undo extra changes
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emlys
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@ -1,4 +1,3 @@
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"""InVEST Crop Production Percentile Model."""
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import collections
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import logging
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@ -12,8 +11,6 @@ import pygeoprocessing
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import taskgraph
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from . import utils
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from . import spec_utils
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from .spec_utils import u
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from . import validation
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@ -31,181 +28,89 @@ ARGS_SPEC = {
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"different_projections_ok": True,
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},
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"args": {
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"workspace_dir": spec_utils.WORKSPACE,
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"results_suffix": spec_utils.SUFFIX,
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"n_workers": spec_utils.N_WORKERS,
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"workspace_dir": validation.WORKSPACE_SPEC,
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"results_suffix": validation.SUFFIX_SPEC,
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"n_workers": validation.N_WORKERS_SPEC,
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"landcover_raster_path": {
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**spec_utils.LULC,
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"projected": True,
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"projection_units": u.meter,
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"validation_options": {
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"projected": True,
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"projection_units": "meters",
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},
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"type": "raster",
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"required": True,
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"about": (
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"A raster file, representing integer land use/land code "
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"covers for each cell. This raster should have a projected "
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"coordinate system with units of meters (e.g. UTM) because "
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"pixel areas are divided by 10000 in order to report some "
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"results in hectares."),
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"name": "Land-Use/Land-Cover Map"
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},
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"landcover_to_crop_table_path": {
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"type": "csv",
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"columns": {
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"lucode": {"type": "integer"},
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"crop_name": {
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"type": "option_string",
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"options": {
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"abaca", "agave", "alfalfa", "almond", "aniseetc",
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"apple", "apricot", "areca", "artichoke", "asparagus",
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"avocado", "bambara", "banana", "barley", "bean",
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"beetfor", "berrynes", "blueberry", "brazil",
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"canaryseed", "carob", "carrot", "carrotfor", "cashew",
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"broadbean", "buckwheat", "cabbage", "cabbagefor",
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"cashewapple", "cassava", "castor", "cauliflower",
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"cerealnes", "cherry", "chestnut", "chickpea",
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"chicory", "chilleetc", "cinnamon", "citrusnes",
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"clove", "clover", "cocoa", "coconut", "coffee",
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"cotton", "cowpea", "cranberry", "cucumberetc",
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"currant", "date", "eggplant", "fibrenes", "fig",
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"flax", "fonio", "fornes", "fruitnes", "garlic",
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"ginger", "gooseberry", "grape", "grapefruitetc",
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"grassnes", "greenbean", "greenbroadbean", "greencorn",
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"greenonion", "greenpea", "groundnut", "hazelnut",
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"hemp", "hempseed", "hop", "jute", "jutelikefiber",
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"kapokfiber", "kapokseed", "karite", "kiwi", "kolanut",
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"legumenes", "lemonlime", "lentil", "lettuce",
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"linseed", "lupin", "maize", "maizefor", "mango",
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"mate", "melonetc", "melonseed", "millet",
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"mixedgrain", "mixedgrass", "mushroom", "mustard",
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"nutmeg", "nutnes", "oats", "oilpalm", "oilseedfor",
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"oilseednes", "okra", "olive", "onion", "orange",
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"papaya", "pea", "peachetc", "pear", "pepper",
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"peppermint", "persimmon", "pigeonpea", "pimento",
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"pineapple", "pistachio", "plantain", "plum", "poppy",
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"potato", "pulsenes", "pumpkinetc", "pyrethrum",
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"quince", "quinoa", "ramie", "rapeseed", "rasberry",
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"rice", "rootnes", "rubber", "rye", "ryefor",
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"safflower", "sesame", "sisal", "sorghum",
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"sorghumfor", "sourcherry, soybean", "spicenes",
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"spinach", "stonefruitnes", "strawberry", "stringbean",
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"sugarbeet", "sugarcane", "sugarnes", "sunflower",
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"swedefor", "sweetpotato", "tangetc", "taro", "tea",
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"tobacco", "tomato", "triticale", "tropicalnes",
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"tung", "turnipfor", "vanilla", "vegetablenes",
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"vegfor", "vetch", "walnut", "watermelon", "wheat",
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"yam", "yautia"
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}
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}
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"validation_options": {
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"required_fields": ["crop_name", "lucode"],
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},
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"type": "csv",
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"required": True,
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"about": (
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"A CSV table mapping canonical crop names to the land use "
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"codes in the landcover/use raster."),
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"A CSV table mapping canonical crop names to land use codes "
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"contained in the landcover/use raster. The allowed crop "
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"names are abaca, agave, alfalfa, almond, aniseetc, apple, "
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"apricot, areca, artichoke, asparagus, avocado, bambara, "
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"banana, barley, bean, beetfor, berrynes, blueberry, brazil, "
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"broadbean, buckwheat, cabbage, cabbagefor, canaryseed, "
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"carob, carrot, carrotfor, cashew, cashewapple, cassava, "
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"castor, cauliflower, cerealnes, cherry, chestnut, chickpea, "
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"chicory, chilleetc, cinnamon, citrusnes, clove, clover, "
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"cocoa, coconut, coffee, cotton, cowpea, cranberry, "
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"cucumberetc, currant, date, eggplant, fibrenes, fig, flax, "
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"fonio, fornes, fruitnes, garlic, ginger, gooseberry, grape, "
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"grapefruitetc, grassnes, greenbean, greenbroadbean, "
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"greencorn, greenonion, greenpea, groundnut, hazelnut, hemp, "
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"hempseed, hop, jute, jutelikefiber, kapokfiber, kapokseed, "
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"karite, kiwi, kolanut, legumenes, lemonlime, lentil, "
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"lettuce, linseed, lupin, maize, maizefor, mango, mate, "
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"melonetc, melonseed, millet, mixedgrain, mixedgrass, "
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"mushroom, mustard, nutmeg, nutnes, oats, oilpalm, "
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"oilseedfor, oilseednes, okra, olive, onion, orange, papaya, "
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"pea, peachetc, pear, pepper, peppermint, persimmon, "
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"pigeonpea, pimento, pineapple, pistachio, plantain, plum, "
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"poppy, potato, pulsenes, pumpkinetc, pyrethrum, quince, "
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"quinoa, ramie, rapeseed, rasberry, rice, rootnes, rubber, "
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"rye, ryefor, safflower, sesame, sisal, sorghum, sorghumfor, "
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"sourcherry, soybean, spicenes, spinach, stonefruitnes, "
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"strawberry, stringbean, sugarbeet, sugarcane, sugarnes, "
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"sunflower, swedefor, sweetpotato, tangetc, taro, tea, "
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"tobacco, tomato, triticale, tropicalnes, tung, turnipfor, "
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"vanilla, vegetablenes, vegfor, vetch, walnut, watermelon, "
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"wheat, yam, and yautia."),
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"name": "Landcover to Crop Table"
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},
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"aggregate_polygon_path": {
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**spec_utils.AOI,
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"projected": True,
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"required": False
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"type": "vector",
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"required": False,
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"validation_options": {
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"projected": True,
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},
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"about": (
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"A polygon vector containing features with which to "
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"aggregate/summarize final results. It is fine to have "
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"overlapping polygons."),
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"name": "Aggregate results polygon"
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},
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"model_data_path": {
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"type": "directory",
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"contents": {
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"climate_percentile_yield_tables": {
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"type": "directory",
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"about": (
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"Table mapping each climate bin to yield percentiles "
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"for each crop"),
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"contents": {
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"[CROP]_percentile_yield_table.csv": {
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"type": "csv",
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"columns": {
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"climate_bin": {"type": "integer"},
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"yield_25th": {
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"type": "number",
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"units": u.metric_ton/u.hectare
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},
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"yield_50th": {
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"type": "number",
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"units": u.metric_ton/u.hectare
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},
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"yield_75th": {
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"type": "number",
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"units": u.metric_ton/u.hectare
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},
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"yield_95th": {
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"type": "number",
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"units": u.metric_ton/u.hectare
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}
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}
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},
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}
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},
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"extended_climate_bin_maps": {
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"type": "directory",
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"about": "Maps of climate bins for each crop",
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"contents": {
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"extendedclimatebins[CROP]": {
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"type": "raster",
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"bands": {1: {"type": "integer"}},
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}
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}
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},
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"observed_yield": {
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"type": "directory",
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"about": "Maps of actual observed yield for each crop",
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"contents": {
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"[CROP]_observed_yield.tif": {
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"type": "raster",
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"bands": {1: {
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"type": "number",
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"units": u.metric_ton/u.hectare
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}}
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}
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}
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},
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"crop_nutrient.csv": {
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"type": "csv",
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"columns": {
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nutrient: {
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"type": "number",
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"units": units
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} for nutrient, units in {
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"protein": u.gram/u.hectogram,
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"lipid": u.gram/u.hectogram, # total lipid
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"energy": u.kilojoule/u.hectogram,
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"ca": u.milligram/u.hectogram, # calcium
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"fe": u.milligram/u.hectogram, # iron
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"mg": u.milligram/u.hectogram, # magnesium
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"ph": u.milligram/u.hectogram, # phosphorus
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"k": u.milligram/u.hectogram, # potassium
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"na": u.milligram/u.hectogram, # sodium
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"zn": u.milligram/u.hectogram, # zinc
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"cu": u.milligram/u.hectogram, # copper
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"fl": u.microgram/u.hectogram, # fluoride
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"mn": u.milligram/u.hectogram, # manganese
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"se": u.microgram/u.hectogram, # selenium
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"vita": u.IU/u.hectogram, # vitamin A
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"betac": u.microgram/u.hectogram, # beta carotene
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"alphac": u.microgram/u.hectogram, # alpha carotene
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"vite": u.milligram/u.hectogram, # vitamin e
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"crypto": u.microgram/u.hectogram, # cryptoxanthin
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"lycopene": u.microgram/u.hectogram, # lycopene
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"lutein": u.microgram/u.hectogram, # lutein + zeaxanthin
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"betaT": u.milligram/u.hectogram, # beta tocopherol
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"gammaT": u.milligram/u.hectogram, # gamma tocopherol
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"deltaT": u.milligram/u.hectogram, # delta tocopherol
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"vitc": u.milligram/u.hectogram, # vitamin C
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"thiamin": u.milligram/u.hectogram,
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"riboflavin": u.milligram/u.hectogram,
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"niacin": u.milligram/u.hectogram,
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"pantothenic": u.milligram/u.hectogram, # pantothenic acid
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"vitb6": u.milligram/u.hectogram, # vitamin B6
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"folate": u.microgram/u.hectogram,
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"vitb12": u.microgram/u.hectogram, # vitamin B12
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"vitk": u.microgram/u.hectogram, # vitamin K
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}.items()
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}
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}
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"required": True,
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"validation_options": {
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"exists": True,
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},
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"about": "Path to the InVEST Crop Production Data directory",
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"name": "model data directory"
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"about": (
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"A path to the InVEST Crop Production Data directory. These "
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"data would have been included with the InVEST installer if "
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"selected, or can be manually downloaded from "
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"http://releases.naturalcapitalproject.org/. If downloaded "
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"with InVEST, the default value should be used."),
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"name": "Directory to model data"
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}
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}
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}
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@ -304,7 +209,7 @@ def execute(args):
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* climate_bin_maps (contains [cropname]_climate_bin.tif files)
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* climate_percentile_yield (contains
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[cropname]_percentile_yield_table.csv files)
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Please see the InVEST user's guide chapter on crop production for
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details about how to download these data.
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args['n_workers'] (int): (optional) The number of worker processes to
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@ -38,7 +38,7 @@ class CropProductionTests(unittest.TestCase):
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from natcap.invest import crop_production_percentile
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args = {
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'workspace_dir': '/Users/emily/Documents/test-cpp-310',
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'workspace_dir': self.workspace_dir,
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'results_suffix': '',
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'landcover_raster_path': os.path.join(
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SAMPLE_DATA_PATH, 'landcover.tif'),
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