Создайте график экваториальных координат RA и DEC с помощью python

Получить цветовую полосу можно путем слияния кода OP с отличным ответом @cphlewis. Я разместил это как готовое решение по запросу OP в чате. Первая версия кода просто добавляет цветную полосу, окончательная версия (под EDIT 2) выполняет аффинное преобразование осей и исправляет несколько параметров / упрощает код, чтобы точно соответствовать спецификации OP.

"""
An experimental support for curvilinear grid.
"""
import numpy as np
import  mpl_toolkits.axisartist.angle_helper as angle_helper
import matplotlib.cm as cmap
from matplotlib.projections import PolarAxes
from matplotlib.transforms import Affine2D

from mpl_toolkits.axisartist import SubplotHost

from mpl_toolkits.axisartist import GridHelperCurveLinear


def curvelinear_test2(fig):
    """
    polar projection, but in a rectangular box.
    """
    global ax1

    # see demo_curvelinear_grid.py for details
    tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()

    extreme_finder = angle_helper.ExtremeFinderCycle(10, 60,
                                                     lon_cycle = 360,
                                                     lat_cycle = None,
                                                     lon_minmax = None,
                                                     lat_minmax = (0, np.inf),
                                                     )

    grid_locator1 = angle_helper.LocatorHMS(12) #changes theta gridline count
    tick_formatter1 = angle_helper.FormatterHMS()

    grid_locator2 = angle_helper.LocatorDMS(6)
    tick_formatter2 = angle_helper.FormatterDMS()

    grid_helper = GridHelperCurveLinear(tr,
                                        extreme_finder=extreme_finder,
                                        grid_locator1=grid_locator1,
                                        tick_formatter1=tick_formatter1,
                                        grid_locator2=grid_locator2,
                                        tick_formatter2=tick_formatter2
                                        )


    ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)

    # make ticklabels of right and top axis visible.
    ax1.axis["right"].major_ticklabels.set_visible(True)
    ax1.axis["top"].major_ticklabels.set_visible(True)
    ax1.axis["bottom"].major_ticklabels.set_visible(True) #Turn off? 
    # let right and bottom axis show ticklabels for 1st coordinate (angle)
    ax1.axis["right"].get_helper().nth_coord_ticks=0
    ax1.axis["bottom"].get_helper().nth_coord_ticks=0



    fig.add_subplot(ax1)

    grid_helper = ax1.get_grid_helper()

    ax1.set_aspect(1.)
    ax1.set_xlim(-4,15) # moves the origin left-right in ax1
    ax1.set_ylim(-3, 20) # moves the origin up-down

    ax1.set_ylabel('90$^\circ$ + Declination')
    ax1.set_xlabel('Ascension')
    ax1.grid(True)
    #ax1.grid(linestyle='--', which='x') # either keyword applies to both
    #ax1.grid(linestyle=':', which='y')  # sets of gridlines

    return tr

import matplotlib.pyplot as plt
fig = plt.figure(1, figsize=(5, 5))
fig.clf()

tr = curvelinear_test2(fig) # tr.transform_point((x, 0)) is always (0,0)
                            # => (theta, r) in but (r, theta) out...
r_test =   [0, 1.2, 2.8, 3.8, 5,  8,  10, 13.3, 17]  # distance from origin
deg_test = [0,  -7, 12,  28,  45, 70, 79, 90,   100] # degrees ascension
out_test = tr.transform(zip(deg_test, r_test))

sizes = [40, 30, 10, 30, 80, 33, 12, 48, 45]
#hues = [.9, .3, .2, .8, .6, .1, .4, .5,.7] # Oddly, floats-to-colormap worked for a while.
hues = np.random.random((9,3)) #RGB values

# Use this block to generate colored points with a colorbar.
cm = plt.cm.get_cmap('RdYlBu_r')
z = np.random.random((len(r_test), 1))  # RGB values

SC = ax1.scatter(out_test[:,0], #ax1 is a global
            out_test[:,1],
            s=sizes,
            c=z,
            cmap=cm,
            zorder=9) #on top of gridlines
            
# Colorbar
cbar = plt.colorbar(SC, shrink=1., pad=0.05)
cbar.ax.tick_params(labelsize=8)
cbar.set_label('colorbar', fontsize=8)


plt.show()

ИЗМЕНИТЬ

Немного очистки параметров, добавление данных OP, удаление избыточности дает следующий график. Все еще нужно центрировать данные на -90 вместо 0 - на данный момент это взломано, но я уверен, что curvelinear_test2() можно изменить, чтобы учесть это...

ИЗМЕНИТЬ 2

После комментария OP к промежуточной версии в этом ответе окончательная версия, как показано ниже, дает сюжет в самом конце поста - с -90 на оси dec и демонстрацией подзаголовка.

"""
An experimental support for curvilinear grid.
"""
import numpy as np
import  mpl_toolkits.axisartist.angle_helper as angle_helper
import matplotlib.cm as cmap
from matplotlib.projections import PolarAxes
from matplotlib.transforms import Affine2D

from mpl_toolkits.axisartist import SubplotHost

from mpl_toolkits.axisartist import GridHelperCurveLinear


def curvelinear_test2(fig, rect=111):
    """
    polar projection, but in a rectangular box.
    """

    # see demo_curvelinear_grid.py for details
    tr = Affine2D().translate(0,90) + Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()

    extreme_finder = angle_helper.ExtremeFinderCycle(10, 60,
                                                     lon_cycle = 360,
                                                     lat_cycle = None,
                                                     lon_minmax = None,
                                                     lat_minmax = (-90, np.inf),
                                                     )

    grid_locator1 = angle_helper.LocatorHMS(12) #changes theta gridline count
    tick_formatter1 = angle_helper.FormatterHMS()

    grid_helper = GridHelperCurveLinear(tr,
                                        extreme_finder=extreme_finder,
                                        grid_locator1=grid_locator1,
                                        tick_formatter1=tick_formatter1
                                        )


    ax1 = SubplotHost(fig, rect, grid_helper=grid_helper)

    # make ticklabels of right and top axis visible.
    ax1.axis["right"].major_ticklabels.set_visible(True)
    ax1.axis["top"].major_ticklabels.set_visible(True)
    ax1.axis["bottom"].major_ticklabels.set_visible(True) #Turn off? 
    # let right and bottom axis show ticklabels for 1st coordinate (angle)
    ax1.axis["right"].get_helper().nth_coord_ticks=0
    ax1.axis["bottom"].get_helper().nth_coord_ticks=0



    fig.add_subplot(ax1)

    grid_helper = ax1.get_grid_helper()

    # You may or may not need these - they set the view window explicitly rather than using the
    # default as determined by matplotlib with extreme finder.
    ax1.set_aspect(1.)
    ax1.set_xlim(-4,25) # moves the origin left-right in ax1
    ax1.set_ylim(-3, 30) # moves the origin up-down

    ax1.set_ylabel('Declination')
    ax1.set_xlabel('Ascension')
    ax1.grid(True)
    #ax1.grid(linestyle='--', which='x') # either keyword applies to both
    #ax1.grid(linestyle=':', which='y')  # sets of gridlines

    return ax1,tr
    
    
def skip_comments(f):
    '''
    Read lines that DO NOT start with a # symbol.
    '''
    for line in f:
        if not line.strip().startswith('#'):
            yield line
            
def get_data_bb():
    '''RA, DEC data file.
    '''

    # Path to data file.
    out_file = 'bb_cat.dat'

    # Read data file
    with open(out_file) as f:
        ra, dec = [], []

        for line in skip_comments(f):
            ra.append(float(line.split()[0]))
            dec.append(float(line.split()[1]))

    return ra, dec


import matplotlib.pyplot as plt
fig = plt.figure(1, figsize=(5, 5))
fig.clf()

ax1, tr = curvelinear_test2(fig,121) # tr.transform_point((x, 0)) is always (0,0)
                            # => (theta, r) in but (r, theta) out...             

# Read RA, DEC data from file.
ra, dec = get_data_bb()
out_test = tr.transform(zip(ra, dec))

# Use this block to generate colored points with a colorbar.
cm = plt.cm.get_cmap('RdYlBu_r')
z = np.random.random((len(ra), 1))  # RGB values

SC = ax1.scatter(out_test[:,0], #ax1 is a global
            out_test[:,1],
            marker = 'o',
            c=z,
            cmap=cm,
            lw = 0.,
            zorder=9) #on top of gridlines
            
# Colorbar
cbar = plt.colorbar(SC, shrink=1., pad=0.1)
cbar.ax.tick_params(labelsize=8)
cbar.set_label('colorbar', fontsize=8)

ax2, tr = curvelinear_test2(fig,122) # tr.transform_point((x, 0)) is always (0,0)
                            # => (theta, r) in but (r, theta) out...             

# Read RA, DEC data from file.
ra, dec = get_data_bb()
out_test = tr.transform(zip(ra, dec))

# Use this block to generate colored points with a colorbar.
cm = plt.cm.get_cmap('RdYlBu_r')
z = np.random.random((len(ra), 1))  # RGB values

SC = ax2.scatter(out_test[:,0], #ax1 is a global
            out_test[:,1],
            marker = 'o',
            c=z,
            cmap=cm,
            lw = 0.,
            zorder=9) #on top of gridlines
            
# Colorbar
cbar = plt.colorbar(SC, shrink=1., pad=0.1)
cbar.ax.tick_params(labelsize=8)
cbar.set_label('colorbar', fontsize=8)

plt.show()

Финальный сюжет:

Жевать пример AxisArtist на самом деле довольно многообещающе (он объединяет два примера AxisArtist — я не удивлюсь, если AxisArtist был написан с учетом графиков RA):

Еще предстоит сделать:

1. Склонение должно варьироваться от -90 в начале координат до 0.
2. Уметь использовать и добавлять цветную полосу
3. отрегулируйте пределы, если рисуете за их пределами

эстетический:

4. Шрифт с засечками в метках осей
5. Пунктирные линии сетки для восхождения

что-нибудь еще?

"""
An experimental support for curvilinear grid.
"""
import numpy as np
import  mpl_toolkits.axisartist.angle_helper as angle_helper
import matplotlib.cm as cmap
from matplotlib.projections import PolarAxes
from matplotlib.transforms import Affine2D

from mpl_toolkits.axisartist import SubplotHost

from mpl_toolkits.axisartist import GridHelperCurveLinear


def curvelinear_test2(fig):
    """
    polar projection, but in a rectangular box.
    """
    global ax1

    # see demo_curvelinear_grid.py for details
    tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()

    extreme_finder = angle_helper.ExtremeFinderCycle(10, 60,
                                                     lon_cycle = 360,
                                                     lat_cycle = None,
                                                     lon_minmax = None,
                                                     lat_minmax = (0, np.inf),
                                                     )

    grid_locator1 = angle_helper.LocatorHMS(12) #changes theta gridline count
    tick_formatter1 = angle_helper.FormatterHMS()

    grid_locator2 = angle_helper.LocatorDMS(6)
    tick_formatter2 = angle_helper.FormatterDMS()

    grid_helper = GridHelperCurveLinear(tr,
                                        extreme_finder=extreme_finder,
                                        grid_locator1=grid_locator1,
                                        tick_formatter1=tick_formatter1,
                                        grid_locator2=grid_locator2,
                                        tick_formatter2=tick_formatter2
                                        )


    ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)

    # make ticklabels of right and top axis visible.
    ax1.axis["right"].major_ticklabels.set_visible(True)
    ax1.axis["top"].major_ticklabels.set_visible(True)
    ax1.axis["bottom"].major_ticklabels.set_visible(True) #Turn off? 
    # let right and bottom axis show ticklabels for 1st coordinate (angle)
    ax1.axis["right"].get_helper().nth_coord_ticks=0
    ax1.axis["bottom"].get_helper().nth_coord_ticks=0



    fig.add_subplot(ax1)

    grid_helper = ax1.get_grid_helper()

    ax1.set_aspect(1.)
    ax1.set_xlim(-4,15) # moves the origin left-right in ax1
    ax1.set_ylim(-3, 20) # moves the origin up-down

    ax1.set_ylabel('90$^\circ$ + Declination')
    ax1.set_xlabel('Ascension')
    ax1.grid(True)
    #ax1.grid(linestyle='--', which='x') # either keyword applies to both
    #ax1.grid(linestyle=':', which='y')  # sets of gridlines

    return tr

import matplotlib.pyplot as plt
fig = plt.figure(1, figsize=(5, 5))
fig.clf()

tr = curvelinear_test2(fig) # tr.transform_point((x, 0)) is always (0,0)
                            # => (theta, r) in but (r, theta) out...
r_test =   [0, 1.2, 2.8, 3.8, 5,  8,  10, 13.3, 17]  # distance from origin
deg_test = [0,  -7, 12,  28,  45, 70, 79, 90,   100] # degrees ascension
out_test = tr.transform(zip(deg_test, r_test))

sizes = [40, 30, 10, 30, 80, 33, 12, 48, 45]
#hues = [.9, .3, .2, .8, .6, .1, .4, .5,.7] # Oddly, floats-to-colormap worked for a while.
hues = np.random.random((9,3)) #RGB values

ax1.scatter(out_test[:,0], #ax1 is a global
            out_test[:,1],
            s=sizes,
            c=hues,
            #cmap=cmap.RdYlBu_r,
            zorder=9) #on top of gridlines


plt.show()

Я думаю, что это может быть проблема с Python 3+, теперь строка

out_test = tr.transform(zip(deg_test, r_test))

возвращает ошибку:

ValueError: невозможно преобразовать массив размера 1 в форму (2)

Меняем строку на

out_test = tr.transform(list(zip(deg_test, r_test)))

устраняет проблему и позволяет правильно построить график.