Merge f5bbda3 into df523f9

.travis.yml

@@ -25,7 +25,7 @@ install:
   - sudo apt-get --assume-yes install gfortran
 
   # Install dependencies in conda
-  - conda create -n reflex_env python=$TRAVIS_PYTHON_VERSION libgfortran
+  - conda create -n reflex_env python=$TRAVIS_PYTHON_VERSION
   - source activate reflex_env
   # Install the remaining requeriments
   - conda install --file requirements.txt -c conda-forge

README.md

@@ -64,6 +64,11 @@ Clone the github repository into a folder in your PYTHONPATH:
 
     $ git clone https://github.com/spectraphilic/reflexible.git
 
+Optionally create a conda environment:
+
+    $ conda create --name reflexible
+    $ conda activate reflexible
+
 Install the requirements:
 
     $ conda install --file requirements.txt -c conda-forge

reflexible/base_read.py

@@ -35,7 +35,6 @@
 import datetime as dt
 
 import numpy as np
-import bcolz
 
 
 from .data_structures import Trajectory
@@ -212,7 +211,10 @@ def read_trajectories(H, trajfile='trajectories.txt', ncluster=5,
 
 
 def get_quantized_ctable(dtype, cparams, quantize=None, expectedlen=None):
-    """Return a ctable with the quantize filter enabled for floating point cols."""
+    """Return a ctable with the quantize filter enabled for floating point cols.
+    """
+    import bcolz
+
     columns, names = [], []
     for fname, ftype in dtype.descr:
         names.append(fname)
@@ -265,6 +267,7 @@ def read_partpositions(filename, nspec, ctable=True, clevel=5, cname="lz4", quan
     Note: Passing a `quantize` param > 0 can increase the compression ratio of the ctable
     container, but it may also slow down the reading speed significantly.
     """
+    import bcolz
 
     xmass_dtype = [('xmass_%d' % (i + 1), 'f4') for i in range(nspec)]
     # note age is calculated from itramem by adding itimein

reflexible/conv2netcdf4/flexpart_read.py

@@ -6,12 +6,10 @@
 import datetime
 import re
 import numpy as np
-import bcolz
 from math import pi, sqrt, cos
 from collections import OrderedDict
 
 import reflexible.conv2netcdf4
-from .helpers import closest
 
 
 def read_releases(pathname):
@@ -42,6 +40,8 @@ def read_releases_v10(pathname):
     -------
     A ctable object from bcolz package.
     """
+    import bcolz
+
     # Setup the container for the data
     dtype = [('IDATE1', np.int32), ('ITIME1', np.int32),
              ('IDATE2', np.int32), ('ITIME2', np.int32),

reflexible/data_structures.py

@@ -7,7 +7,7 @@
 import os
 import datetime as dt
 import itertools
-from collections import Iterable
+from collections.abc import Iterable
 import glob
 
 from math import (pi, cos, sqrt)

reflexible/mapping.py

@@ -110,13 +110,13 @@ def map_regions(map_region='default', map_par=None, fig_par=None):
     # Get the database out of the system YAML file
     mapdb_file = os.path.join(os.path.dirname(__file__), 'mapping_db.yml')
     with open(mapdb_file) as mapdb:
-        mapping_db = yaml.load(mapdb)
+        mapping_db = yaml.safe_load(mapdb)
 
     # and merge it with a possible one pointed by REFLEXIBLE_MAPDB env var
     if 'REFLEXIBLE_MAPDB' in os.environ:
         user_mapdb_file = os.environ['REFLEXIBLE_MAPDB']
         with open(user_mapdb_file) as mapdb:
-            mapping_db.update(yaml.load(mapdb))
+            mapping_db.update(yaml.safe_load(mapdb))
 
     # Lookup the region and its aliases
     try:
@@ -126,7 +126,7 @@ def map_regions(map_region='default', map_par=None, fig_par=None):
         for key in mapping_db:
             if 'alias' in mapping_db[key]:
                 alias = mapping_db[key]['alias']
-                if map_region in re.split(',\s*', alias):
+                if map_region in re.split(r',\s*', alias):
                     region = mapping_db[key]
                     break
         else:
@@ -222,111 +222,92 @@ def draw_grid(m, xdiv=10., ydiv=5., location=[1, 0, 0, 1],
     return m_p, m_m
 
 
-def get_base1(map_region='default', map_par=None, fig_par=None,
-              figname=None, fig=None, drawlsmask=False):
+def get_base_image(map_region='default', map_par=None, fig_par=None,
+                   image=None, figname=None, fig=None, drawlsmask=False):
     """
-    Primarily an internally used function, creates a
-    basemap for plotting. Returns a fig object and
-    a basemap instance.
+    Primarily an internally used function, creates a basemap for plotting.
+    Returns a fig object and a basemap instance.
 
-    Usage::
+    Examples::
 
-      > fig, m = get_base1(map_region="region_name")
+      > fig, m = get_base_image(map_region="region_name")
+      > fig, m = get_base_image(map_region="myregion", image=image)
     """
 
     # Use map_regions function to define input parameters for Basemap
-    map_par_sd, fig_par_sd = map_regions(map_region, map_par, fig_par)
+    map_par, fig_par = map_regions(map_region, map_par, fig_par)
 
     # create the figure
     if fig is None:
-        axlocs = fig_par_sd.pop('axlocs')
-        fig = plt.figure(**fig_par_sd)
+        axlocs = fig_par.pop('axlocs')
+        fig = plt.figure(**fig_par)
         ax = fig.add_axes(axlocs)
     else:
         ax = fig.gca()
 
-    m = basemap.Basemap(**map_par_sd)
-    plt.axes(ax)   # make sure axes ax are current
-    # draw coastlines and political boundaries.
-    m.drawcoastlines(linewidth=0.8)
-    m.drawcountries(linewidth=0.2)
-    m.drawstates(linewidth=0.2)
-    if drawlsmask:
-        m.drawlsmask(ocean_color='#008EBA', zorder=0)
-    # m.fillcontinents(zorder=0.)
-    # draw parallels and meridians
-    # use draw_grid function
-    m_p, m_m = draw_grid(m)
+    plt.axes(ax)  # make the original axes current again
+
+    m = basemap.Basemap(**map_par)
+
+    if image is None:
+        # draw coastlines and political boundaries.
+        m.drawcoastlines(linewidth=0.8)
+        m.drawcountries(linewidth=0.2)
+        m.drawstates(linewidth=0.2)
+        if drawlsmask:
+            m.drawlsmask(ocean_color='#008EBA', zorder=0)
+        # draw parallels and meridians
+        # use draw_grid function
+        draw_grid(m)
+    else:
+        # shows how to warp an image from one map projection to another.
+        # image from http://visibleearth.nasa.gov/
+
+        # need to change back to [0.1,0.1,0.7,0.7]
+        #ax = fig.add_axes([0.1, 0.1, 0.7, 0.7])
+
+        # read in jpeg image to rgba array of normalized floats.
+        pilImage = Image.open(image)
+        rgba = mpl.image.pil_to_array(pilImage)
+        rgba = rgba.astype(np.float32) / 255.  # convert to normalized floats.
+
+        # define lat/lon grid that image spans (projection='cyl').
+        nlons = rgba.shape[1]
+        #nlats = rgba.shape[0]
+        delta = 360. / float(nlons)
+        lons = np.arange(-180. + 0.5 * delta, 180., delta)
+        lats = np.arange(-90. + 0.5 * delta, 90., delta)
+
+        # transform to nx x ny regularly spaced native projection grid
+        # nx and ny chosen to have roughly the same horizontal res as original
+        # image.
+        dx = 2. * np.pi * m.rmajor / float(nlons)
+        nx = int((m.xmax - m.xmin) / dx) + 1
+        ny = int((m.ymax - m.ymin) / dx) + 1
+        rgba_warped = np.zeros((ny, nx, 4), np.float64)
+        # interpolate rgba values from proj='cyl' (geographic coords) to 'lcc'
+        try:
+            for k in range(4):
+                rgba_warped[:, :, k] = m.transform_scalar(
+                    rgba[:, :, k], lons, lats, nx, ny)
+        except:
+            rgba_warped = rgba
+            print('problem with transform_scalar')
+        # plot warped rgba image.
+        m.imshow(rgba_warped)
+
+        # draw coastlines.
+        m.drawcoastlines(linewidth=0.5, color='0.5')
+        if drawlsmask:
+            m.drawlsmask(ocean_color='#008EBA', zorder=0)
+        # draw parallels and meridians.
+        draw_grid(m, linewidth=0.5, color='0.5')
 
     if figname is not None:
         plt.savefig(figname)
     return fig, m
 
 
-def get_base_image(imagefile, map_region='default', map_par=None, fig_par=None,
-                   fig=None):
-    """Warps NASA Blue Marble Image version.
-
-    Create basemap figure for plotting on top of
-    returns a figure and a basemap instance.
-
-    Usage::
-
-        > fig, m = get_base_image(imagefile, map_region="myregion")
-
-    """
-
-    # define Lambert Conformal basemap for North America.
-    mp, fig_par = map_regions(map_region, map_par, fig_par)
-
-    # shows how to warp an image from one map projection to another.
-    # image from http://visibleearth.nasa.gov/
-
-    # read in jpeg image to rgba array of normalized floats.
-    pilImage = Image.open(imagefile)
-    rgba = mpl.image.pil_to_array(pilImage)
-    rgba = rgba.astype(np.float32) / 255.  # convert to normalized floats.
-
-    # define lat/lon grid that image spans (projection='cyl').
-    nlons = rgba.shape[1]
-    #nlats = rgba.shape[0]
-    delta = 360. / float(nlons)
-    lons = np.arange(-180. + 0.5 * delta, 180., delta)
-    lats = np.arange(-90. + 0.5 * delta, 90., delta)
-
-    # create new figure
-    fig = plt.figure(1, **fig_par)
-
-    m = basemap.Basemap(**mp)
-    ax = fig.add_axes(
-        [0.1, 0.1, 0.7, 0.7])  # need to change back to [0.1,0.1,0.7,0.7]
-    plt.axes(ax)  # make the original axes current again
-
-    # transform to nx x ny regularly spaced native projection grid
-    # nx and ny chosen to have roughly the same horizontal res as original
-    # image.
-    dx = 2. * np.pi * m.rmajor / float(nlons)
-    nx = int((m.xmax - m.xmin) / dx) + 1
-    ny = int((m.ymax - m.ymin) / dx) + 1
-    rgba_warped = np.zeros((ny, nx, 4), np.float64)
-    # interpolate rgba values from proj='cyl' (geographic coords) to 'lcc'
-    try:
-        for k in range(4):
-            rgba_warped[:, :, k] = m.transform_scalar(
-                rgba[:, :, k], lons, lats, nx, ny)
-    except:
-        rgba_warped = rgba
-        print('problem with transform_scalar')
-    # plot warped rgba image.
-    m.imshow(rgba_warped)
-    # draw coastlines.
-    m.drawcoastlines(linewidth=0.5, color='0.5')
-    # draw parallels and meridians.
-    draw_grid(m, linewidth=0.5, color='0.5')
-    # draw()
-    return fig, m
-
-
 if __name__ == '__main__':
     # Some tests for reading the mapping YAML database
     map_regions(map_region=sys.argv[1])

reflexible/plotting.py

@@ -173,12 +173,9 @@ def _get_figure(map_region='default', map_par=None, fig_par=None,
     figure = Structure()
 
     if m is None:
-        if image:
-            fig, m = mp.get_base_image(image, map_region, map_par, fig_par)
-        else:
-            fig, m = mp.get_base1(map_region, map_par, fig_par, fig=fig)
+        fig, m = mp.get_base_image(map_region, map_par, fig_par, image=image)
 
-    if fig is None:
+    elif fig is None:
         map_par, fig_par = mp.map_regions(map_region, map_par, fig_par)
         fig = plt.figure(**fig_par)
 
@@ -347,7 +344,7 @@ def plot_sensitivity(H, data, data_range=None,
 
         if m.projection != 'merc':
             if lons[-1] - lons[0] < 360.:
-                topodat, lons = basemap.addcyclic(data, lons)
+                topodat, lons = basemap.addcyclic(data.values, lons)
 
     # get min/max range
     if data_range is not None:

requirements.txt

@@ -1,10 +1,10 @@
 matplotlib
 pillow
-netCDF4>=1.1.1
-xarray
-numpy!=1.12
+netCDF4>=1.1.1,<1.5
+xarray>=0.14.1
+numpy>=1.14.6
 pandas
-basemap==1.0.7
+basemap==1.2.1
 pyyaml
 bcolz
 pytest