Comprehensive Walkthrough¶
The following examples should form a comprehensive walkthrough of downloading the package, getting EnviroOrg output data into the right format for importing, generating a CrossTable instance, calculating and saving a summary table, and plotting various van Krevelen plots.
For detailed information on class attributes, methods, and parameters, consult the Package Reference Documentation or use the help()
command within Python.
Quick Guide¶
Basic runthrough:
#import modules
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import fouriertransform as ft
#generate string to path containing EnviroOrg data
dir_name = 'path_name'
#make the CrossTable instance
ct = ft.CrossTable.from_eo(
dir_name,
file_names = 'all', #can replace with list of names
rescale = 'fraction')
#make the summary table
sum_tab = ct.generate_summary()
#save summary to csv
sum_tab.to_csv('~/Desktop/summary_table.csv')
#plot formula intensities and classes for a single sample
fig, ax = plt.subplots(2,1)
#make van krevelen plot of intensity
ax[0] = ct.plot_sample_vk(
'sample_name',
ax = ax[0],
plot_type = 'intensity',
log = True,
edgecolor = 'w',
s = 40,
cmap = 'YlGnBu')
#make van krevelen plot of classes
ax[1] = ct.plot_sample_vk(
'sample_name',
ax = ax[1]
plot_type = 'class',
edgecolor = 'w',
s = 40)
#plot the presence-absense difference between two samples
fig, ax = plt.subplots(1,1)
ax = ct.plot_difference_vk(
'sample_name1',
'sample_name2',
ax = ax,
edgecolor = 'w',
s = 40)
#plot the Spearman correlations with some environmental parameter
fig, ax = plt.subplots(1,1)
#make van krevelen plot
ax = ct.plot_correlation_vk(
env_param, #values of other parameter (e.g. d13C, D14C, etc.)
ax = ax,
corr_type = 'Spearman',
f = 1, #fraction of samples that formula must be in
alpha = 0.05, #significance cutoff
edgecolor = 'w',
s = 40,
cmap = 'coolwarm',
vmin = -1,
vmax = 1)
Downloading the package¶
Using the pip
package manager¶
fouriertransform
and the associated dependencies can be downloaded directly from the command line using pip
:
$ pip install fouriertransform
You can check that your installed version is up to date with the latest release by doing:
$ pip freeze
Downloading from source¶
Alternatively, fouriertransform
source code can be downloaded directly from my github repo. Or, if you have git installed:
$ git clone git://github.com/FluvialSeds/fouriertransform.git
And keep up-to-date with the latest version by doing:
$ git pull
from within the fouriertransform directory.
Dependencies¶
The following packages are required to run fouriertransform
:
- python >= 2.7, including Python 3.x
- matplotlib >= 1.5.2
- numpy >= 1.11.1
- pandas >= 0.18.1
- scipy >= 0.18.0
If downloading using pip
, these dependencies (except python) are installed
automatically.
Optional Dependencies¶
The following packages are not required but are highly recommended:
- ipython >= 4.1.1
Additionally, if you are new to the Python environment or programming using the command line, consider using a Python integrated development environment (IDE) such as:
Python IDEs provide a “MATLAB-like” environment as well as package management. This option should look familiar for users coming from a MATLAB or RStudio background.
Detailed Walkthrough¶
Coming soon!