
+classmethod read(file_path, read_only=True)
+

Open an existing vessel set from a file for reading.

+

This is a light weight operation that simply reads the meta-data from the vessel set, +and does not read any image or trace data.

+
+

Arguments

+
+
file_pathstr

The path of the file to read.

+
+
read_onlybool

If true, only allow meta-data and data to be read, otherwise allow some meta-data +to be written (e.g. vessel status).

+
+
+
+
+

Returns

+
+
isx.VesselSet

The vessel set that was read. Meta-data is immediately available. +Image and trace data must be read using isx.VesselSet.get_vessel_image_data() +and isx.VesselSet.get_vessel_trace_data() respectively.

+
+
+
+
+ +
+
+set_rbc_velocity_data(index, image, line, trace, direction_trace, correlations_trace=None, name=None)
+

Set the image, line and rbc velocity trace data of a vessel.

+

Vessels must be set in increasing order, otherwise this will error.

+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
imagenumpy.ndarray

The image data in a 2D array.

+
+
linenumpy.ndarray

The line endpoint data in a 2D array.

+
+
tracenumpy.ndarray

The trace data in a 1D array.

+
+
direction_tracenumpy.ndarray

The direction trace data in a 1D array.

+
+
correlations_tracenumpy.ndarray

The correlations trace data in a 4D array T x 3 x W x H +Where T is the number of time samples +W is the width of the correlation heatmap +H is the width of the correlation heatmap +There are three heatmaps for each time sample representing the three temporal offsets (-1, 0, 1)

+
+
namestr

The name of the vessel.

+
+
+
+
+ +
+
+set_vessel_diameter_data(index, image, line, trace, center_trace, name=None)
+

Set the image, line and diameter trace data of a vessel

+

Vessels must be set in increasing order, otherwise this will error.

+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
imagenumpy.ndarray

The image data in a 2D array.

+
+
linenumpy.ndarray

The line endpoint data in a 2D array.

+
+
tracenumpy.ndarray

The trace data in a 1D array.

+
+
center_tracenumpy.ndarray

The center trace data in a 1D array.

+
+
namestr

The name of the vessel.

+
+
+
+
+ +
+
+set_vessel_status(index, status)
+

Set the status of vessel. This will also flush the file.

+
+

Warning

+

As this flushes the file, only use this after all vessels have been +written using isx.VesselSet.set_vessel_data().

+
+
+

Arguments

+
+
indexint >= 0

The index of a vessel.

+
+
status{‘accepted’, ‘undecided’, ‘rejected’}

The desired status of the indexed vessel.

+
+
+
+
+ +
+
+classmethod write(file_path, timing, spacing, vessel_type)
+

Open a new vessel set to a file for writing.

+

This is a light weight operation. It does not write any image or trace data immediately.

+
+

Arguments

+
+
file_pathstr

The path of the file to write. If it already exists, this will error.

+
+
timingisx.Timing

The timing of the vessel set to write. Typically this comes from the movie this +is derived from.

+
+
spacingisx.Spacing

The spacing of the movie to write. Typically this comes from the movie this is +derived from.

+
+
vessel_typestr

The type of metric to store in the vessel set. Either ‘vessel diameter’ or ‘rbc velocity’.

+
+
+
+
+

Returns

+
+
isx.VesselSet

The empty vessel set that was written. +Image and trace data must be written with isx.VesselSet.set_vessel_data().

+
+
+
+
+ +
+
+ +
+
+isx.align_start_times(input_ref_file, input_align_files)
+

Align the epoch start times of files originating from the same paired and synchronized start-stop recording session. +The epoch start time stored in the input align files are modified in-place +so that they are aligned relative to the epoch start time of the input timing reference file

+
+
For each input align file, the epoch start time is recomputed using the following formula:

align_epoch_start_ms = ref_epoch_start_ms + ((align_first_tsc_us - ref_first_tsc_us) / 1e3)

+
+
In the event that the first sample of an input align file is dropped, the tsc value of the first sample is inferred using the following formula:

align_first_tsc_us = align_first_valid_tsc_us - (align_first_valid_idx * align_sample_period_us)

+
+
+
+

Arguments

+
+
+
input_ref_filestr

The path of the file to use as the timing reference to align with the other input files. +This can be either a .gpio file, .isxd movie, or .isxb movie, otherwise the function will throw an error. +If the timing reference is a movie, the movie must contain frame timestamps, otherwise this function will throw an error.

+
+
input_align_fileslist<str>

The path of the files to align to the epoch start time of the input timing reference file. +These files can either be an .isxd movie or .isxb movie, otherwise the function will throw an error. +The movies must contain frame timestamps, otherwise this function will throw an error.

+
+
+
+
+
+ +
+
+isx.convert_type_numpy_array(array, dtype=<class 'numpy.uint16'>, keep_0_to_1=False)
+

Convert a numpy array to a different data type by normalizing and mapping.

+
+ +
+
+isx.create_cell_map(isxd_cellset_file, selected_cell_statuses=['accepted'], cell_thresh=0.3, binary=False, rgb=None, output_isxd_cell_map_file=None, output_tiff_cell_map_file=None)
+

Generate cell map from an .isxd cellset file, saving the image as isxd and tiff.

+
+

Arguments

+
+
isxd_cellset_filestr

Path to an .isxd cellset file.

+
+
selected_cell_statuseslist<str>

a list of cell statuses for decision criteria to keep cell footprints. +Possible list values are ‘accepted’, ‘undecided’, ‘rejected’.

+
+
cell_threshfloat [0, 1]

Pixels with values lower than cell_thresh will be set to 0.

+
+
binaryBool

If true, pixels with values above cell_thresh are set to 1. (Pixels with values +below cell_thresh are set to 0.)

+
+
rgbone of “red”, “blue”, or “green”

Color for the cell map.

+
+
output_isxd_cell_map_filestr

Path to the output isxd cell map image. If not given, will not be generated.

+
+
output_tiff_cell_map_filestr

Path to the output tiff cell map image. If not given, will not be generated.

+
+
+
+
+ +
+
+isx.export_aligned_timestamps(input_ref_file, input_align_files, input_ref_name, input_align_names, output_csv_file, time_ref='start')
+

Export timestamps from files which originate from the same paired and synced start-stop recording session to a .csv file. +Timestamps are aligned to a single start time which is defined as the start time of the specified timing reference file.

+
+

Arguments

+
+
input_ref_filestr

The path of the file to use as the timing reference to align with the other input files. +Timestamps are exported relative to the start time of this file. +This can be either a .gpio file, .isxd movie, or .isxb movie, otherwise the function will throw an error. +If the timing reference is a movie, the movie must contain frame timestamps, otherwise this function will throw an error.

+
+
input_align_fileslist<str>

The path of the files to align to the epoch start time of the input timing reference file. +These files can either be a .gpio file, .isxd movie, or .isxb movie, otherwise the function will throw an error. +The movies must contain frame timestamps, otherwise this function will throw an error.

+
+
input_ref_namestr

The name of the reference data set to use in the output csv.

+
+
input_align_nameslist<str>

The names of the align data sets to use in the output csv.

+
+
output_csv_filestr

The path of the csv file to be written.

+
+
time_ref{‘start’, ‘unix’, ‘tsc’}

The time reference for the CSV time stamps. +If ‘start’ is used, the timestamps represent the seconds since the start of the movie. +If ‘unix’ is used, the timestamps represent the seconds since the Unix epoch. +If ‘tsc’ is used, the timestamps represent the hardware counter value on the acquisition box when each frame was captured.

+
+
+
+
+ +
+
+isx.export_cell_set_to_csv_tiff(input_cell_set_files, output_csv_file, output_tiff_file, time_ref='start', output_props_file='')
+

Export cell sets to a CSV file with trace data and TIFF files with image data.

+

For more details see exportCellsAndStuff.

+

Unlike the desktop application, this will only produce a TIFF cell map image file +and not a PNG file too.

+
+

Arguments

+
+
input_cell_set_fileslist<str>

The file paths of the cell sets to export.

+
+
output_csv_filestr

The path of the CSV file to write.

+
+
output_tiff_filestr

The base name of the TIFF files to write.

+
+
time_ref{‘start’, ‘unix’}

The time reference for the CSV time stamps. +If ‘start’ is used, the time stamps represent the seconds since the start of the cell set. +If ‘unix’ is used, the time stamps represents the second since the Unix epoch.

+
+
output_props_filestr

The path of the properties CSV file to write.

+
+
+
+
+ +
+
+isx.export_ethovision_data_with_isxb_timestamps(input_ethovision_file, input_isxb_file, output_csv_file, input_ref_file=None, time_ref='start')
+
+
Given paths to an Ethovision file and a nVision (.isxb) movie file,

writes a csv file with Ethovision data and a dedicated column, +either isxb Frame Timestamp (s) or isxb Frame Timestamp (us) +depending on the format of the timestamps, +that contains aligned timestamps from the nVision movie.

+
+
It is important to note that internal Inscopix testing has shown that the Ethovision output file

can have a length that is one less than the number of frames in the input movie. When this is true, +the missing data row appears to be at the beginning. +This function applies .isxb timestamps to the Ethovision table while ignoring the first timestamp +to compensate for the length mismatch if the mismatch exists. More recent versions of Ethovision +should prevent this from occuring.

+
+
+
+

Arguments

+
+
input_ethovision_file: str

The path to the Ethovision file (.csv, .xlsx).

+
+
input_isxb_file: str

The path to the nVision (.isxb) movie file.

+
+
output_csv_file: str

The path to the output csv file.

+
+
input_ref_file: str | None

The path to the reference file (.isxd, .gpio, .isxb). +Timestamps from the .isxb file are aligned to the start time of this file. +Generally, this reference is a file from a miniscope recording which was synchronized with this .isxb file. +This argument is required if the time_ref is selected as ‘start’ or ‘unix’. +If the .isxb file is a standalone behaviour recording that is not synchronized to any miniscope file, +simply provide the .isxb file as the reference (if it’s required).

+
+
time_ref{‘start’, ‘unix’, ‘tsc’}

The time reference for the nVision (.isxb) timestamps. +If ‘tsc’ is used, the timestamps represent the hardware counter value in microseconds on the acquisition box when each frame was captured. +If ‘start’ is used, the timestamps represent the seconds since the start of the experiment.

+
+

Note: input_ref_file must be specified if this option is used, otherwise an exception is thrown. +Timestamps are exported relative to the start time of the reference file.

+
+
+
If ‘unix’ is used, the timestamps represent the seconds since the Unix epoch.

Note: input_ref_file must be specified if this option is used, otherwise an exception is thrown. +The input_ref_file ensures that isx.align_start_times has been called +on the .isxb file with the corresponding, synchronized miniscope file.

+
+
+
+
+
+
+ +
+
+isx.export_event_set_to_csv(input_event_set_files, output_csv_file, time_ref='start', output_props_file='', sparse_output=True, write_amplitude=True)
+

Export event sets to a CSV file.

+

For more details see exportCellsAndStuff.

+
+

Arguments

+
+
input_event_set_fileslist<str>

The file paths of the cell sets to export.

+
+
output_csv_filestr

The path of the CSV file to write.

+
+
time_ref{‘start’, ‘unix’}

The time reference for the CSV time stamps. +If ‘start’ is used, the time stamps represent the seconds since the start of the cell set. +If ‘unix’ is used, the time stamps represents the second since the Unix epoch.

+
+
output_props_filestr

The path of the properties CSV file to write.

+
+
sparse_output: bool

If true, output events in sparse format showing all time points, +otherwise, output events in dense format showing only timepoints with events.

+
+
write_amplitude: bool

Only relevant when sparse_output is True. +If true, write amplitudes of each event, +otherwise, writes 1 where events occur and 0 elsewhere.

+
+
+
+
+ +
+
+isx.export_gpio_set_to_csv(input_gpio_set_files, output_csv_file, inter_isxd_file_dir='/tmp', time_ref='start')
+

Export gpio sets to a CSV file.

+

If exporting more than one file, for correct formatting, files should either be all non .imu files or all .imu files.

+

For more details see exportCellsAndStuff.

+
+

Arguments

+
+
input_gpio_set_fileslist<str>

The file paths of the cell sets to export.

+
+
output_csv_filestr

The path of the CSV file to write.

+
+
inter_isxd_file_dirstr

The path of the directory to put intermediate .isxd file +The default path for Mac & Linux is /tmp. The default path for Windows is the directory containing the input gpio file.

+
+
time_ref{‘start’, ‘unix’}

The time reference for the CSV time stamps. +If ‘start’ is used, the time stamps represent the seconds since the start of the cell set. +If ‘unix’ is used, the time stamps represents the second since the Unix epoch.

+
+
+
+
+ +
+
+isx.export_gpio_to_isxd(input_gpio_file, output_isxd_dir)
+

Export GPIO file (.gpio, .raw, .hdf5, .imu) to an Inscopix Data File (.isxd).

+

Output file will have the name <input_file_name>_gpio.isxd

+
+

Arguments

+
+
input_gpio_filelist<str>

The file path of the gpio file to be exported.

+
+
output_isxd_dirstr

The path of the directory to write isxd file.

+
+
+
+
+ +
+
+isx.export_image_to_isxd_tiff(image, isxd_file, tiff_file, rgb=None)
+

Save an image as isxd and tiff. +If rgb is one of ‘red’, ‘green’, ‘blue’, the images will be colored.

+
+ +
+
+isx.export_image_to_tiff(image, tiff_file, write_rgb=False)
+

Save an image as a uint16 tiff.

+
+ +
+
+isx.export_isxd_image_to_tiff(input_isxd_image, output_tiff_file)
+

Convert an ISXD image file to a tiff image. +WARNING: does not export tiff with alignment metadata, use align_image instead

+
+

Arguments

+
+
input_isxd_imagestr

Path to the input ISXD image file.

+
+
output_tiff_filestr

Path to the output tiff file.

+
+
+
+
+ +
+
+isx.export_movie_timestamps_to_csv(input_movie_files, output_csv_file, time_ref='start')
+

Export movie frame timestamps to a csv file. +This operation is supported for .isxd and .isxb movies.

+

For more details see exportMovie.

+
+

Arguments

+
+
input_movie_fileslist<str>

The file paths of the movies to export frame timestamps from.

+
+
output_csv_filestr

The path of the csv file to be written.

+
+
time_ref{‘start’, ‘unix’, ‘tsc’}

The time reference for the CSV time stamps. +If ‘start’ is used, the timestamps represent the seconds since the start of the movie. +If ‘unix’ is used, the timestamps represent the seconds since the Unix epoch. +If ‘tsc’ is used, the timestamps represent the hardware counter value on the acquisition box when each frame was captured.

+
+
+
+
+ +
+
+isx.export_movie_to_mp4(input_movie_files, output_mp4_file, compression_quality=0.1, write_invalid_frames=False, frame_rate_format='float', draw_bounding_box=True, draw_bounding_box_center=True, draw_zones=True)
+

Export movies to an MP4 file.

+

For more details see exportMovie.

+
+

Arguments

+
+
input_movie_fileslist<str>

The file paths of the movies to be exported.

+
+
output_mp4_filestr

The path of the MP4 file to be written.

+
+
compression_qualityfloat

A value between 0.001 and 1 that controls the quality and size of the output file for the MP4 format. +The larger the value, the better the quality of the movie, but the larger the size of the file. +The default value of 0.1 typically produces a good quality movie where the file is at most 10% of the uncompressed original file size, +but may be smaller if the movie content can be efficiently encoded. +More formally, this represents a rough maximum on the output file size as a fraction of the original file size.

+
+
write_invalid_framesbool

If True, write invalid (dropped, cropped, and blank) frames as zero, +otherwise, do not write them at all.

+
+
frame_rate_format{“float”, “int”}

Format to encode the frame rate in the output mp4 file. +If float, the frame rate will be exported as a precise estimate of the input movie sampling rate. +If int, the frame rate will be rounded to the nearest integer.

+
+
draw_bounding_boxbool

Only used for nVision .isxb movies. +If there is nVision tracking data in the .isxb movie, and this flag is enabled, +then draw the bounding box estimate on each frame of the exported mp4 movie.

+
+
draw_bounding_box_centerbool

Only used for nVision .isxb movies. +If there is nVision tracking data in the .isxb movie, and this flag is enabled, +then draw the center of the bounding box estimate on each frame of the exported mp4 movie.

+
+
draw_zonesbool

Only used for nVision .isxb movies. +If there is nVision tracking data in the .isxb movie, and this flag is enabled, +then draw the zones of the tracking area on each frame of the exported mp4 movie.

+
+
+
+
+ +
+
+isx.export_movie_to_nwb(input_movie_files, output_nwb_file, identifier='', session_description='', comments='', description='', experiment_description='', experimenter='', institution='', lab='', session_id='')
+

Export movies to an HDF5-based neurodata without borders (NWB) file.

+

For more details see exportMovie.

+
+

Arguments

+
+
input_movie_fileslist<str>

The file paths of the movies to be exported.

+
+
output_nwb_filestr

The path of the NWB file to be written.

+
+
identifierstr

An identifier for the file according to the NWB spec.

+
+
session_descriptionstr

A session description for the file according to the NWB spec.

+
+
commentsstr

Comments on the recording session.

+
+
descriptionstr

Description for the file according to the NWB spec.

+
+
experiment_descriptionstr

Details about the experiment.

+
+
experimenterstr

The person who recorded the data.

+
+
institutionstr

The place where the recording was performed.

+
+
labstr

The lab where the recording was performed.

+
+
session_idstr

A unique session identifier for the recording.

+
+
+
+
+ +
+
+isx.export_movie_to_tiff(input_movie_files, output_tiff_file, write_invalid_frames=False)
+

Export movies to a TIFF file.

+

For more details see exportMovie.

+
+

Arguments

+
+
input_movie_fileslist<str>

The file paths of the movies to be exported.

+
+
output_tiff_filestr

The path of the TIFF file to be written.

+
+
write_invalid_framesbool

If True, write invalid (dropped, cropped, and blank) frames as zero, +otherwise, do not write them at all.

+
+
+
+
+ +
+
+isx.export_nvision_movie_tracking_frame_data_to_csv(input_movie_files, output_csv_file, time_ref='start')
+

Export frame tracking metadata from an nVision movie. +This operation is supported for .isxb movies.

+
+
The frame tracking metadata is generated by the nVision tracking model, and includes the following columns:
    +

  • Global Frame Number: The frame number in the input movie series.

    • +

  • Movie Number: The movie number in the series.

    • +

  • Local Frame Number: The frame number in the individual movie.

    • +

  • Frame Timestamp: The frame timestamp. In units of seconds or microseconds based on the input time_ref parameter.

    • +

  • Bounding Box Left: X coordinate of the top left corner of the bounding box. In units of pixels.

    • +

  • Bounding Box Top: Y coordinate of the top left corner of the bounding box. In units of pixels.

    • +

  • Bounding Box Right: X coordinate of the bottom right corner of the bounding box. In units of pixels.

    • +

  • Bounding Box Bottom: Y coordinate of the bottom right corner of the bounding box. In units of pixels.

    • +

  • Bounding Box Center X: X coordinate of the center point of the bounding box. In units of pixels.

    • +

  • Bounding Box Center Y: Y coordinate of the center point of the bounding box. In units of pixels.

    • +

  • Confidence: The nVision tracking model confidence of the bounding box estimate. In units of %.

    • +

  • Zone ID: If the nVision tracking model detected the mouse was inside a zone, this column contains the id of that zone.

    • +

  • Zone Name: If the nVision tracking model detected the mouse was inside a zone, this column contains the name of that zone.

    • +
+
+
+

For more details see exportMovie.

+
+

Arguments

+
+
input_movie_fileslist<str>

The file paths of the movies to export frame tracking metadata from.

+
+
output_csv_filestr

The path of the csv file to be written.

+
+
time_ref{‘start’, ‘unix’, ‘tsc’}

The time reference for the CSV time stamps. +If ‘start’ is used, the timestamps represent the seconds since the start of the movie. +If ‘unix’ is used, the timestamps represent the seconds since the Unix epoch. +If ‘tsc’ is used, the timestamps represent the hardware counter value on the acquisition box when each frame was captured.

+
+
+
+
+ +
+
+isx.export_nvision_movie_tracking_zone_data_to_csv(input_movie_files, output_csv_file)
+

Export zone tracking metadata from an nVision movie. +This operation is supported for .isxb movies.

+
+
The zone tracking metadata used by the nVision tracking model, and includes the following columns:
    +

  • ID: Unique identifier for the zone.

    • +

  • Enabled: Flag indicating whether the zone is enabled for tracking.

    • +

  • Name: User friendly name for the zone.

    • +

  • Description: Optional description for the zone

    • +

  • Type: The shape of the zone. Can be either rectangle, polygon, or ellipse.

    • +
  • +
    X i: The ith X coordinate of the zone.

    Note: Since zones can have different shapes, they can have a different number of coordinates. +The csv output will contain n columns for the X coordinate, where n is the maxmimum +number of coordinates across all zones in the metadata.

    +
    +
    +
    • +
  • +
    Y i: The ith Y coordinate of the zone.

    Note: Since zones can have different shapes, they can have a different number of coordinates. +The csv output will contain n columns for the Y coordinate, where n is the maxmimum +number of coordinates across all zones in the metadata.

    +
    +
    +
    • +

  • Major Axis: only outputted for ellipse shaped zones. Length of the major axis.

    • +

  • Minor Axis: only outputted for ellipse shaped zones. Length of the minor axis.

    • +

  • Angle: only outputted for ellipse shaped zones. Ellipse rotation angle in degrees.

    • +
+
+
+

For more details see exportMovie.

+
+

Arguments

+
+
input_movie_fileslist<str>

The file paths of the movies to export frame tracking metadata from.

+
+
output_csv_filestr

The path of the csv file to be written.

+
+
+
+
+ +
+
+isx.export_tiff_to_isxd_image(input_tiff_file, output_isxd_file)
+

Convert an tiff image file to an ISXD image. +WARNING: does not export tiff with alignment metadata, use align_image instead

+
+

Arguments

+
+
input_tiff_filestr

Path to the input tiff file.

+
+
output_isxd_filestr

Path to the output ISXD image file.

+
+
+
+
+ +
+
+isx.export_vessel_set_to_csv_tiff(input_vessel_set_files, output_trace_csv_file='', output_line_csv_file='', output_map_tiff_file='', output_heatmaps_tiff_dir='', time_ref='start')
+

Export vessel sets to a CSV file with trace data and TIFF files with image data.

+
+

Arguments

+
+
input_vessel_set_fileslist<str>

The file paths of the vessel sets to export.

+
+
output_trace_csv_filestr

The path of the trace CSV file to write.

+
+
output_line_csv_filestr

The path of the line CSV file to write.

+
+
output_map_tiff_filestr

The name of the vessel map TIFF file to write.

+
+
output_heatmaps_tiff_dirstr

The name of the directory to write correlation heatmaps as TIFF stacks.

+
+
time_ref{‘start’, ‘unix’}

The time reference for the CSV time stamps. +If ‘start’ is used, the time stamps represent the seconds since the start of the vessel set. +If ‘unix’ is used, the time stamps represents the second since the Unix epoch.

+
+
+
+
+ +
+
+isx.get_file_extension(in_file)
+

Get full extension for file that can have multiple extensions.

+
+ +
+
+isx.get_file_stem(in_file)
+

Get the file stem for file that can have multiple extensions.

+
+ +
+
+isx.make_output_file_path(in_file, out_dir, suffix=None, ext='isxd')
+

Make an output file path from an input path, output directory, suffix and extension.

+

This is useful for generate output file paths for processing steps.

+
+

Arguments

+
+
in_filestr

The input file path.

+
+
out_dirstr

The output directory path.

+
+
suffixstr

The suffix to append to the file stem with a ‘-‘. +If left empty, no suffix is appended.

+
+
ext‘isxd’

The output file extension, not including the ‘.’.

+
+
+
+
+

Returns

+
+
str

The output file path.

+
+
+
+
+

Examples

+

Make the output file path for a preprocessed recording.

+
>>> make_output_file_path('in_dir/in_file.xml', 'out_dir', 'PP')
+'out_dir/in_file-PP.isxd'
+
+
+
+
+ +
+
+isx.make_output_file_paths(in_files, out_dir, suffix, ext='isxd')
+

Like isx.make_output_file_path(), but for many files.

+
+ +
+
+isx.overlay_cell_map_on_image(input_isxd_cell_map_file, input_isxd_image_file, output_tiff_image_file)
+

Overlay a cellmap onto an image, and save as isxd. Can save tiff as well.

+
+

Arguments

+
+
input_isxd_cell_map_filestr

Path to an .isxd cell map image file.

+
+
input_isxd_image_filestr

Path to an .isxd image file to overlay on.

+
+
output_tiff_image_filestr

Path to the output isxd cell map image.

+
+
+
+
+ +
+
+isx.overlay_cellmaps(first_tiff_cellmap_file, second_tiff_cellmap_file, overlayed_tiff_cellmap_file, background_color='#000000', first_color='#00ff00', second_color='#ff00ff', cell_thresh=0.5)
+

Overlay two cellmaps using different colors to show overlap.

+
+

Arguments

+
+
first_tiff_cellmap_filestr

Path to the first tiff cellmap image.

+
+
second_tiff_cellmap_filestr

Path to the second tiff cellmap image.

+
+
overlayed_tiff_cellmap_filestr

Path to the output tiff cellmap.

+
+
background_colorstr

Hex color code for background. Format: #RRGGBB

+
+
first_colorstr

Hex color code for cells in first cellmap. Format: #RRGGBB

+
+
second_colorstr

Hex color code for cells in second cellmap. Format: #RRGGBB

+
+
cell_threshfloat [0, 1]

Pixel values less than cell_thresh will be considered as the background.

+
+
+
+
+ +
+
+isx.verify_deinterleave(in_file, efocus)
+

Verify if all frames from movie has the same efocus as provided.

+
+

Arguments

+
+
in_filestr

The input file path.

+
+
efocusint

The efocus value to be compared with.

+
+
+
+
+

Returns

+
+
bool

True if the movie is successfully verified, False otherwise.

+
+
+
+
+ +
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/search.html b/search.html new file mode 100644 index 0000000..38a8d5c --- /dev/null +++ b/search.html @@ -0,0 +1,128 @@ + + + + + + Search — pyisx 2.0.0 documentation + + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • Search
    • +
  • +
    • +
+
+
+
+
+ + + + +
+ +
+ +
+
+ +
+
+
+
+ + + + + + + + + \ No newline at end of file diff --git a/searchindex.js b/searchindex.js new file mode 100644 index 0000000..51ee8b2 --- /dev/null +++ b/searchindex.js @@ -0,0 +1 @@ +Search.setIndex({"alltitles": {"API Reference": [[8, null]], "Arguments": [[8, "arguments"], [8, "id2"], [8, "id4"], [8, "id6"], [8, "id8"], [8, "id10"], [8, "id11"], [8, "id12"], [8, "id19"], [8, "id21"], [8, "id23"], [8, "id25"], [8, "id27"], [8, "id28"], [8, "id33"], [8, "id35"], [8, "id37"], [8, "id39"], [8, "id44"], [8, "id46"], [8, "id51"], [8, "id53"], [8, "id55"], [8, "id57"], [8, "id58"], [8, "id71"], [8, "id73"], [8, "id75"], [8, "id77"], [8, "id79"], [8, "id81"], [8, "id84"], [8, "id86"], [8, "id89"], [8, "id91"], [8, "id92"], [8, "id93"], [8, "id94"], [8, "id96"], [8, "id97"], [8, "id98"], [8, "id99"], [8, "id100"], [8, "id101"], [8, "id102"], [8, "id103"], [8, "id104"], [8, "id105"], [8, "id106"], [8, "id107"], [8, "id108"], [8, "id109"], [8, "id110"], [8, "id111"], [8, "id112"], [8, 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[[5, "quick-start"]], "Reading Data": [[2, null]], "Reporting Bugs": [[0, "reporting-bugs"]], "Returns": [[8, "returns"], [8, "id1"], [8, "id3"], [8, "id5"], [8, "id7"], [8, "id9"], [8, "id13"], [8, "id18"], [8, "id20"], [8, "id22"], [8, "id24"], [8, "id26"], [8, "id29"], [8, "id32"], [8, "id34"], [8, "id36"], [8, "id38"], [8, "id40"], [8, "id43"], [8, "id45"], [8, "id47"], [8, "id50"], [8, "id52"], [8, "id54"], [8, "id56"], [8, "id59"], [8, "id62"], [8, "id65"], [8, "id66"], [8, "id67"], [8, "id70"], [8, "id72"], [8, "id74"], [8, "id76"], [8, "id78"], [8, "id80"], [8, "id82"], [8, "id83"], [8, "id85"], [8, "id87"], [8, "id88"], [8, "id90"], [8, "id95"], [8, "id114"], [8, "id119"]], "Supported Platforms": [[6, "supported-platforms"]], "Vessel Sets": [[2, "vessel-sets"], [3, "vessel-sets"]], "Writing Data": [[3, null]], "pyisx documentation": [[5, null]]}, "docnames": ["contributing", "examples", "examples/readData", "examples/writeData", "faq", "index", "installation", "overview", 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"eventset (class in isx)": [[8, "isx.EventSet", false]], "export_aligned_timestamps() (in module isx)": [[8, "isx.export_aligned_timestamps", false]], "export_cell_set_to_csv_tiff() (in module isx)": [[8, "isx.export_cell_set_to_csv_tiff", false]], "export_ethovision_data_with_isxb_timestamps() (in module isx)": [[8, "isx.export_ethovision_data_with_isxb_timestamps", false]], "export_event_set_to_csv() (in module isx)": [[8, "isx.export_event_set_to_csv", false]], "export_gpio_set_to_csv() (in module isx)": [[8, "isx.export_gpio_set_to_csv", false]], "export_gpio_to_isxd() (in module isx)": [[8, "isx.export_gpio_to_isxd", false]], "export_image_to_isxd_tiff() (in module isx)": [[8, "isx.export_image_to_isxd_tiff", false]], "export_image_to_tiff() (in module isx)": [[8, "isx.export_image_to_tiff", false]], "export_isxd_image_to_tiff() (in module isx)": [[8, "isx.export_isxd_image_to_tiff", false]], "export_movie_timestamps_to_csv() (in module isx)": [[8, 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isx)": [[8, "isx.get_file_extension", false]], "get_file_stem() (in module isx)": [[8, "isx.get_file_stem", false]], "get_frame_data() (isx.movie method)": [[8, "isx.Movie.get_frame_data", false]], "get_frame_timestamp() (isx.movie method)": [[8, "isx.Movie.get_frame_timestamp", false]], "get_offsets_since_start() (isx.timing method)": [[8, "isx.Timing.get_offsets_since_start", false]], "get_valid_samples() (isx.timing method)": [[8, "isx.Timing.get_valid_samples", false]], "get_valid_samples_mask() (isx.timing method)": [[8, "isx.Timing.get_valid_samples_mask", false]], "get_vessel_center_trace_data() (isx.vesselset method)": [[8, "isx.VesselSet.get_vessel_center_trace_data", false]], "get_vessel_correlations_data() (isx.vesselset method)": [[8, "isx.VesselSet.get_vessel_correlations_data", false]], "get_vessel_direction_trace_data() (isx.vesselset method)": [[8, "isx.VesselSet.get_vessel_direction_trace_data", false]], "get_vessel_image_data() (isx.vesselset method)": [[8, 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