demo + utils venv

This commit is contained in:
d3m1g0d
2019-02-03 13:40:10 +01:00
parent 5fa112490b
commit cfa9c8ea23
5994 changed files with 1353819 additions and 0 deletions
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from .. import axes
from .geo import AitoffAxes, HammerAxes, LambertAxes, MollweideAxes
from .polar import PolarAxes
class ProjectionRegistry:
"""
Manages the set of projections available to the system.
"""
def __init__(self):
self._all_projection_types = {}
def register(self, *projections):
"""
Register a new set of projections.
"""
for projection in projections:
name = projection.name
self._all_projection_types[name] = projection
def get_projection_class(self, name):
"""
Get a projection class from its *name*.
"""
return self._all_projection_types[name]
def get_projection_names(self):
"""
Get a list of the names of all projections currently registered.
"""
return sorted(self._all_projection_types)
projection_registry = ProjectionRegistry()
projection_registry.register(
axes.Axes,
PolarAxes,
AitoffAxes,
HammerAxes,
LambertAxes,
MollweideAxes)
def register_projection(cls):
projection_registry.register(cls)
def get_projection_class(projection=None):
"""
Get a projection class from its name.
If *projection* is None, a standard rectilinear projection is returned.
"""
if projection is None:
projection = 'rectilinear'
try:
return projection_registry.get_projection_class(projection)
except KeyError:
raise ValueError("Unknown projection %r" % projection)
def process_projection_requirements(
figure, *args, polar=False, projection=None, **kwargs):
"""
Handle the args/kwargs to add_axes/add_subplot/gca, returning::
(axes_proj_class, proj_class_kwargs, proj_stack_key)
which can be used for new axes initialization/identification.
"""
if polar:
if projection is not None and projection != 'polar':
raise ValueError(
"polar=True, yet projection=%r. "
"Only one of these arguments should be supplied." %
projection)
projection = 'polar'
if isinstance(projection, str) or projection is None:
projection_class = get_projection_class(projection)
elif hasattr(projection, '_as_mpl_axes'):
projection_class, extra_kwargs = projection._as_mpl_axes()
kwargs.update(**extra_kwargs)
else:
raise TypeError('projection must be a string, None or implement a '
'_as_mpl_axes method. Got %r' % projection)
# Make the key without projection kwargs, this is used as a unique
# lookup for axes instances
key = figure._make_key(*args, **kwargs)
return projection_class, kwargs, key
def get_projection_names():
"""
Get a list of acceptable projection names.
"""
return projection_registry.get_projection_names()
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import numpy as np
import matplotlib
from matplotlib import rcParams
from matplotlib.axes import Axes
import matplotlib.axis as maxis
from matplotlib.patches import Circle
from matplotlib.path import Path
import matplotlib.spines as mspines
from matplotlib.ticker import (
Formatter, NullLocator, FixedLocator, NullFormatter)
from matplotlib.transforms import Affine2D, BboxTransformTo, Transform
class GeoAxes(Axes):
"""An abstract base class for geographic projections."""
class ThetaFormatter(Formatter):
"""
Used to format the theta tick labels. Converts the native
unit of radians into degrees and adds a degree symbol.
"""
def __init__(self, round_to=1.0):
self._round_to = round_to
def __call__(self, x, pos=None):
degrees = (x / np.pi) * 180.0
degrees = np.round(degrees / self._round_to) * self._round_to
if rcParams['text.usetex'] and not rcParams['text.latex.unicode']:
return r"$%0.0f^\circ$" % degrees
else:
return "%0.0f\N{DEGREE SIGN}" % degrees
RESOLUTION = 75
def _init_axis(self):
self.xaxis = maxis.XAxis(self)
self.yaxis = maxis.YAxis(self)
# Do not register xaxis or yaxis with spines -- as done in
# Axes._init_axis() -- until GeoAxes.xaxis.cla() works.
# self.spines['geo'].register_axis(self.yaxis)
self._update_transScale()
def cla(self):
Axes.cla(self)
self.set_longitude_grid(30)
self.set_latitude_grid(15)
self.set_longitude_grid_ends(75)
self.xaxis.set_minor_locator(NullLocator())
self.yaxis.set_minor_locator(NullLocator())
self.xaxis.set_ticks_position('none')
self.yaxis.set_ticks_position('none')
self.yaxis.set_tick_params(label1On=True)
# Why do we need to turn on yaxis tick labels, but
# xaxis tick labels are already on?
self.grid(rcParams['axes.grid'])
Axes.set_xlim(self, -np.pi, np.pi)
Axes.set_ylim(self, -np.pi / 2.0, np.pi / 2.0)
def _set_lim_and_transforms(self):
# A (possibly non-linear) projection on the (already scaled) data
self.transProjection = self._get_core_transform(self.RESOLUTION)
self.transAffine = self._get_affine_transform()
self.transAxes = BboxTransformTo(self.bbox)
# The complete data transformation stack -- from data all the
# way to display coordinates
self.transData = \
self.transProjection + \
self.transAffine + \
self.transAxes
# This is the transform for longitude ticks.
self._xaxis_pretransform = \
Affine2D() \
.scale(1, self._longitude_cap * 2) \
.translate(0, -self._longitude_cap)
self._xaxis_transform = \
self._xaxis_pretransform + \
self.transData
self._xaxis_text1_transform = \
Affine2D().scale(1, 0) + \
self.transData + \
Affine2D().translate(0, 4)
self._xaxis_text2_transform = \
Affine2D().scale(1, 0) + \
self.transData + \
Affine2D().translate(0, -4)
# This is the transform for latitude ticks.
yaxis_stretch = Affine2D().scale(np.pi * 2, 1).translate(-np.pi, 0)
yaxis_space = Affine2D().scale(1, 1.1)
self._yaxis_transform = \
yaxis_stretch + \
self.transData
yaxis_text_base = \
yaxis_stretch + \
self.transProjection + \
(yaxis_space + \
self.transAffine + \
self.transAxes)
self._yaxis_text1_transform = \
yaxis_text_base + \
Affine2D().translate(-8, 0)
self._yaxis_text2_transform = \
yaxis_text_base + \
Affine2D().translate(8, 0)
def _get_affine_transform(self):
transform = self._get_core_transform(1)
xscale, _ = transform.transform_point((np.pi, 0))
_, yscale = transform.transform_point((0, np.pi / 2))
return Affine2D() \
.scale(0.5 / xscale, 0.5 / yscale) \
.translate(0.5, 0.5)
def get_xaxis_transform(self,which='grid'):
if which not in ['tick1', 'tick2', 'grid']:
raise ValueError(
"'which' must be one of 'tick1', 'tick2', or 'grid'")
return self._xaxis_transform
def get_xaxis_text1_transform(self, pad):
return self._xaxis_text1_transform, 'bottom', 'center'
def get_xaxis_text2_transform(self, pad):
return self._xaxis_text2_transform, 'top', 'center'
def get_yaxis_transform(self,which='grid'):
if which not in ['tick1', 'tick2', 'grid']:
raise ValueError(
"'which' must be one of 'tick1', 'tick2', or 'grid'")
return self._yaxis_transform
def get_yaxis_text1_transform(self, pad):
return self._yaxis_text1_transform, 'center', 'right'
def get_yaxis_text2_transform(self, pad):
return self._yaxis_text2_transform, 'center', 'left'
def _gen_axes_patch(self):
return Circle((0.5, 0.5), 0.5)
def _gen_axes_spines(self):
return {'geo':mspines.Spine.circular_spine(self,
(0.5, 0.5), 0.5)}
def set_yscale(self, *args, **kwargs):
if args[0] != 'linear':
raise NotImplementedError
set_xscale = set_yscale
def set_xlim(self, *args, **kwargs):
raise TypeError("It is not possible to change axes limits "
"for geographic projections. Please consider "
"using Basemap or Cartopy.")
set_ylim = set_xlim
def format_coord(self, lon, lat):
'return a format string formatting the coordinate'
lon, lat = np.rad2deg([lon, lat])
if lat >= 0.0:
ns = 'N'
else:
ns = 'S'
if lon >= 0.0:
ew = 'E'
else:
ew = 'W'
return ('%f\N{DEGREE SIGN}%s, %f\N{DEGREE SIGN}%s'
% (abs(lat), ns, abs(lon), ew))
def set_longitude_grid(self, degrees):
"""
Set the number of degrees between each longitude grid.
"""
# Skip -180 and 180, which are the fixed limits.
grid = np.arange(-180 + degrees, 180, degrees)
self.xaxis.set_major_locator(FixedLocator(np.deg2rad(grid)))
self.xaxis.set_major_formatter(self.ThetaFormatter(degrees))
def set_latitude_grid(self, degrees):
"""
Set the number of degrees between each latitude grid.
"""
# Skip -90 and 90, which are the fixed limits.
grid = np.arange(-90 + degrees, 90, degrees)
self.yaxis.set_major_locator(FixedLocator(np.deg2rad(grid)))
self.yaxis.set_major_formatter(self.ThetaFormatter(degrees))
def set_longitude_grid_ends(self, degrees):
"""
Set the latitude(s) at which to stop drawing the longitude grids.
"""
self._longitude_cap = np.deg2rad(degrees)
self._xaxis_pretransform \
.clear() \
.scale(1.0, self._longitude_cap * 2.0) \
.translate(0.0, -self._longitude_cap)
def get_data_ratio(self):
'''
Return the aspect ratio of the data itself.
'''
return 1.0
### Interactive panning
def can_zoom(self):
"""
Return *True* if this axes supports the zoom box button functionality.
This axes object does not support interactive zoom box.
"""
return False
def can_pan(self) :
"""
Return *True* if this axes supports the pan/zoom button functionality.
This axes object does not support interactive pan/zoom.
"""
return False
def start_pan(self, x, y, button):
pass
def end_pan(self):
pass
def drag_pan(self, button, key, x, y):
pass
class _GeoTransform(Transform):
# Factoring out some common functionality.
input_dims = 2
output_dims = 2
is_separable = False
def __init__(self, resolution):
"""
Create a new geographical transform.
Resolution is the number of steps to interpolate between each input
line segment to approximate its path in curved space.
"""
Transform.__init__(self)
self._resolution = resolution
def __str__(self):
return "{}({})".format(type(self).__name__, self._resolution)
def transform_path_non_affine(self, path):
vertices = path.vertices
ipath = path.interpolated(self._resolution)
return Path(self.transform(ipath.vertices), ipath.codes)
transform_path_non_affine.__doc__ = \
Transform.transform_path_non_affine.__doc__
class AitoffAxes(GeoAxes):
name = 'aitoff'
class AitoffTransform(_GeoTransform):
"""The base Aitoff transform."""
def transform_non_affine(self, ll):
longitude = ll[:, 0]
latitude = ll[:, 1]
# Pre-compute some values
half_long = longitude / 2.0
cos_latitude = np.cos(latitude)
alpha = np.arccos(cos_latitude * np.cos(half_long))
# Avoid divide-by-zero errors using same method as NumPy.
alpha[alpha == 0.0] = 1e-20
# We want unnormalized sinc. numpy.sinc gives us normalized
sinc_alpha = np.sin(alpha) / alpha
xy = np.empty_like(ll, float)
xy[:, 0] = (cos_latitude * np.sin(half_long)) / sinc_alpha
xy[:, 1] = np.sin(latitude) / sinc_alpha
return xy
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return AitoffAxes.InvertedAitoffTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
class InvertedAitoffTransform(_GeoTransform):
def transform_non_affine(self, xy):
# MGDTODO: Math is hard ;(
return xy
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return AitoffAxes.AitoffTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
def __init__(self, *args, **kwargs):
self._longitude_cap = np.pi / 2.0
GeoAxes.__init__(self, *args, **kwargs)
self.set_aspect(0.5, adjustable='box', anchor='C')
self.cla()
def _get_core_transform(self, resolution):
return self.AitoffTransform(resolution)
class HammerAxes(GeoAxes):
name = 'hammer'
class HammerTransform(_GeoTransform):
"""The base Hammer transform."""
def transform_non_affine(self, ll):
longitude = ll[:, 0:1]
latitude = ll[:, 1:2]
# Pre-compute some values
half_long = longitude / 2.0
cos_latitude = np.cos(latitude)
sqrt2 = np.sqrt(2.0)
alpha = np.sqrt(1.0 + cos_latitude * np.cos(half_long))
x = (2.0 * sqrt2) * (cos_latitude * np.sin(half_long)) / alpha
y = (sqrt2 * np.sin(latitude)) / alpha
return np.concatenate((x, y), 1)
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return HammerAxes.InvertedHammerTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
class InvertedHammerTransform(_GeoTransform):
def transform_non_affine(self, xy):
x, y = xy.T
z = np.sqrt(1 - (x / 4) ** 2 - (y / 2) ** 2)
longitude = 2 * np.arctan((z * x) / (2 * (2 * z ** 2 - 1)))
latitude = np.arcsin(y*z)
return np.column_stack([longitude, latitude])
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return HammerAxes.HammerTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
def __init__(self, *args, **kwargs):
self._longitude_cap = np.pi / 2.0
GeoAxes.__init__(self, *args, **kwargs)
self.set_aspect(0.5, adjustable='box', anchor='C')
self.cla()
def _get_core_transform(self, resolution):
return self.HammerTransform(resolution)
class MollweideAxes(GeoAxes):
name = 'mollweide'
class MollweideTransform(_GeoTransform):
"""The base Mollweide transform."""
def transform_non_affine(self, ll):
def d(theta):
delta = (-(theta + np.sin(theta) - pi_sin_l)
/ (1 + np.cos(theta)))
return delta, np.abs(delta) > 0.001
longitude = ll[:, 0]
latitude = ll[:, 1]
clat = np.pi/2 - np.abs(latitude)
ihigh = clat < 0.087 # within 5 degrees of the poles
ilow = ~ihigh
aux = np.empty(latitude.shape, dtype=float)
if ilow.any(): # Newton-Raphson iteration
pi_sin_l = np.pi * np.sin(latitude[ilow])
theta = 2.0 * latitude[ilow]
delta, large_delta = d(theta)
while np.any(large_delta):
theta[large_delta] += delta[large_delta]
delta, large_delta = d(theta)
aux[ilow] = theta / 2
if ihigh.any(): # Taylor series-based approx. solution
e = clat[ihigh]
d = 0.5 * (3 * np.pi * e**2) ** (1.0/3)
aux[ihigh] = (np.pi/2 - d) * np.sign(latitude[ihigh])
xy = np.empty(ll.shape, dtype=float)
xy[:,0] = (2.0 * np.sqrt(2.0) / np.pi) * longitude * np.cos(aux)
xy[:,1] = np.sqrt(2.0) * np.sin(aux)
return xy
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return MollweideAxes.InvertedMollweideTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
class InvertedMollweideTransform(_GeoTransform):
def transform_non_affine(self, xy):
x = xy[:, 0:1]
y = xy[:, 1:2]
# from Equations (7, 8) of
# http://mathworld.wolfram.com/MollweideProjection.html
theta = np.arcsin(y / np.sqrt(2))
lon = (np.pi / (2 * np.sqrt(2))) * x / np.cos(theta)
lat = np.arcsin((2 * theta + np.sin(2 * theta)) / np.pi)
return np.concatenate((lon, lat), 1)
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return MollweideAxes.MollweideTransform(self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
def __init__(self, *args, **kwargs):
self._longitude_cap = np.pi / 2.0
GeoAxes.__init__(self, *args, **kwargs)
self.set_aspect(0.5, adjustable='box', anchor='C')
self.cla()
def _get_core_transform(self, resolution):
return self.MollweideTransform(resolution)
class LambertAxes(GeoAxes):
name = 'lambert'
class LambertTransform(_GeoTransform):
"""The base Lambert transform."""
def __init__(self, center_longitude, center_latitude, resolution):
"""
Create a new Lambert transform. Resolution is the number of steps
to interpolate between each input line segment to approximate its
path in curved Lambert space.
"""
_GeoTransform.__init__(self, resolution)
self._center_longitude = center_longitude
self._center_latitude = center_latitude
def transform_non_affine(self, ll):
longitude = ll[:, 0:1]
latitude = ll[:, 1:2]
clong = self._center_longitude
clat = self._center_latitude
cos_lat = np.cos(latitude)
sin_lat = np.sin(latitude)
diff_long = longitude - clong
cos_diff_long = np.cos(diff_long)
inner_k = (1.0 +
np.sin(clat)*sin_lat +
np.cos(clat)*cos_lat*cos_diff_long)
# Prevent divide-by-zero problems
inner_k = np.where(inner_k == 0.0, 1e-15, inner_k)
k = np.sqrt(2.0 / inner_k)
x = k*cos_lat*np.sin(diff_long)
y = k*(np.cos(clat)*sin_lat -
np.sin(clat)*cos_lat*cos_diff_long)
return np.concatenate((x, y), 1)
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return LambertAxes.InvertedLambertTransform(
self._center_longitude,
self._center_latitude,
self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
class InvertedLambertTransform(_GeoTransform):
def __init__(self, center_longitude, center_latitude, resolution):
_GeoTransform.__init__(self, resolution)
self._center_longitude = center_longitude
self._center_latitude = center_latitude
def transform_non_affine(self, xy):
x = xy[:, 0:1]
y = xy[:, 1:2]
clong = self._center_longitude
clat = self._center_latitude
p = np.sqrt(x*x + y*y)
p = np.where(p == 0.0, 1e-9, p)
c = 2.0 * np.arcsin(0.5 * p)
sin_c = np.sin(c)
cos_c = np.cos(c)
lat = np.arcsin(cos_c*np.sin(clat) +
((y*sin_c*np.cos(clat)) / p))
lon = clong + np.arctan(
(x*sin_c) / (p*np.cos(clat)*cos_c - y*np.sin(clat)*sin_c))
return np.concatenate((lon, lat), 1)
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def inverted(self):
return LambertAxes.LambertTransform(
self._center_longitude,
self._center_latitude,
self._resolution)
inverted.__doc__ = Transform.inverted.__doc__
def __init__(self, *args, center_longitude=0, center_latitude=0, **kwargs):
self._longitude_cap = np.pi / 2
self._center_longitude = center_longitude
self._center_latitude = center_latitude
GeoAxes.__init__(self, *args, **kwargs)
self.set_aspect('equal', adjustable='box', anchor='C')
self.cla()
def cla(self):
GeoAxes.cla(self)
self.yaxis.set_major_formatter(NullFormatter())
def _get_core_transform(self, resolution):
return self.LambertTransform(
self._center_longitude,
self._center_latitude,
resolution)
def _get_affine_transform(self):
return Affine2D() \
.scale(0.25) \
.translate(0.5, 0.5)
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