| _version_ | 1866902290709872640 |
|---|---|
| author | Shangyong Shi |
| author_facet | Shangyong Shi |
| contents | <p>We feature significant improvements in this release. The package should now be easily installed and applied to both single point and multi- dimentional data.</p> <ol> <li>Enabled pip install. In the path of EnergyPhaseClassification, <code>pip install .</code> and the EnergyPhase package can be imported by Python using <code>import EnergyPhase</code>.</li> <li>Rearranged the module structure. The functions are easier to use. <code>from EnergyPhase.energy_area import energy_area</code></li> <li>Enables array inputs and parallel computation for large data processing. Three examples are provided in /EnergyPhaseClassification/examples: single point data, MERRA2 reanalysis data, and high resolution CONUS404 data. The parallel computation of the 1-km energy fields has been tested on HPC.</li> <li>Besides simple phase classification based on thresholds, added estimation of snow conditional probability (snow fraction) based on functions and LUTs. <code>from EnergyPhase.snowprob import snowprob_func, snowprob_LUT</code> Example import:</li> </ol> <pre><code>from EnergyPhase.energy_area import energy_area # energy_area module to compute energies from vertical profiles. Accomadates array inputs now. from EnergyPhase.snowprob import snowprob_func, snowprob_LUT # snowprob module for estimating snow probability and classify phase. from EnergyPhase.watervapor import TwFromSH, TiFromSH, w2rh # watervapor module includes almost all functions you need for water vapor related computations, including conversions between RH and dew point/wet bulb temperature, saturation vapor pressure, etc. from EnergyPhase.basemap import figure_basemap. # just for plotting the basemaps from EnergyPhase.lapse_rate import lapse_rate_vec # compute lowest 500m lapse rate, not needed for the EnergyPhase method but useful if you need to use the Sims and Liu (2015) Probsnow scheme. </code></pre> <p><strong>Full Changelog</strong>: https://github.com/ShangyongShi/PhaseClassification/compare/v1...v2</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15033215 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | ShangyongShi/PhaseClassification: Updated EnergyPhase with more functions and easier applications Shangyong Shi <p>We feature significant improvements in this release. The package should now be easily installed and applied to both single point and multi- dimentional data.</p> <ol> <li>Enabled pip install. In the path of EnergyPhaseClassification, <code>pip install .</code> and the EnergyPhase package can be imported by Python using <code>import EnergyPhase</code>.</li> <li>Rearranged the module structure. The functions are easier to use. <code>from EnergyPhase.energy_area import energy_area</code></li> <li>Enables array inputs and parallel computation for large data processing. Three examples are provided in /EnergyPhaseClassification/examples: single point data, MERRA2 reanalysis data, and high resolution CONUS404 data. The parallel computation of the 1-km energy fields has been tested on HPC.</li> <li>Besides simple phase classification based on thresholds, added estimation of snow conditional probability (snow fraction) based on functions and LUTs. <code>from EnergyPhase.snowprob import snowprob_func, snowprob_LUT</code> Example import:</li> </ol> <pre><code>from EnergyPhase.energy_area import energy_area # energy_area module to compute energies from vertical profiles. Accomadates array inputs now. from EnergyPhase.snowprob import snowprob_func, snowprob_LUT # snowprob module for estimating snow probability and classify phase. from EnergyPhase.watervapor import TwFromSH, TiFromSH, w2rh # watervapor module includes almost all functions you need for water vapor related computations, including conversions between RH and dew point/wet bulb temperature, saturation vapor pressure, etc. from EnergyPhase.basemap import figure_basemap. # just for plotting the basemaps from EnergyPhase.lapse_rate import lapse_rate_vec # compute lowest 500m lapse rate, not needed for the EnergyPhase method but useful if you need to use the Sims and Liu (2015) Probsnow scheme. </code></pre> <p><strong>Full Changelog</strong>: https://github.com/ShangyongShi/PhaseClassification/compare/v1...v2</p> |
| title | ShangyongShi/PhaseClassification: Updated EnergyPhase with more functions and easier applications |
| url | https://doi.org/10.5281/zenodo.15033215 |