StarryProcess self._M doesn't depend on ydeg

[RomanAkhmetshyn]

I'm trying to visualize a custom-generated array of time-variable spherical harmonics using sp.visualize(), however when computing a dot product of self._M (I assume that's a design matrix) and transposed Y_lm matrix in sp.mollweide, self._M is always of shape (45000,256) no matter what ydeg I set when initializing SP object. I can understand that 45000 = 300 * 150 by default, but where can I change the second axis? Full code:

import starry
starry.config.lazy = False
starry.config.quiet = True

import numpy as np

try:
    np.distutils.__config__.blas_opt_info = np.distutils.__config__.blas_ilp64_opt_info
except Exception:
    pass
import theano
theano.config.gcc__cxxflags += " -fexceptions"
theano.config.on_opt_error = "raise"
theano.tensor.opt.constant_folding
theano.graph.opt.EquilibriumOptimizer

from starry_process import StarryProcess
import numpy as np
import matplotlib.pyplot as plt


import matplotlib as mpl
mpl.rcParams['figure.dpi'] = 300

import numpy as np


ydeg = 5
deg_num = (ydeg+1)**2
sp = StarryProcess(ydeg = ydeg)
sp._time_variable = True

def Y_evo(Y_t0, Y_dot, t, t0):
    Y_t = Y_t0 + Y_dot * (t - t0)
    return Y_t

#%%

t0 = 0
times = np.linspace(t0, 100, 100)


Y_t0 = np.random.normal(10, 2, deg_num)
Y_dot = np.random.normal(0, 0.5, deg_num)


Ys = []
for t in times:
    Ys.append(Y_evo(Y_t0, Y_dot, t, t0))
    
    
plt.plot(times, Ys)
plt.show()

stacked_array = np.stack(Ys, axis=0)

reshaped_array = stacked_array.reshape(1, 100, deg_num)

flux = sp.flux(y = reshaped_array, t = times, i=75.0, p=33, u=[0.0, 0.0])

flux = flux.eval()
plt.plot(times, flux[0])
plt.show()
    
print(sp._M.shape)
sp.visualize(y = reshaped_array, file = 'something.gif')

ValueError: shapes (45000,256) and (36,100) not aligned: 256 (dim 1) != 36 (dim 0)