Data set and Python language for curve fitting the elliptical shape
This data set contains the digitization of bamboo culm's and log's circumference that resemble an ellipse and a circle. The data was adjusted, transformed into polar coordinates, and curve fitted using non linear regression. The Phyton coding to curve this ellipse are also generated. In th...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Dataset |
| Sprache: | eng |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | Effendi Tri Bahtiar |
| description | This data set contains the digitization of bamboo culm's and log's circumference that resemble an ellipse and a circle. The data was adjusted, transformed into polar coordinates, and curve fitted using non linear regression. The Phyton coding to curve this ellipse are also generated.
In this version we revised the Phyton code:
# calculate r_estimate using the curve model
def r_estimate(row):
numer = estimate["R"] * ((estimate["a"] ** 2 - estimate["b"] ** 2) * np.sin(row["theta"] + estimate["k"] * np.pi) * np.sin(estimate["T"] + estimate["k"] * np.pi) + estimate["b"] ** 2 * np.cos(row["theta"] - estimate["T"])) + estimate["a"] * estimate["b"] * \
((estimate["a"] ** 2 - estimate["b"] ** 2) * (np.sin(row["theta"] + estimate["k"] * np.pi) ** 2) + estimate["b"] ** 2 - estimate["R"] ** 2 * (np.sin(row["theta"] - estimate["T"]) ** 2)) ** 0.5
denom = (estimate["a"] ** 2 - estimate["b"] ** 2) * (np.sin(row["theta"] + estimate["k"] * np.pi) ** 2) + estimate["b"] ** 2 |
| doi_str_mv | 10.17632/c83yb2fgmr.2 |
| format | Dataset |
| fullrecord | <record><control><sourceid>datacite_PQ8</sourceid><recordid>TN_cdi_datacite_primary_10_17632_c83yb2fgmr_2</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_17632_c83yb2fgmr_2</sourcerecordid><originalsourceid>FETCH-datacite_primary_10_17632_c83yb2fgmr_23</originalsourceid><addsrcrecordid>eNqVjrEKwjAURbM4iDq6vx9obRKo7lVxdHAPz_Q1DaRpSV-F_r1FBGenc4fD5Qixl0Uuj6VWB3vS81M1rku5WovqjIwwEgPGGu4zt32EgNFN6AiaPoGd0mtZntlHB9wSUAh-YG8xwNjiQFuxajCMtPtyI7Lr5VHdsnr5tp7JDMl3mGYjC_OJML8Io_S__hsESkGS</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>dataset</recordtype></control><display><type>dataset</type><title>Data set and Python language for curve fitting the elliptical shape</title><source>DataCite</source><creator>Effendi Tri Bahtiar</creator><creatorcontrib>Effendi Tri Bahtiar</creatorcontrib><description>This data set contains the digitization of bamboo culm's and log's circumference that resemble an ellipse and a circle. The data was adjusted, transformed into polar coordinates, and curve fitted using non linear regression. The Phyton coding to curve this ellipse are also generated.
In this version we revised the Phyton code:
# calculate r_estimate using the curve model
def r_estimate(row):
numer = estimate["R"] * ((estimate["a"] ** 2 - estimate["b"] ** 2) * np.sin(row["theta"] + estimate["k"] * np.pi) * np.sin(estimate["T"] + estimate["k"] * np.pi) + estimate["b"] ** 2 * np.cos(row["theta"] - estimate["T"])) + estimate["a"] * estimate["b"] * \
((estimate["a"] ** 2 - estimate["b"] ** 2) * (np.sin(row["theta"] + estimate["k"] * np.pi) ** 2) + estimate["b"] ** 2 - estimate["R"] ** 2 * (np.sin(row["theta"] - estimate["T"]) ** 2)) ** 0.5
denom = (estimate["a"] ** 2 - estimate["b"] ** 2) * (np.sin(row["theta"] + estimate["k"] * np.pi) ** 2) + estimate["b"] ** 2</description><identifier>DOI: 10.17632/c83yb2fgmr.2</identifier><language>eng</language><publisher>Mendeley</publisher><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>780,1893</link.rule.ids><linktorsrc>$$Uhttps://commons.datacite.org/doi.org/10.17632/c83yb2fgmr.2$$EView_record_in_DataCite.org$$FView_record_in_$$GDataCite.org$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Effendi Tri Bahtiar</creatorcontrib><title>Data set and Python language for curve fitting the elliptical shape</title><description>This data set contains the digitization of bamboo culm's and log's circumference that resemble an ellipse and a circle. The data was adjusted, transformed into polar coordinates, and curve fitted using non linear regression. The Phyton coding to curve this ellipse are also generated.
In this version we revised the Phyton code:
# calculate r_estimate using the curve model
def r_estimate(row):
numer = estimate["R"] * ((estimate["a"] ** 2 - estimate["b"] ** 2) * np.sin(row["theta"] + estimate["k"] * np.pi) * np.sin(estimate["T"] + estimate["k"] * np.pi) + estimate["b"] ** 2 * np.cos(row["theta"] - estimate["T"])) + estimate["a"] * estimate["b"] * \
((estimate["a"] ** 2 - estimate["b"] ** 2) * (np.sin(row["theta"] + estimate["k"] * np.pi) ** 2) + estimate["b"] ** 2 - estimate["R"] ** 2 * (np.sin(row["theta"] - estimate["T"]) ** 2)) ** 0.5
denom = (estimate["a"] ** 2 - estimate["b"] ** 2) * (np.sin(row["theta"] + estimate["k"] * np.pi) ** 2) + estimate["b"] ** 2</description><fulltext>true</fulltext><rsrctype>dataset</rsrctype><creationdate>2023</creationdate><recordtype>dataset</recordtype><sourceid>PQ8</sourceid><recordid>eNqVjrEKwjAURbM4iDq6vx9obRKo7lVxdHAPz_Q1DaRpSV-F_r1FBGenc4fD5Qixl0Uuj6VWB3vS81M1rku5WovqjIwwEgPGGu4zt32EgNFN6AiaPoGd0mtZntlHB9wSUAh-YG8xwNjiQFuxajCMtPtyI7Lr5VHdsnr5tp7JDMl3mGYjC_OJML8Io_S__hsESkGS</recordid><startdate>20230825</startdate><enddate>20230825</enddate><creator>Effendi Tri Bahtiar</creator><general>Mendeley</general><scope>DYCCY</scope><scope>PQ8</scope></search><sort><creationdate>20230825</creationdate><title>Data set and Python language for curve fitting the elliptical shape</title><author>Effendi Tri Bahtiar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-datacite_primary_10_17632_c83yb2fgmr_23</frbrgroupid><rsrctype>datasets</rsrctype><prefilter>datasets</prefilter><language>eng</language><creationdate>2023</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Effendi Tri Bahtiar</creatorcontrib><collection>DataCite (Open Access)</collection><collection>DataCite</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Effendi Tri Bahtiar</au><format>book</format><genre>unknown</genre><ristype>DATA</ristype><title>Data set and Python language for curve fitting the elliptical shape</title><date>2023-08-25</date><risdate>2023</risdate><abstract>This data set contains the digitization of bamboo culm's and log's circumference that resemble an ellipse and a circle. The data was adjusted, transformed into polar coordinates, and curve fitted using non linear regression. The Phyton coding to curve this ellipse are also generated.
In this version we revised the Phyton code:
# calculate r_estimate using the curve model
def r_estimate(row):
numer = estimate["R"] * ((estimate["a"] ** 2 - estimate["b"] ** 2) * np.sin(row["theta"] + estimate["k"] * np.pi) * np.sin(estimate["T"] + estimate["k"] * np.pi) + estimate["b"] ** 2 * np.cos(row["theta"] - estimate["T"])) + estimate["a"] * estimate["b"] * \
((estimate["a"] ** 2 - estimate["b"] ** 2) * (np.sin(row["theta"] + estimate["k"] * np.pi) ** 2) + estimate["b"] ** 2 - estimate["R"] ** 2 * (np.sin(row["theta"] - estimate["T"]) ** 2)) ** 0.5
denom = (estimate["a"] ** 2 - estimate["b"] ** 2) * (np.sin(row["theta"] + estimate["k"] * np.pi) ** 2) + estimate["b"] ** 2</abstract><pub>Mendeley</pub><doi>10.17632/c83yb2fgmr.2</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | DOI: 10.17632/c83yb2fgmr.2 |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_datacite_primary_10_17632_c83yb2fgmr_2 |
| source | DataCite |
| title | Data set and Python language for curve fitting the elliptical shape |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T16%3A02%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-datacite_PQ8&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=unknown&rft.au=Effendi%20Tri%20Bahtiar&rft.date=2023-08-25&rft_id=info:doi/10.17632/c83yb2fgmr.2&rft_dat=%3Cdatacite_PQ8%3E10_17632_c83yb2fgmr_2%3C/datacite_PQ8%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |