Merge branch 'feature/add_quiverplot' into develop

.gitlab-ci.yml

@@ -19,8 +19,8 @@ stages:
 test_arosics:
   stage: test
   script:
-    - source /root/anaconda3/bin/activate
-    - export GDAL_DATA=/root/anaconda3/share/gdal
+    - source /root/miniconda3/bin/activate
+    - export GDAL_DATA=/root/miniconda3/share/gdal
     - export PYTHONPATH=$PYTHONPATH:/root  # /root <- directory needed later
     - make nosetests
     - make docs
@@ -36,8 +36,8 @@ test_arosics:
 test_styles:
   stage: test
   script:
-    - source /root/anaconda3/bin/activate
-    - export GDAL_DATA=/root/anaconda3/share/gdal
+    - source /root/miniconda3/bin/activate
+    - export GDAL_DATA=/root/miniconda3/share/gdal
     - export PYTHONPATH=$PYTHONPATH:/root  # /root <- directory needed later
     - make lint
   artifacts:
@@ -51,8 +51,8 @@ test_styles:
 test_arosics_install:
   stage: test
   script:
-    - source /root/anaconda3/bin/activate
-    - export GDAL_DATA=/root/anaconda3/share/gdal
+    - source /root/miniconda3/bin/activate
+    - export GDAL_DATA=/root/miniconda3/share/gdal
     - conda create -y -q --name arosics python=3
     - source activate arosics
      # resolve some requirements with conda
@@ -106,7 +106,7 @@ deploy_pypi:
   dependencies:
     - test_arosics
   script:   # Configure the PyPI credentials, then push the package, and cleanup the creds.
-    - source /root/anaconda3/bin/activate
+    - source /root/miniconda3/bin/activate
     - mkdir -p public/images/
     - cp -r docs/images/* public/images/
     - printf "[distutils]\nindex-servers =\n    pypi\n\n" >> ~/.pypirc

arosics/CoReg_local.py

@@ -335,11 +335,15 @@ class COREG_LOCAL(object):
         footprints of the input images as well as the corresponding overlap area."""
         return self.COREG_obj.show_image_footprints()
 
-    def view_CoRegPoints(self, attribute2plot='ABS_SHIFT', cmap=None, exclude_fillVals=True, backgroundIm='tgt',
-                         hide_filtered=True, figsize=None, savefigPath='', savefigDPI=96, showFig=True,
-                         vmin=None, vmax=None, return_map=False, zoomable=False):
+    def view_CoRegPoints(self, shapes2plot='points', attribute2plot='ABS_SHIFT', cmap=None, exclude_fillVals=True,
+                         backgroundIm='tgt', hide_filtered=True, figsize=None, title='', vector_scale=1.,
+                         savefigPath='', savefigDPI=96, showFig=True, vmin=None, vmax=None, return_map=False,
+                         zoomable=False):
+        # type: (str, str, plt.cm, bool, str, bool, tuple, str, float, str, int, bool, float, float, bool) -> tuple
         """Shows a map of the calculated tie point grid with the target image as background.
 
+        :param shapes2plot:         <str> 'points': plot points representing values of 'attribute2plot' onto the map
+                                          'vectors': plot shift vectors onto the map
         :param attribute2plot:      <str> the attribute of the tie point grid to be shown (default: 'ABS_SHIFT')
         :param cmap:                <plt.cm.<colormap>> a custom color map to be applied to the plotted grid points
                                                         (default: 'RdYlGn_r')
@@ -350,6 +354,8 @@ class COREG_LOCAL(object):
         :param hide_filtered:       <bool> hide all points that have been filtered out according to tie point filter
                                     level
         :param figsize:             <tuple> size of the figure to be viewed, e.g. (10,10)
+        :param title:               <str> plot title
+        :param vector_scale:        <float> scale factor for shift vector length (default: 1 -> no scaling)
         :param savefigPath:
         :param savefigDPI:
         :param showFig:             <bool> whether to show or to hide the figure
@@ -371,7 +377,7 @@ class COREG_LOCAL(object):
         # ax.tick_params(axis='both', which='minor', labelsize=8)
 
         # fig, ax, map2show = backgroundIm.show_map_utm(figsize=(20,20), nodataVal=self.nodata[1], return_map=True)
-        plt.title(attribute2plot)
+        plt.title(title or attribute2plot)
 
         # transform all points of tie point grid to LonLat
         outlierCols = [c for c in self.CoRegPoints_table.columns if 'OUTLIER' in c]
@@ -437,25 +443,45 @@ class COREG_LOCAL(object):
             if self.tieP_filter_level > 0:
                 plt.legend(loc=0, scatterpoints=1)
 
-        # plot all points on top
+        # plot all points or vectors on top
         if not GDF.empty:
-            vmin_auto, vmax_auto = (np.percentile(GDF[attribute2plot], 0), np.percentile(GDF[attribute2plot], 95)) \
+            vmin_auto, vmax_auto = (np.percentile(GDF[attribute2plot], 0), np.percentile(GDF[attribute2plot], 98)) \
                 if attribute2plot != 'ANGLE' else (0, 360)
             vmin = vmin if vmin is not None else vmin_auto
             vmax = vmax if vmax is not None else vmax_auto
 
-            points = plt.scatter(GDF['plt_X'], GDF['plt_Y'], c=GDF[attribute2plot], lw=0,
-                                 cmap=palette, marker='o' if len(GDF) < 10000 else '.', s=50, alpha=1.0,
-                                 vmin=vmin, vmax=vmax)
+            if shapes2plot == 'vectors':
+                # plot shift vectors
+                # doc: https://matplotlib.org/devdocs/api/_as_gen/matplotlib.axes.Axes.quiver.html
+                plt.quiver(GDF['plt_X'], GDF['plt_Y'],
+                           -GDF['X_SHIFT_M'], -GDF['Y_SHIFT_M'],  # invert absolute shifts to make arrows point to tgt
+                           GDF[attribute2plot].clip(vmin, vmax),  # sets the colors
+                           scale=1200 / vector_scale,  # larger values decrease the arrow length
+                           width=.0015,  # arrow width (in relation to plot width)
+                           # linewidth=1, # maybe use this to mark outliers instead of scatter points
+                           cmap=palette,
+                           pivot='middle'  # position the middle point of the arrows onto the tie point location
+                           )
+                mappable = None
+
+            elif shapes2plot == 'points':
+                # plot tie points
+                points = plt.scatter(GDF['plt_X'], GDF['plt_Y'], c=GDF[attribute2plot], lw=0,
+                                     cmap=palette, marker='o' if len(GDF) < 10000 else '.', s=50, alpha=1.0,
+                                     vmin=vmin, vmax=vmax)
+                mappable = points
 
-            # plot shift vectors
-            # map2show.quiver(GDF['plt_X'], GDF['plt_Y'], GDF['X_SHIFT_M'], GDF['Y_SHIFT_M'])#, scale=700)
+            else:
+                raise ValueError("The parameter 'shapes2plot' must be set to 'vectors' or 'points'. Received %s."
+                                 % shapes2plot)
 
             # add colorbar
             divider = make_axes_locatable(plt.gca())
-            cax = divider.append_axes("right", size="2%",
-                                      pad=0.1)  # create axis on the right; size =2% of ax; padding = 0.1 inch
-            plt.colorbar(points, cax=cax)
+            # create axis on the right; size =2% of ax; padding = 0.1 inch
+            cax = divider.append_axes("right", size="2%", pad=0.1)
+
+            plt.colorbar(mappable, cax=cax)
+
         else:
             if not self.q:
                 warnings.warn('Cannot plot any tie point because none is left after tie point validation.')

arosics/__init__.py

@@ -12,8 +12,8 @@ from arosics.Tie_Point_Grid import Tie_Point_Grid
 
 __author__ = """Daniel Scheffler"""
 __email__ = 'daniel.scheffler@gfz-potsdam.de'
-__version__ = '0.6.9'
-__versionalias__ = '2017-11-16_02'
+__version__ = '0.7.0'
+__versionalias__ = '2017-11-20_01'
 __all__ = ['COREG',
            'COREG_LOCAL',
            'DESHIFTER',

setup.py

@@ -28,7 +28,7 @@ test_requirements = requirements + ['coverage', 'nose', 'nose-htmloutput', 'redn
 
 setup(
     name='arosics',
-    version='0.6.9',
+    version='0.7.0',
     description="An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data",
     long_description=readme + '\n\n' + history,
     author="Daniel Scheffler",

tests/CI_docker/build_arosics_testsuite_image.sh

@@ -2,7 +2,7 @@
 
 context_dir="./context"
 dockerfile="arosics_ci.docker"
-tag="arosics_ci:0.6.9"
+tag="arosics_ci:0.6.10"
 gitlab_runner="arosics_gitlab_CI_runner"
 
 echo "#### Build runner docker image"

tests/CI_docker/context/arosics_ci.docker

-FROM centos:7
-# matplotlib requires freetype, freetype-devel, libpng-devel under centos
-# scikit-image requires blas-devel, lapack-devel, atlas-devel under centos
-RUN yum update -y && \
-    yum install -y wget vim bzip2 gcc gcc-c++ make libgl1-mesa-glx mesa-libGL qt5-qtbase-gui git freetype \
-        freetype-devel libpng-devel blas-devel lapack-devel atlas-devel
-
-ENV anaconda_dl 'Anaconda3-5.0.0-Linux-x86_64.sh'
-RUN /bin/bash -i -c "cd /root; wget https://repo.continuum.io/archive/$anaconda_dl ; \
-    bash -i /root/$anaconda_dl -b ; \
-    rm -f /root/$anaconda_dl"
-
-# 'conda install --yes -c conda-forge 'icu=58.*' lxml' fixing a bug for conda-forge gdal build, as of 06/2017
-# holoviews and bokeh is only needed for geoarray because its not installable via pip during geoarray.setup.py
-RUN /bin/bash -i -c "source /root/anaconda3/bin/activate ; \
-    conda install --yes pyqt; \
-    conda install --yes -c conda-forge pyfftw=0.10.4 ; \
-    conda install --yes -c ioam holoviews bokeh ; \
-    conda install --yes -c conda-forge numpy gdal scikit-image matplotlib pyproj rasterio shapely basemap pykrige geopandas; \
-    conda install --yes -c conda-forge 'icu=58.*' lxml ; \
-    pip install dicttoxml jsmin cerberus pyprind pint iso8601 tqdm mpld3 sphinx-argparse \
-        geoarray>=0.6.12 py_tools_ds>=0.12.1 plotly flake8 pycodestyle pylint pydocstyle coverage nose nose2 \
-        nose-htmloutput rednose"   # must include all the requirements needed to build the docs!
+FROM gms_base_centos:pinned_v0.1
 
 # copy some needed stuff to /root
-#COPY *.pkl /root/ # EXAMPLE
-#COPY *.h5 /root/  # EXAMPLE
-
-# install git lfs
-RUN /bin/bash -i -c "curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.rpm.sh | bash"
-
-# installing git large file support, see here: https://git-lfs.github.com/ , change version number below for future upgrades
-ENV git_lfs_v='2.1.1'
-RUN /bin/bash -i -c "wget https://github.com/git-lfs/git-lfs/releases/download/v${git_lfs_v}/git-lfs-linux-amd64-${git_lfs_v}.tar.gz; \
-    tar -zxvf git-lfs-linux-amd64-${git_lfs_v}.tar.gz; \
-    cd git-lfs-${git_lfs_v}; \
-    bash ./install.sh"
+COPY *.yml /root/
 
-# set matplotlib backend to Agg as default, Qt won't work in headless docker containers
-RUN bash -i -c 'source /root/anaconda3/bin/activate; \
-    sed -i "/backend      : tkagg/c\backend      : Agg" $(python -c "import matplotlib; print(matplotlib.matplotlib_fname())"); \
-    sed -i "/backend      : Qt4Agg/c\backend      : Agg" $(python -c "import matplotlib; print(matplotlib.matplotlib_fname())"); \
-    sed -i "/backend      : qt5agg/c\backend      : Agg" $(python -c "import matplotlib; print(matplotlib.matplotlib_fname())")'
+RUN /bin/bash -i -c "\
+    source /root/miniconda3/bin/activate ; \
+    conda env update -n root -f /root/environment_arosics.yml"

tests/CI_docker/context/environment_arosics.yml

+name: arosics
+
+channels: &id1
+  - http://conda.anaconda.org/ioam  # only for holoviews
+  - http://conda.anaconda.org/conda-forge
+
+dependencies:
+  - python=3.*.*
+  - pyqt
+  - numpy
+  - gdal
+  - scikit-image
+  - rasterio
+  - pyproj
+  - lxml
+  - geopandas
+  - ipython
+  - shapely
+  - matplotlib
+  - basemap
+  - holoviews
+  - bokeh
+  - pykrige
+  - pip:
+    - dicttoxml
+    - jsmin
+    - cerberus
+    - pyprind
+    - pint
+    - iso8601
+    - tqdm
+    - mpld3
+    - sphinx-argparse
+    - six
+    - spectral
+    - flake8
+    - pycodestyle
+    - pylint
+    - pydocstyle
+    - nose
+    - nose2
+    - nose-htmloutput
+    - coverage
+    - rednose
+    - cmocean
+    - plotly
+    - geoarray>=0.6.16
+    - py_tools_ds>=0.12.1

tests/test_COREG_LOCAL.py

@@ -65,7 +65,9 @@ class CompleteWorkflow_INTER1_S2A_S2A(unittest.TestCase):
 
         # test tie point grid visualization
         if util.find_spec('mpl_toolkits.basemap'):  # only works if basemap is installed
-            CRL.view_CoRegPoints()
+            CRL.view_CoRegPoints(hide_filtered=True)
+            CRL.view_CoRegPoints(hide_filtered=False)
+            CRL.view_CoRegPoints(shapes2plot='vectors')
 
         # test shift correction and output writer
         CRL.correct_shifts()