Merge branch 'main' of https://github.com/arviz-devs/arviz into devel…

…opment/plot_dist_comparison_warning

Resolve conflicts

.azure-pipelines/azure-pipelines-external.yml

@@ -88,6 +88,9 @@ jobs:
       if [ "$(pymc3.version)" = "github" ]; then
           # Pip installation is failing for some reason. This is the same thing
           git clone https://github.com/pymc-devs/pymc3
+          cd pymc3
+          git checkout v3
+          cd ..
           pip install $PWD/pymc3
           # python -m pip --no-cache-dir --log log.txt install git+https://github.com/pymc-devs/pymc3
           # cat log.txt

.pylintrc

@@ -73,7 +73,8 @@ disable=missing-docstring,
         not-an-iterable,
         no-member,
         #TODO: Remove this once todos are done
-        fixme
+        fixme,
+        consider-using-with
 
 
 # Enable the message, report, category or checker with the given id(s). You can

CHANGELOG.md

@@ -170,7 +170,7 @@
 
 ## v0.9.0 (2020 June 23)
 ### New features
-* loo-pit plot. The kde is computed over the data interval (this could be shorter than [0, 1]). The HDI is computed analitically ([1215](https://github.com/arviz-devs/arviz/pull/1215))
+* loo-pit plot. The kde is computed over the data interval (this could be shorter than [0, 1]). The HDI is computed analytically ([1215](https://github.com/arviz-devs/arviz/pull/1215))
 * Added `html_repr` of InferenceData objects for jupyter notebooks. ([1217](https://github.com/arviz-devs/arviz/pull/1217))
 * Added support for PyJAGS via the function `from_pyjags`. ([1219](https://github.com/arviz-devs/arviz/pull/1219) and [1245](https://github.com/arviz-devs/arviz/pull/1245))
 * `from_pymc3` can now retrieve `coords` and `dims` from model context ([1228](https://github.com/arviz-devs/arviz/pull/1228), [1240](https://github.com/arviz-devs/arviz/pull/1240) and [1249](https://github.com/arviz-devs/arviz/pull/1249))

arviz/data/base.py

@@ -1,6 +1,7 @@
 """Low level converters usually used by other functions."""
 import datetime
 import functools
+import re
 import warnings
 from copy import deepcopy
 from typing import Any, Callable, Dict, List, Optional, Tuple, TypeVar, Union
@@ -438,3 +439,47 @@ def _make_json_serializable(data: dict) -> dict:
                 f"Value associated with variable `{type(value)}` is not JSON serializable."
             )
     return ret
+
+
+def infer_stan_dtypes(stan_code):
+    """Infer Stan integer variables from generated quantities block."""
+    # Remove old deprecated comments
+    stan_code = "\n".join(
+        line if "#" not in line else line[: line.find("#")] for line in stan_code.splitlines()
+    )
+    pattern_remove_comments = re.compile(
+        r'//.*?$|/\*.*?\*/|\'(?:\\.|[^\\\'])*\'|"(?:\\.|[^\\"])*"', re.DOTALL | re.MULTILINE
+    )
+    stan_code = re.sub(pattern_remove_comments, "", stan_code)
+
+    # Check generated quantities
+    if "generated quantities" not in stan_code:
+        return {}
+
+    # Extract generated quantities block
+    gen_quantities_location = stan_code.index("generated quantities")
+    block_start = gen_quantities_location + stan_code[gen_quantities_location:].index("{")
+
+    curly_bracket_count = 0
+    block_end = None
+    for block_end, char in enumerate(stan_code[block_start:], block_start + 1):
+        if char == "{":
+            curly_bracket_count += 1
+        elif char == "}":
+            curly_bracket_count -= 1
+
+            if curly_bracket_count == 0:
+                break
+
+    stan_code = stan_code[block_start:block_end]
+
+    stan_integer = r"int"
+    stan_limits = r"(?:\<[^\>]+\>)*"  # ignore group: 0 or more <....>
+    stan_param = r"([^;=\s\[]+)"  # capture group: ends= ";", "=", "[" or whitespace
+    stan_ws = r"\s*"  # 0 or more whitespace
+    stan_ws_one = r"\s+"  # 1 or more whitespace
+    pattern_int = re.compile(
+        "".join((stan_integer, stan_ws_one, stan_limits, stan_ws, stan_param)), re.IGNORECASE
+    )
+    dtypes = {key.strip(): "int" for key in re.findall(pattern_int, stan_code)}
+    return dtypes

arviz/data/datasets.py

@@ -204,7 +204,7 @@ def load_arviz_data(dataset=None, data_home=None):
 
     Run with no parameters to get a list of all available models.
 
-    The directory to save to can also be set with the environement
+    The directory to save to can also be set with the environment
     variable `ARVIZ_HOME`. The checksum of the dataset is checked against a
     hardcoded value to watch for data corruption.
 

arviz/data/inference_data.py

@@ -1874,7 +1874,7 @@ def concat(*args, dim=None, copy=True, inplace=False, reset_dim=True):
                     msg = "Mismatch between the groups."
                     raise TypeError(msg)
             for group in arg._groups_all:
-                # handle data groups seperately
+                # handle data groups separately
                 if group not in ["observed_data", "constant_data", "predictions_constant_data"]:
                     # assert that groups are equal
                     if group not in arg0_groups:

arviz/data/io_cmdstan.py

@@ -1,16 +1,18 @@
+# pylint: disable=too-many-lines
 """CmdStan-specific conversion code."""
 import logging
 import os
 import re
 from collections import defaultdict
 from glob import glob
+from pathlib import Path
 from typing import Dict, List, Optional, Union
 
 import numpy as np
 
 from .. import utils
 from ..rcparams import rcParams
-from .base import CoordSpec, DimSpec, dict_to_dataset, requires
+from .base import CoordSpec, DimSpec, dict_to_dataset, infer_stan_dtypes, requires
 from .inference_data import InferenceData
 
 _log = logging.getLogger(__name__)
@@ -83,9 +85,19 @@ def __init__(
         self.index_origin = index_origin
 
         if dtypes is None:
-            self.dtypes = {}
-        else:
-            self.dtypes = dtypes
+            dtypes = {}
+        elif isinstance(dtypes, str):
+            dtypes_path = Path(dtypes)
+            if dtypes_path.exists():
+                with dtypes_path.open("r") as f_obj:
+                    model_code = f_obj.read()
+            else:
+                model_code = dtypes
+
+            dtypes = infer_stan_dtypes(model_code)
+
+        self.dtypes = dtypes
+
         # populate posterior and sample_stats
         self._parse_posterior()
         self._parse_prior()
@@ -963,8 +975,9 @@ def from_cmdstan(
     save_warmup : bool
         Save warmup iterations into InferenceData object, if found in the input files.
         If not defined, use default defined by the rcParams.
-    dtypes : dict
+    dtypes : dict or str
         A dictionary containing dtype information (int, float) for parameters.
+        If input is a string, it is assumed to be a model code or path to model code file.
 
     Returns
     -------