revert to strict reqs

npucino · Oct 9, 2021 · 94e5ae3 · 94e5ae3
1 parent 24dd6f7
commit 94e5ae3
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Showing 4 changed files with 41 additions and 42 deletions.
diff --git a/requirements.txt b/requirements.txt
@@ -1,11 +1,14 @@
-geopandas
-pandas
-pysal
-rasterio
-richdem
-scikit-image
-scikit-learn
-seaborn
-tqdm
-pooch
+geopandas==0.8.2
+matplotlib==3.3.4
+numpy==1.20.1
+pandas==1.2.2
+pysal==2.1
+rasterio==1.2.0
+richdem==0.3.4
+scikit-image==0.18.1
+scikit-learn==0.24.1
+scipy==1.6.0
+seaborn==0.11.1
+tqdm==4.56.2
+pooch==1.4.0
 fuzzywuzzy
diff --git a/sandpyper/common.py b/sandpyper/common.py
@@ -61,16 +61,16 @@
 
 from pysal.lib import weights
 
-#import pysal.explore.esda.moran as moran
-#from pysal.explore.esda.util import fdr
-from esda import moran
-from esda.util import fdr
+import pysal.explore.esda.moran as moran
+from pysal.explore.esda.util import fdr
+#from esda import moran
+#from esda.util import fdr
 
-#from pysal.explore.giddy.markov import Markov
-from giddy.markov import Markov
+from pysal.explore.giddy.markov import Markov
+#from giddy.markov import Markov
 
-#from pysal.lib.weights import DistanceBand, Queen, higher_order
-from libpysal.weights import DistanceBand, Queen, higher_order
+from pysal.lib.weights import DistanceBand, Queen, higher_order
+#from libpysal.weights import DistanceBand, Queen, higher_order
 
 from pysal.viz.mapclassify import (EqualInterval,
  FisherJenks,
@@ -1633,7 +1633,7 @@ def get_rbcd_transect(df_labelled, loc_specs, reliable_action, dirNameTrans, lab
  ).geometry
 
  ss_transects_idx_loc = gpd.GeoDataFrame(
- merged_erodepo, geometry="geometry", crs=CRS.from_epsg(crs_dict_string[loc]))
+ merged_erodepo, geometry="geometry", crs=crs_dict_string[loc] )
 
  ss_transects_idx=pd.concat([ss_transects_idx_loc,ss_transects_idx], ignore_index=True)
 
@@ -2272,7 +2272,7 @@ def cleanit(to_clean, l_dicts, cluster_field='label_k', fill_class='sand',
  selection=data_in[data_in.coordinates.intersects(row.geometry)]
 
  if selection.shape[0]==0:
- selection=data_in[data_in.to_crs(CRS.from_epsg(crs_dict_string[loc])).coordinates.intersects(row.geometry)]
+ selection=data_in[data_in.to_crs(crs_dict_string[loc] ).coordinates.intersects(row.geometry)]
  else:
  pass
  selection["finetuned_label"]=new_class
@@ -2346,7 +2346,7 @@ def cleanit(to_clean, l_dicts, cluster_field='label_k', fill_class='sand',
  selection=subset_data[subset_data.geometry.intersects(subset_masks.geometry)]
  if selection.shape[0]==0:
  print(f"Reprojecting")
- selection=subset_data[subset_data.geometry.intersects(subset_masks.to_crs(CRS.from_epsg(crs_dict_string[loc])).geometry.any())]
+ selection=subset_data[subset_data.geometry.intersects(subset_masks.to_crs(crs_dict_string[loc]).geometry.any())]
  else:
  pass
 
@@ -2415,7 +2415,7 @@ def cleanit(to_clean, l_dicts, cluster_field='label_k', fill_class='sand',
  if in_shore.shape[0]>=1:
  pass
  else:
- in_shore=loc_selection[loc_selection.geometry.intersects(shore.to_crs(CRS.from_epsg(crs_dict_string[loc])).geometry.any())]
+ in_shore=loc_selection[loc_selection.geometry.intersects(shore.to_crs(crs_dict_string[loc]).geometry.any())]
 
  print(f"Removing {loc_selection.shape[0] - in_shore.shape[0]} pts falling outside provided shore polygones.")
  inshore_cleaned=pd.concat([in_shore,inshore_cleaned], ignore_index=True)
@@ -4198,7 +4198,7 @@ def error_from_gt(
  Returns:
  pd.DataFrame: Dataframe containing the distances from groundtruth at each timestep.
  """
- crs = CRS.from_epsg(crs_dict_string[loc])
+ crs = crs_dict_string[loc]
 
  if os.path.isfile(baseline_mode):
  print("Fixed baseline mode selected.")
@@ -4530,7 +4530,7 @@ def tidal_correction(
  gt_shores = cs_shores.query(
  f"location=='{location}' & raw_date in @list_dates"
  ) # get groudtruths shores
- crs = CRS.from_epsg(crs_dict_string[loc]) # get crs of location
+ crs = crs_dict_string[loc] # get crs of location
 
  if shores_to_corr.crs != crs:
  shores_to_corr = shores_to_corr.to_crs(crs)
@@ -5176,7 +5176,7 @@ def save_slope_corr_files(
  print(f"Working on {location} .")
  slope_file_name = f"slopeprofiles_{location}_{alongshore_resolution}_{tick_length}_{across_shore_resolution_txt}.csv"
 
- crs = CRS.from_epsg(crs_dict_string[loc]) # get crs of location
+ crs = crs_dict_string[loc] # get crs of location
 
  baseline_location_path = [
  os.path.join(baseline_folder, baseline)
@@ -5559,7 +5559,7 @@ def tiles_from_grid(
  """
 
  loc = getLoc(img_path, list_loc_codes)
- crs = CRS.from_epsg(crs_dict_string[loc])
+ crs = crs_dict_string[loc]
 
  if driver == "PNG":
  ext = "png"
@@ -5621,7 +5621,7 @@ def tiles_from_grid(
  width_idx = 2
 
  # creates gereferenced bounding box of the image
- geom_im = gpd.GeoSeries(box(*dataset.bounds), crs=CRS.from_epsg(crs_dict_string[loc]))
+ geom_im = gpd.GeoSeries(box(*dataset.bounds), crs=crs_dict_string[loc] )
 
  # evaluates which tiles are fully within the raster bounds
  fully_contains = [
@@ -5725,7 +5725,7 @@ def arr2geotiff(
  count=array.shape[2],
  dtype=dtype,
  transform=transform,
- crs=CRS.from_epsg(crs_dict_string[loc])
+ crs=crs_dict_string[loc]
  )
 
  mem_dataset.write(array.reshape((shape[0], shape[1])), indexes=shape[2])
@@ -5740,7 +5740,7 @@ def arr2geotiff(
  count=array.shape[2],
  dtype=dtype,
  transform=transform,
- crs=CRS.from_epsg(crs_dict_string[loc])
+ crs=crs_dict_string[loc]
  ) as dest:
  if driver == "PNG":
  dest.write(mem_dataset.astype(ras.uint16), indexes=1)
@@ -5841,7 +5841,7 @@ def LISA_site_level(
  df_in = df.query(f"location=='{loc}'") # subset a location
 
  # create a GeoDataFrame with the right CRS
- gdf = gpd.GeoDataFrame(df_in, geometry=geometry_column, crs=CRS.from_epsg(crs_dict_string[loc]))
+ gdf = gpd.GeoDataFrame(df_in, geometry=geometry_column, crs=crs_dict_string[loc] )
 
  dts = gdf.dt.unique() # obtain list of periods
 

diff --git a/sandpyper/sandpyper.py b/sandpyper/sandpyper.py
@@ -11,8 +11,8 @@
 import matplotlib.pyplot as plt
 from itertools import product as prod
 
-from giddy.markov import Markov
-#from pysal.explore.giddy.markov import Markov
+#from giddy.markov import Markov
+from pysal.explore.giddy.markov import Markov
 
 from pysal.viz.mapclassify import (EqualInterval,
  FisherJenks,

diff --git a/tests/test_sandpyper.py b/tests/test_sandpyper.py
@@ -9,10 +9,6 @@
 import pickle
 import numpy as np
 import geopandas as gpd
-
-from pyproj import CRS
-
-
 import pandas as pd
 import shapely
 import sandpyper
@@ -32,7 +28,7 @@
  'min_points':6}}
 
 loc_search_dict = {'leo': ['St', 'Leonards', 'leonards', 'leo'], 'mar': ['Marengo', 'marengo', 'mar'] }
-crs_dict_string = {'mar': 32754, 'leo':32755}
+crs_dict_string = {'mar': {'init': 'epsg:32754'}, 'leo':{'init': 'epsg:32755'} }
 
 labels=["Undefined", "Small", "Medium", "High", "Extreme"]
 
@@ -149,7 +145,7 @@ def test_000_CreateTransects(self):
  sampling_step=20,
  tick_length=50,
  location='leo',
- crs=CRS.from_epsg(crs_dict_string['leo']),
+ crs=crs_dict_string['leo'],
  side='both'
  )
  self.assertEqual(transects_leo.shape, (59, 3))
@@ -163,7 +159,7 @@ def test_001_CreateTransects(self):
  sampling_step=20,
  tick_length=50,
  location='mar',
- crs=CRS.from_epsg(crs_dict_string['mar']),
+ crs=crs_dict_string['mar'],
  side='both'
  )
 
@@ -177,21 +173,21 @@ def test_002_CreateTransects(self):
  create_transects(self.leo_shoreline,
  sampling_step=0,
  tick_length=100,
- location='leo' ,crs=CRS.from_epsg(crs_dict_string['leo']),
+ location='leo' ,crs=crs_dict_string['leo'],
  side='both'
  )
 
  def test_003_CreateTransects(self):
  right=create_transects(self.mar_shoreline,
  sampling_step=150,
  tick_length=50,
- location='mar' ,crs=CRS.from_epsg(crs_dict_string['mar']),
+ location='mar' ,crs=crs_dict_string['mar'],
  side='right'
  )
  left=create_transects(self.mar_shoreline,
  sampling_step=150,
  tick_length=50,
- location='mar' ,crs=CRS.from_epsg(crs_dict_string['mar']),
+ location='mar' ,crs=crs_dict_string['mar'],
  side='left'
  )
  self.assertTrue(right.touches(left).all())