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kurannn merged 1 commit into from
Sep 28, 2026
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fix: hyperlinks in notebooks #17

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6 changes: 3 additions & 3 deletions openquake/quaket/auxiliary/catalogue.ipynb
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"source": [
"# Catalogue\n",
"\n",
"This notebook shows how you can examine statistical parameters of an [earthquake catalogue](../../html/contents/glossary.html) and visualize it on a high-quality map."
"This notebook shows how you can examine statistical parameters of an [earthquake catalogue](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Earthquake-catalogue) and visualize it on a high-quality map."
]
},
{
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"id": "634c324f-37be-476a-8660-183e26b0a82e",
"metadata": {},
"source": [
"Descriptions of inputs and input files used here are briefly summarized below. For more detailed information, please see [Data Format section](../../contents/data_formats.html). \n",
"Descriptions of inputs and input files used here are briefly summarized below. For more detailed information, please see [Data Format section](https://gemsciencetools.github.io/quakeT/contents/data_formats.html). \n",
"- **catalogue (str):** Path to the HMTK-formatted CSV catalogue.\n",
"- **polygon (str):** Path to the GeoJSON file for the study area boundary.\n",
"- **region (list):** Map extent [West, East, South, North].\n",
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"source": [
"## Statistics of catalogue\n",
"\n",
"This block loads the [earthquake catalogue](../../html/contents/glossary.html) and generates a descriptive statistics table, including [mean](../../html/contents/glossary.html), [standard deviation](../../html/contents/glossary.html), and [median](../../html/contents/glossary.html), to provide an overview of the catalogue’s range and distribution. "
"This block loads the [earthquake catalogue](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Earthquake-catalogue) and generates a descriptive statistics table, including [mean](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Mean-average-or-arithmetic-mean), [standard deviation](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Standard-deviation), and [median](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Median-discrete-sample), to provide an overview of the catalogue’s range and distribution. "
]
},
{
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8 changes: 4 additions & 4 deletions openquake/quaket/auxiliary/completeness.ipynb
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"source": [
"# Completeness\n",
"\n",
"In the early stages of processing an [instrumental catalogue](../../html/contents/glossary.html) for use in [Probabilistic Seismic Hazard Analysis (PSHA)](../../html/contents/glossary.html), it is necessary to determine the [magnitude completeness (Mc)](../../html/contents/glossary.html) of the [earthquake catalogue](../../html/contents/glossary.html). Incomplete catalogues can introduce bias into earthquake recurrence models, which may significantly affect seismic hazard estimates at a site. Therefore, identifying Mc is an essential step in preparing input data for PSHA.\n",
"In the early stages of processing an [instrumental catalogue](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Instrumental-catalogue) for use in [Probabilistic Seismic Hazard Analysis (PSHA)](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Probabilistic-Seismic-Hazard-Analysis-PSHA), it is necessary to determine the [magnitude completeness (Mc)](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Magnitude-completeness-Mc) of the [earthquake catalogue](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Earthquake-catalogue). Incomplete catalogues can introduce bias into earthquake recurrence models, which may significantly affect seismic hazard estimates at a site. Therefore, identifying Mc is an essential step in preparing input data for PSHA.\n",
"\n",
"In this notebook, two catalogue completeness methodologies are presented: the Stepp (1971) method [[7]](references.html#ref-stepp-1972) and an iterative approach [[8]](references.html#ref-johnson-2026). The methodology for analysing catalogue completeness is implemented in the current version of the Modeller’s Toolkit [[1]](references.html#ref-weatherill-2014)."
]
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"source": [
"## Stepp, 1971\n",
"\n",
"This is one of the earliest analytical approaches to estimation of [magnitude completeness](../../html/contents/glossary.html). It is based on estimators of the [seismicity rate](../../html/contents/glossary.html), identifying the completeness magnitude when the observed rate of earthquakes above Mc begins to deviate from the expected rate.\n",
"This is one of the earliest analytical approaches to estimation of [magnitude completeness](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Magnitude-completeness-Mc). It is based on estimators of the [seismicity rate](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Seismicity-rate), identifying the completeness magnitude when the observed rate of earthquakes above Mc begins to deviate from the expected rate.\n",
"\n",
"The analysis of Stepp (1971) is a coarse, but relatively robust, approach to estimating the temporal variation in completeness of a catalogue. It has been widely applied since its development. The accuracy of the Mc depends on the magnitude and time intervals considered, and a degree of judgement is often needed to determine the time at which the rate deviates from the expected values. It has tended to be applied to catalogues on a large scale and for relatively higher Mc."
]
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"\n",
"They develop a technique to simultaneously estimate $b$-values and time-magnitude completeness windows that relies upon one of two regularly made assumptions about event distributions in a study region: that the magnitudes in the catalogue follow a Gutenberg-Richter magnitude distribution and that the rate of events in time follows a Poisson distribution.\n",
"\n",
"In this methodology, there are two supplementary techniques to determine completeness and [magnitude-frequency distribution (MFD)](../../html/contents/glossary.html) parameters such that the two assumptions can trade-off. The two approaches are based on the same fundamental principles, but they differ in the metric used to determine the optimal combined solution. Their automated method enables users to choose multiple potential completeness magnitudes and corresponding years, while the final selection is determined by a statistical algorithm designed to satisfy a key principle of PSHA. However, if users already have reliable knowledge of the completeness characteristics of their catalogue, they can restrict the range of magnitudes and years considered."
"In this methodology, there are two supplementary techniques to determine completeness and [magnitude-frequency distribution (MFD)](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-MagnitudeFrequency-Distribution-MFD) parameters such that the two assumptions can trade-off. The two approaches are based on the same fundamental principles, but they differ in the metric used to determine the optimal combined solution. Their automated method enables users to choose multiple potential completeness magnitudes and corresponding years, while the final selection is determined by a statistical algorithm designed to satisfy a key principle of PSHA. However, if users already have reliable knowledge of the completeness characteristics of their catalogue, they can restrict the range of magnitudes and years considered."
]
},
{
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"id": "4096f054-ec02-4ac6-84ad-020d767eecb7",
"metadata": {},
"source": [
"The `completeness_generate` function uses the completeness-related data provided in the [TOML configuration](../../contents/data_formats.html) file. It first reads the defined `years` and `mags` values, which should be selected based on available knowledge of the catalogue and the periods during which completeness might have changed. In the initial step, the function generates all possible completeness windows from the provided years and magnitude values."
"The `completeness_generate` function uses the completeness-related data provided in the [TOML configuration](https://gemsciencetools.github.io/quakeT/contents/data_formats.html#completeness-configuration) file. It first reads the defined `years` and `mags` values, which should be selected based on available knowledge of the catalogue and the periods during which completeness might have changed. In the initial step, the function generates all possible completeness windows from the provided years and magnitude values."
]
},
{
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4 changes: 2 additions & 2 deletions openquake/quaket/auxiliary/declustering.ipynb
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"source": [
"# Declustering\n",
"\n",
"[Declustering](../../html/contents/glossary.html) is a fundamental preprocessing step in [Probabilistic Seismic Hazard Analysis (PSHA) ](../../html/contents/glossary.html) that aims to purge dependent earthquakes ([aftershocks](../../html/contents/glossary.html), [foreshocks](../../html/contents/glossary.html), and [swarm-type seismicity](../../html/contents/glossary.html)) from [earthquake catalogues](../../html/contents/glossary.html), leaving only independent earthquakes [(mainshocks)](../../html/contents/glossary.html) for analysis. This script shows three different space-time windowing declustering methods available [here](https://github.com/gem/oq-engine/blob/master/openquake/hmtk/seismicity/declusterer/distance_time_windows.py). \n",
"[Declustering](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Declustering) is a fundamental preprocessing step in [Probabilistic Seismic Hazard Analysis (PSHA) ](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Probabilistic-Seismic-Hazard-Analysis-PSHA) that aims to purge dependent earthquakes ([aftershocks](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Aftershock), [foreshocks](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Foreshock), and [swarm-type seismicity](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Swarm-type-seismicity)) from [earthquake catalogues](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Earthquake-catalogue), leaving only independent earthquakes [(mainshocks)](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Mainshock) for analysis. This script shows three different space-time windowing declustering methods available [here](https://github.com/gem/oq-engine/blob/master/openquake/hmtk/seismicity/declusterer/distance_time_windows.py). \n",
"\n",
"- Gardner and Knopoff, 1974 (GK) [[3]](references.html#ref-gk-1974)\n",
"- Uhrhammer, 1986 (UH) [[4]](references.html#ref-uh-1986)\n",
Expand All @@ -33,7 +33,7 @@
"id": "a9fcc93b-f6f8-44a3-8bda-10d340ce1e7f",
"metadata": {},
"source": [
"The required input is briefly described below. For more detailed information, please see [Data Format section](../../contents/data_formats.html). \n",
"The required input is briefly described below. For more detailed information, please see [Data Format section](https://gemsciencetools.github.io/quakeT/contents/data_formats.html#catalogue). \n",
"\n",
"- **catalogue (str):** Path to the HMTK-formatted CSV catalogue."
]
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4 changes: 2 additions & 2 deletions openquake/quaket/auxiliary/homogenising.ipynb
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"source": [
"# Magnitude Homogenization\n",
"\n",
"[Magnitude Homogenization](../../html/contents/glossary.html) is one of the fundamental steps in seismic hazard analysis. The process involves combining earthquake data from multiple catalogues into a single consistent [earthquake catalogue](../../html/contents/glossary.html) by carefully evaluating available bulletins, identifying duplicate events across different sources, and applying empirical conversion relationships to transform various native magnitude scales into a common target magnitude scale [[9]](references.html#ref-weatherill-2016).\n",
"[Magnitude Homogenization](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Magnitude-homogenization) is one of the fundamental steps in seismic hazard analysis. The process involves combining earthquake data from multiple catalogues into a single consistent [earthquake catalogue](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Earthquake-catalogue) by carefully evaluating available bulletins, identifying duplicate events across different sources, and applying empirical conversion relationships to transform various native magnitude scales into a common target magnitude scale [[9]](references.html#ref-weatherill-2016).\n",
"\n",
"There is a [homogenisor module in oq-mbtk](https://github.com/GEMScienceTools/oq-mbtk/blob/master/openquake/cat/isc_homogenisor.py) that was developed for the database of the [International Seismological Center (ISC)](https://www.isc.ac.uk/), but can be used for any other compiled database to create a magnitude-homogeneous global [earthquake catalogue](../../html/contents/glossary.html). Please note that the module contains not only the reviewed and reprocessed time/location (origin) and magnitude solutions for each event, but also the original solutions from all of the contributing local recording networks [[9]](references.html#ref-weatherill-2016). This homogenisor supports several agency-magnitude scales (e.g., [surface-wave magnitude](../../html/contents/glossary.html) ($M_s$), [body-wave magnitude](../../html/contents/glossary.html) ($m_b$), and [moment magnitude](../../html/contents/glossary.html) ($M_w$)) and converts them to a standardized $M_w$ using empirical relations based on their hierarchical criteria for selection of origin and magnitude for homogenizing a global earthquake catalogue."
"There is a [homogenisor module in oq-mbtk](https://github.com/GEMScienceTools/oq-mbtk/blob/master/openquake/cat/isc_homogenisor.py) that was developed for the database of the [International Seismological Center (ISC)](https://www.isc.ac.uk/), but can be used for any other compiled database to create a magnitude-homogeneous global [earthquake catalogue](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Earthquake-catalogue). Please note that the module contains not only the reviewed and reprocessed time/location (origin) and magnitude solutions for each event, but also the original solutions from all of the contributing local recording networks [[9]](references.html#ref-weatherill-2016). This homogenisor supports several agency-magnitude scales (e.g., [surface-wave magnitude](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Surface-wave-magnitude-M-s) ($M_s$), [body-wave magnitude](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Body-wave-magnitude-m-b) ($m_b$), and [moment magnitude](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Moment-magnitude-M-w) ($M_w$)) and converts them to a standardized $M_w$ using empirical relations based on their hierarchical criteria for selection of origin and magnitude for homogenizing a global earthquake catalogue."
]
},
{
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2 changes: 1 addition & 1 deletion openquake/quaket/auxiliary/interevent.ipynb
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"source": [
"# Poisson Stationarity Analysis\n",
"\n",
"Poisson Stationarity Analysis is one of the key components used in the evaluation of an [earthquake catalogue](../../html/contents/glossary.html) to check if it follows the Poisson distribution in terms of time. This script analyzes exactly the temporal distribution of the catalogue by calculating inter-event times and fitting statistical models."
"Poisson Stationarity Analysis is one of the key components used in the evaluation of an [earthquake catalogue](https://gemsciencetools.github.io/quakeT/contents/glossary.html#term-Earthquake-catalogue) to check if it follows the Poisson distribution in terms of time. This script analyzes exactly the temporal distribution of the catalogue by calculating inter-event times and fitting statistical models."
]
},
{
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