diff --git a/README.md b/README.md
index 8f11f43..159c8e5 100644
--- a/README.md
+++ b/README.md
@@ -1,8 +1,9 @@
-
-
-
+
+
+\
+
@@ -34,15 +35,20 @@ pip install fitting-toolkit==1.0.1
You can find all releases here:
-[](https://github.com/davidkowalk/fitting_toolkit/releases)
+
+To install the current development version ahead of releases check out the development branches.
+| Branch | Purpose
+|-----------------|-------------
+| development-1.0 | Bug fixes and documentation adding onto version 1.0.1
+| development-1.1 | Development of new major features
After downloading the desired version you can find the `fitting_toolkit.py` in the `src` folder and copy it into your project.
To build the project yourself and install it, make sure `setuptools` and `wheel` are installed, then run
```
python3 setup.py sdist bdist_wheel
-pip install .\dist\fitting_toolkit-1.0.1-py3-none-any.whl --force-reinstall
+pip install --no-deps --force-reinstall ./dist/fitting_toolkit-VERSION_NUMBER-py3-none-any.whl
pip show fitting-toolkit -v
```
diff --git a/docs/img/download.svg b/docs/img/download.svg
new file mode 100644
index 0000000..421529b
--- /dev/null
+++ b/docs/img/download.svg
@@ -0,0 +1,6 @@
+
\ No newline at end of file
diff --git a/package_description.md b/package_description.md
new file mode 100644
index 0000000..7e800da
--- /dev/null
+++ b/package_description.md
@@ -0,0 +1,98 @@
+
+
+
+
+
+
+\
+
+
+
+
+# Fitting Toolkit
+This toolkit aims at providing flexible and powerful tools for data analysis and modelling, but remain easy to use.
+This toolkit is aimed primarily at my peers, students of physics at the university of bonn, and to a degree at professionals within my field. I am optimizing this toolkit to be used on the scale typical of lab courses and homework assignments but if possible it should be powerful enough to run decently sized datasets on an average laptop.
+
+This package wraps numpy for fast data management and manipulation, scipy for `curve_fit()` and matplotlib for display options.
+
+## Quick Introduction
+
+### Installation
+
+There are multiple ways to install this package. The easiest is via pip:
+```
+pip install fitting-toolkit
+```
+If you need a specific version (for example due to compatibillity issues) you can specify the version via `fitting-toolkit==version`, e.g:
+```
+pip install fitting-toolkit==1.0.1
+```
+
+### Alternative Installation Methods
+
+To install the current development version ahead of releases check out the development branches on GitHub.
+| Branch | Purpose
+|-----------------|-------------
+| development-1.0 | Bug fixes and documentation adding onto version 1.0.1
+| development-1.1 | Development of new major features
+
+After downloading the desired version you can find the `fitting_toolkit.py` in the `src` folder and copy it into your project.
+
+To build the project yourself and install it, make sure `setuptools` and `wheel` are installed, then run
+```
+python3 setup.py sdist bdist_wheel
+pip install --no-deps --force-reinstall ./dist/fitting_toolkit-VERSION_NUMBER-py3-none-any.whl
+pip show fitting-toolkit -v
+```
+
+### Requirements
+This project requires the following modules along with their dependencies:
+- numpy
+- matplotlib
+- scipy
+
+It is highly recommended that the user familiarizes themselves with the functionality of these modules first. A rudimentary understanding of `numpy` and `matplotlib.pyplot` is required.
+
+If you install via pip the dependencies will automatically be installed. However if the project files are used directly you may want to install dependencies manually:
+
+To install the dependencies, first a [virtual environment](https://docs.python.org/3/library/venv.html) should be created. `requirements.txt` lists all necessary packages. Run:
+```
+pip install -r requirements.txt
+```
+
+### Getting Started
+
+You can now import the relevant functions into your code:
+```python
+from fitting_toolkit import curve_fit, plot_fit
+import numpy as np
+```
+The `curve_fit` requires numpy-arrays. Therefore numpy has to be imported as well.
+
+We can now start by defining our data.
+```python
+x = np.array((1, 2, 3, 4, 5))
+y = np.array((1, 2, 1.75, 2.25, 3))
+dy = 0.1*y+0.05
+dx = 0.1
+```
+We chose a simple linear model:
+```python
+def f(x, a, b):
+ return a * x + b
+```
+We can now fit the model to the data:
+```python
+params, cov, lower_conf, upper_conf = curve_fit(f, x, y, yerror=dy)
+```
+This functions returns 4 arrays. First the parameters of the model, the covariance matrix of those parameters and then the lower and upper limits of the confidence interval around the fit. Note that the confidence interval is absolute. To get the error in relation to the fitted function you would need to find the difference at each point.
+
+The resulting fit can now be plotted. This toolkit provides a premade function to generate plots:
+```python
+from matplotlib import pyplot as plt
+fig, ax = plot_fit(x, y, f, params, lower_conf, upper_conf, xerror=dx, yerror=dy)
+plt.show()
+```
+Note that the fitted function is not automatically displayed. Instead the figure and axis-objects are returned.
+
+
\ No newline at end of file
diff --git a/setup.py b/setup.py
index df2b1d5..9aa3537 100644
--- a/setup.py
+++ b/setup.py
@@ -1,7 +1,7 @@
from setuptools import setup
#run with python3 setup.py sdist bdist_wheel
-with open("./README.md") as f:
+with open("./package_description.md") as f:
description = f.read()
with open("./requirements.txt", encoding="utf-16") as f:
@@ -9,17 +9,22 @@
setup(
name = "fitting_toolkit",
- version = "1.0.1",
+ version = "1.0.2",
package_dir={"": "src"},
packages=[""],
long_description=description,
long_description_content_type="text/markdown",
install_requires = requirements,
project_urls = {
- "Documentation": "https://github.com/davidkowalk/fitting_toolkit/blob/development/docs/manual.md",
+ "Documentation": "https://github.com/davidkowalk/fitting_toolkit/blob/Stable/docs/manual.md",
"Source": "https://github.com/davidkowalk/fitting_toolkit/",
"Tracker": "https://github.com/davidkowalk/fitting_toolkit/issues"
},
+ classifiers=[
+ "Programming Language :: Python",
+ "Programming Language :: Python :: 3",
+ "Natural Language :: English"
+ ],
license="MIT",
description="Easy and Flexible Curve Fitting",
url="https://github.com/davidkowalk/fitting_toolkit/"
](https://github.com/davidkowalk/fitting_toolkit/releases)
+
+To install the current development version ahead of releases check out the development branches.
+| Branch | Purpose
+|-----------------|-------------
+| development-1.0 | Bug fixes and documentation adding onto version 1.0.1
+| development-1.1 | Development of new major features
After downloading the desired version you can find the `fitting_toolkit.py` in the `src` folder and copy it into your project.
To build the project yourself and install it, make sure `setuptools` and `wheel` are installed, then run
```
python3 setup.py sdist bdist_wheel
-pip install .\dist\fitting_toolkit-1.0.1-py3-none-any.whl --force-reinstall
+pip install --no-deps --force-reinstall ./dist/fitting_toolkit-VERSION_NUMBER-py3-none-any.whl
pip show fitting-toolkit -v
```
diff --git a/docs/img/download.svg b/docs/img/download.svg
new file mode 100644
index 0000000..421529b
--- /dev/null
+++ b/docs/img/download.svg
@@ -0,0 +1,6 @@
+
\ No newline at end of file
diff --git a/package_description.md b/package_description.md
new file mode 100644
index 0000000..7e800da
--- /dev/null
+++ b/package_description.md
@@ -0,0 +1,98 @@
+
+
+
+
+
+
+\
+
+
+
+
+# Fitting Toolkit
+This toolkit aims at providing flexible and powerful tools for data analysis and modelling, but remain easy to use.
+This toolkit is aimed primarily at my peers, students of physics at the university of bonn, and to a degree at professionals within my field. I am optimizing this toolkit to be used on the scale typical of lab courses and homework assignments but if possible it should be powerful enough to run decently sized datasets on an average laptop.
+
+This package wraps numpy for fast data management and manipulation, scipy for `curve_fit()` and matplotlib for display options.
+
+## Quick Introduction
+
+### Installation
+
+There are multiple ways to install this package. The easiest is via pip:
+```
+pip install fitting-toolkit
+```
+If you need a specific version (for example due to compatibillity issues) you can specify the version via `fitting-toolkit==version`, e.g:
+```
+pip install fitting-toolkit==1.0.1
+```
+
+### Alternative Installation Methods
+
+To install the current development version ahead of releases check out the development branches on GitHub.
+| Branch | Purpose
+|-----------------|-------------
+| development-1.0 | Bug fixes and documentation adding onto version 1.0.1
+| development-1.1 | Development of new major features
+
+After downloading the desired version you can find the `fitting_toolkit.py` in the `src` folder and copy it into your project.
+
+To build the project yourself and install it, make sure `setuptools` and `wheel` are installed, then run
+```
+python3 setup.py sdist bdist_wheel
+pip install --no-deps --force-reinstall ./dist/fitting_toolkit-VERSION_NUMBER-py3-none-any.whl
+pip show fitting-toolkit -v
+```
+
+### Requirements
+This project requires the following modules along with their dependencies:
+- numpy
+- matplotlib
+- scipy
+
+It is highly recommended that the user familiarizes themselves with the functionality of these modules first. A rudimentary understanding of `numpy` and `matplotlib.pyplot` is required.
+
+If you install via pip the dependencies will automatically be installed. However if the project files are used directly you may want to install dependencies manually:
+
+To install the dependencies, first a [virtual environment](https://docs.python.org/3/library/venv.html) should be created. `requirements.txt` lists all necessary packages. Run:
+```
+pip install -r requirements.txt
+```
+
+### Getting Started
+
+You can now import the relevant functions into your code:
+```python
+from fitting_toolkit import curve_fit, plot_fit
+import numpy as np
+```
+The `curve_fit` requires numpy-arrays. Therefore numpy has to be imported as well.
+
+We can now start by defining our data.
+```python
+x = np.array((1, 2, 3, 4, 5))
+y = np.array((1, 2, 1.75, 2.25, 3))
+dy = 0.1*y+0.05
+dx = 0.1
+```
+We chose a simple linear model:
+```python
+def f(x, a, b):
+ return a * x + b
+```
+We can now fit the model to the data:
+```python
+params, cov, lower_conf, upper_conf = curve_fit(f, x, y, yerror=dy)
+```
+This functions returns 4 arrays. First the parameters of the model, the covariance matrix of those parameters and then the lower and upper limits of the confidence interval around the fit. Note that the confidence interval is absolute. To get the error in relation to the fitted function you would need to find the difference at each point.
+
+The resulting fit can now be plotted. This toolkit provides a premade function to generate plots:
+```python
+from matplotlib import pyplot as plt
+fig, ax = plot_fit(x, y, f, params, lower_conf, upper_conf, xerror=dx, yerror=dy)
+plt.show()
+```
+Note that the fitted function is not automatically displayed. Instead the figure and axis-objects are returned.
+
+
\ No newline at end of file
diff --git a/setup.py b/setup.py
index df2b1d5..9aa3537 100644
--- a/setup.py
+++ b/setup.py
@@ -1,7 +1,7 @@
from setuptools import setup
#run with python3 setup.py sdist bdist_wheel
-with open("./README.md") as f:
+with open("./package_description.md") as f:
description = f.read()
with open("./requirements.txt", encoding="utf-16") as f:
@@ -9,17 +9,22 @@
setup(
name = "fitting_toolkit",
- version = "1.0.1",
+ version = "1.0.2",
package_dir={"": "src"},
packages=[""],
long_description=description,
long_description_content_type="text/markdown",
install_requires = requirements,
project_urls = {
- "Documentation": "https://github.com/davidkowalk/fitting_toolkit/blob/development/docs/manual.md",
+ "Documentation": "https://github.com/davidkowalk/fitting_toolkit/blob/Stable/docs/manual.md",
"Source": "https://github.com/davidkowalk/fitting_toolkit/",
"Tracker": "https://github.com/davidkowalk/fitting_toolkit/issues"
},
+ classifiers=[
+ "Programming Language :: Python",
+ "Programming Language :: Python :: 3",
+ "Natural Language :: English"
+ ],
license="MIT",
description="Easy and Flexible Curve Fitting",
url="https://github.com/davidkowalk/fitting_toolkit/"