How to use the pyregion.parse function in pyregion

wcs = pywcs.WCS(naxis=2)

    wcs.wcs.crpix = [5.5, 5.5]
    wcs.wcs.cdelt = [0.1, -0.1]
    wcs.wcs.crval = [l, b]
    wcs.wcs.ctype = ["GLON-ZEA".encode("ascii"), "GLAT-ZEA".encode("ascii")]

    import pyregion.wcs_helper as wcs_helper
    proj = wcs_helper.get_kapteyn_projection(wcs)
    cdelt = wcs_helper.estimate_cdelt(proj, 5.5, 5.5)
    
    assert np.allclose([cdelt], [0.1])

    region_string="fk5; circle(%s, %s, 0.5000)" % (ra,dec)
    reg = pyregion.parse(region_string).as_imagecoord(wcs)

    assert np.allclose([reg[0].coord_list[-1]], [0.5/0.1])

def filter_events(self, region):
        """
        Filter events using a ds9 *region*. Requires the pyregion package.
        Returns a new EventList.
        """
        import pyregion
        import os
        if os.path.exists(region):
            reg = pyregion.open(region)
        else:
            reg = pyregion.parse(region)
        r = reg.as_imagecoord(header=self.wcs.to_header())
        f = r.get_filter()
        idxs = f.inside_x_y(self["xpix"], self["ypix"])
        if idxs.sum() == 0:
            raise RuntimeError("No events are inside this region!")
        new_events = {}
        for k, v in self.items():
            new_events[k] = v[idxs]
        return EventList(new_events, self.parameters)

def ellipses(ra_list, dec_list, height_list, width_list, angle_list):

    # Initialize the region string
    region_string = "# Region file format: DS9 version 3.0\n"
    region_string += "global color=green\n"
    region_string += "fk5\n"

    for ra, dec, height, width, angle in zip(ra_list, dec_list, height_list, width_list, angle_list):

        line = "fk5;ellipse(%s,%s,%.2f\",%.2f\",%s)\n" % (ra, dec, height, width, angle)
        region_string += line

    region = pyregion.parse(region_string)

    # Return the region
    return region

"""
        Extract a masked subcube from a ds9 region or a pyregion Region object
        (only functions on celestial dimensions)

        Parameters
        ----------
        ds9region: str or `pyregion.Shape`
            The region to extract
        allow_empty: bool
            If this is False, an exception will be raised if the region
            contains no overlap with the cube
        """
        import pyregion

        if isinstance(ds9region, six.string_types):
            shapelist = pyregion.parse(ds9region)
        else:
            shapelist = ds9region

        if shapelist[0].coord_format not in ('physical','image'):
            # Requires astropy >0.4...
            # pixel_regions = shapelist.as_imagecoord(self.wcs.celestial.to_header())
            # convert the regions to image (pixel) coordinates
            celhdr = self.wcs.sub([wcs.WCSSUB_CELESTIAL]).to_header()
            celhdr['NAXIS1'] = self.shape[2]
            celhdr['NAXIS2'] = self.shape[1]
            pixel_regions = shapelist.as_imagecoord(celhdr)
            recompute_shifted_mask = False
        else:
            pixel_regions = copy.deepcopy(shapelist)
            # we need to change the reference pixel after cropping
            recompute_shifted_mask = True

import matplotlib.pyplot as plt
import pyregion

region = """
image
circle(100, 100, 80)
box(200, 150, 150, 120, 0)
"""

r = pyregion.parse(region)
mask_1or2 = r.get_mask(shape=(300, 300))

myfilter = r.get_filter()
mask_1and2 = (myfilter[0] & myfilter[1]).mask((300, 300))

plt.subplot(121).imshow(mask_1or2, origin="lower", interpolation="nearest")
plt.subplot(122).imshow(mask_1and2, origin="lower", interpolation="nearest")
plt.show()

# Loop over the objects in the coordinates list, adding a line for each one
    for object in coordinates:

        if type(object).__name__ == "Gaussian2D": line = "ellipse(" + str(object.x_mean.value) + "," + str(object.y_mean.value) + "," + str(object.x_stddev.value) + "," + str(object.y_stddev.value) + ",0.0)\n"
        elif type(object).__name__ == "AiryDisk2D":
            # see https://en.wikipedia.org/wiki/Airy_disk#Approximation_using_a_Gaussian_profile and
            # http://astropy.readthedocs.org/en/latest/api/astropy.modeling.functional_models.AiryDisk2D.html#astropy.modeling.functional_models.AiryDisk2D
            sigma = 0.42 * object.radius.value * 0.81989397882
            line = "ellipse(" + str(object.x_0.value) + "," + str(object.y_0.value) + "," + str(sigma) + "," + str(sigma) + ",0.0)\n"
        else: raise ValueError("Models other than Gaussian2D and AiryDisk2D are not yet supported")

        region_string += line

    # Parse the region string into a region object
    region = pyregion.parse(region_string)

    # Return the region
    return region

def circles(ra_list, dec_list, radius_list):

    # Initialize the region string
    region_string = "# Region file format: DS9 version 3.0\n"
    region_string += "global color=green\n"
    region_string += "fk5\n"

    for ra, dec, radius in zip(ra_list, dec_list, radius_list):

        line = "fk5;circle(%s,%s,%.2f\")\n" % (ra, dec, radius)
        region_string += line

    region = pyregion.parse(region_string)

    # Return the region
    return region

def subcube_from_ds9region(self, ds9region):
        """
        Extract a masked subcube from a ds9 region or a pyregion Region object
        (only functions on celestial dimensions)

        Parameters
        ----------
        ds9region: str or `pyregion.Shape`
            The region to extract
        """
        import pyregion

        if isinstance(ds9region, six.string_types):
            shapelist = pyregion.parse(ds9region)
        else:
            shapelist = ds9region

        if shapelist[0].coord_format not in ('physical','image'):
            # Requires astropy >0.4...
            # pixel_regions = shapelist.as_imagecoord(self.wcs.celestial.to_header())
            # convert the regions to image (pixel) coordinates
            celhdr = self.wcs.sub([wcs.WCSSUB_CELESTIAL]).to_header()
            pixel_regions = shapelist.as_imagecoord(celhdr)
        else:
            # For this to work, we'd need to change the reference pixel after cropping.
            # Alternatively, we can just make the full-sized mask... todo....
            raise NotImplementedError("Can't use non-celestial coordinates with regions.")
            pixel_regions = shapelist

        # This is a hack to use mpl to determine the outer bounds of the regions