replaced numpy bool/int/float to prevent deprecation warnings (#48)

notebooks/Check Tide Map.ipynb

@@ -272,7 +272,7 @@
     "    mz = np.invert(hz.mask)\n",
     "    # adjust longitudinal convention of input latitude and longitude\n",
     "    # to fit tide model convention\n",
-    "    x,y = np.copy([LON,LAT]).astype(np.float)\n",
+    "    x,y = np.copy([LON,LAT]).astype(np.float64)\n",
     "    lt0, = np.nonzero(x < 0)\n",
     "    x[lt0] += 360.0\n",
     "elif (model_format == 'GOT'):\n",
@@ -283,7 +283,7 @@
     "    mz = np.invert(hc.mask)\n",
     "    # adjust longitudinal convention of input latitude and longitude\n",
     "    # to fit tide model convention\n",
-    "    x,y = np.copy([LON,LAT]).astype(np.float)\n",
+    "    x,y = np.copy([LON,LAT]).astype(np.float64)\n",
     "    lt0, = np.nonzero(x < 0)\n",
     "    x[lt0] += 360.0\n",
     "elif (model_format == 'FES'):\n",
@@ -295,7 +295,7 @@
     "    mz = np.invert(hc.mask)\n",
     "    # adjust longitudinal convention of input latitude and longitude\n",
     "    # to fit tide model convention\n",
-    "    x,y = np.copy([LON,LAT]).astype(np.float)\n",
+    "    x,y = np.copy([LON,LAT]).astype(np.float64)\n",
     "    lt0, = np.nonzero(x < 0)\n",
     "    x[lt0] += 360.0\n",
     "\n",

notebooks/Plot Antarctic Tidal Currents.ipynb

@@ -303,8 +303,8 @@
     "y = np.arange(ylimits[1],ylimits[0]+spacing[1],spacing[1])\n",
     "xgrid,ygrid = np.meshgrid(x,y)\n",
     "#-- x and y dimensions\n",
-    "nx = np.int((xlimits[1]-xlimits[0])/spacing[0])+1\n",
-    "ny = np.int((ylimits[0]-ylimits[1])/spacing[1])+1\n",
+    "nx = int((xlimits[1]-xlimits[0])/spacing[0])+1\n",
+    "ny = int((ylimits[0]-ylimits[1])/spacing[1])+1\n",
     "#-- convert image coordinates from polar stereographic to latitude/longitude\n",
     "crs1 = pyproj.CRS.from_string(\"epsg:{0:d}\".format(3031))\n",
     "crs2 = pyproj.CRS.from_string(\"epsg:{0:d}\".format(4326))\n",

notebooks/Plot Antarctic Tide Range.ipynb

@@ -284,8 +284,8 @@
     "y = np.arange(ylimits[1],ylimits[0]+spacing[1],spacing[1])\n",
     "xgrid,ygrid = np.meshgrid(x,y)\n",
     "#-- x and y dimensions\n",
-    "nx = np.int((xlimits[1]-xlimits[0])/spacing[0])+1\n",
-    "ny = np.int((ylimits[0]-ylimits[1])/spacing[1])+1\n",
+    "nx = int((xlimits[1]-xlimits[0])/spacing[0])+1\n",
+    "ny = int((ylimits[0]-ylimits[1])/spacing[1])+1\n",
     "#-- convert image coordinates from polar stereographic to latitude/longitude\n",
     "crs1 = pyproj.CRS.from_string(\"epsg:{0:d}\".format(3031))\n",
     "crs2 = pyproj.CRS.from_string(\"epsg:{0:d}\".format(4326))\n",

notebooks/Plot Arctic Ocean Map.ipynb

@@ -330,8 +330,8 @@
     "y = np.arange(ylimits[1],ylimits[0]+spacing[1],spacing[1])\n",
     "xgrid,ygrid = np.meshgrid(x,y)\n",
     "#-- x and y dimensions\n",
-    "nx = np.int((xlimits[1]-xlimits[0])/spacing[0])+1\n",
-    "ny = np.int((ylimits[0]-ylimits[1])/spacing[1])+1\n",
+    "nx = int((xlimits[1]-xlimits[0])/spacing[0])+1\n",
+    "ny = int((ylimits[0]-ylimits[1])/spacing[1])+1\n",
     "#-- convert image coordinates from polar stereographic to latitude/longitude\n",
     "crs1 = pyproj.CRS.from_string(\"epsg:{0:d}\".format(3413))\n",
     "crs2 = pyproj.CRS.from_string(\"epsg:{0:d}\".format(4326))\n",

notebooks/Plot Ross Ice Shelf Map.ipynb

@@ -304,8 +304,8 @@
     "y = np.arange(ylimits[1],ylimits[0]+spacing[1],spacing[1])\n",
     "xgrid,ygrid = np.meshgrid(x,y)\n",
     "#-- x and y dimensions\n",
-    "nx = np.int((xlimits[1]-xlimits[0])/spacing[0])+1\n",
-    "ny = np.int((ylimits[0]-ylimits[1])/spacing[1])+1\n",
+    "nx = int((xlimits[1]-xlimits[0])/spacing[0])+1\n",
+    "ny = int((ylimits[0]-ylimits[1])/spacing[1])+1\n",
     "#-- convert image coordinates from polar stereographic to latitude/longitude\n",
     "crs1 = pyproj.CRS.from_string(\"epsg:{0:d}\".format(3031))\n",
     "crs2 = pyproj.CRS.from_string(\"epsg:{0:d}\".format(4326))\n",

notebooks/Plot Tide Forecasts.ipynb

@@ -377,7 +377,7 @@
     "TIDE.data[:] *= 100.0\n",
     "\n",
     "#-- differentiate to calculate high and low tides\n",
-    "diff = np.zeros_like(tide_time, dtype=np.float)\n",
+    "diff = np.zeros_like(tide_time, dtype=np.float64)\n",
     "#-- forward differentiation for starting point\n",
     "diff[0] = TIDE.data[1] - TIDE.data[0]\n",
     "#-- backward differentiation for end point\n",

pyTMD/bilinear_interp.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python
 u"""
-bilinear_interp.py (02/2021)
+bilinear_interp.py (03/2021)
 Bilinear interpolation of input data to output coordinates
 
 CALLING SEQUENCE:
@@ -26,7 +26,7 @@
         https://numpy.org/doc/stable/user/numpy-for-matlab-users.html
 
 UPDATE HISTORY:
-    Updated 02/2021: replaced numpy bool to prevent deprecation warning
+    Updated 03/2021: replaced numpy bool/int to prevent deprecation warnings
     Updated 12/2020: using numpy isclose to check corner points
     Updated 08/2020: check that output coordinates are within bounds
         allow small extrapolations if individual grid cells are invalid
@@ -38,7 +38,7 @@
 
 #-- PURPOSE: bilinear interpolation of input data to output data
 def bilinear_interp(ilon,ilat,idata,lon,lat,fill_value=np.nan,
-    dtype=np.float):
+    dtype=np.float64):
     """
     Bilinear interpolation of input data to output coordinates
 

pyTMD/eop.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 u"""
 eop.py
-Written by Tyler Sutterley (11/2020)
+Written by Tyler Sutterley (03/2021)
 Utilities for maintaining Earth Orientation Parameter (EOP) files
 
 PYTHON DEPENDENCIES:
@@ -14,6 +14,7 @@
     utilities: download and management utilities for syncing files
 
 UPDATE HISTORY:
+    Updated 03/2021: replaced numpy bool/int to prevent deprecation warnings
     Written 11/2020
 """
 import os
@@ -107,7 +108,7 @@ def calculate_mean_pole(verbose=False, mode=0o775):
     for i,line in enumerate(file_contents[1:]):
         line_contents = line.split()
         for h,l in zip(header,line_contents):
-            data[h][i] = np.float(l)
+            data[h][i] = np.float64(l)
     #-- output mean pole coordinates
     xm = np.zeros((nlines))
     ym = np.zeros((nlines))

pyTMD/nearest_extrap.py

@@ -36,6 +36,7 @@
     Updated 03/2021: add checks to prevent runtime exception
         where there are no valid points within the input bounds
         or no points to be extrapolated
+        replaced numpy bool/int to prevent deprecation warnings
     Updated 02/2021: replaced numpy bool to prevent deprecation warning
     Written 12/2020
 """
@@ -45,7 +46,7 @@
 
 #-- PURPOSE: Nearest-neighbor extrapolation of valid data to output data
 def nearest_extrap(ilon,ilat,idata,lon,lat,fill_value=np.nan,
-    dtype=np.float,cutoff=np.inf,EPSG='4326'):
+    dtype=np.float64,cutoff=np.inf,EPSG='4326'):
     """
     Nearest-neighbor extrapolation of valid model data
 

pyTMD/read_FES_model.py

@@ -54,6 +54,7 @@
     Updated 03/2021: add extrapolation check where there are no invalid points
         prevent ComplexWarning for fill values when calculating amplitudes
         simplified inputs to be similar to binary OTIS read program
+        replaced numpy bool/int to prevent deprecation warnings
         use uuid for reading from gzipped netCDF4 files
     Updated 02/2021: set invalid values to nan in extrapolation
         replaced numpy bool to prevent deprecation warning
@@ -235,16 +236,16 @@ def read_ascii_file(input_file,GZIP=False,TYPE=None,VERSION=None):
             file_contents = f.read().splitlines()
     #-- parse header text
     #-- longitude range (lonmin, lonmax)
-    lonmin,lonmax = np.array(file_contents[0].split(), dtype=np.float)
+    lonmin,lonmax = np.array(file_contents[0].split(), dtype=np.float64)
     #-- latitude range (latmin, latmax)
-    latmin,latmax = np.array(file_contents[1].split(), dtype=np.float)
+    latmin,latmax = np.array(file_contents[1].split(), dtype=np.float64)
     #-- grid step size (dlon, dlat)
-    dlon,dlat = np.array(file_contents[2].split(), dtype=np.float)
+    dlon,dlat = np.array(file_contents[2].split(), dtype=np.float64)
     #-- grid dimensions (nlon, nlat)
-    nlon,nlat = np.array(file_contents[3].split(), dtype=np.int)
+    nlon,nlat = np.array(file_contents[3].split(), dtype=int)
     #-- mask fill value
     masked_values = file_contents[4].split()
-    fill_value = np.float(masked_values[0])
+    fill_value = np.float64(masked_values[0])
     #-- create output variables
     lat = np.linspace(latmin, latmax, nlat)
     lon = np.linspace(lonmin,lonmax,nlon)

pyTMD/read_GOT_model.py

@@ -40,6 +40,7 @@
     Updated 03/2021: add extrapolation check where there are no invalid points
         prevent ComplexWarning for fill values when calculating amplitudes
         simplified inputs to be similar to binary OTIS read program
+        replaced numpy bool/int to prevent deprecation warnings
     Updated 02/2021: set invalid values to nan in extrapolation
         replaced numpy bool to prevent deprecation warning
     Updated 12/2020: added valid data extrapolation with nearest_extrap
@@ -265,13 +266,13 @@ def read_GOT_grid(input_file, GZIP=False):
     constituent_list = ['Q1','O1','P1','K1','N2','M2','S2','K2','S1','M4']
     regex = re.compile(r'|'.join(constituent_list), re.IGNORECASE)
     cons = regex.findall(file_contents[0]).pop().lower()
-    nlat,nlon = np.array(file_contents[2].split(), dtype=np.int)
+    nlat,nlon = np.array(file_contents[2].split(), dtype=int)
     #-- longitude range
-    ilat = np.array(file_contents[3].split(), dtype=np.float)
+    ilat = np.array(file_contents[3].split(), dtype=np.float64)
     #-- latitude range
-    ilon = np.array(file_contents[4].split(), dtype=np.float)
+    ilon = np.array(file_contents[4].split(), dtype=np.float64)
     #-- mask fill value
-    fill_value = np.array(file_contents[5].split(), dtype=np.float)
+    fill_value = np.array(file_contents[5].split(), dtype=np.float64)
     #-- create output variables
     lat = np.linspace(ilat[0],ilat[1],nlat)
     lon = np.linspace(ilon[0],ilon[1],nlon)
@@ -282,7 +283,7 @@ def read_GOT_grid(input_file, GZIP=False):
     ph.mask = np.zeros((nlat,nlon),dtype=bool)
     #-- starting lines to fill amplitude and phase variables
     l1 = 7
-    l2 = 14 + np.int(nlon//11)*nlat + nlat
+    l2 = 14 + int(nlon//11)*nlat + nlat
     #-- for each latitude
     for i in range(nlat):
         for j in range(nlon//11):

pyTMD/read_iers_EOP.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 u"""
 read_iers_EOP.py
-Written by Tyler Sutterley (07/2020)
+Written by Tyler Sutterley (03/2021)
 Provides the daily earth orientation parameters (EOP) from IERS
     http://www.usno.navy.mil/USNO/earth-orientation/eo-products/weekly
 Data format: http://maia.usno.navy.mil/ser7/readme.finals
@@ -25,6 +25,7 @@
         IERS Technical Note No. 36, BKG (2010)
 
 UPDATE HISTORY:
+    Updated 03/2021: replaced numpy bool/int to prevent deprecation warnings
     Updated 07/2020: added function docstrings
     Written 09/2017
 """
@@ -62,13 +63,13 @@ def read_iers_EOP(input_file):
     while (flag == 'I'):
         line = file_contents[counter]
         i = 2+2+2+1; j = i+8
-        dinput['MJD'][counter] = np.float(line[i:j])
+        dinput['MJD'][counter] = np.float64(line[i:j])
         i = j+1
         flag = line[i]
         i += 2; j = i+9
-        dinput['x'][counter] = np.float(line[i:j])
+        dinput['x'][counter] = np.float64(line[i:j])
         i = j+10; j = i+9
-        dinput['y'][counter] = np.float(line[i:j])
+        dinput['y'][counter] = np.float64(line[i:j])
         counter += 1
     #-- reduce to data values
     dinput['MJD'] = dinput['MJD'][:counter]

pyTMD/read_ocean_pole_tide.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python
 u"""
-read_ocean_pole_tide.py (08/2020)
+read_ocean_pole_tide.py (03/2021)
 Reads ocean pole load tide coefficients provided by IERS
 http://maia.usno.navy.mil/conventions/2010/2010_official/chapter7/tn36_c7.pdf
 http://maia.usno.navy.mil/conventions/2010/2010_update/chapter7/icc7.pdf
@@ -29,6 +29,7 @@
         doi: 10.1007/s00190-015-0848-7
 
 UPDATE HISTORY:
+    Updated 03/2021: replaced numpy bool/int to prevent deprecation warnings
     Updated 08/2020: output north load and east load deformation components
     Updated 07/2020: added function docstrings
     Updated 12/2018: Compatibility updates for Python3
@@ -84,8 +85,8 @@ def read_ocean_pole_tide(input_file):
     #-- read lines of file and add to output variables
     for i,line in enumerate(file_contents[count:]):
         ln,lt,urr,uri,unr,uni,uer,uei = np.array(line.split(), dtype='f8')
-        ilon = np.int(ln/dlon)
-        ilat = np.int((90.0-lt)/dlat)
+        ilon = int(ln/dlon)
+        ilat = int((90.0-lt)/dlat)
         ur[ilon,ilat] = urr + 1j*uri
         un[ilon,ilat] = unr + 1j*uni
         ue[ilon,ilat] = uer + 1j*uei

pyTMD/read_tide_model.py

@@ -55,6 +55,7 @@
     Updated 03/2021: add extrapolation check where there are no invalid points
         prevent ComplexWarning for fill values when calculating amplitudes
         can read from single constituent TPXO9 ATLAS binary files
+        replaced numpy bool/int to prevent deprecation warnings
     Updated 02/2021: set invalid values to nan in extrapolation
         replaced numpy bool to prevent deprecation warning
     Updated 12/2020: added valid data extrapolation with nearest_extrap
@@ -964,8 +965,8 @@ def create_atlas_mask(xi,yi,mz,local,VARIABLE=None):
         for indy,indx in zip(validy,validx):
             #-- check if model is -180:180
             lon30 = (X[indy,indx]+360.) if (X[indy,indx]<=0.0) else X[indy,indx]
-            ii = np.int((lon30 - x30[0])/d30)
-            jj = np.int((Y[indy,indx] - y30[0])/d30)
+            ii = int((lon30 - x30[0])/d30)
+            jj = int((Y[indy,indx] - y30[0])/d30)
             #-- fill global mask with regional solution
             m30[jj,ii] = 1
     #-- return the 2 arc-minute mask
@@ -1028,8 +1029,8 @@ def combine_atlas_model(xi,yi,zi,pmask,local,VARIABLE=None):
         for indy,indx in zip(validy,validx):
             #-- check if model is -180:180
             lon30 = (X[indy,indx]+360.) if (X[indy,indx]<=0.0) else X[indy,indx]
-            ii = np.int((lon30 - x30[0])/d30)
-            jj = np.int((Y[indy,indx] - y30[0])/d30)
+            ii = int((lon30 - x30[0])/d30)
+            jj = int((Y[indy,indx] - y30[0])/d30)
             #-- fill global model with regional solution
             z30.data[jj,ii] = zlocal[indy,indx]
     #-- return 2 arc-minute solution and coordinates
@@ -1042,18 +1043,18 @@ def Muv(hz):
     Construct masks for zeta, u and v nodes on a C-grid
     """
     ny,nx = np.shape(hz)
-    mz = (hz > 0).astype(np.int)
+    mz = (hz > 0).astype(int)
     #-- x-indices
-    indx = np.zeros((nx),dtype=np.int)
+    indx = np.zeros((nx),dtype=int)
     indx[:-1] = np.arange(1,nx)
     indx[-1] = 0
     #-- y-indices
-    indy = np.zeros((ny),dtype=np.int)
+    indy = np.zeros((ny),dtype=int)
     indy[:-1] = np.arange(1,ny)
     indy[-1] = 0
     #-- calculate mu and mv
-    mu = np.zeros((ny,nx),dtype=np.int)
-    mv = np.zeros((ny,nx),dtype=np.int)
+    mu = np.zeros((ny,nx),dtype=int)
+    mv = np.zeros((ny,nx),dtype=int)
     mu[indy,:] = mz*mz[indy,:]
     mv[:,indx] = mz*mz[:,indx]
     return (mu,mv,mz)
@@ -1066,11 +1067,11 @@ def Huv(hz):
     ny,nx = np.shape(hz)
     mu,mv,mz = Muv(hz)
     #-- x-indices
-    indx = np.zeros((nx),dtype=np.int)
+    indx = np.zeros((nx),dtype=int)
     indx[0] = nx-1
     indx[1:] = np.arange(1,nx)
     #-- y-indices
-    indy = np.zeros((ny),dtype=np.int)
+    indy = np.zeros((ny),dtype=int)
     indy[0] = ny-1
     indy[1:] = np.arange(1,ny)
     #-- calculate hu and hv

pyTMD/spatial.py

@@ -21,6 +21,7 @@
 UPDATE HISTORY:
     Updated 03/2021: added polar stereographic area scale calculation
         add routines for converting to and from cartesian coordinates
+        eplaced numpy bool/int to prevent deprecation warnings
     Updated 01/2021: add streaming from bytes for ascii, netCDF4, HDF5, geotiff
         set default time for geotiff files to 0
     Updated 12/2020: added module for converting ellipsoids
@@ -111,7 +112,7 @@ def from_ascii(filename, compression=None, verbose=False,
             dinput[c] = np.zeros((file_lines-count))
             dinput['attributes'][c] = YAML_HEADER['header']['variables'][c]
         #-- update number of file lines to skip for reading data
-        header = np.int(count)
+        header = int(count)
     else:
         #-- output spatial data and attributes
         dinput = {c:np.zeros((file_lines-header)) for c in columns}
@@ -124,7 +125,7 @@ def from_ascii(filename, compression=None, verbose=False,
         column = {c:r.replace('D','E') for c,r in zip(columns,rx.findall(line))}
         #-- copy variables from column dict to output dictionary
         for c in columns:
-            dinput[c][i] = np.float(column[c])
+            dinput[c][i] = np.float64(column[c])
     #-- convert to masked array if fill values
     if '_FillValue' in dinput['attributes']['data'].keys():
         dinput['data'] = np.ma.asarray(dinput['data'])