linear_motion_plot.py

from __future__ import print_function, division
import numpy as np
import matplotlib.pyplot as plt
import h5py
import matplotlib
from matplotlib.backends.backend_pdf import PdfPages

if __name__ == "__main__":
    with PdfPages("linear_motion_all.pdf") as pdf:
        print ("Loading data...")

        #Load the data from the HDF5 file
        df = h5py.File("linear_motion.hdf5", mode = "r")
        for i in range(len(df)):
            group = df["stepwise_motion%03d" % i]
            N_points = len(group) - 2
            data = np.zeros([2000 * N_points, 3])
            for i in range(N_points):
                dset1 = group["sequence_%05d" % i]
                dset2 = dset1["camera_motion"]
                for j in range(2000):
                    data[2000 * i + j, :] = dset2[j, :]

            matplotlib.rcParams.update({'font.size': 12})

            microns_per_pixel = 1.72

            t = data[:, 0]
            x = data[:, 1] * microns_per_pixel
            x -= np.mean(x)
            y = data[:, 2] * microns_per_pixel
            y -= np.mean(y)

            fig, ax = plt.subplots(1, 2)

            ax[0].plot(t, x, "r-")
            ax2 = ax[0].twinx()
            ax2.plot(t, y, "b-")
    
            # Make the scale the same for X and Y (so it's obvious which is moving)
            xmin, xmax = ax[0].get_ylim()
            ymin, ymax = ax2.get_ylim()
            r = max(xmax - xmin, ymax - ymin)
            ax[0].set_ylim((xmax + xmin)/2 - r/2, (xmax + xmin)/2 + r/2)
            ax2.set_ylim((ymax + ymin)/2 - r/2, (ymax + ymin)/2 + r/2)
    
            # plot the XY motion, make the limits equal (because it looks nice)
            ax[1].plot(x, y, ".-")
            ax[1].set_aspect(1)
            xmin, xmax = ax[1].get_xlim()
            ymin, ymax = ax[1].get_ylim()
            r = max(xmax - xmin, ymax - ymin)
            ax[1].set_xlim((xmax + xmin)/2 - r/2, (xmax + xmin)/2 + r/2)
            ax[1].set_ylim((ymax + ymin)/2 - r/2, (ymax + ymin)/2 + r/2)

            ax[0].set_xlabel('Time [$\mathrm{s}$]')
            ax[0].set_ylabel('X Position [$\mathrm{\mu m}$]')
            ax2.set_ylabel('Y Position [$\mathrm{\mu m}$]')
            ax[1].set_xlabel('X Position [$\mathrm{\mu m}$]')
            ax[1].set_ylabel('Y Position [$\mathrm{\mu m}$]')

            fig.suptitle(group.name[1:])

            plt.tight_layout()

            pdf.savefig(fig)
            plt.close(fig)

    df.close()