From f20903afbbc11e2c7d278850ce1e0e41d313e024 Mon Sep 17 00:00:00 2001
From: Lionel GUEZ <guez@lmd.ens.fr>
Date: Mon, 21 Jan 2019 15:05:59 +0100
Subject: [PATCH] Define functions fig_hist, fig_distr_funct and plot_all in
module distribution_function. This allows to plot comparisons of various
combinations of runs.
Update plot_snapshot.py to work with version 2 of pyshp.
---
Analysis/distribution_function.py | 149 +++++++++++++++---------------
Analysis/plot_snapshot.py | 7 +-
2 files changed, 75 insertions(+), 81 deletions(-)
diff --git a/Analysis/distribution_function.py b/Analysis/distribution_function.py
index 68797f53..c9403bb8 100755
--- a/Analysis/distribution_function.py
+++ b/Analysis/distribution_function.py
@@ -3,16 +3,17 @@
import shapefile
import numpy as np
import matplotlib.pyplot as plt
+import itertools
-def plot_distr_funct(X, label = None, ax = None):
- """Sort and plot distribution function."""
+def plot_distr_funct(x, label = None, ax = None):
+ """Sort and plot distribution function. x should be a Numpy array."""
- X.sort()
- nx = np.size(X)
+ x.sort()
+ nx = np.size(x)
if ax is None: ax = plt.gca()
- ax.plot(X, (1 + np.arange(nx)) / nx, label = label)
- print("minimum value:", X[0])
- print("maximum value:", X[-1])
+ ax.plot(x, (1 + np.arange(nx)) / nx, label = label)
+ print("minimum value:", x[0])
+ print("maximum value:", x[-1])
print("number of values:", nx, "\n")
def read(end_filename = ""):
@@ -51,90 +52,84 @@ def read(end_filename = ""):
"rad_speed": np.array(rad_speed), "amp_outer": np.array(amp_outer),
"amp_speed": np.array(amp_speed)}
-if __name__ == "__main__":
- import argparse
-
- parser = argparse.ArgumentParser()
- parser.add_argument("-e", "--end_filename",
- help = "add character string after "
- "extremum, outermost_contour and max_speed_contour",
- default = "")
- args = parser.parse_args()
- d = read(args.end_filename)
-
- xlabel = "speed, in m s-1"
+def fig_hist(xlabel, x, label):
+ """Complete figure with histogram. x and label can also be sequences."""
plt.figure()
- plt.hist(d["speed"], bins = "auto")
+ plt.hist(x, bins = "auto", histtype = "step", label = label)
plt.xlabel(xlabel)
plt.ylabel("number of occurrences")
+ if label is not None: plt.legend()
- plt.figure()
- print("speed, when positive:")
- plot_distr_funct(d["speed"][d["speed"] >= 0], label = "positive")
- print("- speed, when negative:")
- plot_distr_funct(- d["speed"][d["speed"] < 0], label = "negative")
- plt.xlabel(xlabel)
- plt.legend()
-
- xlabel = "equivalent radius of outermost contour, in km"
-
- plt.figure()
- plt.hist(d["rad_outer"], bins = "auto")
- plt.xlabel(xlabel)
- plt.ylabel("number of occurrences")
+def fig_distr_funct(xlabel, x, label = None):
+ """Complete figure with distribution function. x must be a sequence of
+ Numpy arrays and label None or a sequence of strings.
- plt.figure()
- print(xlabel + ":")
- plot_distr_funct(d["rad_outer"])
- plt.xlabel(xlabel)
- plt.ylabel("distribution function")
+ """
- xlabel = "equivalent radius of max-speed contour, in km"
-
- plt.figure()
- plt.hist(d["rad_speed"], bins = "auto")
- plt.xlabel(xlabel)
- plt.ylabel("number of occurrences")
-
plt.figure()
print(xlabel + ":")
- plot_distr_funct(d["rad_speed"])
+
+ label_None = label is None
+ if label_None: label = itertools.repeat(None)
+
+ for xi, li in zip(x, label):
+ plot_distr_funct(xi, label = li)
+
plt.xlabel(xlabel)
plt.ylabel("distribution function")
-
- xlabel = "amplitude of outermost contour, in m"
+ if not label_None: plt.legend()
- plt.figure()
- plt.hist(d["amp_outer"], bins = "auto")
- plt.xlabel(xlabel)
- plt.ylabel("number of occurrences")
+def plot_all(dict_list, label = None):
+ """dict_list: list of dictionaries. label: list of labels, one label
+ for each dictionary.
- plt.figure()
- print("amplitude of outermost contour, anticyclones:")
- plot_distr_funct(d["amp_outer"][d["amp_outer"] >= 0],
- label = "anticyclones")
- print("amplitude of outermost contour, cyclones:")
- plot_distr_funct(- d["amp_outer"][d["amp_outer"] < 0], label = "cyclones")
- plt.xlabel(xlabel)
- plt.ylabel("distribution function")
- plt.legend()
+ """
- xlabel = "amplitude of max-speed contour, in m"
+ fig_hist("speed, in m s-1", [d["speed"] for d in dict_list], label)
+ fig_distr_funct("speed, when positive, in m s-1",
+ [d["speed"][d["speed"] >= 0] for d in dict_list], label)
+ fig_distr_funct("speed, when negative, in m s-1",
+ [- d["speed"][d["speed"] < 0] for d in dict_list], label)
- plt.figure()
- plt.hist(d["amp_speed"], bins = "auto")
- plt.xlabel(xlabel)
- plt.ylabel("number of occurrences")
-
- plt.figure()
- print("amplitude of max-speed contour, anticyclones:")
- plot_distr_funct(d["amp_speed"][d["amp_speed"] >= 0],
- label = "anticyclones")
- print("amplitude of max-speed contour, cyclones:")
- plot_distr_funct(- d["amp_speed"][d["amp_speed"] < 0], label = "cyclones")
- plt.xlabel(xlabel)
- plt.ylabel("distribution function")
- plt.legend()
+ fig_hist("equivalent radius of outermost contour, in km",
+ [d["rad_outer"] for d in dict_list], label)
+ fig_distr_funct("equivalent radius of outermost contour, in km",
+ [d["rad_outer"] for d in dict_list], label)
+
+ fig_hist("equivalent radius of max-speed contour, in km",
+ [d["rad_speed"] for d in dict_list], label)
+ fig_distr_funct("equivalent radius of max-speed contour, in km",
+ [d["rad_speed"] for d in dict_list], label)
+
+ fig_hist("amplitude of outermost contour, in m",
+ [d["amp_outer"] for d in dict_list], label)
+ fig_distr_funct("amplitude of outermost contour, anticyclones, in m",
+ [d["amp_outer"][d["amp_outer"] >= 0] for d in dict_list],
+ label)
+ fig_distr_funct("amplitude of outermost contour, cyclones, in m",
+ [- d["amp_outer"][d["amp_outer"] < 0] for d in dict_list],
+ label)
+
+ fig_hist("amplitude of max-speed contour, in m",
+ [d["amp_speed"] for d in dict_list], label)
+ fig_distr_funct("amplitude of max-speed contour, anticyclones, in m",
+ [d["amp_speed"][d["amp_speed"] >= 0] for d in dict_list],
+ label)
+ fig_distr_funct("amplitude of max-speed contour, cyclones, in m",
+ [- d["amp_speed"][d["amp_speed"] < 0] for d in dict_list],
+ label)
+
+if __name__ == "__main__":
+ import argparse
+
+ parser = argparse.ArgumentParser()
+ parser.add_argument("-e", "--end_filename",
+ help = "add character string after "
+ "extremum, outermost_contour and max_speed_contour",
+ default = "")
+ args = parser.parse_args()
+ d = read(args.end_filename)
+ plot_all([d])
plt.show()
diff --git a/Analysis/plot_snapshot.py b/Analysis/plot_snapshot.py
index 8ef3ff0e..6dcf8ca3 100755
--- a/Analysis/plot_snapshot.py
+++ b/Analysis/plot_snapshot.py
@@ -48,8 +48,7 @@ try:
except shapefile.ShapefileException:
print("Shapefile max_speed_contour_1 not found. "
"Max-speed contours will not be plotted.")
- w = shapefile.Writer(shapeType = shapefile.NULL)
- m_s_iterShapes = itertools.repeat(w)
+ m_s_iterShapes = itertools.repeat(None)
else:
m_s_iterShapes = reader_m_s.iterShapes()
@@ -129,12 +128,12 @@ for shape_rec_extr, shape_outer, shape_m_s \
# Invalid outermost contour
lines[0].set_marker("s")
lines[0].set_fillstyle("none")
- elif shape_m_s.shapeType == shapefile.NULL:
+ elif shape_m_s == None or shape_m_s.shapeType == shapefile.NULL:
lines[0].set_marker("x")
else:
lines[0].set_marker("o")
- if shape_m_s.shapeType != shapefile.NULL:
+ if shape_m_s != None and shape_m_s.shapeType != shapefile.NULL:
points = np.array(shape_m_s.points)
if shape_rec_extr.record.cyclone == 0:
--
GitLab