diff --git a/.gitignore b/.gitignore
index 3e15faa6c1a06f724c00b713303351c561f0aa2c..2de011678e02b0fde788425f0bf446977da9c403 100644
--- a/.gitignore
+++ b/.gitignore
@@ -68,3 +68,22 @@ beaufortSea/images/*
# sbtools
beaufortSea/.Renviron
+
+#fire and ice
+fireInIce/*/out
+fireInIce/*/tmp
+fireInIce/*/src/__pycache__
+
+#remove cache and dataout
+fireInIce/cache
+fireInIce/data_out
+
+#remove snakemake files
+fireInIce/.snakemake
+
+#exceptions Spatial
+!fireInIce/2_visualize/in/*.cpg
+!fireInIce/2_visualize/in/*.dbf
+!fireInIce/2_visualize/in/*.prj
+!fireInIce/2_visualize/in/*.shp
+!fireInIce/2_visualize/in/*.shx
\ No newline at end of file
diff --git a/fireInIce/0_fetch/src/download_dem.py b/fireInIce/0_fetch/src/download_dem.py
new file mode 100644
index 0000000000000000000000000000000000000000..2aa92ca0898e996e50c26fc66002d7b3d0d13a95
--- /dev/null
+++ b/fireInIce/0_fetch/src/download_dem.py
@@ -0,0 +1,121 @@
+import os
+import geopandas as gpd
+from bmi_topography import Topography
+import py3dep
+from shapely.geometry import Polygon
+
+def snakemake_type_exists(snakemake_type,string,default_input):
+ if hasattr(snakemake_type, string):
+ return snakemake_type[string]
+ else:
+ return default_input
+
+def get_shapefile_extent(shapefile):
+ west, south, east, north = shapefile.geometry.total_bounds
+ length = east - west
+ height = north - south
+ return west, east, length, south, north, height
+
+
+def buffer_shapefile(west, east, length, south, north, height, buffer):
+ west -= buffer / 100.0 * length
+ south -= buffer / 100.0 * height
+ east += buffer / 100.0 * length
+ north += buffer / 100.0 * height
+ return west, east, south, north
+
+
+def bmi_download_dem(extent_shpfile, demfile, data_product, dem_product, buffer):
+ # make out_dir if it doesn't exist
+ out_dir = os.path.dirname(demfile)
+ if not os.path.exists(out_dir):
+ os.makedirs(out_dir)
+
+ # load shapefile
+ shp = gpd.read_file(extent_shpfile)
+ # get extent of shapefile #assums WGS84 or some sort of geographic coordinate system, Potential FIX: could convert if necessary.
+ west, east, length, south, north, height = get_shapefile_extent(shp)
+ buff_west, buff_east, buff_south, buff_north = buffer_shapefile(
+ west, east, length, south, north, height, buffer
+ )
+
+ # set parameters of dem download
+ params = Topography.DEFAULT.copy()
+ params["data_type"] = data_product
+ params["dem_type"] = dem_product
+ params["output_format"] = "GTiff"
+ params["west"] = buff_west
+ params["south"] = buff_south
+ params["east"] = buff_east
+ params["north"] = buff_north
+ params["cache_dir"] = out_dir
+
+ # set api key if exists (you need this when you run out of free requests)
+ if os.path.isfile("opentopography_api_key.txt"):
+ with open("opentopography_api_key.txt", "r") as f:
+ api_key = f.read()
+ params["api_key"] = api_key
+
+ # setup request and fetch
+ topo_request = Topography(**params)
+ topo_request.fetch()
+
+ # rename the file
+ os.rename(
+ out_dir
+ + "/"
+ + str(params["dem_type"])
+ + "_"
+ + str(params["south"])
+ + "_"
+ + str(params["west"])
+ + "_"
+ + str(params["north"])
+ + "_"
+ + str(params["east"])
+ + ".tif",
+ out_dir + "/dem.tif",
+ )
+
+def py3dep_download_dem(extent_shpfile, demfile, py3dep_resolution, buffer):
+ # make out_dir if it doesn't exist
+ out_dir = os.path.dirname(demfile)
+ if not os.path.exists(out_dir):
+ os.makedirs(out_dir)
+
+ # load shapefile
+ shp = gpd.read_file(extent_shpfile)
+ # get extent of shapefile #assums WGS84 or some sort of geographic coordinate system, Potential FIX: could convert if necessary.
+ west, east, length, south, north, height = get_shapefile_extent(shp)
+ buff_west, buff_east, buff_south, buff_north = buffer_shapefile(
+ west, east, length, south, north, height, buffer
+ )
+
+ #specify geometry to download dem from
+ buffered_domain_polygon = Polygon(
+ zip(
+ [buff_west, buff_west, buff_east, buff_east],
+ [buff_north, buff_south, buff_south, buff_north],
+ )
+ )
+
+ #download dem
+ dem = py3dep.get_map("DEM", buffered_domain_polygon, resolution = py3dep_resolution, geo_crs = shp.crs, crs = 4326)
+
+ #save dem
+ dem.rio.to_raster(out_dir + "/dem.tif")
+
+if __name__ == "__main__":
+ data_product = snakemake_type_exists(snakemake.params,"data_product","/API/globaldem")
+ dem_product = snakemake_type_exists(snakemake.params,"dem_product","NASADEM")
+ py3dep_resolution = snakemake_type_exists(snakemake.params,"py3dep_resolution",30)
+ buffer = snakemake.params["buffer"]
+ extent_shpfile = snakemake.input["extent_shpfile"]
+ demfile = snakemake.output["demfile"]
+ download_mode = snakemake_type_exists(snakemake.params,"download_mode","bmi")
+ if download_mode == "bmi":
+ bmi_download_dem(extent_shpfile, demfile, data_product, dem_product, buffer)
+ elif download_mode == "py3dep":
+ py3dep_download_dem(extent_shpfile, demfile, py3dep_resolution, buffer)
+ else:
+ raise Exception("Incorrect download mode. Please use bmi or py3dep.")
diff --git a/fireInIce/0_fetch/src/download_dem_bounding_box.py b/fireInIce/0_fetch/src/download_dem_bounding_box.py
new file mode 100644
index 0000000000000000000000000000000000000000..ae343a87b11624c655a266efbb94a32ebb228d1d
--- /dev/null
+++ b/fireInIce/0_fetch/src/download_dem_bounding_box.py
@@ -0,0 +1,76 @@
+import os
+import numpy as np
+import geopandas as gpd
+from bmi_topography import Topography
+from shapely.geometry import Polygon
+
+def snakemake_type_exists(snakemake_type,string,default_input):
+ if hasattr(snakemake_type, string):
+ return snakemake_type[string]
+ else:
+ return default_input
+
+def bmi_download_dem(UL_corner, LR_corner,extent_shpfile, demfile, data_product, dem_product, buffer):
+ # make out_dir if it doesn't exist
+ out_dir = os.path.dirname(demfile)
+ if not os.path.exists(out_dir):
+ os.makedirs(out_dir)
+
+ # set parameters of dem download
+ params = Topography.DEFAULT.copy()
+ params["data_type"] = data_product
+ params["dem_type"] = dem_product
+ params["output_format"] = "GTiff"
+ params["west"] = float(UL_corner[1])
+ params["south"] = float(LR_corner[0])
+ params["east"] = float(LR_corner[1])
+ params["north"] = float(UL_corner[0])
+ params["cache_dir"] = out_dir
+
+ # set api key if exists (you need this when you run out of free requests)
+ if os.path.isfile("opentopography_api_key.txt"):
+ with open("opentopography_api_key.txt", "r") as f:
+ api_key = f.read()
+ params["api_key"] = api_key
+
+ # setup request and fetch
+ topo_request = Topography(**params)
+ topo_request.fetch()
+
+ # rename the file
+ os.rename(
+ out_dir
+ + "/"
+ + str(params["dem_type"])
+ + "_"
+ + str(params["south"])
+ + "_"
+ + str(params["west"])
+ + "_"
+ + str(params["north"])
+ + "_"
+ + str(params["east"])
+ + ".tif",
+ demfile,
+ )
+
+ domain_geom = Polygon(
+ zip(
+ [UL_corner[1],UL_corner[1], LR_corner[1],LR_corner[1]],
+ [UL_corner[0], LR_corner[0], LR_corner[0], UL_corner[0]],
+ )
+ )
+ domain_polygon = gpd.GeoDataFrame(index=[0], crs="EPSG:4326", geometry=[domain_geom])
+ domain_polygon.to_file(extent_shpfile)
+
+
+if __name__ == "__main__":
+ data_product = snakemake_type_exists(snakemake.params,"data_product","/API/globaldem")
+ dem_product = snakemake_type_exists(snakemake.params,"dem_product","NASADEM")
+ buffer = snakemake.params["buffer"]
+ UL_corner = snakemake.params["UL_corner"]
+ LR_corner = snakemake.params["LR_corner"]
+ extent_shpfile = snakemake.output["extent_shpfile"]
+ demfile = snakemake.output["demfile"]
+ download_mode = snakemake_type_exists(snakemake.params,"download_mode","bmi")
+ bmi_download_dem(UL_corner, LR_corner, extent_shpfile, demfile, data_product, dem_product, buffer)
diff --git a/fireInIce/0_fetch/src/download_sb.py b/fireInIce/0_fetch/src/download_sb.py
new file mode 100644
index 0000000000000000000000000000000000000000..139add21e3550cab42b3555b5e5d79729e912419
--- /dev/null
+++ b/fireInIce/0_fetch/src/download_sb.py
@@ -0,0 +1,17 @@
+import os
+import sciencebasepy
+
+def main(sb_id,zipfile):
+ # make out_dir if it doesn't exist
+ out_dir = os.path.dirname(zipfile)
+ if not os.path.exists(out_dir):
+ os.makedirs(out_dir)
+ # download the file
+ sb = sciencebasepy.SbSession()
+ sb_item = sb.get_item(sb_id)
+ sb.get_item_files_zip(sb_item,out_dir)
+
+if __name__ == "__main__":
+ sb_id = snakemake.params["sb_id"]
+ zipfile = snakemake.output["zipfile"]
+ main(sb_id,zipfile)
\ No newline at end of file
diff --git a/fireInIce/0_fetch/src/get_wbd.py b/fireInIce/0_fetch/src/get_wbd.py
new file mode 100644
index 0000000000000000000000000000000000000000..885ef8d2f8ed188bd9a819561cd1a8967e4b7d9d
--- /dev/null
+++ b/fireInIce/0_fetch/src/get_wbd.py
@@ -0,0 +1,25 @@
+import os
+import pandas as pd
+import geopandas as gpd
+from pygeohydro import WBD
+
+def main(huc_list, extent_shpfile):
+ # make out_dir if it doesn't exist
+ out_dir = os.path.dirname(extent_shpfile)
+ if not os.path.exists(out_dir):
+ os.makedirs(out_dir)
+
+ #download huc
+ wbd_list = []
+ for huc in huc_list:
+ huc_level = str(len(huc))
+ wbd = WBD("huc" + huc_level)
+ wbd_list += [wbd.byids("huc" + huc_level, [huc]).dissolve()]
+
+ extent = gpd.GeoDataFrame(pd.concat(wbd_list)).dissolve()
+ extent.to_file(extent_shpfile)
+
+if __name__ == "__main__":
+ huc_list = snakemake.params["huc_list"]
+ extent_shpfile = snakemake.output["extent_shpfile"]
+ main(huc_list, extent_shpfile)
diff --git a/fireInIce/0_fetch/src/unzip_file.py b/fireInIce/0_fetch/src/unzip_file.py
new file mode 100644
index 0000000000000000000000000000000000000000..c7cb32955c46e66de3d3e0e9039d89f39666bf85
--- /dev/null
+++ b/fireInIce/0_fetch/src/unzip_file.py
@@ -0,0 +1,28 @@
+import os
+import zipfile as zf
+import py7zr
+
+def unzip_file(zipfile, out_dir):
+ if zipfile.endswith(".7z"):
+ with py7zr.SevenZipFile(zipfile) as zip_ref:
+ zip_ref.extractall(out_dir)
+ elif zipfile.endswith (".zip"):
+ with zf.ZipFile(zipfile, "r") as zip_ref:
+ zip_ref.extractall(out_dir)
+
+def main(zipfile):
+ # make out_dir if it doesn't exist
+ tmp_dir = os.path.dirname(zipfile)
+ if zipfile.endswith(".7z"):
+ out_dir = tmp_dir + '/' + os.path.basename(zipfile[:-3])
+ elif zipfile.endswith (".zip"):
+ out_dir = tmp_dir + '/' + os.path.basename(zipfile[:-4])
+ if not os.path.exists(out_dir):
+ os.makedirs(out_dir)
+ # unzip the file
+ unzip_file(zipfile, out_dir)
+
+
+if __name__ == "__main__":
+ zipfile = snakemake.input["zipfile"]
+ main(zipfile)
diff --git a/fireInIce/1_process/src/calc_bedrock.py b/fireInIce/1_process/src/calc_bedrock.py
new file mode 100644
index 0000000000000000000000000000000000000000..e9b427d0c0bcf850dd8f96a8c49b4bab31290128
--- /dev/null
+++ b/fireInIce/1_process/src/calc_bedrock.py
@@ -0,0 +1,61 @@
+
+import os
+import numpy as np
+from osgeo import gdal, osr
+
+def calc_bedrock(dem_file,ice_thickness_file,ice_height_file,bedrock_file):
+ # make out_dir if it doesn't exist
+ out_dir = os.path.dirname(bedrock_file)
+ if not os.path.exists(out_dir):
+ os.makedirs(out_dir)
+
+ # read in the dem
+ ds = gdal.Open(dem_file)
+ ds_it = gdal.Open(ice_thickness_file)
+
+ #get metadata
+ gt = ds.GetGeoTransform()
+ cs = ds.GetProjection()
+ dtype = ds.GetRasterBand(1).DataType
+ cellsx = ds.GetRasterBand(1).XSize
+ cellsy = ds.GetRasterBand(1).YSize
+ NaN = ds.GetRasterBand(1).GetNoDataValue()
+ if NaN == None:
+ NaN = -9999
+
+ #convert to numpy array
+ dem = np.array(ds.GetRasterBand(1).ReadAsArray())
+ it = np.array(ds_it.GetRasterBand(1).ReadAsArray())
+
+ #calc bedrock
+ bedrock = dem - it
+
+ #ice_height
+ ih = np.zeros_like(dem) - 100000.
+ ih[it!=0] = dem[it!=0]
+
+ driver = gdal.GetDriverByName('GTiff')
+ dataset = driver.Create(ice_height_file,cellsx,cellsy, 1, gdal.GDT_Float32)
+ dataset.GetRasterBand(1).WriteArray(ih)
+ dataset.GetRasterBand(1).SetNoDataValue(NaN)
+
+ dataset.SetGeoTransform(gt)
+ dataset.SetProjection(cs)
+ dataset.FlushCache()
+ dataset=None
+
+ dataset = driver.Create(bedrock_file,cellsx,cellsy, 1, gdal.GDT_Float32)
+ dataset.GetRasterBand(1).WriteArray(bedrock)
+ dataset.GetRasterBand(1).SetNoDataValue(NaN)
+
+ dataset.SetGeoTransform(gt)
+ dataset.SetProjection(cs)
+ dataset.FlushCache()
+ dataset=None
+
+if __name__ == "__main__":
+ dem_file = snakemake.input["dem_file"]
+ ice_thickness_file = snakemake.input["ice_thickness_file"]
+ ice_height_file = snakemake.output["ice_height_file"]
+ bedrock_file = snakemake.output["bedrock_file"]
+ calc_bedrock(dem_file,ice_thickness_file,ice_height_file,bedrock_file)
\ No newline at end of file
diff --git a/fireInIce/1_process/src/cores_to_shp.py b/fireInIce/1_process/src/cores_to_shp.py
new file mode 100644
index 0000000000000000000000000000000000000000..61584e1697e96fd33fd4320194789e81562ef210
--- /dev/null
+++ b/fireInIce/1_process/src/cores_to_shp.py
@@ -0,0 +1,42 @@
+import pandas as pd
+import geopandas as gpd
+def main(core_data,core_shpfile):
+ cd = pd.read_excel(core_data)
+ cd.loc[2, 'Latitude'] = "58° 51’ 16.1†N" #datafix 2016, C3
+ cd.loc[2, 'Longitude'] = "134° 10’ 31.1†W" #datafix 2016, C3
+
+ core_name = []
+ Lat = []
+ Long = []
+ for i in range(0,len(cd)):
+ core_name += [cd['U.S. Geological Survey site name'][i]]
+ Lat += [convert_coor_to_dec(cd['Latitude'][i])]
+ Long += [convert_coor_to_dec(cd['Longitude'][i])]
+ print (cd['U.S. Geological Survey site name'][i],cd['Latitude'][i],cd['Longitude'][i],\
+ convert_coor_to_dec(cd['Latitude'][i]),convert_coor_to_dec(cd['Longitude'][i]))
+
+ df = pd.DataFrame(
+ {
+ "Core Name": core_name,
+ "Latitude": Lat,
+ "Longitude": Long,
+ }
+ )
+
+ gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.Longitude, df.Latitude), crs="EPSG:4326")
+
+ gdf.to_file(core_shpfile, driver='ESRI Shapefile')
+
+
+import re
+def convert_coor_to_dec(coor):
+ deg, minutes, seconds, direction = re.split('[°’â€]', coor)
+ return(float(deg) + float(minutes)/60 + float(seconds)/(60*60)) * (-1 if direction in [' W', ' S', 'Â W', 'Â S'] else 1)
+
+if __name__ == "__main__":
+ core_data = snakemake.input["core_data"]
+ core_shpfile = snakemake.output["core_shpfile"]
+ main(
+ core_data,
+ core_shpfile
+ )
\ No newline at end of file
diff --git a/fireInIce/1_process/src/regrid.py b/fireInIce/1_process/src/regrid.py
new file mode 100644
index 0000000000000000000000000000000000000000..4470475d114885a53fad48f72cbf1b38de803bcc
--- /dev/null
+++ b/fireInIce/1_process/src/regrid.py
@@ -0,0 +1,36 @@
+
+#code modified from https://stackoverflow.com/questions/10454316/how-to-project-and-resample-a-grid-to-match-another-grid-with-gdal-python
+from osgeo import gdal, gdalconst
+import os
+
+def main(src_file,match_file,dst_file):
+ out_dir = os.path.dirname(dst_file)
+ if not os.path.exists(out_dir):
+ os.makedirs(out_dir)
+
+ # Source
+ src = gdal.Open(src_file, gdalconst.GA_ReadOnly)
+ src_proj = src.GetProjection()
+
+ # We want a section of source that matches this:
+ match_ds = gdal.Open(match_file, gdalconst.GA_ReadOnly)
+ match_proj = match_ds.GetProjection()
+ match_geotrans = match_ds.GetGeoTransform()
+ wide = match_ds.RasterXSize
+ high = match_ds.RasterYSize
+
+ # Output / destination
+ dst = gdal.GetDriverByName('GTiff').Create(dst_file, wide, high, 1, gdalconst.GDT_Float32)
+ dst.SetGeoTransform( match_geotrans )
+ dst.SetProjection( match_proj)
+
+ # Do the work
+ gdal.ReprojectImage(src, dst, src_proj, match_proj, gdalconst.GRA_Bilinear)
+
+ del dst # Flush
+
+if __name__ == "__main__":
+ src_file = snakemake.input["src_file"]
+ match_file = snakemake.input["match_file"]
+ dst_file = snakemake.output["dst_file"]
+ main(src_file,match_file,dst_file)
\ No newline at end of file
diff --git a/fireInIce/1_process/src/remove_nans.py b/fireInIce/1_process/src/remove_nans.py
new file mode 100644
index 0000000000000000000000000000000000000000..5a2f6fb1effb0437116c5efd6418c84724f6d5bd
--- /dev/null
+++ b/fireInIce/1_process/src/remove_nans.py
@@ -0,0 +1,82 @@
+from astropy.convolution import Gaussian2DKernel, interpolate_replace_nans
+import os
+import numpy as np
+from osgeo import gdal, osr
+
+x_nei = [-1,0,1,-1,1,-1,0,1]
+y_nei = [1,1,1,0,0,-1,-1,-1]
+
+def seed_ice_hole(it,cellsx,cellsy,it_threshold):
+ for x in range(0,cellsx):
+ for y in range(0,cellsy):
+ if it[y,x] > it_threshold:
+ for nei in range(0,8):
+ if it[y+y_nei[nei],x+x_nei[nei]] == 0:
+ it[y+y_nei[nei],x+x_nei[nei]] = -9999
+ return it
+
+def fill_ice_hole(it,cellsx,cellsy):
+ trigger = 0
+ fill_iteration = 0
+ while trigger == 0:
+ trigger = 1
+ for x in range(0,cellsx):
+ for y in range(0,cellsy):
+ if it[y,x] == -9999:
+ trigger = 0
+ mini_trigger = 0
+ for nei in range(0,8):
+ if it[y+y_nei[nei],x+x_nei[nei]] == 0:
+ mini_trigger = 1
+ it[y+y_nei[nei],x+x_nei[nei]] = -9999
+ if mini_trigger == 0:
+ it[y,x] = -999999
+ fill_iteration += 1
+ print ("filling ice, try " + str(fill_iteration) + "...")
+ return it
+
+def remove_nans(ice_thickness_file,fixed_ice_thickness_file,convolution_window):
+ # make out_dir if it doesn't exist
+ out_dir = os.path.dirname(fixed_ice_thickness_file)
+ if not os.path.exists(out_dir):
+ os.makedirs(out_dir)
+
+ # read in the dem
+ ds_it = gdal.Open(ice_thickness_file)
+
+ #get metadata
+ gt = ds_it.GetGeoTransform()
+ cs = ds_it.GetProjection()
+ dtype = ds_it.GetRasterBand(1).DataType
+ cellsx = ds_it.GetRasterBand(1).XSize
+ cellsy = ds_it.GetRasterBand(1).YSize
+ NaN =0
+
+ #convert to numpy array
+ it = np.array(ds_it.GetRasterBand(1).ReadAsArray())
+
+ #convert zero to NaN
+ it = seed_ice_hole(it,cellsx,cellsy,750.)
+ it = fill_ice_hole(it,cellsx,cellsy)
+ it[it==-999999] = np.nan
+
+ #set kernal to one neighbor
+ kernel = Gaussian2DKernel(x_stddev=convolution_window)
+
+ # create a "fixed" image with NaNs replaced by interpolated values
+ fixed_it= interpolate_replace_nans(it, kernel)
+
+ driver = gdal.GetDriverByName('GTiff')
+ dataset = driver.Create(fixed_ice_thickness_file,cellsx,cellsy, 1, gdal.GDT_Float32)
+ dataset.GetRasterBand(1).WriteArray(fixed_it)
+ dataset.GetRasterBand(1).SetNoDataValue(NaN)
+ dataset.SetGeoTransform(gt)
+ dataset.SetProjection(cs)
+ dataset.FlushCache()
+ dataset=None
+
+if __name__ == "__main__":
+ convolution_window = snakemake.params["convolution_window"]
+ ice_thickness_file = snakemake.input["ice_thickness_file"]
+ fixed_ice_thickness_file = snakemake.output["ice_thickness_file"]
+ remove_nans(ice_thickness_file,fixed_ice_thickness_file,convolution_window)
\ No newline at end of file
diff --git a/fireInIce/2_visualize/in/extent_regional_fires.cpg b/fireInIce/2_visualize/in/extent_regional_fires.cpg
new file mode 100644
index 0000000000000000000000000000000000000000..3ad133c048f2189041151425a73485649e6c32c0
--- /dev/null
+++ b/fireInIce/2_visualize/in/extent_regional_fires.cpg
@@ -0,0 +1 @@
+UTF-8
\ No newline at end of file
diff --git a/fireInIce/2_visualize/in/extent_regional_fires.dbf b/fireInIce/2_visualize/in/extent_regional_fires.dbf
new file mode 100644
index 0000000000000000000000000000000000000000..da477da384ddf3206e8ddf436213aa3151bed2e6
Binary files /dev/null and b/fireInIce/2_visualize/in/extent_regional_fires.dbf differ
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diff --git a/fireInIce/2_visualize/in/tdump.160303.txt b/fireInIce/2_visualize/in/tdump.160303.txt
new file mode 100644
index 0000000000000000000000000000000000000000..775820d2c8989ba4410bb886994e387c0836ddd7
--- /dev/null
+++ b/fireInIce/2_visualize/in/tdump.160303.txt
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diff --git a/fireInIce/2_visualize/src/regional_fires_map.py b/fireInIce/2_visualize/src/regional_fires_map.py
new file mode 100644
index 0000000000000000000000000000000000000000..a395042bea966b8c2fc05597d4b7403f15401837
--- /dev/null
+++ b/fireInIce/2_visualize/src/regional_fires_map.py
@@ -0,0 +1,208 @@
+import matplotlib.pyplot as plt
+from matplotlib.collections import LineCollection
+import geopandas as gpd
+import pandas as pd
+from mpl_toolkits.basemap import Basemap
+import matplotlib.patheffects as path_effects
+import numpy as np
+import os
+from svgpath2mpl import parse_path
+from shapely.geometry import Point
+import matplotlib as mpl
+
+parent = os.getcwd()
+
+# add the condensed universe font
+mpl.font_manager.fontManager.addfont(parent + '/font/Univers-Condensed.otf')
+prop = mpl.font_manager.FontProperties(fname= parent + '/font/Univers-Condensed.otf')
+mpl.rcParams["font.family"] = "sans-serif"
+mpl.rcParams["font.sans-serif"] = [prop.get_name()]
+mpl.rcParams['svg.fonttype'] = 'none'
+mpl.rcParams["font.size"] = 18
+
+smoke_label_fontsize = 18
+label_fontsize = 18
+big_label_fontsize = 24
+
+# figure dimensions
+fig_width = 8.0
+fig_height = 7.0
+
+# map CRS
+map_crs = 'EPSG:3857'
+
+# axis dimensions
+ax_height = 0.9
+
+def get_shapefile_extent(shapefile):
+ west, south, east, north = shapefile.geometry.total_bounds
+ length = east - west
+ height = north - south
+ return west, east, length, south, north, height
+
+# Function to create a SVG marker
+def load_svg_marker(svg_file):
+ # Read the SVG file and create an OffsetImage
+ return OffsetImage(plt.imread(svg_file), zoom=0.1) # Adjust zoom as necessary
+
+def draw_line(p1,p2):
+ points = 100
+ return np.linspace(p1[0],p2[0],points), np.linspace(p1[1],p2[1],points)
+
+def draw_box(west,east,south,north):
+ x1,y1 = draw_line([west,south],[east,south])
+ x2,y2 = draw_line([east,south],[east,north])
+ x3,y3 = draw_line([east,north],[west,north])
+ x4,y4 = draw_line([west,north],[west,south])
+ return np.concatenate((x1,x2,x3,x4)),np.concatenate((y1,y2,y3,y4))
+
+def load_trajectory(traj_file, map_crs):
+ df_traj = pd.read_csv(traj_file, sep="\s+", header=None, skiprows=30)
+ df_traj.columns = ['trajectory_num','grid_num','year','month','day','hour','minute','forecast_hour','trajectory_age','Latitude','Longitude','height','pressure']
+ gdf_traj = gpd.GeoDataFrame(df_traj, geometry=gpd.points_from_xy(df_traj.Longitude, df_traj.Latitude), crs="EPSG:4326").to_crs(map_crs)
+ for trajectory_num in range(np.min(gdf_traj['trajectory_num']),np.max(gdf_traj['trajectory_num']+1)):
+ temp_age = gdf_traj[gdf_traj['trajectory_num']==trajectory_num]['trajectory_age'].copy()
+ temp_age[temp_age!=0] = temp_age[temp_age!=0] - np.min(temp_age[temp_age!=0])
+ gdf_traj.loc[gdf_traj['trajectory_num']==trajectory_num,'trajectory_age'] = temp_age.values
+ return gdf_traj
+
+def main(
+ fires,
+ fire_labels,
+ renderfile,
+ extent_shpfile,
+ forward_trajectory_files,
+ regional_fires_mapfile,
+ regional_fires_svg_mapfile
+ ):
+
+ # make figure
+ fig = plt.figure(1,figsize=(fig_width,fig_height))
+
+ #get the extent of the basemap in degrees
+ west_deg, east_deg, length_deg, south_deg, north_deg, height_deg = get_shapefile_extent(gpd.read_file(extent_shpfile))
+
+ #load the shpfile, project to the map crs and get the extent
+ extent_shp = gpd.read_file(extent_shpfile).to_crs(map_crs)
+ west, east, length, south, north, height = get_shapefile_extent(extent_shp)
+
+ #load the render image
+ basemap = plt.imread(renderfile)
+
+ #plot render
+ ax = fig.add_axes([0.05,0.05,.9,.9])
+ ax.imshow(basemap,extent=[west,east,south,north],alpha=0.8)
+
+ #set up axis
+ ax.set_xlim(west,east)
+ ax.set_ylim(south,north)
+ ytick_labels = np.array([57,59,61,63,65])
+ xtick_labels = np.array([-145,-140,-135,-130])
+ ytick_labels_str = [str(i) + r'$^{\circ}$N' for i in ytick_labels]
+ xtick_labels_str = [str(-i) + r'$^{\circ}$W' for i in xtick_labels]
+ lat_slope = (north-south)/(north_deg-south_deg)
+ long_slope = (east-west)/(east_deg-west_deg)
+ ax.set_xticks((xtick_labels - west_deg) * long_slope + west,xtick_labels_str)
+ ax.set_yticks((ytick_labels - south_deg) * lat_slope + south,ytick_labels_str, rotation='vertical',va='center')
+
+ # set up basemap
+ # set up orthographic map projection with
+ # use low resolution coastlines.
+ ax2 = fig.add_axes([0.7,0.7,0.225,0.225])
+ map = Basemap(projection='ortho',lat_0=0.5*(south_deg+north_deg),lon_0=0.5*(west_deg+east_deg),resolution='l')
+ # draw coastlines, country boundaries, fill continents.
+ map.drawcoastlines(linewidth=0.0)
+ map.drawcountries(linewidth=0.0)
+ map.fillcontinents(color=(0.75,0.75,0.75),lake_color='w',alpha=0.75)
+ # draw the edge of the map projection region (the projection limb)
+ # draw lat/lon grid lines every 30 degrees.
+ map.drawmeridians(np.arange(0,360,30),linewidth=0.15)
+ map.drawparallels(np.arange(-90,90,30),linewidth=0.15)
+ circle = map.drawmapboundary(fill_color='w')#[0.118,0.565,1.0,0.5])
+ circle.set_clip_on(False)
+ x_box, y_box = draw_box(west_deg,east_deg,south_deg,north_deg)
+ x,y=map(x_box,y_box)
+ map.plot(x, y, color='k', linewidth=1.0)
+
+ # draw flame icon svg
+ flameicon = parse_path("""M18.61,54.89C15.7,28.8,30.94,10.45,59.52,0C42.02,22.71,74.44,47.31,76.23,70.89 c4.19-7.15,6.57-16.69,7.04-29.45c21.43,33.62,3.66,88.57-43.5,80.67c-4.33-0.72-8.5-2.09-12.3-4.13C10.27,108.8,0,88.79,0,69.68 C0,57.5,5.21,46.63,11.95,37.99C12.85,46.45,14.77,52.76,18.61,54.89L18.61,54.89z""")
+ flameicon.vertices -= flameicon.vertices.mean(axis=0)
+ flameicon = flameicon.transformed(mpl.transforms.Affine2D().rotate_deg(180))
+ flameicon = flameicon.transformed(mpl.transforms.Affine2D().scale(-1,1))
+
+ # set default fire and trajectory that show on website load
+ default_trajectory = 8
+ default_fire = 1
+
+ for i in range(0,fires):
+ #load geo databases for the trajector data
+ gdf_for_traj = load_trajectory(forward_trajectory_files[i], map_crs)
+
+ # draw smoke lines
+ for trajectory_num in range(np.min(gdf_for_traj['trajectory_num']),np.max(gdf_for_traj['trajectory_num']+1)):
+ traj_x = gdf_for_traj[gdf_for_traj['trajectory_num']==trajectory_num].geometry.x
+ traj_y = gdf_for_traj[gdf_for_traj['trajectory_num']==trajectory_num].geometry.y
+ ax.plot(traj_x,traj_y,\
+ color=(0.375,0.375,0.375,),alpha=0.0,linewidth = 8.0,gid='trajectory-'+str(i)+'-'+str(trajectory_num)+'-0')
+
+ # add label to default trajectory
+ if trajectory_num == default_trajectory and i == default_fire:
+ label_offset_y = 70000
+ label_offset_x = 30000
+ label_index = int(len(traj_x)*0.5)
+ ax.text(label_offset_x+traj_x[traj_x.index[label_index]],label_offset_y+traj_y[traj_x.index[label_index]],"Potential Smoke Path",color='w',fontsize=smoke_label_fontsize,va='bottom',ha='center',rotation=-15,rotation_mode='anchor',gid='single-path-label',
+ bbox=dict(facecolor=(0,0,0,0.75),boxstyle='round',edgecolor='none', pad=0.2,linewidth=0.0),alpha=1.0)
+
+ #fire location
+ inner_flame_offset_y = -25000
+ inner_flame_offset_x = 2000
+ ax.scatter(gdf_for_traj.geometry.x[0],gdf_for_traj.geometry.y[0],s=1600,linewidth=0.0,marker=flameicon,facecolor='tab:red',edgecolor='k',zorder=3)
+ ax.scatter(gdf_for_traj.geometry.x[0]+inner_flame_offset_x,gdf_for_traj.geometry.y[0]+inner_flame_offset_y,s=400,linewidth=0.0,marker=flameicon,facecolor='tab:orange',edgecolor='k',zorder=3)
+ ax.scatter(gdf_for_traj.geometry.x[0],gdf_for_traj.geometry.y[0],s=1600,alpha=0.00001,marker=flameicon,facecolor='w',edgecolor='none',zorder=4,gid='source-'+str(i))
+
+ #label wild fire location
+ x_offset_label = -50000
+ y_offset_label = -200000
+ ax.text(gdf_for_traj.geometry.x[0]-x_offset_label,gdf_for_traj.geometry.y[0]+y_offset_label,fire_labels[i],color='w',fontsize=label_fontsize,va='center',ha='right',alpha=1.0,gid='wildfire-label-'+str(i),
+ bbox=dict(facecolor=(0,0,0,0.75),boxstyle='round', edgecolor='none', pad=0.2,linewidth=0.0))
+
+ # juneau icefield symbol and label
+ x_offset_ice_label = 120000
+ y_offset_ice_label = 60000
+ gdf_juneau_icefield = gpd.GeoDataFrame({'geometry': [Point(-134.188,58.842)], 'name': ['Sample Point']}, crs="EPSG:4326").to_crs(map_crs)
+ ax.scatter(gdf_juneau_icefield.geometry.x[0],gdf_juneau_icefield.geometry.y[0],s=400,linewidth=1.5,marker='v',facecolor='tab:blue',edgecolor='k',zorder=3,gid='sink-'+str(i))
+ ax.text(gdf_juneau_icefield.geometry.x[0]+x_offset_ice_label,gdf_juneau_icefield.geometry.y[0]+y_offset_ice_label,"Juneau\nIcefield",color='w',fontsize=label_fontsize,va='center',ha='left',alpha=1.0,gid='JIF-label',
+ bbox=dict(facecolor=(0,0,0,0.75),boxstyle='round', edgecolor='none', pad=0.2,linewidth=0.0))
+
+ # desktop only annotations
+ ax.text((west+east)/2.0,south+0.1*(north-south),"Hover over fires to show all potential\nsmoke paths within a 10-day window",color='w',fontsize=big_label_fontsize,va='center',ha='center',alpha=1.0,gid='multi-path-label-dt',
+ bbox=dict(facecolor=(0,0,0,0.75),boxstyle='round', edgecolor='none', pad=0.2,linewidth=0.0))
+
+ # mobile only annotations
+ ax.text((west+east)/2.0,south+0.1*(north-south),"Click here to show the major regional\nwildfires that occurred from 2015-2016",color='w',fontsize=big_label_fontsize,va='center',ha='center',alpha=0.0,gid='multi-path-label-mb-1',
+ bbox=dict(facecolor=(0,0,0,0.0),boxstyle='round', edgecolor='none', pad=0.2,linewidth=0.0))
+
+ ax.text((west+east)/2.0,south+0.1*(north-south),"Click fires to show all potential smoke\npaths within a 10-day window",color='w',fontsize=big_label_fontsize,va='center',ha='center',alpha=0.0,gid='multi-path-label-mb-2',
+ bbox=dict(facecolor=(0,0,0,0.0),boxstyle='round', edgecolor='none', pad=0.2,linewidth=0.0))
+
+ # save file
+ fig.savefig(regional_fires_mapfile,dpi=240)
+ fig.savefig(regional_fires_svg_mapfile,dpi=240,transparent=True)
+
+if __name__ == "__main__":
+ fires = snakemake.params["fires"]
+ fire_labels = snakemake.params["fire_labels"]
+ renderfile = snakemake.input["renderfile"]
+ extent_shpfile = snakemake.input["extent_shpfile"]
+ forward_trajectory_files = snakemake.input["forward_trajectory_files"]
+ regional_fires_mapfile = snakemake.output["regional_fires_mapfile"]
+ regional_fires_svg_mapfile = snakemake.output["regional_fires_svg_mapfile"]
+ main(
+ fires,
+ fire_labels,
+ renderfile,
+ extent_shpfile,
+ forward_trajectory_files,
+ regional_fires_mapfile,
+ regional_fires_svg_mapfile
+ )
\ No newline at end of file
diff --git a/fireInIce/2_visualize/src/remove_metadata.py b/fireInIce/2_visualize/src/remove_metadata.py
new file mode 100644
index 0000000000000000000000000000000000000000..b10d702a479836aee48f95780bba65bf41b2cb3f
--- /dev/null
+++ b/fireInIce/2_visualize/src/remove_metadata.py
@@ -0,0 +1,13 @@
+import re
+
+# remove annoying metadata that sets vue warnings off
+def remove_metadata(infile, outfile):
+ output = open(outfile, "w")
+ input = open(infile).read()
+ output.write(re.sub("<metadata>.*?</metadata>\n", "", input, flags=re.DOTALL))
+ output.close()
+
+if __name__ == "__main__":
+ infile = snakemake.input["infile"]
+ outfile = snakemake.output["outfile"]
+ remove_metadata(infile,outfile)
\ No newline at end of file
diff --git a/fireInIce/2_visualize/src/xs_functions.py b/fireInIce/2_visualize/src/xs_functions.py
new file mode 100644
index 0000000000000000000000000000000000000000..c53e9d33c95c38d967baaa154682559d95a94b6a
--- /dev/null
+++ b/fireInIce/2_visualize/src/xs_functions.py
@@ -0,0 +1,49 @@
+import matplotlib as mpl
+import numpy as np
+
+def translatexy(x,y,x_o,y_o,angle):
+ x_trans = x - x_o
+ y_trans = y - y_o
+ x_rot_trans = x_trans * np.cos(angle) - y_trans * np.sin(angle)
+ y_rot_trans = x_trans * np.sin(angle) + y_trans * np.cos(angle)
+ x_rot = x_rot_trans + x_o
+ y_rot = y_rot_trans + y_o
+ return x_rot,y_rot
+
+def align_marker(marker, halign='center', valign='middle',):
+ if isinstance(halign, (str)):
+ halign = {'right': -1.,
+ 'middle': 0.,
+ 'center': 0.,
+ 'left': 1.,
+ }[halign]
+
+ if isinstance(valign, (str)):
+ valign = {'top': -1.,
+ 'middle': 0.,
+ 'center': 0.,
+ 'bottom': 1.,
+ }[valign]
+
+ # Define the base marker
+ bm = mpl.markers.MarkerStyle(marker)
+
+ # Get the marker path and apply the marker transform to get the
+ # actual marker vertices (they should all be in a unit-square
+ # centered at (0, 0))
+ m_arr = bm.get_path().transformed(bm.get_transform()).vertices
+
+ # Shift the marker vertices for the specified alignment.
+ m_arr[:, 0] += halign / 2
+ m_arr[:, 1] += valign / 2
+
+ return mpl.path.Path(m_arr, bm.get_path().codes)
+
+#scale bar arms
+def scale_bar_arm(sclx,scly1,scly2,label,label_buffer,ax,scale_bar_line_width):
+ ax.plot([sclx,sclx],[scly1,scly2],
+ color = 'k',linewidth=scale_bar_line_width,clip_on=False,zorder=6)
+ if label.endswith('km'):
+ ax.text(sclx,scly2+label_buffer,label,va='bottom',ha='center',zorder=10)
+ else:
+ ax.text(sclx,scly2+label_buffer,label,va='bottom',ha='center',zorder=10)
\ No newline at end of file
diff --git a/fireInIce/2_visualize/src/xs_process.py b/fireInIce/2_visualize/src/xs_process.py
new file mode 100644
index 0000000000000000000000000000000000000000..c9dcb8990d39fdf44f97bdbb4fd530ddebf2f838
--- /dev/null
+++ b/fireInIce/2_visualize/src/xs_process.py
@@ -0,0 +1,443 @@
+#import libraries
+import os, sys, importlib
+import geopandas as gpd
+from osgeo import gdal, osr
+import numpy as np
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+from pyproj import CRS
+from pyproj.aoi import AreaOfInterest
+from pyproj.database import query_utm_crs_info
+from shapely.geometry import Polygon
+from scipy.interpolate import RegularGridInterpolator
+from scipy.stats import linregress
+from scipy import ndimage
+from svgpath2mpl import parse_path
+
+#get parent path
+parent = os.getcwd()
+
+# get custom functions
+sys.path.insert(1, "0_fetch/src")
+from download_dem import get_shapefile_extent, buffer_shapefile, snakemake_type_exists
+sys.path.insert(1, "2_visualize/src")
+from xs_functions import translatexy, align_marker, scale_bar_arm
+
+#change the font to universe condensed
+mpl.font_manager.fontManager.addfont(parent + '/font/Univers-Condensed.otf')
+font_prop = mpl.font_manager.FontProperties(fname= parent + '/font/Univers-Condensed.otf')
+mpl.rcParams["font.family"] = "sans-serif"
+mpl.rcParams["font.sans-serif"] = [font_prop.get_name()]
+mpl.rcParams['svg.fonttype'] = 'none'
+mpl.rcParams["font.size"] = 18
+tutorial_fontsize = 28
+north_fontsize = 21
+
+# number of cross sections
+points = 201
+
+# number of sampling points making up cross section
+xs_points = 301
+
+# starting location x space
+x_start = 538000.
+
+# ending location x space
+x_end = 550100.
+
+# width of cross section
+width = 50000.
+
+# figure dimensions
+fig_width = 8.0
+fig_height = 8.0
+fig_buffer_bottom = 0.66
+fig_buffer_left = 0.6
+fig_buffer_right = 0.15
+fig_buffer_between = 0.3
+render_height = 5.
+
+# map adjustment
+map_offset_y = 0.0
+map_offset_x = 0.0
+map_width = 110000.
+
+#core marker and line colors
+core_color = 'tab:blue'
+core_line_color = 'tab:blue'
+
+#cross section map line thickness
+ar_base = 2.0
+
+# lower limit of the cross section plot
+lower_limit = -500
+
+#scale bar parameters
+scale_bar_rel_x = 0.325
+scale_bar_rel_y = 0.3
+scale_bar_length = 16000
+scale_bar_height = 1000
+scale_bar_line_width = 1.0
+
+#north arrow parameters
+north_scale_x = -.35
+north_rel_y = scale_bar_rel_y + 0.0075
+N_loc = (0.85,-0.55)
+
+def get_raster_extent(dataset):
+ ulx, xres, xskew, uly, yskew, yres = dataset.GetGeoTransform()
+ lrx = ulx + (dataset.RasterXSize * xres)
+ lry = uly + (dataset.RasterYSize * yres)
+ return ulx, lrx, lry, uly
+
+def project(file, map_crs, tmp_dir, dummy):
+
+ # read in the dem as a numpy array
+ ds = gdal.Open(file)
+ array = np.array(ds.GetRasterBand(1).ReadAsArray())
+
+ # reproject dem
+ if dummy == True:
+ prefix = "/dummy_proj"
+ else:
+ prefix = "/proj_"
+ proj_ds = gdal.Warp(tmp_dir + prefix + os.path.basename(file), ds, dstSRS=map_crs)
+ proj_array = np.array(proj_ds.GetRasterBand(1).ReadAsArray())
+
+ # get min and max of dem
+ NaN = proj_ds.GetRasterBand(1).GetNoDataValue()
+ if NaN != None:
+ if np.isnan(NaN):
+ min_array = np.nanmin(proj_array[~np.isnan(proj_array)])
+ max_array = np.nanmax(proj_array[~np.isnan(proj_array)])
+ else:
+ min_array = np.nanmin(proj_array[proj_array != NaN])
+ max_array = np.nanmax(proj_array[proj_array != NaN])
+ else:
+ min_array = np.nanmin(proj_array)
+ max_array = np.nanmax(proj_array)
+
+ return proj_array, proj_ds, min_array, max_array
+
+
+#main function to make the cross-section
+def main(
+ photo_indices,
+ photo_locations,
+ default_plot,
+ extent_shpfile,
+ demfile,
+ layerfile,
+ renderfile,
+ core_shpfile,
+ xs_file, xs_svg_file
+):
+
+ # make out_dir if it doesn't exist
+ out_dir = os.path.dirname(xs_file)
+ if not os.path.exists(out_dir):
+ os.makedirs(out_dir)
+
+ tmp_dir = out_dir.replace("out","tmp")
+ # make tmp_dir if it doesn't exist
+ if not os.path.exists(tmp_dir):
+ os.makedirs(tmp_dir)
+
+ # get UTM zone for reprojection
+ utm_crs = gpd.read_file(extent_shpfile).estimate_utm_crs()
+
+ # read in the dem and ice layer as a numpy array
+ proj_dem, proj_ds, min_dem, max_dem = project(demfile,utm_crs,tmp_dir,True)
+ proj_layer, proj_ds_layer, min_layer, max_layer = project(layerfile,utm_crs,tmp_dir,True)
+
+ # load extent mask
+ extent_shp = gpd.read_file(extent_shpfile).to_crs(utm_crs)
+ west, east, length, south, north, height = get_shapefile_extent(extent_shp)
+ # make mask covering extent
+ buff_west, buff_east, buff_south, buff_north = buffer_shapefile(
+ west, east, length, south, north, height, 25.0
+ )
+
+ # build interpolators to sampling data from dem and ice field
+ extent = list(get_raster_extent(proj_ds))
+ x = np.linspace(extent[0],extent[1],proj_dem.shape[1])
+ y = np.linspace(extent[3],extent[2],proj_dem.shape[0])
+ interpol = RegularGridInterpolator((y,x),proj_dem,method="linear")
+ interpol_L = RegularGridInterpolator((y,x),proj_layer,method="linear")
+ xx = np.linspace(extent[0],extent[1],300)
+ yy = np.linspace(extent[3],extent[2],200)#
+ Y, X = np.meshgrid(yy, xx, indexing='ij')
+
+ #get photo data
+ photo_shp = gpd.read_file(photo_locations).to_crs(utm_crs)
+
+ #get the least squared residual line from the core locations
+ core_shp = gpd.read_file(core_shpfile).to_crs(utm_crs)
+ res = linregress(core_shp.geometry.x,core_shp.geometry.y)
+ y_start = x_start * res.slope + res.intercept
+ y_end = x_end * res.slope + res.intercept
+ x_track = np.linspace(x_start,x_end,points)
+ y_track = np.linspace(y_start,y_end,points)
+ slope = (y_end - y_start) / (x_end - x_start)
+ angle = np.arctan(np.abs(slope))
+
+ #get the dx and dy from the LSRL
+ y_decomp = np.cos(angle) * width / 2.0
+ x_decomp = -np.sin(angle) * width / 2.0
+
+ # get aspect of the rendered image
+ render_aspect = render_height / (fig_width - fig_buffer_left - fig_buffer_right)
+
+ # get height of map
+ map_height = map_width * render_aspect
+
+ # get center of map
+ map_center_x = 0.5 * (buff_west + buff_east)
+ map_center_y = 0.5 * (buff_north + buff_south)
+
+ # make figure and axis
+ fig_xs = plt.figure(1,figsize=(fig_width,fig_height),facecolor='w')
+
+ # axis with map
+ ax_texturemap = fig_xs.add_axes([fig_buffer_left/fig_width,
+ (fig_height - render_height)/fig_height,
+ 1.0 - (fig_buffer_left+fig_buffer_right)/fig_width,
+ render_height/fig_height])
+ # set map bounds
+ ax_texturemap.set_xlim(map_center_x - map_width * 0.5 + map_offset_x, map_center_x + map_width * 0.5 + map_offset_x)
+ ax_texturemap.set_ylim(map_center_y - map_height * 0.5 + map_offset_y, map_center_y + map_height * 0.5 + map_offset_y)
+ ax_texturemap.axis('off')
+
+ # axis with cross-section
+ ax_xs = fig_xs.add_axes([fig_buffer_left/fig_width,
+ fig_buffer_bottom/fig_height,
+ 1.0 - (fig_buffer_left+fig_buffer_right)/fig_width,
+ (fig_height - render_height - fig_buffer_between - fig_buffer_bottom)/fig_height])
+
+ #read in render and rotate it so the LSRL is pointing northward
+ render = plt.imread(renderfile)
+ render = ndimage.rotate(render,90.-angle*180./np.pi,reshape=False)
+ ax_texturemap.imshow(render,zorder=1,extent=[buff_west,buff_east,buff_south,buff_north],alpha=1.0)
+
+ #rotate the cores aroudn the raster center
+ core_shp_rot = core_shp.rotate(90.-angle*180./np.pi,(0.5*(buff_west+buff_east),0.5*(buff_south+buff_north)))
+
+ #rotate photo cores around the raster center
+ photo_shp_rot = photo_shp.rotate(90.-angle*180./np.pi,(0.5*(buff_west+buff_east),0.5*(buff_south+buff_north)))
+
+ #rotate LSRL (around raster center)
+ x_rot_track,y_rot_track = translatexy(x_track,y_track,\
+ 0.5*(buff_east+buff_west),0.5*(buff_south+buff_north),\
+ np.pi/2.0-angle)
+
+ #LSRL "zone"
+ ax_texturemap.plot(x_rot_track - width/2.0,y_rot_track,color='k',zorder=2,linestyle='--',linewidth=1,alpha=1.0)
+ ax_texturemap.plot(x_rot_track + width/2.0,y_rot_track,color='k',zorder=2,linestyle='--',linewidth=1,alpha=1.0)
+ ax_texturemap.fill_between([x_rot_track[0] - width/2.0, x_rot_track[0] + width/2.0],[y_rot_track[0]-height,y_rot_track[0]-height],[y_rot_track[0],y_rot_track[0]],edgecolor=(0.0,0.0,0.0,0.0),facecolor=(1.0,1.0,1.0,0.25))
+ ax_texturemap.fill_between([x_rot_track[0] - width/2.0, x_rot_track[0] + width/2.0],[y_rot_track[-1],y_rot_track[-1]],[y_rot_track[-1]+height,y_rot_track[-1]+height],edgecolor=(0.0,0.0,0.0,0.0),facecolor=(1.0,1.0,1.0,0.25))
+ ax_texturemap.fill_between([x_rot_track[0] - length, x_rot_track[0] - width/2.0],[y_rot_track[0]-height,y_rot_track[0]-height],[y_rot_track[-1]+height,y_rot_track[-1]+height],edgecolor=(0.0,0.0,0.0,0.0),facecolor=(1.0,1.0,1.0,0.25))
+ ax_texturemap.fill_between([x_rot_track[0] + width/2.0, x_rot_track[0] + length],[y_rot_track[0]-height,y_rot_track[0]-height],[y_rot_track[-1]+height,y_rot_track[-1]+height],edgecolor=(0.0,0.0,0.0,0.0),facecolor=(1.0,1.0,1.0,0.25))
+
+ # x coordinates for the cross section
+ x_xs=np.linspace(0,width,xs_points)
+
+ #camera svg
+ camicon = parse_path("""M521.5,170.5v289H54.5V170.5h161v.5H55v288h466V171h-160.5v-.5h161ZM216,117h144v53.5h.5v-54h-145v54h.5v-53.5ZM360,171h.5v.5h160v287H55.5V171.5h160v-.5h.5v-.5h.5v-53h143v53h.5v.5Z""")
+ # Calculate the extent
+ min_x = camicon.vertices[:, 0].min()
+ max_x = camicon.vertices[:, 0].max()
+ min_y = camicon.vertices[:, 1].min()
+ max_y = camicon.vertices[:, 1].max()
+
+ # Calculate the center of the extent
+ center_x = (min_x + max_x) / 2
+ center_y = (min_y + max_y) / 2
+
+ # Center the icon using the extent
+ camicon.vertices -= np.array([center_x, center_y])
+ camicon = camicon.transformed(mpl.transforms.Affine2D().rotate_deg(180))
+ camicon = camicon.transformed(mpl.transforms.Affine2D().scale(-1,1))
+
+ # drill svg
+ drillicon = parse_path("""M.5,288.5V.5h72v288l-36,36.4L.5,288.9""")
+ # centered drill svg for legend
+ cent_drillicon = parse_path("""M.5,288.5V.5h72v288l-36,36.4L.5,288.9""")
+
+ # Calculate the extent
+ min_x = drillicon.vertices[:, 0].min()
+ max_x = drillicon.vertices[:, 0].max()
+ min_y = drillicon.vertices[:, 1].min()
+ max_y = drillicon.vertices[:, 1].max()
+
+ # Calculate the center of the extent
+ center_x = (min_x + max_x) / 2
+ center_y = (min_y + max_y) / 2
+
+ # Center the icon using the extent
+ drillicon.vertices -= np.array([center_x, max_y])
+ drillicon = drillicon.transformed(mpl.transforms.Affine2D().rotate_deg(180))
+ drillicon = drillicon.transformed(mpl.transforms.Affine2D().scale(-1,1))
+
+ # Center the icon using the extent
+ cent_drillicon.vertices -= np.array([center_x, center_y])
+ cent_drillicon = cent_drillicon.transformed(mpl.transforms.Affine2D().rotate_deg(180))
+ cent_drillicon = cent_drillicon.transformed(mpl.transforms.Affine2D().scale(-1,1))
+
+ #find where the core is closest to the cross-section lines.
+ core_ids = []
+ for i in range(len(core_shp_rot.geometry.y)):
+ core_ids += [np.argmin(np.abs(y_rot_track-core_shp_rot.geometry.y[i]))]
+
+ photo_ids = []
+ for i in photo_indices:
+ photo_ids += [np.argmin(np.abs(y_rot_track-photo_shp_rot.geometry.y[i]))]
+
+ # plot the cross seciton lines
+ for i in range(0,points):
+ if i == default_plot:
+ alpha_plot = 0.8
+ else:
+ alpha_plot = 0.0
+ #get the cross section x and y locations
+ xs = np.linspace(x_track[i] - x_decomp, x_track[i] + x_decomp, xs_points)
+ ys = np.linspace(y_track[i] - y_decomp, y_track[i] + y_decomp, xs_points)
+ #get the cross section x and y locations in the rotated view
+ xs_rot = np.linspace(x_rot_track[i] - width/2.0, x_rot_track[i] + width/2.0, xs_points)
+ ys_rot = np.linspace(y_rot_track[i] , y_rot_track[i] , xs_points)
+
+ #if the cross section is one that has a core in it, plot the line in a different color, otherwise black
+ for j, core_i in enumerate(core_ids):
+ if core_i == i:
+ ax_texturemap.plot(xs_rot,ys_rot,color=core_line_color,alpha=alpha_plot,gid='xs-main-'+str(i),zorder=3,linewidth=ar_base)
+ if (i in core_ids) == False:
+ ax_texturemap.plot(xs_rot,ys_rot,color='k',alpha=alpha_plot,gid='xs-main-'+str(i),zorder=3,linewidth=ar_base)
+ #find the bedrock elevation along the cross section
+ topo_layer = interpol((ys,xs))
+ #plot the bedrock topography
+ ax_xs.fill_between(x_xs,lower_limit*np.ones_like(x_xs),topo_layer,alpha=alpha_plot,zorder=2,gid='xs-topo-'+str(i),edgecolor=(0.,0.,0.,0.2),facecolor="#c49051")
+ #find the ice elevation along the cross section
+ ice_layer = interpol_L((ys,xs))
+ #if the ice topography is "below" the bedrock, just make it the same as the bedrock
+ ice_layer[ice_layer<topo_layer]=topo_layer[ice_layer<topo_layer]
+ #plot the ice topography
+ ax_xs.fill_between(x_xs,lower_limit*np.ones_like(x_xs),ice_layer,alpha=alpha_plot,zorder=1,gid='xs-ice-'+str(i),edgecolor=(0.,0.,0.,0.2),facecolor='#dddddd')
+ #if the cross section is one that has the core in it, find the elevation of the core location and plot the core on the cross-section plot
+ for j, core_i in enumerate(core_ids):
+ if core_i == i:
+ distance = ((core_shp.geometry.y[j]-ys[0])**2.0+(core_shp.geometry.x[j]-xs[0])**2.0) ** 0.5
+ x_xs_i = np.argmin(abs(distance-x_xs))
+ ax_texturemap.scatter(core_shp_rot.geometry.x[j],core_shp_rot.geometry.y[j],facecolor=core_color,edgecolor='k',linewidth=1.0,marker=drillicon,s=3201+i/1000,alpha=0.8,zorder=1001,gid='xs-c-lg-'+str(i))
+ ax_xs.scatter(x_xs[x_xs_i],ice_layer[x_xs_i],facecolor=core_color,edgecolor='k',linewidth=1.0,marker=drillicon,s=3200+i/1000,zorder=1001,clip_on=False,gid='xs-c-sm-'+str(i),alpha=alpha_plot)
+ # draw camera locations
+ for j, core_i in enumerate(photo_ids):
+ if core_i == i:
+ photo_index = photo_indices[j]
+ distance = ((photo_shp.geometry.y[photo_index ]-ys[0])**2.0+(photo_shp.geometry.x[photo_index ]-xs[0])**2.0) ** 0.5
+ x_xs_i = np.argmin(abs(distance-x_xs))
+ ax_texturemap.scatter(photo_shp_rot.geometry.x[photo_index],photo_shp_rot.geometry.y[photo_index],facecolor="tab:red",edgecolor='k',linewidth=1.0,marker=camicon,s=400+i/1000,zorder=1000,alpha=0.8,gid='photo-lg-'+str(photo_index).zfill(3)+'-'+str(i))
+ ax_xs.scatter(x_xs[x_xs_i],ice_layer[x_xs_i],facecolor="tab:red",edgecolor='k',linewidth=1.0,marker=camicon,s=401+i/1000,zorder=1000,alpha=alpha_plot,gid='photo-sm-'+str(photo_index).zfill(3)+'-'+str(i))
+
+ #legend
+ ax_texturemap.scatter(0,0,facecolor=core_color,edgecolor='k',linewidth=1.0,marker=cent_drillicon,s=802,label='Ice Core')
+ ax_texturemap.scatter(0,0,facecolor="tab:red",edgecolor='k',linewidth=1.0,marker=camicon,s=402,alpha=0.8,label='Photo')
+ ax_texturemap.legend(loc='right',bbox_to_anchor=(1.01, 0.5),facecolor='w',edgecolor='none',framealpha=0.75, fancybox=False,markerfirst=True)
+
+ #make the scale bar
+ sclx1 = buff_west + (buff_east-buff_west) * scale_bar_rel_x
+ sclx2 = sclx1 + scale_bar_length
+ scly1 = buff_south + (buff_north-buff_south) * scale_bar_rel_y
+ scly2 = scly1 + scale_bar_height
+ ax_texturemap.plot([sclx1,sclx2],[scly1,scly1],
+ color = 'k',linewidth=scale_bar_line_width,clip_on=False,zorder=6)
+
+ for prop in [0,1.0/2.0,1.0]:
+ if prop == 1:
+ label = str(round(prop*scale_bar_length/1000.)) + ' km'
+ else:
+ label = str(round(prop*scale_bar_length/1000.))
+ scale_bar_arm((1.0-prop)*sclx1+prop*sclx2,scly1,scly2,label,100,ax_texturemap,scale_bar_line_width)
+
+ #make north arrow
+ northx = (1.0-north_scale_x)*sclx1+north_scale_x*sclx2
+ northy = buff_south + (buff_north-buff_south) * north_rel_y
+ north_arrow_length = 5500
+ north_arrow = mpl.patches.FancyArrowPatch((northx, northy),(northx - np.sin(np.pi/2.0-angle) * north_arrow_length, northy + np.cos(np.pi/2.0-angle) * north_arrow_length) ,
+ arrowstyle='simple,head_length=0.4,head_width=0.5,tail_width=0.2', mutation_scale=20,facecolor='k',edgecolor='k',zorder=6)
+ ax_texturemap.add_patch(north_arrow)
+ ax_texturemap.annotate('N',N_loc,xycoords=north_arrow,ha='center', va='center',fontweight='bold',fontsize=north_fontsize,zorder=6)
+
+ #white box around scale bar to improve readibility
+ scale_box = mpl.patches.Rectangle((0.01,0.01),0.27,0.15,transform = ax_texturemap.transAxes,facecolor='w',edgecolor='none',alpha=0.75)
+ ax_texturemap.add_patch(scale_box)
+
+ # tutorial
+ ax_texturemap.text(0.01,0.99,"Hover to MRI\nthe glacier!",
+ transform=ax_texturemap.transAxes,fontweight='bold',va='top',ha='left',fontsize=tutorial_fontsize,zorder=6,
+ bbox=dict(facecolor='w', alpha=0.7, edgecolor="none",pad=2.0),gid='tutorial-dt-1')
+
+ ax_texturemap.text(0.99,0.625,"Hover over\npoints of\ninterest!",
+ transform=ax_texturemap.transAxes,fontweight='bold',va='bottom',ha='right',fontsize=tutorial_fontsize,zorder=6,
+ bbox=dict(facecolor='w', alpha=0.7, edgecolor="none",pad=2.0),gid='tutorial-dt-2')
+
+ ax_texturemap.text(0.01,0.99,"Click to MRI\nthe glacier!",
+ transform=ax_texturemap.transAxes,fontweight='bold',va='top',ha='left',fontsize=tutorial_fontsize,zorder=6,
+ bbox=dict(facecolor='w', alpha=0.0, edgecolor="none",pad=2.0),gid='tutorial-mb-1',alpha=0.0)
+
+ ax_texturemap.text(0.99,0.625,"Click on\npoints of\ninterest!",
+ transform=ax_texturemap.transAxes,fontweight='bold',va='bottom',ha='right',fontsize=tutorial_fontsize,zorder=6,
+ bbox=dict(facecolor='w', alpha=0.0, edgecolor="none",pad=2.0),gid='tutorial-mb-2',alpha=0.0)
+
+ # tutorial arrow
+ tutorial_arrow = mpl.patches.FancyArrowPatch((0.32,0.95),(0.45,0.55) , transform = ax_texturemap.transAxes, gid = "tutorial_arrow",
+ arrowstyle='simple,head_length=0.8,head_width=0.8,tail_width=0.3', alpha = 0.75, mutation_scale=20,facecolor='k',edgecolor='none',connectionstyle='arc3,rad=-0.3',zorder=6)
+ ax_texturemap.add_patch(tutorial_arrow)
+
+ #cross section axis properties
+ ax_xs.fill_between([-10,10],[0,0],[1,1],alpha=1.0,zorder=0,edgecolor='none',label='Ice',facecolor="#dddddd")
+ ax_xs.fill_between([-10,10],[0,0],[1,1],alpha=1.0,zorder=0,edgecolor='none',label='Rock',facecolor="#c49051")
+ ax_xs.set_xlim(x_xs[-1],x_xs[0])
+ ax_xs.set_ylim(lower_limit,2500)
+ ax_xs.set_yticks([0,1000,2000,3000,4000],[0,1,2,3,4])
+ leg = ax_xs.legend(loc='upper right',facecolor='none',edgecolor='none',markerfirst=True,ncol=1)
+ bb = leg.get_bbox_to_anchor().transformed(ax_xs.transAxes.inverted())
+
+ # Change to location of the legend.
+ bb.y1 += 0.2
+ leg.set_bbox_to_anchor(bb, transform = ax_xs.transAxes)
+ ax_xs.spines["top"].set_visible(False)
+ ax_xs.spines["right"].set_visible(False)
+ ax_xs.set_ylabel('Elevation (km)')
+ ax_xs.set_xlabel('Cross-Sectional Distance (km)')
+
+ #x ticks
+ x_ticks = 5
+ x_tick_locs = [x_xs[-1]+float(i)/float(x_ticks)*(x_xs[0]-x_xs[-1]) for i in range(0,x_ticks+1)]
+ x_tick_labs = [int(width * float(i) / float(x_ticks) / 1000) for i in range(0,x_ticks+1)]
+ ax_xs.set_xticks(x_tick_locs,x_tick_labs)
+
+ #save the figure
+ fig_xs.savefig(xs_svg_file, dpi=240, transparent=True)
+ fig_xs.savefig(xs_file, dpi=240)
+
+if __name__ == "__main__":
+ photo_indices = snakemake.params["photo_indices"]
+ default_plot = snakemake.params["default_plot"]
+ extent_shpfile = snakemake.input["extent_shpfile"]
+ demfile = snakemake.input["demfile"]
+ photo_locations = snakemake.input["photo_locations"]
+ core_shpfile = snakemake.input["core_shpfile"]
+ layerfile = snakemake_type_exists(snakemake.input,"layerfile","NULL")
+ renderfile = snakemake.input["renderfile"]
+ xs_file = snakemake.output["xs_file"]
+ xs_svg_file = snakemake.output["xs_svg_file"]
+ main(
+ photo_indices,
+ photo_locations,
+ default_plot,
+ extent_shpfile,
+ demfile,
+ layerfile,
+ renderfile,
+ core_shpfile,
+ xs_file, xs_svg_file
+ )
diff --git a/fireInIce/Snakefile_glacial_scan b/fireInIce/Snakefile_glacial_scan
new file mode 100644
index 0000000000000000000000000000000000000000..099526520fef1518b86b1bd1b0b20cf24540f46c
--- /dev/null
+++ b/fireInIce/Snakefile_glacial_scan
@@ -0,0 +1,134 @@
+sb_id = "5e472c3ee4b0ff554f6837bc"
+
+rule all:
+ input:
+ "2_visualize/out/xs_19010301and19010304.svg",
+ "data_out/glacial_mri.svg"
+
+# download sb item 5e472c3ee4b0ff554f6837bc
+rule download_FI_DATA:
+ params:
+ sb_id = sb_id
+ output:
+ zipfile = "0_fetch/tmp/"+sb_id+".zip"
+ script:
+ "0_fetch/src/download_sb.py"
+
+# unzip the sb item 5e472c3ee4b0ff554f6837bc
+rule unzip_FI_DATA:
+ input:
+ zipfile = "0_fetch/tmp/"+sb_id+".zip"
+ output:
+ "0_fetch/tmp/"+sb_id+"/Juneau Icefield Alaska Map.jpg",
+ "0_fetch/tmp/"+sb_id+"/Metadata Juneau Icefield.xml",
+ "0_fetch/tmp/"+sb_id+"/Table 1 Site Locations.xlsx",
+ "0_fetch/tmp/"+sb_id+"/Table 2 Constituents Analyzed.xlsx",
+ "0_fetch/tmp/"+sb_id+"/Table 3 Quality Assurance.xlsx",
+ "0_fetch/tmp/"+sb_id+"/Table 4 Constituent Data.xlsx"
+ script:
+ "0_fetch/src/unzip_file.py"
+
+# get the extent, a combo of HUC 19010301 and 19010304
+rule get_wbd:
+ params:
+ huc_list = lambda wildcards: f"{wildcards.huc_id}".split("and")
+ output:
+ extent_shpfile = "0_fetch/out/{huc_id}/extent.shp"
+ script:
+ "0_fetch/src/get_wbd.py"
+
+# download the dem over the extent
+rule download_dem:
+ params:
+ data_product = '/API/globaldem',
+ dem_product = 'COP90',
+ buffer = 5.0,
+ download_mode = 'bmi'
+ input:
+ extent_shpfile = "0_fetch/out/{huc_id}/extent.shp"
+ output:
+ demfile = "0_fetch/out/{huc_id}/dem.tif"
+ script:
+ "0_fetch/src/download_dem.py"
+
+#"0_fetch/tmp/RGI-2.zip" was downloaded from here: https://doi.org/10.6096/1007
+#Western Canada and USA
+rule unzip_ice_thickness:
+ input:
+ zipfile = "0_fetch/tmp/RGI-2.zip"
+ output:
+ "0_fetch/tmp/RGI-2/RGI-2/THICKNESS_RGI-2.1_2021July09.tif"
+ script:
+ "0_fetch/src/unzip_file.py"
+
+# regrid the ice thickness data to have the same grid as the dem
+rule regrid_ice_thickness:
+ input:
+ src_file = "0_fetch/tmp/RGI-2/RGI-2/THICKNESS_RGI-2.1_2021July09.tif",
+ match_file = "0_fetch/out/{huc_id}/dem.tif"
+ output:
+ dst_file = "1_process/tmp/{huc_id}/unfilled_ice_thickness.tif"
+ script:
+ "1_process/src/regrid.py"
+
+# remove the NaNs and fill via interpolation
+rule remove_nans:
+ params:
+ convolution_window = 4.0
+ input:
+ ice_thickness_file = "1_process/tmp/{huc_id}/unfilled_ice_thickness.tif"
+ output:
+ ice_thickness_file = "1_process/tmp/{huc_id}/ice_thickness.tif"
+ script:
+ "1_process/src/remove_nans.py"
+
+# make a shapefile of the cores from the sb item 5e472c3ee4b0ff554f6837bc
+rule make_core_shpfile:
+ input:
+ core_data = '0_fetch/tmp/5e472c3ee4b0ff554f6837bc/Table 1 Site Locations.xlsx'
+ output:
+ core_shpfile = "1_process/out/{huc_id}/core_locations.shp"
+ script:
+ "1_process/src/cores_to_shp.py"
+
+# Calculate bedrock by subtracting ice thickness from the surface elevation
+rule calc_bedrock:
+ input:
+ dem_file = "0_fetch/out/{huc_id}/dem.tif",
+ ice_thickness_file = "1_process/tmp/{huc_id}/ice_thickness.tif"
+ output:
+ bedrock_file = "1_process/tmp/{huc_id}/bedrock.tif",
+ ice_height_file = "1_process/tmp/{huc_id}/ice_height.tif"
+ script:
+ "1_process/src/calc_bedrock.py"
+
+# create the map vs. cross section plot
+# renderfile is a basemap generated in Blender using the following sources:
+# DEM: https://portal.opentopography.org/raster?opentopoID=OTSDEM.032021.4326.1
+# Ice Thickness https://doi.org/10.6096/1007
+# NHD files were downloaded using PyNHD: https://doi.org/10.21105/joss.03175
+rule create_xs:
+ params:
+ default_plot = 113,
+ photo_indices = [10,18,21,51,85,138,140,156,203]
+ input:
+ extent_shpfile = "0_fetch/out/{huc_id}/extent.shp",
+ demfile = "1_process/tmp/{huc_id}/bedrock.tif",
+ layerfile = "1_process/tmp/{huc_id}/ice_height.tif",
+ renderfile = "2_visualize/in/render_{huc_id}.png",
+ photo_locations = '2_visualize/in/photo_locations.shp',
+ core_shpfile = "1_process/out/{huc_id}/core_locations.shp"
+ output:
+ xs_file = "2_visualize/out/xs_{huc_id}.png",
+ xs_svg_file = "2_visualize/out/xs_{huc_id}.svg"
+ script:
+ "2_visualize/src/xs_process.py"
+
+# remove the metadata from the svg and save into the data_out folder
+rule remove_metadata:
+ input:
+ infile = "2_visualize/out/xs_19010301and19010304.svg"
+ output:
+ outfile = "data_out/glacial_mri.svg",
+ script:
+ "2_visualize/src/remove_metadata.py"
\ No newline at end of file
diff --git a/fireInIce/Snakefile_regional_fires b/fireInIce/Snakefile_regional_fires
new file mode 100644
index 0000000000000000000000000000000000000000..f7f468bdc4d99ae9118b841f220c3127d2e6931f
--- /dev/null
+++ b/fireInIce/Snakefile_regional_fires
@@ -0,0 +1,34 @@
+rule all:
+ input:
+ "data_out/regional_fires_map.svg"
+
+# tdump files were generated with NOAA's HYSPLIT model using archive trajectories: https://www.ready.noaa.gov/hypub-bin/trajtype.pl?runtype=archive
+# forward trajectories from the two fires, dennison fork 2015 wildfire and the steamboat creek 2016 wildfire were generated
+# HYSPLIT model's parameters were taken from https://iopscience.iop.org/article/10.1088/1748-9326/ab8fd2/pdf
+
+# This makes the svg map for the regional fires viz
+# renderfile is a basemap generated in Blender using the following sources:
+# DEM: https://portal.opentopography.org/raster?opentopoID=OTSRTM.122019.4326.1
+# Ice Thickness https://doi.org/10.6096/1007
+rule regional_fires_map:
+ params:
+ fires = 2,
+ fire_labels = ["Dennison Fork\n2015 Wildfire","Steamboat Creek\n2016 Wildfire"]
+ input:
+ renderfile = "2_visualize/in/render_{name}.png",
+ extent_shpfile = "2_visualize/in/extent_{name}.shp",
+ forward_trajectory_files = ["2_visualize/in/tdump.111986.txt","2_visualize/in/tdump.160303.txt"]
+ output:
+ regional_fires_mapfile = "2_visualize/out/{name}_map.png",
+ regional_fires_svg_mapfile = "2_visualize/out/{name}_map.svg"
+ script:
+ "2_visualize/src/regional_fires_map.py"
+
+# remove the metadata from the svg and save into the data_out folder
+rule remove_metadata:
+ input:
+ infile = "2_visualize/out/{name}_map.svg"
+ output:
+ outfile = "data_out/{name}_map.svg"
+ script:
+ "2_visualize/src/remove_metadata.py"
\ No newline at end of file
diff --git a/fireInIce/environment.yaml b/fireInIce/environment.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..5b173c7ea59c62c311ab03f408d7132d7cb95bbc
--- /dev/null
+++ b/fireInIce/environment.yaml
@@ -0,0 +1,30 @@
+name: climate-chart
+channels:
+ - conda-forge
+ - bioconda
+dependencies:
+ - python
+ - pip
+ - mamba
+ - snakemake
+ - pandas
+ - numpy
+ - py7zr
+ - matplotlib
+ - gdal
+ - geopandas
+ - py3dep
+ - pynhd
+ - pygeohydro
+ - earthengine-api
+ - basemap
+ - rasterio
+ - astropy
+ - utm
+ - openpyxl
+ - opencv
+ - svgpath2mpl
+ - pip:
+ - sciencebasepy
+ - git+https://github.com/jeffskwang/bmi-topography-usgs.git
+ - exif
\ No newline at end of file
diff --git a/fireInIce/font/Univers-Condensed.otf b/fireInIce/font/Univers-Condensed.otf
new file mode 100644
index 0000000000000000000000000000000000000000..dc811d4a0a57d279734a8ad4067039522dec9e7e
Binary files /dev/null and b/fireInIce/font/Univers-Condensed.otf differ