[yt-svn] commit/yt: 2 new changesets
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Fri Feb 15 16:07:56 PST 2013
2 new commits in yt:
https://bitbucket.org/yt_analysis/yt/commits/329d11eeff22/
changeset: 329d11eeff22
branch: stable
user: MatthewTurk
date: 2013-02-16 00:59:27
summary: Minor docfix improvements
affected #: 3 files
diff -r 6b246ba83cb38d6fd2467bf76e265e6ca4f78beb -r 329d11eeff224ed16d054e989680ba6f193318e9 yt/analysis_modules/halo_merger_tree/enzofof_merger_tree.py
--- a/yt/analysis_modules/halo_merger_tree/enzofof_merger_tree.py
+++ b/yt/analysis_modules/halo_merger_tree/enzofof_merger_tree.py
@@ -730,8 +730,22 @@
x_quantity, y_quantity : str, optional
The quantity that you want to plot as the x_coord (or y_coords).
Valid options are:
- cycle, mass, fraction, halo_id, redshift, dense_x, dense_y, dense_z
- COM_x, COM_y, COM_z, COM_vx, COM_vy, COM_vz
+
+ * cycle
+ * mass
+ * fraction
+ * halo_id
+ * redshift
+ * dense_x
+ * dense_y
+ * dense_z
+ * COM_x
+ * COM_y
+ * COM_z
+ * COM_vx
+ * COM_vy
+ * COM_vz
+
x_log, y_log : bool, optional
Do you want the x(y)-axis to be in log or linear?
FOF_directory : str, optional
@@ -739,23 +753,23 @@
Examples
--------
- # generates mass history plots for the 20 most massive halos at t_fin.
- ts = TimeSeriesData.from_filenames("DD????/DD????")
-
- # long step--must run FOF on each DD, but saves outputs for later use
- for pf in ts:
- halo_list = FOFHaloFinder(pf)
- i = int(pf.basename[2:])
- halo_list.write_out("FOF/groups_%05i.txt" % i)
- halo_list.write_particle_lists("FOF/particles_%05i" % i)
-
- mt = EnzoFOFMergerTree(external_FOF=False)
- for i in range(20):
- mt.build_tree(i)
- mt.save_halo_evolution('halos.h5')
- for i in range(20):
- plot_halo_evolution('halos.h5', i)
+ >>> # generates mass history plots for the 20 most massive halos at t_fin.
+ >>> ts = TimeSeriesData.from_filenames("DD????/DD????")
+ >>> # long step--must run FOF on each DD, but saves outputs for later use
+ >>> for pf in ts:
+ ... halo_list = FOFHaloFinder(pf)
+ ... i = int(pf.basename[2:])
+ ... halo_list.write_out("FOF/groups_%05i.txt" % i)
+ ... halo_list.write_particle_lists("FOF/particles_%05i" % i)
+ ...
+ >>> mt = EnzoFOFMergerTree(external_FOF=False)
+ >>> for i in range(20):
+ ... mt.build_tree(i)
+ ... mt.save_halo_evolution('halos.h5')
+ ...
+ >>> for i in range(20):
+ ... plot_halo_evolution('halos.h5', i)
"""
import matplotlib.pyplot as plt
f = h5py.File("%s/%s" % (FOF_directory, filename), 'r')
diff -r 6b246ba83cb38d6fd2467bf76e265e6ca4f78beb -r 329d11eeff224ed16d054e989680ba6f193318e9 yt/data_objects/data_containers.py
--- a/yt/data_objects/data_containers.py
+++ b/yt/data_objects/data_containers.py
@@ -4523,24 +4523,22 @@
Examples
--------
- from yt.mods import *
- pf = load("redshift0058")
- dd = pf.h.sphere("max", (200, "kpc"))
- rho = 5e-27
-
- bounds = [(dd.center[i] - 100.0/pf['kpc'],
- dd.center[i] + 100.0/pf['kpc']) for i in range(3)]
-
- surf = pf.h.surface(dd, "Density", rho)
-
- rv = surf.export_sketchfab(
- title = "Testing Upload",
- description = "A simple test of the uploader",
- color_field = "Temperature",
- color_map = "hot",
- color_log = True,
- bounds = bounds
- )
+ >>> from yt.mods import *
+ >>> pf = load("redshift0058")
+ >>> dd = pf.h.sphere("max", (200, "kpc"))
+ >>> rho = 5e-27
+ >>> bounds = [(dd.center[i] - 100.0/pf['kpc'],
+ ... dd.center[i] + 100.0/pf['kpc']) for i in range(3)]
+ ...
+ >>> surf = pf.h.surface(dd, "Density", rho)
+ >>> rv = surf.export_sketchfab(
+ ... title = "Testing Upload",
+ ... description = "A simple test of the uploader",
+ ... color_field = "Temperature",
+ ... color_map = "hot",
+ ... color_log = True,
+ ... bounds = bounds)
+ ...
"""
api_key = api_key or ytcfg.get("yt","sketchfab_api_key")
if api_key in (None, "None"):
diff -r 6b246ba83cb38d6fd2467bf76e265e6ca4f78beb -r 329d11eeff224ed16d054e989680ba6f193318e9 yt/testing.py
--- a/yt/testing.py
+++ b/yt/testing.py
@@ -172,7 +172,7 @@
keyword arguments and all of the values for these arguments that you
want to test.
- It will return a list of **kwargs dicts containing combinations of
+ It will return a list of kwargs dicts containing combinations of
the various kwarg values you passed it. These can then be passed
to the appropriate function in nosetests.
https://bitbucket.org/yt_analysis/yt/commits/56c9e8e1d092/
changeset: 56c9e8e1d092
branch: yt
user: MatthewTurk
date: 2013-02-16 00:59:27
summary: Minor docfix improvements
affected #: 3 files
diff -r 19b12255a0157c5d1b3c512da18b77066f289d38 -r 56c9e8e1d0920d28c93e6b03d39097079466c17c yt/analysis_modules/halo_merger_tree/enzofof_merger_tree.py
--- a/yt/analysis_modules/halo_merger_tree/enzofof_merger_tree.py
+++ b/yt/analysis_modules/halo_merger_tree/enzofof_merger_tree.py
@@ -730,8 +730,22 @@
x_quantity, y_quantity : str, optional
The quantity that you want to plot as the x_coord (or y_coords).
Valid options are:
- cycle, mass, fraction, halo_id, redshift, dense_x, dense_y, dense_z
- COM_x, COM_y, COM_z, COM_vx, COM_vy, COM_vz
+
+ * cycle
+ * mass
+ * fraction
+ * halo_id
+ * redshift
+ * dense_x
+ * dense_y
+ * dense_z
+ * COM_x
+ * COM_y
+ * COM_z
+ * COM_vx
+ * COM_vy
+ * COM_vz
+
x_log, y_log : bool, optional
Do you want the x(y)-axis to be in log or linear?
FOF_directory : str, optional
@@ -739,23 +753,23 @@
Examples
--------
- # generates mass history plots for the 20 most massive halos at t_fin.
- ts = TimeSeriesData.from_filenames("DD????/DD????")
-
- # long step--must run FOF on each DD, but saves outputs for later use
- for pf in ts:
- halo_list = FOFHaloFinder(pf)
- i = int(pf.basename[2:])
- halo_list.write_out("FOF/groups_%05i.txt" % i)
- halo_list.write_particle_lists("FOF/particles_%05i" % i)
-
- mt = EnzoFOFMergerTree(external_FOF=False)
- for i in range(20):
- mt.build_tree(i)
- mt.save_halo_evolution('halos.h5')
- for i in range(20):
- plot_halo_evolution('halos.h5', i)
+ >>> # generates mass history plots for the 20 most massive halos at t_fin.
+ >>> ts = TimeSeriesData.from_filenames("DD????/DD????")
+ >>> # long step--must run FOF on each DD, but saves outputs for later use
+ >>> for pf in ts:
+ ... halo_list = FOFHaloFinder(pf)
+ ... i = int(pf.basename[2:])
+ ... halo_list.write_out("FOF/groups_%05i.txt" % i)
+ ... halo_list.write_particle_lists("FOF/particles_%05i" % i)
+ ...
+ >>> mt = EnzoFOFMergerTree(external_FOF=False)
+ >>> for i in range(20):
+ ... mt.build_tree(i)
+ ... mt.save_halo_evolution('halos.h5')
+ ...
+ >>> for i in range(20):
+ ... plot_halo_evolution('halos.h5', i)
"""
import matplotlib.pyplot as plt
f = h5py.File("%s/%s" % (FOF_directory, filename), 'r')
diff -r 19b12255a0157c5d1b3c512da18b77066f289d38 -r 56c9e8e1d0920d28c93e6b03d39097079466c17c yt/data_objects/data_containers.py
--- a/yt/data_objects/data_containers.py
+++ b/yt/data_objects/data_containers.py
@@ -4523,24 +4523,22 @@
Examples
--------
- from yt.mods import *
- pf = load("redshift0058")
- dd = pf.h.sphere("max", (200, "kpc"))
- rho = 5e-27
-
- bounds = [(dd.center[i] - 100.0/pf['kpc'],
- dd.center[i] + 100.0/pf['kpc']) for i in range(3)]
-
- surf = pf.h.surface(dd, "Density", rho)
-
- rv = surf.export_sketchfab(
- title = "Testing Upload",
- description = "A simple test of the uploader",
- color_field = "Temperature",
- color_map = "hot",
- color_log = True,
- bounds = bounds
- )
+ >>> from yt.mods import *
+ >>> pf = load("redshift0058")
+ >>> dd = pf.h.sphere("max", (200, "kpc"))
+ >>> rho = 5e-27
+ >>> bounds = [(dd.center[i] - 100.0/pf['kpc'],
+ ... dd.center[i] + 100.0/pf['kpc']) for i in range(3)]
+ ...
+ >>> surf = pf.h.surface(dd, "Density", rho)
+ >>> rv = surf.export_sketchfab(
+ ... title = "Testing Upload",
+ ... description = "A simple test of the uploader",
+ ... color_field = "Temperature",
+ ... color_map = "hot",
+ ... color_log = True,
+ ... bounds = bounds)
+ ...
"""
api_key = api_key or ytcfg.get("yt","sketchfab_api_key")
if api_key in (None, "None"):
diff -r 19b12255a0157c5d1b3c512da18b77066f289d38 -r 56c9e8e1d0920d28c93e6b03d39097079466c17c yt/testing.py
--- a/yt/testing.py
+++ b/yt/testing.py
@@ -172,7 +172,7 @@
keyword arguments and all of the values for these arguments that you
want to test.
- It will return a list of **kwargs dicts containing combinations of
+ It will return a list of kwargs dicts containing combinations of
the various kwarg values you passed it. These can then be passed
to the appropriate function in nosetests.
Repository URL: https://bitbucket.org/yt_analysis/yt/
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