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@@ -1,2 +1,3 @@
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include nuwavsource/pixpos/*
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include nuwavdet/pixpos/*
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include nuwavsource/badpix_headers/*
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include nuwavdet/badpix_headers/*
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61
README.md
61
README.md
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# nuwavsource
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# nuwavdet
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This package is supposed to be used to detect the sources in NuStar observations and generate a mask excluding the signal from the sources of any kind.
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This pacakge is used to generate region masks separating any focused X-ray flux from background signal in NuSTAR observations.
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Additionaly, it generates a table containing:
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## Installation
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This package is to be used with Python 3.x.x
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```python
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pip install git+http://heagit.cosmos.ru/nustar/nuwavdet.git
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```
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Useful data about the observation:
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## Main use
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To use the package in your project, import it in by writing:
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```python
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from nuwavdet import nuwavdet as nw
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```
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The main functionality of the pacakge is presented with a single function
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```python
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process(obs_path, thresh)
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```
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Inputs are string with path to the _cl.evt file to use and a tuple of thresholds, e.g.
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```python
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process('D:\\Data\\obs_cl.evt', (3, 2))
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```
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Outputs of the function are:
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1. dictionary with some metadata and properties of the observation after mask generation procedure.
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2. region array with mask in DET1 coordinate frame. Note that this mask is for numpy mask application so 1 corresponds to masked pixel and 0 otherwise.
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3. custom bad pixel table with flagged pixels in RAW coordinates. It can be exported as fits file or each separate table can be acessed directly.
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4. array with the sum of wavelet planes used in the processing.
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Metadata about the observation file:
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1. OBS_ID
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1. OBS_ID
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2. Detector
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2. Detector
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@@ -14,32 +41,16 @@ Useful data about the observation:
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Useful algorythm-related data:
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Useful algorythm-related data:
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6. Average count rate on unmasked area
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6. Average count rate of unmasked area
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7. Portion of unmasked area
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7. Fraction of unmasked area
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8. Specific statistical metric[1] before and after masking the detected sources
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8. Modified Cash-statistic per bin before and after masking the detected sources
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9. Root-mean-square of counts in unmasked area
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## Installation
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## Other uses
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This package is to be used with Python 3.x.x
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To install tha package write
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```bash
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pip install nuwavsource
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```
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## Usage
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To use the package in your project, import it in by writing
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```python
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from nuwavsource import nuwavsource
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```
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You can process the cl.evt file by creating an Observation class object:
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You can process the cl.evt file by creating an Observation class object:
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```python
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```python
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obs = nuwavsource.Observation(path_to_evt_file)
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obs = nw.Observation(path_to_evt_file)
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```
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```
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Additionally, the energy band in KeV to get events from can be passed as an argument. The default value is [3,20].
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Additionally, the energy band in KeV to get events from can be passed as an argument. The default value is [3,20].
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1
nuwavdet/__init__.py
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1
nuwavdet/__init__.py
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name = 'nuwavdet'
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Load Diff
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name = 'nuwavsource'
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6
setup.py
6
setup.py
@@ -4,14 +4,14 @@ with open("README.md", "r") as fh:
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long_description = fh.read()
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long_description = fh.read()
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setuptools.setup(
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setuptools.setup(
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name="nuwavsource",
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name="nuwavdet",
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version="0.0.8",
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version="0.1.0",
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author="Andrey Mukhin",
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author="Andrey Mukhin",
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author_email="amukhin@phystech.edu",
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author_email="amukhin@phystech.edu",
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description="A package for source exclusion in NuStar observation data using wavelet decomposition",
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description="A package for source exclusion in NuStar observation data using wavelet decomposition",
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long_description=long_description,
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long_description=long_description,
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long_description_content_type="text/markdown",
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long_description_content_type="text/markdown",
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url="https://github.com/Andreyousan/nuwavsource",
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url="https://github.com/andrey-rrousan/nuwavdet",
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packages=setuptools.find_packages(),
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packages=setuptools.find_packages(),
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include_package_data=True,
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include_package_data=True,
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classifiers=(
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classifiers=(
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