diff_classifier.heatmaps

diff_classifier.heatmaps

diff_classifier.heatmaps.plot_heatmap(prefix, feature='asymmetry1', vmin=0, vmax=1, resolution=512, rows=4, cols=4, upload=True, dpi=None, figsize=(12, 10), remote_folder='01_18_Experiment', bucket='ccurtis.data')

Plot heatmap of trajectories in video with colors corresponding to features.

Parameters:

prefix: string

Prefix of file name to be plotted e.g. features_P1.csv prefix is P1.

feature: string

Feature to be plotted. See features_analysis.py

vmin: float64

Lower intensity bound for heatmap.

vmax: float64

Upper intensity bound for heatmap.

resolution: int

Resolution of base image. Only needed to calculate bounds of image.

rows: int

Rows of base images used to build tiled image.

cols: int

Columns of base images used to build tiled images.

upload: boolean

True if you want to upload to s3.

dpi: int

Desired dpi of output image.

figsize: list

Desired dimensions of output image.

diff_classifier.heatmaps.plot_histogram(prefix, xlabel='Log Diffusion Coefficient Dist', ylabel='Trajectory Count', fps=100.02, umppx=0.16, frames=651, y_range=100, frame_interval=20, frame_range=100, analysis='log', theta='D', upload=True, remote_folder='01_18_Experiment', bucket='ccurtis.data')

Plot heatmap of trajectories in video with colors corresponding to features.

Parameters:

prefix: string

Prefix of file name to be plotted e.g. features_P1.csv prefix is P1.

xlabel: string

X axis label.

ylabel: string

Y axis label.

fps: float64

Frames per second of video.

umppx: float64

Resolution of video in microns per pixel.

frames: int

Number of frames in video.

y_range: float64 or int

Desire y range of graph.

frame_interval: int

Desired spacing between MSDs/Deffs to be plotted.

analysis: string

Desired output format. If log, will plot log(MSDs/Deffs)

theta: string

Desired output. D for diffusion coefficients. Anything else, MSDs.

upload: boolean

True if you want to upload to s3.

diff_classifier.heatmaps.plot_individual_msds(prefix, x_range=100, y_range=20, umppx=0.16, fps=100.02, alpha=0.01, folder='.', upload=True, remote_folder='01_18_Experiment', bucket='ccurtis.data', figsize=(10, 10))

Plot MSDs of trajectories and the geometric average.

Parameters:

prefix: string

Prefix of file name to be plotted e.g. features_P1.csv prefix is P1.

x_range: float64 or int

Desire x range of graph.

y_range: float64 or int

Desire y range of graph.

fps: float64

Frames per second of video.

umppx: float64

Resolution of video in microns per pixel.

alpha: float64

Transparency factor. Between 0 and 1.

upload: boolean

True if you want to upload to s3.

Returns:

geo_mean: numpy array

Geometric mean of trajectory MSDs at all time points.

geo_SEM: numpy array

Geometric standard errot of trajectory MSDs at all time points.

diff_classifier.heatmaps.plot_particles_in_frame(prefix, x_range=600, y_range=2000, upload=True, remote_folder='01_18_Experiment', bucket='ccurtis.data')

Plot number of particles per frame as a function of time.

Parameters:

prefix: string

Prefix of file name to be plotted e.g. features_P1.csv prefix is P1.

x_range: float64 or int

Desire x range of graph.

y_range: float64 or int

Desire y range of graph.

upload: boolean

True if you want to upload to s3.

diff_classifier.heatmaps.plot_scatterplot(prefix, feature='asymmetry1', vmin=0, vmax=1, resolution=512, rows=4, cols=4, dotsize=10, figsize=(12, 10), upload=True, remote_folder='01_18_Experiment', bucket='ccurtis.data')

Plot scatterplot of trajectories in video with colors corresponding to features.

Parameters:

prefix: string

Prefix of file name to be plotted e.g. features_P1.csv prefix is P1.

feature: string

Feature to be plotted. See features_analysis.py

vmin: float64

Lower intensity bound for heatmap.

vmax: float64

Upper intensity bound for heatmap.

resolution: int

Resolution of base image. Only needed to calculate bounds of image.

rows: int

Rows of base images used to build tiled image.

cols: int

Columns of base images used to build tiled images.

upload: boolean

True if you want to upload to s3.

diff_classifier.heatmaps.plot_trajectories(prefix, resolution=512, rows=4, cols=4, upload=True, remote_folder='01_18_Experiment', bucket='ccurtis.data', figsize=(12, 12))

Plot trajectories in video.

Parameters:

prefix: string

Prefix of file name to be plotted e.g. features_P1.csv prefix is P1.

resolution: int

Resolution of base image. Only needed to calculate bounds of image.

rows: int

Rows of base images used to build tiled image.

cols: int

Columns of base images used to build tiled images.

upload: boolean

True if you want to upload to s3.

diff_classifier.heatmaps.voronoi_finite_polygons_2d(vor, radius=None)

Reconstruct infinite voronoi regions in a 2D diagram to finite regions.

Parameters:

vor : Voronoi

Input diagram

radius : float, optional

Distance to ‘points at infinity’.

Returns:

regions : list of tuples

Indices of vertices in each revised Voronoi regions.

vertices : list of tuples

Coordinates for revised Voronoi vertices. Same as coordinates of input vertices, with ‘points at infinity’ appended to the end.