Merge pull request #11 from Techtonique/plot-mts

Plot mts

Author: thierrymoudiki

.DS_Store

@@ -0,0 +1,37 @@
+name: Publish Python 🐍 distribution 📦 to PyPI
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - master  # Replace with your branch name
+
+jobs:
+  publish:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+
+      - name: Set up Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: '3.x'  # Replace with your Python version
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install wheel setuptools twine
+
+      - name: Build distribution
+        run: python setup.py sdist bdist_wheel
+
+      - name: Run examples 
+        run: pip install .&&find examples -maxdepth 2 -name "*.py" -exec  python3 {} \;
+
+      - name: Publish to PyPI                
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          password: ${{ secrets.PYPI_AHEAD }}
+          repository-url: https://upload.pypi.org/legacy/

.github/workflows/python-publish.yml

@@ -1,3 +1,9 @@
+# version 0.10.0
+
+- Naming series in input data frame
+- Plot method for all the objects 
+- More about the code: begin refactoring and DRYing --> Base class 
+
 # version 0.9.0
 
 - Align with R version

CHANGES.md

@@ -1,8 +1,9 @@
+
 .PHONY: clean clean-test clean-pyc clean-build docs help
 .DEFAULT_GOAL := help
 
 define BROWSER_PYSCRIPT
-import os, webbrowser, sys
+import os, webbrowser, sys, mkdocs
 
 from urllib.request import pathname2url
 
@@ -31,55 +32,51 @@ clean: clean-build clean-pyc clean-test ## remove all build, test, coverage and
 clean-build: ## remove build artifacts
 	rm -fr build/
 	rm -fr dist/
-	rm -fr .eggs/
+	rm -fr .eggs/	
 	find . -name '*.egg-info' -exec rm -fr {} +
-	find . -name '*.egg' -exec rm -rf {} +
+	find . -name '*.egg' -exec rm -fr {} +
 
 clean-pyc: ## remove Python file artifacts
 	find . -name '*.pyc' -exec rm -f {} +
 	find . -name '*.pyo' -exec rm -f {} +
 	find . -name '*~' -exec rm -f {} +
 	find . -name '__pycache__' -exec rm -fr {} +
 
-clean-test: ## remove test and coverage artifacts
-	rm -fr .tox/
-	rm -f .coverage
-	rm -fr htmlcov/
-	rm -fr .pytest_cache
+clean-test: ## remove test and coverage artifacts	
+	rm -fr htmlcov
 
 lint: ## check style with flake8
 	flake8 ahead tests
 
-test: ## run tests quickly with the default Python
-	python -m unittest 
-
-test-all: ## run tests on every Python version with tox
-	tox
-
 coverage: ## check code coverage quickly with the default Python
 	coverage run --source ahead setup.py test
 	coverage report -m
 	coverage html
 	$(BROWSER) htmlcov/index.html
 
-docs: ## generate mkdocs
-	 rm -rf docs/sources
-	 make install	 
-	 python3 docs/autogen.py	 
+docs: ## generate docs		
+	pip install black pdoc 
+	black ahead/* --line-length=80	
+	pdoc -t docs ahead/* --output-dir ahead-docs
+	find . -name '__pycache__' -exec rm -fr {} +
 
-servedocs: docs ## compile the docs watching for changes
-	cd docs&&mkdocs serve
-	cd ..
+servedocs: ## compile the docs watching for change	 	
+	pip install black pdoc 
+	black ahead/* --line-length=80	
+	pdoc -t docs ahead/* 
+	find . -name '__pycache__' -exec rm -fr {} +
 
 release: dist ## package and upload a release
-	twine upload dist/*
+	pip install twine --ignore-installed
+	python3 -m twine upload --repository pypi dist/* --verbose
 
 dist: clean ## builds source and wheel package
-	python3 setup.py bdist_wheel
+	python3 setup.py sdist
+	python3 setup.py bdist_wheel	
 	ls -l dist
 
 install: clean ## install the package to the active Python's site-packages
-	python3 -m pip install .
+	python3 -m pip install . --verbose
 
 build-site: docs ## put docs website in a directory
 	cd docs&&mkdocs build

Makefile

@@ -27,13 +27,13 @@ The Python implementation contains only the [automatic version](https://thierrym
 - From Pypi, stable version:
 
 ```bash
-pip install ahead
+pip install ahead --verbose
 ```
 
 - From Github, for the development version: 
 
 ```bash
-pip install git+https://github.com/Techtonique/ahead_python.git
+pip install git+https://github.com/Techtonique/ahead_python.git --verbose
 ```
 
 ## Quickstart 

README.md

@@ -4,8 +4,9 @@
 from ..utils import univariate as uv
 from ..utils import unimultivariate as umv
 
+
 class ArmaGarch(object):
-    """ ARMA(1, 1)-GARCH(1, 1) forecasting (with simulation)
+    """ARMA(1, 1)-GARCH(1, 1) forecasting (with simulation)
 
     Parameters:
 
@@ -25,7 +26,7 @@ class ArmaGarch(object):
             distribution of innovations ("student" or "gaussian")
 
         seed: an integer;
-            reproducibility seed                
+            reproducibility seed
 
         date_formatting: a string;
             Currently:
@@ -45,15 +46,15 @@ class ArmaGarch(object):
 
         output_dates_: a list;
             a list of output dates (associated to forecast)
-        
+
         mean_: a numpy array
-            contains series mean forecast as a numpy array 
+            contains series mean forecast as a numpy array
 
-        lower_: a numpy array 
-            contains series lower bound forecast as a numpy array   
+        lower_: a numpy array
+            contains series lower bound forecast as a numpy array
 
-        upper_: a numpy array 
-            contains series upper bound forecast as a numpy array   
+        upper_: a numpy array
+            contains series upper bound forecast as a numpy array
 
         result_df_: a data frame;
             contains 3 columns, mean forecast, lower + upper
@@ -68,24 +69,19 @@ def __init__(
         self,
         h=5,
         level=95,
-        B = 250,
-        cl = 1,
-        dist = "student",
-        seed = 123,
+        B=250,
+        cl=1,
+        dist="student",
+        seed=123,
         date_formatting="original",
-    ): 
-        if not config.R_IS_INSTALLED:
-            raise ImportError("R is not installed! \n" + config.USAGE_MESSAGE)
-        
-        if not config.RPY2_IS_INSTALLED:
-            raise ImportError(config.RPY2_ERROR_MESSAGE + config.USAGE_MESSAGE)
-        
+    ):
+
         self.h = h
         self.level = level
         self.B = B
         self.cl = cl
         self.dist = dist
-        self.seed = seed 
+        self.seed = seed
         self.date_formatting = date_formatting
         self.input_df = None
 
@@ -94,10 +90,10 @@ def __init__(
         self.ranges_ = None
         self.output_dates_ = []
         self.mean_ = []
-        self.lower_= []
-        self.upper_= []
+        self.lower_ = []
+        self.upper_ = []
         self.result_df_ = None
-        self.sims_ = None 
+        self.sims_ = None
 
     def forecast(self, df):
         """Forecasting method from `ArmaGarch` class
@@ -109,47 +105,32 @@ def forecast(self, df):
 
         """
 
-        self.input_df = df
+        # get input dates, output dates, number of series, series names, etc. 
+        self.init_forecasting_params(df)        
 
-        # obtain dates 'forecast' -----
-
-        output_dates, frequency = umv.compute_output_dates(
-            self.input_df, self.h
-        )
+        # obtain time series object -----
+        self.format_input()
 
-        # obtain time series forecast -----
-
-        y = uv.compute_y_ts(df=self.input_df, df_frequency=frequency)
-
-        self.fcast_ = config.AHEAD_PACKAGE.armagarchf(
-            y=y,
-            h=self.h,
-            level=self.level,
-            B=self.B,
-            cl=self.cl,
-            dist=self.dist,
-            seed=self.seed
-        )
+        self.get_forecast("armagarch")
 
         # result -----
-
         (
             self.averages_,
             self.ranges_,
             self.output_dates_,
         ) = uv.format_univariate_forecast(
             date_formatting=self.date_formatting,
-            output_dates=output_dates,
+            output_dates=self.output_dates_,
             horizon=self.h,
             fcast=self.fcast_,
         )
 
-        self.mean_ = np.asarray(self.fcast_.rx2['mean'])
-        self.lower_= np.asarray(self.fcast_.rx2['lower'])
-        self.upper_= np.asarray(self.fcast_.rx2['upper'])
+        self.mean_ = np.asarray(self.fcast_.rx2["mean"])
+        self.lower_ = np.asarray(self.fcast_.rx2["lower"])
+        self.upper_ = np.asarray(self.fcast_.rx2["upper"])
 
         self.result_df_ = umv.compute_result_df(self.averages_, self.ranges_)
 
-        self.sims_ = np.asarray(self.fcast_.rx2['sims'])
+        self.sims_ = np.asarray(self.fcast_.rx2["sims"])
 
         return self