tqdm ProgressBar replaces deprecated ProgressMeter (PR #2617)

* Fixes #928
* Fixes #2504
* Added the ProgressBar class which inherits the tqdm.auto.tqdm object. 
   - For now, the disable keyword takes precedence over verbose, i.e. if both are set to 
     True the progress bar won't show. Setting disable=True will disable the progress bar 
     as expected. Setting verbose=False will disable the progress bar.
  - Automatically detect which version of tqdm to use (console or notebook):
     If run from a jupyter notebook or jupyter lab, will use the
     tqdm.notebook.tqdm class, else (ipython, shell, or anything else)
     will use the default tqdm.tqdm class
* add tqdm to dependencies
* Deprecate ProgressMeter through warning and text
* Replace ProgressMeter with ProgressBar everywhere in MDAnalysis
* add tests (for #928 and #2504)
* update CHANGELOG and AUTHORS

.appveyor.yml

@@ -10,7 +10,7 @@ cache:
 environment:
     global:
         CONDA_CHANNELS: conda-forge
-        CONDA_DEPENDENCIES: pip setuptools wheel cython mock six biopython networkx joblib matplotlib scipy vs2015_runtime pytest mmtf-python GridDataFormats hypothesis pytest-cov codecov chemfiles
+        CONDA_DEPENDENCIES: pip setuptools wheel cython mock six biopython networkx joblib matplotlib scipy vs2015_runtime pytest mmtf-python GridDataFormats hypothesis pytest-cov codecov chemfiles tqdm
         PIP_DEPENDENCIES: gsd==1.9.3 duecredit parmed
         DEBUG: "False"
         MINGW_64: C:\mingw-w64\x86_64-6.3.0-posix-seh-rt_v5-rev1\mingw64\bin

.travis.yml

@@ -28,7 +28,7 @@ env:
     - SETUP_CMD="${PYTEST_FLAGS}"
     - BUILD_CMD="pip install -e package/ && (cd testsuite/ && python setup.py build)"
     - CONDA_MIN_DEPENDENCIES="mmtf-python mock six biopython networkx cython matplotlib scipy griddataformats hypothesis gsd codecov"
-    - CONDA_DEPENDENCIES="${CONDA_MIN_DEPENDENCIES} seaborn>=0.7.0 clustalw=2.1 netcdf4 scikit-learn joblib>=0.12 chemfiles"
+    - CONDA_DEPENDENCIES="${CONDA_MIN_DEPENDENCIES} seaborn>=0.7.0 clustalw=2.1 netcdf4 scikit-learn joblib>=0.12 chemfiles tqdm>=4.43.0"
     - CONDA_CHANNELS='biobuilds conda-forge'
     - CONDA_CHANNEL_PRIORITY=True
     - PIP_DEPENDENCIES="duecredit parmed"
@@ -73,7 +73,7 @@ matrix:
            PIP_DEPENDENCIES="${PIP_DEPENDENCIES} setuptools<45.0.0"
 
     - env: NAME="asv check"
-           PYTHON_VERSION=2.7 
+           PYTHON_VERSION=2.7
            CODECOV="false"
            MAIN_CMD=""
            SETUP_CMD=""

package/AUTHORS

@@ -136,6 +136,7 @@ Chronological list of authors
   - Anshul Angaria
   - Shubham Sharma
   - Yuxuan Zhuang
+  - Cédric Bouysset
   - Abhishek Shandilya
   - Morgan L. Nance
   - Faraaz Shah

package/CHANGELOG

@@ -17,7 +17,7 @@ mm/dd/yy richardjgowers, kain88-de, lilyminium, p-j-smith, bdice, joaomcteixeira
          PicoCentauri, davidercruz, jbarnoud, RMeli, IAlibay, mtiberti, CCook96,
          Yuan-Yu, xiki-tempula, HTian1997, Iv-Hristov, hmacdope, AnshulAngaria,
          ss62171, Luthaf, yuxuanzhuang, abhishandy, mlnance, shfrz, orbeckst,
-         wvandertoorn
+         wvandertoorn, cbouy
 
   * 0.21.0
 
@@ -114,6 +114,8 @@ Enhancements
   * PersistenceLength.plot() now create new axes if current axes not provided (Issue #2590)
 
 Changes
+  * Deprecated :class:`ProgressMeter` and replaced it with :class:`ProgressBar` using
+    the tqdm package (Issue #928, PR #2617). Also fixes issue #2504.
   * Removed `details` from `ClusteringMethod`s (Issue #2575, PR #2620)
   * Removed deprecated :meth:`PersistenceLength.perform_fit` (Issue #2596)
   * Changed :meth:`PSAnalysis.generate_paths` keywords `store` and `filename`

package/MDAnalysis/analysis/base.py

@@ -38,7 +38,7 @@
 import numpy as np
 from MDAnalysis import coordinates
 from MDAnalysis.core.groups import AtomGroup
-from MDAnalysis.lib.log import ProgressMeter
+from MDAnalysis.lib.log import ProgressBar
 
 logger = logging.getLogger(__name__)
 
@@ -131,13 +131,6 @@ def _setup_frames(self, trajectory, start=None, stop=None, step=None):
         self.stop = stop
         self.step = step
         self.n_frames = len(range(start, stop, step))
-        interval = int(self.n_frames // 100)
-        if interval == 0:
-            interval = 1
-
-        verbose = getattr(self, '_verbose', False)
-        self._pm = ProgressMeter(self.n_frames if self.n_frames else 1,
-                                 interval=interval, verbose=verbose)
 
     def _single_frame(self):
         """Calculate data from a single frame of trajectory
@@ -178,13 +171,13 @@ def run(self, start=None, stop=None, step=None, verbose=None):
         self._setup_frames(self._trajectory, start, stop, step)
         logger.info("Starting preparation")
         self._prepare()
-        for i, ts in enumerate(
-                self._trajectory[self.start:self.stop:self.step]):
+        for i, ts in enumerate(ProgressBar(
+                self._trajectory[self.start:self.stop:self.step],
+                verbose=verbose)):
             self._frame_index = i
             self._ts = ts
             # logger.info("--> Doing frame {} of {}".format(i+1, self.n_frames))
             self._single_frame()
-            self._pm.echo(self._frame_index)
         logger.info("Finishing up")
         self._conclude()
         return self

package/MDAnalysis/analysis/density.py

@@ -191,7 +191,8 @@
 from MDAnalysis import NoDataError, MissingDataWarning
 from .. import units
 from ..lib import distances
-from MDAnalysis.lib.log import ProgressMeter
+from MDAnalysis.lib.log import ProgressBar 
+from MDAnalysis.lib.log import ProgressMeter   # remove in 2.0
 from MDAnalysis.lib.util import deprecate
 
 from .base import AnalysisBase
@@ -1078,21 +1079,15 @@ def current_coordinates():
     start, stop, step = u.trajectory.check_slice_indices(start, stop, step)
     n_frames = len(range(start, stop, step))
 
-    pm = ProgressMeter(n_frames, interval=interval,
-                       verbose=verbose,
-                       format="Histogramming %(n_atoms)6d atoms in frame "
-                       "%(step)5d/%(numsteps)d  [%(percentage)5.1f%%]")
-
-    for index, ts in enumerate(u.trajectory[start:stop:step]):
+    for ts in ProgressBar(u.trajectory[start:stop:step],
+                          verbose=verbose, desc="Histogramming"):
         coord = current_coordinates()
 
-        pm.echo(index, n_atoms=len(coord))
         if len(coord) == 0:
             continue
 
         h[:], edges[:] = np.histogramdd(coord, bins=bins, range=arange, normed=False)
         grid += h  # accumulate average histogram
-
     grid /= float(n_frames)
 
     metadata = metadata if metadata is not None else {}

package/MDAnalysis/analysis/hbonds/hbond_analysis.py

@@ -331,7 +331,7 @@ class HydrogenBondAnalysis_OtherFF(HydrogenBondAnalysis):
 
 from MDAnalysis import MissingDataWarning, NoDataError, SelectionError, SelectionWarning
 from .. import base
-from MDAnalysis.lib.log import ProgressMeter
+from MDAnalysis.lib.log import ProgressBar
 from MDAnalysis.lib.NeighborSearch import AtomNeighborSearch
 from MDAnalysis.lib import distances
 
@@ -952,10 +952,6 @@ def run(self, start=None, stop=None, step=None, verbose=None, **kwargs):
         self._timeseries = []
         self.timesteps = []
 
-        pm = ProgressMeter(self.n_frames,
-                           format="HBonds frame {current_step:5d}: {step:5d}/{numsteps} [{percentage:5.1f}%]\r",
-                           verbose=kwargs.get('verbose', False))
-
         try:
             self.u.trajectory.time
             def _get_timestep():
@@ -970,7 +966,9 @@ def _get_timestep():
         logger.info("Starting analysis (frame index start=%d stop=%d, step=%d)",
                     self.start, self.stop, self.step)
 
-        for progress, ts in enumerate(self.u.trajectory[self.start:self.stop:self.step]):
+        for ts in ProgressBar(self.u.trajectory[self.start:self.stop:self.step],
+                              desc="HBond analysis",
+                              verbose=kwargs.get('verbose', False)):
             # all bonds for this timestep
             frame_results = []
             # dict of tuples (atom.index, atom.index) for quick check if
@@ -981,7 +979,6 @@ def _get_timestep():
             timestep = _get_timestep()
             self.timesteps.append(timestep)
 
-            pm.echo(progress, current_step=frame)
             self.logger_debug("Analyzing frame %(frame)d, timestep %(timestep)f ps", vars())
             if self.update_selection1:
                 self._update_selection_1()
@@ -1041,7 +1038,6 @@ def _get_timestep():
                                     dist, angle])
 
             self._timeseries.append(frame_results)
-
         logger.info("HBond analysis: complete; timeseries  %s.timeseries",
                     self.__class__.__name__)
 

package/MDAnalysis/analysis/hbonds/hbond_autocorrel.py

@@ -213,7 +213,7 @@
 
 import warnings
 
-from MDAnalysis.lib.log import ProgressMeter
+from MDAnalysis.lib.log import ProgressBar
 from MDAnalysis.lib.distances import capped_distance, calc_angles, calc_bonds
 from MDAnalysis.core.groups import requires
 
@@ -392,12 +392,9 @@ def run(self, force=False):
         # for normalising later
         counter = np.zeros_like(master_results, dtype=np.float32)
 
-        pm = ProgressMeter(self.nruns, interval=1,
-                           format="Performing run %(step)5d/%(numsteps)d"
-                                  "[%(percentage)5.1f%%]")
-
-        for i, (start, stop) in enumerate(zip(self._starts, self._stops)):
-            pm.echo(i)
+        for i, (start, stop) in ProgressBar(enumerate(zip(self._starts,
+                                            self._stops)), total=self.nruns,
+                                            desc="Performing run"):
 
             # needed else trj seek thinks a np.int64 isn't an int?
             results = self._single_run(int(start), int(stop))

package/MDAnalysis/analysis/helanal.py

@@ -124,7 +124,7 @@
 import numpy as np
 
 import MDAnalysis
-from MDAnalysis.lib.log import ProgressMeter
+from MDAnalysis.lib.log import ProgressBar
 from MDAnalysis.lib import mdamath
 
 import warnings
@@ -346,14 +346,10 @@ def helanal_trajectory(universe, select="name CA",
     global_fitted_tilts = []
     global_screw = []
 
-    pm = ProgressMeter(n_frames, verbose=verbose,
-                       format="Frame {step:5d}/{numsteps} "
-                       "  [{percentage:5.1f}%]")
+    for ts in ProgressBar(trajectory[start_frame:end_frame:frame_step],
+                          verbose=verbose, desc="Helix analysis"):
 
-    for index, ts in enumerate(trajectory[start_frame:end_frame:frame_step]):
-        pm.echo(index)
         frame = ts.frame
-
         ca_positions = ca.positions
         twist, bending_angles, height, rnou, origins, local_helix_axes, local_screw_angles = \
             main_loop(ca_positions, ref_axis=ref_axis)
@@ -414,7 +410,6 @@ def helanal_trajectory(universe, select="name CA",
             store.append(tmp)
         #for store,tmp in zip(global_tilt,local_helix_axes): store.append(mdamath.angle(tmp,ref_axis))
 
-
     twist_mean, twist_sd, twist_abdev = stats(global_twist)
     height_mean, height_sd, height_abdev = stats(global_height)
     rnou_mean, rnou_sd, rnou_abdev = stats(global_rnou)

package/MDAnalysis/analysis/pca.py

@@ -111,7 +111,7 @@
 
 from MDAnalysis import Universe
 from MDAnalysis.analysis.align import _fit_to
-from MDAnalysis.lib.log import ProgressMeter
+from MDAnalysis.lib.log import ProgressBar
 
 from .base import AnalysisBase
 
@@ -161,11 +161,11 @@ class PCA(AnalysisBase):
     Notes
     -----
     Computation can be speed up by supplying a precalculated mean structure
-    
+
     .. versionchanged:: 1.0.0
        align=True now correctly aligns the trajectory and computes the correct
        means and covariance matrix
-    
+
     .. versionchanged:: 0.19.0
        The start frame is used when performing selections and calculating
        mean positions.  Previously the 0th frame was always used.
@@ -230,15 +230,8 @@ def _prepare(self):
         self._ref_atom_positions -= self._ref_cog
 
         if self._calc_mean:
-            interval = int(self.n_frames // 100)
-            interval = interval if interval > 0 else 1
-            format = ("Mean Calculation Step"
-                      "%(step)5d/%(numsteps)d [%(percentage)5.1f%%]")
-            mean_pm = ProgressMeter(self.n_frames if self.n_frames else 1,
-                                    interval=interval, verbose=self._verbose,
-                                    format=format)
-            for i, ts in enumerate(self._u.trajectory[self.start:self.stop:
-                                                      self.step]):
+            for ts in ProgressBar(self._u.trajectory[self.start:self.stop:self.step],
+                                  verbose=self._verbose, desc="Mean Calculation"):
                 if self.align:
                     mobile_cog = self._atoms.center_of_geometry()
                     mobile_atoms, old_rmsd = _fit_to(self._atoms.positions - mobile_cog,
@@ -248,7 +241,6 @@ def _prepare(self):
                                                      ref_com=self._ref_cog)
 
                 self.mean += self._atoms.positions.ravel()
-                mean_pm.echo(i)
             self.mean /= self.n_frames
 
         self.mean_atoms = self._atoms

package/MDAnalysis/analysis/rms.py

@@ -145,7 +145,6 @@
 import MDAnalysis.lib.qcprot as qcp
 from MDAnalysis.analysis.base import AnalysisBase
 from MDAnalysis.exceptions import SelectionError, NoDataError
-from MDAnalysis.lib.log import ProgressMeter
 from MDAnalysis.lib.util import asiterable, iterable, get_weights
 
 
@@ -625,8 +624,6 @@ def _prepare(self):
         self.rmsd = np.zeros((self.n_frames,
                               3 + len(self._groupselections_atoms)))
 
-        self._pm.format = ("RMSD {rmsd:5.2f} A at frame "
-                           "{step:5d}/{numsteps}  [{percentage:5.1f}%]")
         self._mobile_coordinates64 = self.mobile_atoms.positions.copy().astype(np.float64)
 
     def _single_frame(self):
@@ -673,8 +670,6 @@ def _single_frame(self):
                 self._ref_coordinates64, self._mobile_coordinates64,
                 self._n_atoms, None, self.weights_select)
 
-        self._pm.rmsd = self.rmsd[self._frame_index, 2]
-
 
 class RMSF(AnalysisBase):
     r"""Calculate RMSF of given atoms across a trajectory.

package/MDAnalysis/analysis/waterdynamics.py

@@ -455,7 +455,7 @@
 
 import numpy as np
 import MDAnalysis.analysis.hbonds
-from MDAnalysis.lib.log import ProgressMeter
+from MDAnalysis.lib.log import ProgressBar
 
 
 class HydrogenBondLifetimes(object):
@@ -808,11 +808,9 @@ def _sameMolecTandDT(self, selection, t0d, tf):
 
     def _selection_serial(self, universe, selection_str):
         selection = []
-        pm = ProgressMeter(universe.trajectory.n_frames,
-                           interval=10, verbose=True)
-        for ts in universe.trajectory:
+        for ts in ProgressBar(universe.trajectory, verbose=True,
+                              total=universe.trajectory.n_frames):
             selection.append(universe.select_atoms(selection_str))
-            pm.echo(ts.frame)
         return selection
 
     @staticmethod
@@ -983,11 +981,9 @@ def run(self, **kwargs):
 
     def _selection_serial(self, universe, selection_str):
         selection = []
-        pm = ProgressMeter(universe.trajectory.n_frames,
-                           interval=10, verbose=True)
-        for ts in universe.trajectory:
+        for ts in ProgressBar(universe.trajectory, verbose=True,
+                              total=universe.trajectory.n_frames):
             selection.append(universe.select_atoms(selection_str))
-            pm.echo(ts.frame)
         return selection
 
 
@@ -1125,11 +1121,9 @@ def _sameMolecTandDT(self, selection, t0d, tf):
 
     def _selection_serial(self, universe, selection_str):
         selection = []
-        pm = ProgressMeter(universe.trajectory.n_frames,
-                           interval=10, verbose=True)
-        for ts in universe.trajectory:
+        for ts in ProgressBar(universe.trajectory, verbose=True,
+                              total=universe.trajectory.n_frames):
             selection.append(universe.select_atoms(selection_str))
-            pm.echo(ts.frame)
         return selection
 
     def run(self, **kwargs):