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MGAP IPA PPNA_UFFIP id_campo: ID_Campo data
ID_Campo from MGAP IPA PPNA_UFFIP: PPNA predios UFFIP.Independent Variables (Grids)
- id_lote
- grid: /id_lote (unitless) ordered (1) to (220) by 1.0 N= 220 pts :grid
Other Info
| Key | |
|---|---|
| 1 | Bautista_Duarte |
| 2 | Escobal |
| 3 | Gimenez_Irigoyen |
| 4 | Gonzales_Lombardo |
| 5 | HnoBarrios |
| 6 | Lopez |
| 7 | LosSantos |
| 8 | Makinnon_Souza |
| 9 | Malaquin |
| 10 | Mendina |
| 11 | Mouton |
| 12 | Nicora |
| 13 | NuevoHorizonte |
| 14 | Olveira_Perez |
- bufferwordsize
- 4
- datatype
- realarraytype
- scale_max
- 14
- scale_min
- 1
- units
- ids
Last updated: Tue, 27 Jun 2017 15:57:17 GMT
Data Views
Views
line plots
color bars
scatter| id_lote | |
 doc[] | |
 MGAP IPA PPNA_UFFIP id_campo[ id_lote |] | M |
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Filters
Here are some filters that are useful for manipulating data. There are actually many more available, but they have to be entered manually. See Ingrid Function Documentation for more information.- Monthly Climatology calculates a monthly climatology by averaging over all years.
- anomalies calculates the difference between the (above) monthly climatology and the original data.
- Integrate along id_lote
- Differentiate along id_lote
- Take differences along id_lote
RMS (root mean square with mean *not* removed) over id_lote |
RMSA (root mean square with mean removed) over id_lote |
Maximum over id_lote |
Minimum over id_lote |
Detrend (best-fit-line) over id_lote |
Note on units