Source code for vaex.geo

import vaex
import numpy as np
from .utils import _ensure_strings_from_expressions, _ensure_string_from_expression

[docs]class DataFrameAccessorGeo(object): """Geometry/geographic helper methods Example: >>> df_xyz = df.geo.spherical2cartesian(df.longitude, df.latitude, df.distance) """
[docs] def __init__(self, df): self.df = df
[docs] def spherical2cartesian(self, alpha, delta, distance, xname="x", yname="y", zname="z", propagate_uncertainties=False, center=[0, 0, 0], radians=False, inplace=False): """Convert spherical to cartesian coordinates. :param alpha: :param delta: polar angle, ranging from the -90 (south pole) to 90 (north pole) :param distance: radial distance, determines the units of x, y and z :param xname: :param yname: :param zname: :param propagate_uncertainties: {propagate_uncertainties} :param center: :param radians: :return: New dataframe (in inplace is False) with new x,y,z columns """ df = self.df if inplace else self.df.copy() alpha = df._expr(alpha) delta = df._expr(delta) distance = df._expr(distance) if not radians: alpha = alpha * df._expr('pi')/180 delta = delta * df._expr('pi')/180 # TODO: use sth like .optimize by default to get rid of the +0 ? if center[0]: df[xname] = np.cos(alpha) * np.cos(delta) * distance + center[0] else: df[xname] = np.cos(alpha) * np.cos(delta) * distance if center[1]: df[yname] = np.sin(alpha) * np.cos(delta) * distance + center[1] else: df[yname] = np.sin(alpha) * np.cos(delta) * distance if center[2]: df[zname] = np.sin(delta) * distance + center[2] else: df[zname] = np.sin(delta) * distance if propagate_uncertainties: df.propagate_uncertainties([df[xname], df[yname], df[zname]]) return df
[docs] def cartesian2spherical(self, x="x", y="y", z="z", alpha="l", delta="b", distance="distance", radians=False, center=None, center_name="solar_position", inplace=False): """Convert cartesian to spherical coordinates. :param x: :param y: :param z: :param alpha: :param delta: name for polar angle, ranges from -90 to 90 (or -pi to pi when radians is True). :param distance: :param radians: :param center: :param center_name: :return: """ df = self.df if inplace else self.df.copy() transform = "" if radians else "*180./pi" if center is not None: df.add_variable(center_name, center) if center is not None and center[0] != 0: x = "({x} - {center_name}[0])".format(**locals()) if center is not None and center[1] != 0: y = "({y} - {center_name}[1])".format(**locals()) if center is not None and center[2] != 0: z = "({z} - {center_name}[2])".format(**locals()) df.add_virtual_column(distance, "sqrt({x}**2 + {y}**2 + {z}**2)".format(**locals())) # df.add_virtual_column(alpha, "((arctan2({y}, {x}) + 2*pi) % (2*pi)){transform}".format(**locals())) df.add_virtual_column(alpha, "arctan2({y}, {x}){transform}".format(**locals())) df.add_virtual_column(delta, "(-arccos({z}/{distance})+pi/2){transform}".format(**locals())) return df
[docs] def cartesian_to_polar(self, x="x", y="y", radius_out="r_polar", azimuth_out="phi_polar", propagate_uncertainties=False, radians=False, inplace=False): """Convert cartesian to polar coordinates :param x: expression for x :param y: expression for y :param radius_out: name for the virtual column for the radius :param azimuth_out: name for the virtual column for the azimuth angle :param propagate_uncertainties: {propagate_uncertainties} :param radians: if True, azimuth is in radians, defaults to degrees :return: """ df = self.df if inplace else self.df.copy() x = df._expr(x) y = df._expr(y) if radians: to_degrees = "" else: to_degrees = "*180/pi" r = np.sqrt(x**2 + y**2) df[radius_out] = r phi = np.arctan2(y, x) if not radians: phi = phi * 180/np.pi df[azimuth_out] = phi if propagate_uncertainties: df.propagate_uncertainties([df[radius_out], df[azimuth_out]]) return df
[docs] def velocity_polar2cartesian(self, x='x', y='y', azimuth=None, vr='vr_polar', vazimuth='vphi_polar', vx_out='vx', vy_out='vy', propagate_uncertainties=False, inplace=False): """ Convert cylindrical polar velocities to Cartesian. :param x: :param y: :param azimuth: Optional expression for the azimuth in degrees , may lead to a better performance when given. :param vr: :param vazimuth: :param vx_out: :param vy_out: :param propagate_uncertainties: {propagate_uncertainties} """ df = self.df if inplace else self.df.copy() x = df._expr(x) y = df._expr(y) vr = df._expr(vr) vazimuth = df._expr(vazimuth) if azimuth is not None: azimuth = df._expr(azimuth) azimuth = np.deg2rad(azimuth) else: azimuth = np.arctan2(y, x) azimuth = df._expr(azimuth) df[vx_out] = vr * np.cos(azimuth) - vazimuth * np.sin(azimuth) df[vy_out] = vr * np.sin(azimuth) + vazimuth * np.cos(azimuth) if propagate_uncertainties: df.propagate_uncertainties([df[vx_out], df[vy_out]]) return df
[docs] def velocity_cartesian2polar(self, x="x", y="y", vx="vx", radius_polar=None, vy="vy", vr_out="vr_polar", vazimuth_out="vphi_polar", propagate_uncertainties=False, inplace=False): """Convert cartesian to polar velocities. :param x: :param y: :param vx: :param radius_polar: Optional expression for the radius, may lead to a better performance when given. :param vy: :param vr_out: :param vazimuth_out: :param propagate_uncertainties: {propagate_uncertainties} :return: """ df = self.df if inplace else self.df.copy() x = df._expr(x) y = df._expr(y) vx = df._expr(vx) vy = df._expr(vy) if radius_polar is None: radius_polar = np.sqrt(x**2 + y**2) radius_polar = df._expr(radius_polar) df[vr_out] = (x*vx + y*vy) / radius_polar df[vazimuth_out] = (x*vy - y*vx) / radius_polar if propagate_uncertainties: df.propagate_uncertainties([df[vr_out], df[vazimuth_out]]) return df
[docs] def velocity_cartesian2spherical(self, x="x", y="y", z="z", vx="vx", vy="vy", vz="vz", vr="vr", vlong="vlong", vlat="vlat", distance=None, inplace=False): """Convert velocities from a cartesian to a spherical coordinate system TODO: uncertainty propagation :param x: name of x column (input) :param y: y :param z: z :param vx: vx :param vy: vy :param vz: vz :param vr: name of the column for the radial velocity in the r direction (output) :param vlong: name of the column for the velocity component in the longitude direction (output) :param vlat: name of the column for the velocity component in the latitude direction, positive points to the north pole (output) :param distance: Expression for distance, if not given defaults to sqrt(x**2+y**2+z**2), but if this column already exists, passing this expression may lead to a better performance :return: """ # see df = self.df if inplace else self.df.copy() if distance is None: distance = "sqrt({x}**2+{y}**2+{z}**2)".format(**locals()) df.add_virtual_column(vr, "({x}*{vx}+{y}*{vy}+{z}*{vz})/{distance}".format(**locals())) df.add_virtual_column(vlong, "-({vx}*{y}-{x}*{vy})/sqrt({x}**2+{y}**2)".format(**locals())) df.add_virtual_column(vlat, "-({z}*({x}*{vx}+{y}*{vy}) - ({x}**2+{y}**2)*{vz})/( {distance}*sqrt({x}**2+{y}**2) )".format(**locals())) return df
[docs] def project_aitoff(self, alpha, delta, x, y, radians=True, inplace=False): """Add aitoff ( projection :param alpha: azimuth angle :param delta: polar angle :param x: output name for x coordinate :param y: output name for y coordinate :param radians: input and output in radians (True), or degrees (False) :return: """ df = self.df if inplace else self.df.copy() transform = "" if radians else "*pi/180." aitoff_alpha = "__aitoff_alpha_%s_%s" % (alpha, delta) # sanatize aitoff_alpha = re.sub("[^a-zA-Z_]", "_", aitoff_alpha) df.add_virtual_column(aitoff_alpha, "arccos(cos({delta}{transform})*cos({alpha}{transform}/2))".format(**locals())) df.add_virtual_column(x, "2*cos({delta}{transform})*sin({alpha}{transform}/2)/sinc({aitoff_alpha}/pi)/pi".format(**locals())) df.add_virtual_column(y, "sin({delta}{transform})/sinc({aitoff_alpha}/pi)/pi".format(**locals())) return df
[docs] def project_gnomic(self, alpha, delta, alpha0=0, delta0=0, x="x", y="y", radians=False, postfix="", inplace=False): """Adds a gnomic projection to the DataFrame""" df = self.df if inplace else self.df.copy() if not radians: alpha = "pi/180.*%s" % alpha delta = "pi/180.*%s" % delta alpha0 = alpha0 * np.pi / 180 delta0 = delta0 * np.pi / 180 transform = "" if radians else "*180./pi" # aliases ra = alpha dec = delta ra_center = alpha0 dec_center = delta0 gnomic_denominator = 'sin({dec_center}) * tan({dec}) + cos({dec_center}) * cos({ra} - {ra_center})'.format(**locals()) denominator_name = 'gnomic_denominator' + postfix xi = 'sin({ra} - {ra_center})/{denominator_name}{transform}'.format(**locals()) eta = '(cos({dec_center}) * tan({dec}) - sin({dec_center}) * cos({ra} - {ra_center}))/{denominator_name}{transform}'.format(**locals()) df.add_virtual_column(denominator_name, gnomic_denominator) df.add_virtual_column(x, xi) df.add_virtual_column(y, eta) return df
[docs] def rotation_2d(self, x, y, xnew, ynew, angle_degrees, propagate_uncertainties=False, inplace=False): """Rotation in 2d. :param str x: Name/expression of x column :param str y: idem for y :param str xnew: name of transformed x column :param str ynew: :param float angle_degrees: rotation in degrees, anti clockwise :return: """ df = self.df if inplace else self.df.copy() x = _ensure_string_from_expression(x) y = _ensure_string_from_expression(y) theta = np.radians(angle_degrees) matrix = np.array([[np.cos(theta), -np.sin(theta)], [np.sin(theta), np.cos(theta)]]) m = matrix_name = x + "_" + y + "_rot" for i in range(2): for j in range(2): df.set_variable(matrix_name + "_%d%d" % (i, j), matrix[i, j].item()) df[xnew] = df._expr("{m}_00 * {x} + {m}_01 * {y}".format(**locals())) df[ynew] = df._expr("{m}_10 * {x} + {m}_11 * {y}".format(**locals())) if propagate_uncertainties: df.propagate_uncertainties([df[xnew], df[ynew]]) return df
[docs] def bearing(self, lon1, lat1, lon2, lat2, bearing="bearing", inplace=False): """Calculates a bearing, based on""" df = self.df if inplace else self.df.copy() lon1 = "(pickup_longitude * pi / 180)" lon2 = "(dropoff_longitude * pi / 180)" lat1 = "(pickup_latitude * pi / 180)" lat2 = "(dropoff_latitude * pi / 180)" p1 = lat1 p2 = lat2 l1 = lon1 l2 = lon2 # from expr = "arctan2(sin({l2}-{l1}) * cos({p2}), cos({p1})*sin({p2}) - sin({p1})*cos({p2})*cos({l2}-{l1}))" \ .format(**locals()) df.add_virtual_column(bearing, expr) return df