Python prep_stan_data Exemples

Exemple #1

Fichier : 1.2 - OOS performance using model5.2 (n=500, by cell type).py Projet : csetraynor/immune-infiltrate-explorations

# In[2]:

model_name = 'model5.2'
by = 'cell_type'
sample_n = 500

# In[3]:

sample_df = cache.cached(models.prep_sample_df, sample_n=sample_n)
(training_df, test_df) = models.split_sample_df(sample_df=sample_df,
                                                test_sample_n=1)

# In[4]:

model_file = models.get_model_file(model_name=model_name)
#print(cache._read_file(model_file))

# In[5]:

stan_data = models.prep_stan_data(sample_df=training_df,
                                  test_df=test_df,
                                  by=by)

# In[ ]:

model_fit = cache.cached_stan_fit(file=model_file,
                                  data=stan_data,
                                  model_name=model_name)

# In[ ]:

Exemple #2

Fichier : 0.868 model5 by SubSet (n=1000).py Projet : csetraynor/immune-infiltrate-explorations

print(df.columns)

#apply(lambda x: x.startswith('C'))

# ## sample genes for analysis

# In[7]:

sample_df = cache.cached(models.prep_sample_df, sample_n=sample_n)

# ## fit model

# In[8]:

stan_data = models.prep_stan_data(sample_df, by=by)

# In[9]:

model_file = models.get_model_file(model_name=model_name)
print(cache._read_file(model_file))

# In[10]:

model_fit = models.cached_stan_fit(file=model_file,
                                   data=stan_data,
                                   model_name=model_name)

# ## check convergence (superficially)

# In[11]:

Exemple #3

Fichier : 0.8722 compare model5.3 across values of nu by SubSet (n=100).py Projet : csetraynor/immune-infiltrate-explorations

by = 'SubSet'
sample_n = 100


# ## get data, as we did in earlier examples

# This will help in case we want to compare estimates for particular genes or samples

# In[4]:

sample_df = cache.cached(models.prep_sample_df, sample_n=sample_n)


# In[5]:

stan_data1 = models.prep_stan_data(sample_df, by=by, nu=1)
stan_data2 = models.prep_stan_data(sample_df, by=by, nu=2)
stan_data3 = models.prep_stan_data(sample_df, by=by, nu=3)
stan_data4 = models.prep_stan_data(sample_df, by=by, nu=4)
stan_data5 = models.prep_stan_data(sample_df, by=by, nu=5)
stan_data6 = models.prep_stan_data(sample_df, by=by, nu=6)


# In[6]:

model = models.get_model_file(model_name=model_name)


# ## get models from cache

# In[7]: