Repository providing python code to load, visualize, analyze, and plot Map Manager files. This can be done in three ways
- Pure Python code using the bMapManager.py class library
- Using the GUI of stackbrowser.py
- Creating web based plots and analysis using bokeh.py
See [bMapManager][bMapManager]. Include the following in a Python script...
from bMapManager import bMap
from bMapManager import bStack
from bMapManager import bStackPlot
To run inside an ipython/jupiter notebook, also include
%matplotlib inline
from plotly.offline import init_notebook_mode
init_notebook_mode() # run at the start of every ipython notebook to use plotly.offline
Requires numpy, pandas, tifffile
See [map.ipynb][1] for more sample code.
A full GUI stack browser implemented in Python using [pyqt][pyqt]. Run the browser with...
python stackbrowser2.py
The next image shows the stack browser interface. A single image plane of a 3D stack is displayed with an overlay of stack db points (red spines). The bottom table shows the stack db.
Eventual features are:
- Load a single timepoint from Map Manager
- 3D stack can be scrolled (image slices), panned, and zoomed
- Image contrast can be adjusted
- Display stack db points overload on image and as a table
- Clicking a point in the image will select it in the table and visa-versa
- Provide x/y plots. Clicking on a point in the plot will propogate to other views
- Provide statistics (mean, standard error, and n) for any plot.
numpy
pandas
pyqt #see below
tifffile #see below
pip install tifffile
brew install pyqt
The QT .jpg reader is not installed by default. Just use .png until this is figured out.
Use the [bokeh][bokeh] python library to generates html pages with a table and x/y plots from a Map Manager file. Selecting points in one plot/table will propagate the selected points to other plots/tables.
python bokeh1.py
Eventual features are:
- Make a Flask app where a Map Manager map or single timepoint file can be loaded.
- Interface to select x/y data from table and then make a new plot.
- On selection, report mean/sd/se/n for selection in each plot
- Provide more advanced plotting and statistics using pandas pivot tables. For example, plot all sLen2d and then create a visual mask and output statistics for each segment.
