make release-tag: Merge branch 'master' into stable

HISTORY.md

@@ -1,5 +1,13 @@
 # History
 
+## v0.1.3 - 2021-02-13
+
+Updates the required dependecies to facilitate a conda release.
+
+### Issues closed
+
+* Upgrade sktime - Issue [#49](https://github.com/sdv-dev/SDMetrics/issues/49) by @fealho
+
 ## v0.1.2 - 2021-01-27
 
 Big fixing release that addresses several minor errors.

README.md

@@ -62,7 +62,7 @@ pip install sdmetrics
 **Using `conda`:**
 
 ```bash
-conda install -c sdv-dev -c conda-forge sdmetrics
+conda install -c sdv-dev -c conda-forge -c pytorch sdmetrics
 ```
 
 For more installation options please visit the [SDMetrics installation Guide](INSTALL.md)

conda/README.md

@@ -17,7 +17,7 @@ branch and build the conda package.
 ```bash
 git checkout stable
 cd conda
-conda build -c sdv-dev -c conda-forge .
+conda build -c sdv-dev -c conda-forge -c pytorch .
 ```
 
 ## Upload to Anaconda

conda/meta.yaml

@@ -1,5 +1,5 @@
 {% set name = 'sdmetrics' %}
-{% set version = '0.1.2' %}
+{% set version = '0.1.3.dev1' %}
 
 package:
   name: "{{ name|lower }}"
@@ -22,20 +22,21 @@ requirements:
     - scipy >=1.1.0,<1.6.0
     - numpy >=1.15.4,<2
     - pandas >=1,<1.1.5
-    - seaborn >=0.9,<0.11
-    - matplotlib >=2.2.2,<3.2.2
     - pomegranate >=0.13.0,<0.13.5
-    - rdt >=0.2.10,<0.3
+    - rdt >=0.2.10,<0.4
+    - pytorch >=1,<2
+    - sktime >=0.5,<0.6
+
   run:
     - python
     - scikit-learn >=0.20,<1
     - scipy >=1.1.0,<1.6.0
     - numpy >=1.15.4,<2
     - pandas >=1,<1.1.5
-    - seaborn >=0.9,<0.11
-    - matplotlib >=2.2.2,<3.2.2
     - pomegranate >=0.13.0,<0.13.5
-    - rdt >=0.2.10,<0.3
+    - rdt >=0.2.10,<0.4
+    - pytorch >=1,<2
+    - sktime >=0.5,<0.6
 
 about:
   home: "https://github.com/sdv-dev/SDMetrics"

sdmetrics/__init__.py

@@ -4,7 +4,7 @@
 
 __author__ = 'MIT Data To AI Lab'
 __email__ = '[email protected]'
-__version__ = '0.1.2'
+__version__ = '0.1.3.dev1'
 
 import pandas as pd
 

sdmetrics/timeseries/ml_scorers.py

@@ -4,7 +4,11 @@
 import torch
 from sklearn.pipeline import Pipeline
 from sktime.classification.compose import TimeSeriesForestClassifier
-from sktime.transformers.series_as_features.compose import ColumnConcatenator
+
+try:
+    from sktime.transformers.series_as_features.compose import ColumnConcatenator
+except (ImportError, AttributeError):
+    from sktime.transformations.panel.compose import ColumnConcatenator
 
 
 def tsf_classifier(X_train, X_test, y_train, y_test):

setup.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.1.2
+current_version = 0.1.3.dev1
 commit = True
 tag = True
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\.(?P<release>[a-z]+)(?P<candidate>\d+))?

setup.py

@@ -12,16 +12,13 @@
     history = history_file.read()
 
 install_requires = [
-    'scikit-learn>=0.20,<1',
-    'sktime>=0.4,<0.5',
-    'tsfresh>=0.15,<1',
-    'scipy>=1.1.0,<1.6.0',
     'numpy>=1.15.4,<2',
     'pandas>=1,<1.1.5',
-    'seaborn>=0.9,<0.11',
-    'matplotlib>=2.2.2,<3.2.2',
     'pomegranate>=0.13.0,<0.13.5',
     'rdt>=0.2.10,<0.4',
+    'scikit-learn>=0.20,<1',
+    'scipy>=1.1.0,<1.6.0',
+    'sktime>=0.4,<0.6',
     'torch>=1,<2',
 ]
 
@@ -101,6 +98,6 @@
     test_suite='tests',
     tests_require=tests_require,
     url='https://github.com/sdv-dev/SDMetrics',
-    version='0.1.2',
+    version='0.1.3.dev1',
     zip_safe=False,
 )