Commit 7aae4516 authored by Somnath, Suhas's avatar Somnath, Suhas
Browse files

Useful image plotting function for papers

parent 5e1689bf
......@@ -365,6 +365,74 @@ def plot_map(axis, data, stdevs=2, origin='lower', **kwargs):
return im
def single_img_cbar_plot(fig, axis, img, show_xy_ticks=True, show_cbar=True,
x_size=1, y_size=1, num_ticks=4, cbar_label=None,
tick_font_size=14, **kwargs):
Plots an image within the given axis with a color bar + label and appropriate X, Y tick labels.
This is particularly useful to get readily interpretable plots for papers
fig : matplotlib.figure object
Handle to figure
axis : matplotlib.axis object
Axis to plot this image onto
img : 2D numpy array with real values
Data for the image plot
show_xy_ticks : bool, Optional, default = True
Whether or not to show X, Y ticks
show_cbar : bool, optional, default = True
Whether or not to show the colorbar
x_size : float, optional, default = 1
Extent of tick marks in the X axis. This could be something like 1.5 for 1.5 microns
y_size : float, optional, default = 1
Extent of tick marks in y axis
num_ticks : unsigned int, optional, default = 4
Number of tick marks on the X and Y axes
cbar_label : str, optional, default = None
Labels for the colorbar. Use this for something like quantity (units)
tick_font_size : unsigned int, optional, default = 14
Font size to apply to x, y, colorbar ticks and colorbar label
kwargs : dictionary
Anything else that will be passed on to plot_map or imshow
im_handle : handle to image plot
handle to image plot
cbar : handle to color bar
handle to color bar
if 'clim' not in kwargs:
im_handle = plot_map(axis, img, aspect='auto', **kwargs)
im_handle = axis.imshow(img, origin='lower', **kwargs)
if show_xy_ticks:
x_ticks = np.linspace(0, img.shape[1] - 1, num_ticks, dtype=int)
y_ticks = np.linspace(0, img.shape[0] - 1, num_ticks, dtype=int)
axis.set_xticklabels([str(np.round(ind * x_size / (img.shape[1] - 1), 2)) for ind in x_ticks])
axis.set_yticklabels([str(np.round(ind * y_size / (img.shape[0] - 1), 2)) for ind in y_ticks])
set_tick_font_size(axis, tick_font_size)
if show_cbar:
cbar = fig.colorbar(im_handle, ax=axis)
if cbar_label is not None:
cbar.set_label(cbar_label, fontsize=tick_font_size)
z_lims = cbar.get_clim()
cbar.set_ticks(np.linspace(z_lims[0],z_lims[1], num_ticks))
return im_handle, cbar
def plot_loops(excit_wfm, datasets, line_colors=[], dataset_names=[], evenly_spaced=True,
plots_on_side=5, x_label='', y_label='', subtitles='Position', title='',
central_resp_size=None, use_rainbow_plots=False, h5_pos=None):
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