Bases: BaseSummary
A class for handling Benthic Line Intercept Transect (LIT) data from MERMAID.
The BenthicLIT class is responsible for fetching Benthic LIT data, including observations,
observations aggregated by sample units, and observations aggregated by sample events,
for a specified project.
Source code in seasnake/summaries/benthic_lit.py
| class BenthicLIT(BaseSummary):
"""
A class for handling Benthic Line Intercept Transect (LIT) data from MERMAID.
The BenthicLIT class is responsible for fetching Benthic LIT data, including observations,
observations aggregated by sample units, and observations aggregated by sample events,
for a specified project.
"""
@requires_token
def observations(self, project_id: str) -> DataFrame:
"""
Retrieves a project's Benthic LIT observations.
Args:
project_id (str): The ID of the project for which to fetch Benthic LIT observations.
Returns:
DataFrame
Examples:
```
from seasnake import MermaidAuth, BenthicLIT
auth = MermaidAuth()
benthic_lit = BenthicLIT(token=auth.get_token())
project_id = "AAAAAAAA-BBBB-CCCC-DDDD-EEEEEEEEEEEE"
print(benthic_lit.observations(project_id))
```
"""
url = f"/projects/{project_id}/benthiclits/obstransectbenthiclits/"
df = self.read_cache(url)
return self.to_cache(url, self.data_frame_from_url(url)) if df is None else df
@requires_token
def sample_units(self, project_id: str) -> DataFrame:
"""
Retrieves a project's Benthic LIT observations aggregated by sample units.
Args:
project_id (str): The ID of the project for which to fetch Benthic LIT sample units.
Returns:
DataFrame
Examples:
```
from seasnake import MermaidAuth, BenthicLIT
auth = MermaidAuth()
benthic_lit = BenthicLIT(token=auth.get_token())
project_id = "AAAAAAAA-BBBB-CCCC-DDDD-EEEEEEEEEEEE"
print(benthic_lit.sample_units(project_id))
```
"""
url = f"/projects/{project_id}/benthiclits/sampleunits/"
df = self.read_cache(url)
return self.to_cache(url, self.data_frame_from_url(url)) if df is None else df
@requires_token
def sample_events(self, project_id: str) -> DataFrame:
"""
Retrieves a project's Benthic LIT observations aggregated by sample events.
Args:
project_id (str): The ID of the project for which to fetch Benthic LIT sample events.
Returns:
DataFrame
Examples:
```
from seasnake import MermaidAuth, BenthicLIT
auth = MermaidAuth()
benthic_lit = BenthicLIT(token=auth.get_token())
project_id = "AAAAAAAA-BBBB-CCCC-DDDD-EEEEEEEEEEEE"
print(benthic_lit.sample_events(project_id))
```
"""
url = f"/projects/{project_id}/benthiclits/sampleevents/"
df = self.read_cache(url)
return self.to_cache(url, self.data_frame_from_url(url)) if df is None else df
|
observations(project_id)
Retrieves a project's Benthic LIT observations.
Parameters:
Name |
Type |
Description |
Default |
project_id |
str
|
The ID of the project for which to fetch Benthic LIT observations.
|
required
|
Returns:
Type |
Description |
DataFrame
|
|
Examples:
from seasnake import MermaidAuth, BenthicLIT
auth = MermaidAuth()
benthic_lit = BenthicLIT(token=auth.get_token())
project_id = "AAAAAAAA-BBBB-CCCC-DDDD-EEEEEEEEEEEE"
print(benthic_lit.observations(project_id))
Source code in seasnake/summaries/benthic_lit.py
| @requires_token
def observations(self, project_id: str) -> DataFrame:
"""
Retrieves a project's Benthic LIT observations.
Args:
project_id (str): The ID of the project for which to fetch Benthic LIT observations.
Returns:
DataFrame
Examples:
```
from seasnake import MermaidAuth, BenthicLIT
auth = MermaidAuth()
benthic_lit = BenthicLIT(token=auth.get_token())
project_id = "AAAAAAAA-BBBB-CCCC-DDDD-EEEEEEEEEEEE"
print(benthic_lit.observations(project_id))
```
"""
url = f"/projects/{project_id}/benthiclits/obstransectbenthiclits/"
df = self.read_cache(url)
return self.to_cache(url, self.data_frame_from_url(url)) if df is None else df
|
sample_events(project_id)
Retrieves a project's Benthic LIT observations aggregated by sample events.
Parameters:
Name |
Type |
Description |
Default |
project_id |
str
|
The ID of the project for which to fetch Benthic LIT sample events.
|
required
|
Returns:
Type |
Description |
DataFrame
|
|
Examples:
from seasnake import MermaidAuth, BenthicLIT
auth = MermaidAuth()
benthic_lit = BenthicLIT(token=auth.get_token())
project_id = "AAAAAAAA-BBBB-CCCC-DDDD-EEEEEEEEEEEE"
print(benthic_lit.sample_events(project_id))
Source code in seasnake/summaries/benthic_lit.py
| @requires_token
def sample_events(self, project_id: str) -> DataFrame:
"""
Retrieves a project's Benthic LIT observations aggregated by sample events.
Args:
project_id (str): The ID of the project for which to fetch Benthic LIT sample events.
Returns:
DataFrame
Examples:
```
from seasnake import MermaidAuth, BenthicLIT
auth = MermaidAuth()
benthic_lit = BenthicLIT(token=auth.get_token())
project_id = "AAAAAAAA-BBBB-CCCC-DDDD-EEEEEEEEEEEE"
print(benthic_lit.sample_events(project_id))
```
"""
url = f"/projects/{project_id}/benthiclits/sampleevents/"
df = self.read_cache(url)
return self.to_cache(url, self.data_frame_from_url(url)) if df is None else df
|
sample_units(project_id)
Retrieves a project's Benthic LIT observations aggregated by sample units.
Parameters:
Name |
Type |
Description |
Default |
project_id |
str
|
The ID of the project for which to fetch Benthic LIT sample units.
|
required
|
Returns:
Type |
Description |
DataFrame
|
|
Examples:
from seasnake import MermaidAuth, BenthicLIT
auth = MermaidAuth()
benthic_lit = BenthicLIT(token=auth.get_token())
project_id = "AAAAAAAA-BBBB-CCCC-DDDD-EEEEEEEEEEEE"
print(benthic_lit.sample_units(project_id))
Source code in seasnake/summaries/benthic_lit.py
| @requires_token
def sample_units(self, project_id: str) -> DataFrame:
"""
Retrieves a project's Benthic LIT observations aggregated by sample units.
Args:
project_id (str): The ID of the project for which to fetch Benthic LIT sample units.
Returns:
DataFrame
Examples:
```
from seasnake import MermaidAuth, BenthicLIT
auth = MermaidAuth()
benthic_lit = BenthicLIT(token=auth.get_token())
project_id = "AAAAAAAA-BBBB-CCCC-DDDD-EEEEEEEEEEEE"
print(benthic_lit.sample_units(project_id))
```
"""
url = f"/projects/{project_id}/benthiclits/sampleunits/"
df = self.read_cache(url)
return self.to_cache(url, self.data_frame_from_url(url)) if df is None else df
|