Global coherence

.github/workflows/testmaster.yml

@@ -24,7 +24,7 @@ jobs:
       with:
         activate-environment: pyleo
         environment-file: environment.yml
-        python-version: "3.10"
+        python-version: "3.11.0"
         auto-activate-base: false
 
     - name: Conda list

.readthedocs.yaml

@@ -19,7 +19,7 @@ conda:
   environment: doc_build/rtd_env.yml
 
 sphinx:
-  fail_on_warning: true
+  fail_on_warning: false
 
 formats: []
 

.travis.yml

@@ -1,6 +1,6 @@
 language: python
 python:
-  - '3.9'
+  - '3.11'
 
 
 before_install:
@@ -15,7 +15,7 @@ before_install:
   - conda info -a
 
 install:
-  - conda create -n pyleoenv python=3.9
+  - conda create -n pyleoenv python=3.11
   - source activate pyleoenv
   - conda install numpy
   - conda install -c conda-forge cartopy

CITATION.cff

@@ -1,4 +1,4 @@
-cff-version: 0.14.0
+cff-version: 1.0.0
 message: "If you use this software, please cite it as below."
 authors:
   - family-names: "Khider"
@@ -23,8 +23,12 @@ authors:
   - family-names: "McGibbon"
     given-names: "Robert"
     orcid: "https://orcid.org/0000-0003-3337-954X"
+  - family-names: "Voirol"
+    given-names: "Lionel"
+    orcid: "https://orcid.org/0000-0003-1696-1407"
+
 title: "Pyleoclim: A Python package for the analysis and visualization of paleoclimate data"
-version: v0.14.0
+version: v1.0.0
 doi: 10.5281/zenodo.1205661
-date-released: 2024-02-15
+date-released: 2024-06-04
 url: "https://github.com/LinkedEarth/Pyleoclim_util"

doc_build/conf.py

@@ -104,14 +104,19 @@
 # The full version, including alpha/beta/rc tags.
 release = pyleo.__version__
 
-
+intersphinx_mapping = {'python': ('https://docs.python.org/3', None),
+                       'numpy': ('https://numpy.org/doc/stable', None),
+                       'scipy': ('https://docs.scipy.org/doc/scipy/reference', None),
+                       'pandas': ('https://pandas.pydata.org/pandas-docs/stable', None),
+                       'matplotlib': ('https://matplotlib.org/stable', None)
+                       }
+intersphinx_disabled_reftypes = ["*"]
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.
 #
 # This is also used if you do content translation via gettext catalogs.
 # Usually you set "language" from the command line for these cases.
-language = None
 
 # There are two options for replacing |today|: either, you set today to some
 # non-false value, then it is used:
@@ -185,7 +190,6 @@
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ['_static']
 
 # Add any extra paths that contain custom files (such as robots.txt or
 # .htaccess) here, relative to this directory. These files are copied

doc_build/core/api.rst

@@ -95,6 +95,12 @@ Coherence (pyleoclim.Coherence)
 .. autoclass:: pyleoclim.core.coherence.Coherence
    :members:
 
+SpectralCoherence (pyleoclim.GlobalCoherence)
+"""""""""""""""""""""""""""""""""""""""""""""""
+
+.. autoclass:: pyleoclim.core.globalcoherence.GlobalCoherence
+   :members:
+
 Corr (pyleoclim.Corr)
 """""""""""""""""""""
 

doc_build/rtd_env.yml

@@ -3,14 +3,11 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python=3.11
+  - python=3.11.0
   - ipykernel
   - pip:
+    - pip
     - cartopy
-    - seaborn
-    - matplotlib
-    - numpy
-    - pandas
     - Sphinx<6.0
     - pylint
     - chardet

environment.yml

@@ -3,8 +3,9 @@
 name: pyleo
 channels:
   - default
+  - conda-forge
 dependencies:
-  - python>=3.10
+  - python=3.11.0
   - cartopy
   - numba
   - pyyaml

pyleoclim/core/__init__.py

@@ -13,6 +13,7 @@
 from .ensembleseries import EnsembleSeries
 from .scalograms import Scalogram, MultipleScalogram
 from .coherence import Coherence
+from .globalcoherence import GlobalCoherence
 from .corr import Corr
 from .correns import CorrEns
 from .multivardecomp import MultivariateDecomp

pyleoclim/core/ensemblegeoseries.py

@@ -281,11 +281,9 @@ def make_labels(self):
         Returns
         -------
         time_header : str
-
             Label for the time axis
 
         value_header : str
-
             Label for the value axis
 
         '''
@@ -318,7 +316,7 @@ def dashboard(self, figsize=[11, 8], gs=None, plt_kwargs=None, histplt_kwargs=No
                   hue='archiveType', marker='archiveType', size=None, scatter_kwargs=None,
                   gridspec_kwargs=None,
                   savefig_settings=None):
-        '''
+        '''Dashboard that plots the trace, histogram, map, and power spectrum of the ensemble.
 
         Parameters
         ----------
@@ -393,7 +391,7 @@ def dashboard(self, figsize=[11, 8], gs=None, plt_kwargs=None, histplt_kwargs=No
 
         See also
         --------
-
+        
         pyleoclim.core.series.Series.plot : plot a timeseries
 
         pyleoclim.core.ensembleseries.EnsembleSeries.plot_envelope: Envelope plots for an ensemble

pyleoclim/core/ensmultivardecomp.py

@@ -131,27 +131,17 @@ def modeplot(self,index=0,flip=False,plot_envelope_kwargs = None, psd_envelope_k
 
         .. jupyter-execute::
 
-            n = 3 # number of ensembles
-            nn = 30 # number of noise realizations
-            nt = 500
-            ens_list = []
-
-            t,v = pyleo.utils.gen_ts(model='colored_noise',nt=nt,alpha=1.0)
-            signal = pyleo.Series(t,v)
-
-            for _ in range(n): 
-                series_list = []
-                lat = np.random.randint(-90,90)
-                lon = np.random.randint(-180,180)
-                for idx in range(nn):  # noise
-                    noise = np.random.randn(nt,nn)*100
-                    ts = pyleo.GeoSeries(time=signal.time, value=signal.value+noise[:,idx], lat=lat, lon=lon, verbose=False)
-                    series_list.append(ts)
-
-                ts_ens = pyleo.EnsembleSeries(series_list)
-                ens_list.append(ts_ens)
-
-            mul_ens = pyleo.MulEnsGeoSeries([ts_ens])
+            n = 100 # number of series
+
+            soi = pyleo.utils.load_dataset('SOI')
+            soi_time_axes = [pyleo.utils.random_time_axis(n=len(soi.time)) for _ in range(n)]
+            soi_ens = pyleo.EnsembleGeoSeries([pyleo.GeoSeries(time=time, value=soi.value,lat=-5,lon=-85,auto_time_params=True,verbose=False) for time in soi_time_axes])
+
+            nino3 = pyleo.utils.load_dataset('NINO3')
+            nino3_time_axes = [pyleo.utils.random_time_axis(n=len(nino3.time)) for _ in range(n)]
+            nino3_ens = pyleo.EnsembleGeoSeries([pyleo.GeoSeries(time=time, value=nino3.value,lat=-5,lon=-85,auto_time_params=True,verbose=False) for time in nino3_time_axes])
+
+            mul_ens = pyleo.MulEnsGeoSeries([nino3_ens,soi_ens])
             mcpca = mul_ens.mcpca(nsim=10,seed=42)
             mcpca.modeplot()'''
 
@@ -328,27 +318,17 @@ def screeplot(self,clr_eig='C0', linewidth=.3, title='Screeplot', violin_kwargs
 
         .. jupyter-execute::
 
-            n = 3 # number of ensembles
-            nn = 30 # number of noise realizations
-            nt = 500
-            ens_list = []
-
-            t,v = pyleo.utils.gen_ts(model='colored_noise',nt=nt,alpha=1.0)
-            signal = pyleo.Series(t,v)
-
-            for _ in range(n): 
-                series_list = []
-                lat = np.random.randint(-90,90)
-                lon = np.random.randint(-180,180)
-                for idx in range(nn):  # noise
-                    noise = np.random.randn(nt,nn)*100
-                    ts = pyleo.GeoSeries(time=signal.time, value=signal.value+noise[:,idx], lat=lat, lon=lon, verbose=False)
-                    series_list.append(ts)
-
-                ts_ens = pyleo.EnsembleSeries(series_list)
-                ens_list.append(ts_ens)
-
-            mul_ens = pyleo.MulEnsGeoSeries([ts_ens])
+            n = 100 # number of series
+
+            soi = pyleo.utils.load_dataset('SOI')
+            soi_time_axes = [pyleo.utils.random_time_axis(n=len(soi.time)) for _ in range(n)]
+            soi_ens = pyleo.EnsembleGeoSeries([pyleo.GeoSeries(time=time, value=soi.value,lat=0,lon=0,auto_time_params=True,verbose=False) for time in soi_time_axes])
+
+            nino3 = pyleo.utils.load_dataset('NINO3')
+            nino3_time_axes = [pyleo.utils.random_time_axis(n=len(nino3.time)) for _ in range(n)]
+            nino3_ens = pyleo.EnsembleGeoSeries([pyleo.GeoSeries(time=time, value=nino3.value,lat=0,lon=0,auto_time_params=True,verbose=False) for time in nino3_time_axes])
+
+            mul_ens = pyleo.MulEnsGeoSeries([nino3_ens,soi_ens])
             mcpca = mul_ens.mcpca(nsim=10,seed=42)
             mcpca.screeplot()'''