Javi Merino | 491cf73 | 2014-03-31 17:34:44 +0100 | [diff] [blame] | 1 | #!/usr/bin/python |
Javi Merino | 5bd3d44 | 2014-04-08 12:55:13 +0100 | [diff] [blame] | 2 | """Process the output of the power allocator trace in the current |
| 3 | directory's trace.dat""" |
Javi Merino | 572049d | 2014-03-31 16:45:23 +0100 | [diff] [blame] | 4 | |
| 5 | import os |
Javi Merino | ee56c36 | 2014-03-31 17:30:34 +0100 | [diff] [blame] | 6 | import re |
Javi Merino | 952815a | 2014-03-31 18:08:32 +0100 | [diff] [blame] | 7 | from StringIO import StringIO |
Javi Merino | f78ea5b | 2014-03-31 17:51:38 +0100 | [diff] [blame] | 8 | import pandas as pd |
Javi Merino | a6399fb | 2014-03-31 19:17:08 +0100 | [diff] [blame] | 9 | from matplotlib import pyplot as plt |
Javi Merino | 572049d | 2014-03-31 16:45:23 +0100 | [diff] [blame] | 10 | |
Javi Merino | 7686f36 | 2014-04-02 11:26:40 +0100 | [diff] [blame] | 11 | GOLDEN_RATIO = 1.618034 |
| 12 | |
Javi Merino | c2ec568 | 2014-04-01 15:16:06 +0100 | [diff] [blame] | 13 | class BaseThermal(object): |
Javi Merino | 5bd3d44 | 2014-04-08 12:55:13 +0100 | [diff] [blame] | 14 | """Base class to parse trace.dat dumps. |
| 15 | |
| 16 | Don't use directly, create a subclass that defines the unique_word |
| 17 | you want to match in the output""" |
Javi Merino | 6846155 | 2014-04-08 11:40:09 +0100 | [diff] [blame] | 18 | def __init__(self, basepath, unique_word): |
| 19 | if basepath is None: |
| 20 | basepath = "." |
Javi Merino | c2ec568 | 2014-04-01 15:16:06 +0100 | [diff] [blame] | 21 | |
Javi Merino | 6846155 | 2014-04-08 11:40:09 +0100 | [diff] [blame] | 22 | self.basepath = basepath |
Javi Merino | 952815a | 2014-03-31 18:08:32 +0100 | [diff] [blame] | 23 | self.data_csv = "" |
Javi Merino | f78ea5b | 2014-03-31 17:51:38 +0100 | [diff] [blame] | 24 | self.data_frame = False |
Javi Merino | 6846155 | 2014-04-08 11:40:09 +0100 | [diff] [blame] | 25 | self.unique_word = unique_word |
| 26 | |
| 27 | if not os.path.isfile(os.path.join(basepath, "trace.txt")): |
| 28 | self.__run_trace_cmd_report() |
Javi Merino | 572049d | 2014-03-31 16:45:23 +0100 | [diff] [blame] | 29 | |
Javi Merino | 572049d | 2014-03-31 16:45:23 +0100 | [diff] [blame] | 30 | def __run_trace_cmd_report(self): |
Javi Merino | 5bd3d44 | 2014-04-08 12:55:13 +0100 | [diff] [blame] | 31 | """Run "trace-cmd report > trace.txt". |
| 32 | |
| 33 | Overwrites the contents of trace.txt if it exists.""" |
Javi Merino | ee56c36 | 2014-03-31 17:30:34 +0100 | [diff] [blame] | 34 | from subprocess import check_output |
| 35 | |
Javi Merino | 6846155 | 2014-04-08 11:40:09 +0100 | [diff] [blame] | 36 | if not os.path.isfile(os.path.join(self.basepath, "trace.dat")): |
Javi Merino | 1a3725a | 2014-03-31 18:35:15 +0100 | [diff] [blame] | 37 | raise IOError("No such file or directory: trace.dat") |
| 38 | |
Javi Merino | 6846155 | 2014-04-08 11:40:09 +0100 | [diff] [blame] | 39 | previous_path = os.getcwd() |
| 40 | os.chdir(self.basepath) |
Javi Merino | 572049d | 2014-03-31 16:45:23 +0100 | [diff] [blame] | 41 | |
Javi Merino | 6846155 | 2014-04-08 11:40:09 +0100 | [diff] [blame] | 42 | # This would better be done with a context manager (i.e. |
| 43 | # http://stackoverflow.com/a/13197763/970766) |
| 44 | try: |
| 45 | with open(os.devnull) as devnull: |
| 46 | out = check_output(["trace-cmd", "report"], stderr=devnull) |
| 47 | |
| 48 | finally: |
| 49 | os.chdir(previous_path) |
| 50 | |
Javi Merino | 5bd3d44 | 2014-04-08 12:55:13 +0100 | [diff] [blame] | 51 | with open(os.path.join(self.basepath, "trace.txt"), "w") as fout: |
| 52 | fout.write(out) |
Javi Merino | c08ca68 | 2014-03-31 17:29:27 +0100 | [diff] [blame] | 53 | |
Javi Merino | c2ec568 | 2014-04-01 15:16:06 +0100 | [diff] [blame] | 54 | def parse_into_csv(self): |
Javi Merino | 5bd3d44 | 2014-04-08 12:55:13 +0100 | [diff] [blame] | 55 | """Create a csv representation of the thermal data and store |
| 56 | it in self.data_csv""" |
Javi Merino | c08ca68 | 2014-03-31 17:29:27 +0100 | [diff] [blame] | 57 | pat_timestamp = re.compile(r"([0-9]+\.[0-9]+):") |
Javi Merino | 0e83b61 | 2014-06-05 11:45:23 +0100 | [diff] [blame] | 58 | pat_data = re.compile(r"[A-Za-z0-9_]+=([^ ]+)") |
| 59 | pat_header = re.compile(r"([A-Za-z0-9_]+)=[^ ]+") |
Javi Merino | c08ca68 | 2014-03-31 17:29:27 +0100 | [diff] [blame] | 60 | header = "" |
| 61 | |
Javi Merino | 6846155 | 2014-04-08 11:40:09 +0100 | [diff] [blame] | 62 | with open(os.path.join(self.basepath, "trace.txt")) as fin: |
Javi Merino | 952815a | 2014-03-31 18:08:32 +0100 | [diff] [blame] | 63 | for line in fin: |
Javi Merino | c2ec568 | 2014-04-01 15:16:06 +0100 | [diff] [blame] | 64 | if not re.search(self.unique_word, line): |
Javi Merino | 952815a | 2014-03-31 18:08:32 +0100 | [diff] [blame] | 65 | continue |
| 66 | |
| 67 | line = line[:-1] |
| 68 | |
Javi Merino | 5bd3d44 | 2014-04-08 12:55:13 +0100 | [diff] [blame] | 69 | timestamp_match = re.search(pat_timestamp, line) |
| 70 | timestamp = timestamp_match.group(1) |
Javi Merino | 952815a | 2014-03-31 18:08:32 +0100 | [diff] [blame] | 71 | |
Javi Merino | c2ec568 | 2014-04-01 15:16:06 +0100 | [diff] [blame] | 72 | data_start_idx = re.search(r"[A-Za-z0-9_]+=", line).start() |
| 73 | data_str = line[data_start_idx:] |
Javi Merino | 952815a | 2014-03-31 18:08:32 +0100 | [diff] [blame] | 74 | |
| 75 | if not header: |
Javi Merino | 0af4721 | 2014-04-02 16:23:23 +0100 | [diff] [blame] | 76 | header = re.sub(pat_header, r"\1", data_str) |
| 77 | header = re.sub(r" ", r",", header) |
Javi Merino | 952815a | 2014-03-31 18:08:32 +0100 | [diff] [blame] | 78 | header = "time," + header + "\n" |
| 79 | self.data_csv = header |
| 80 | |
Javi Merino | 0af4721 | 2014-04-02 16:23:23 +0100 | [diff] [blame] | 81 | parsed_data = re.sub(pat_data, r"\1", data_str) |
| 82 | parsed_data = re.sub(r" ", r",", parsed_data) |
Javi Merino | 952815a | 2014-03-31 18:08:32 +0100 | [diff] [blame] | 83 | |
| 84 | parsed_data = timestamp + "," + parsed_data + "\n" |
| 85 | self.data_csv += parsed_data |
| 86 | |
Javi Merino | f78ea5b | 2014-03-31 17:51:38 +0100 | [diff] [blame] | 87 | def get_data_frame(self): |
| 88 | """Return a pandas data frame for the run""" |
Javi Merino | 92f1a6d | 2014-04-10 16:30:36 +0100 | [diff] [blame] | 89 | if self.data_frame is None: |
Javi Merino | f78ea5b | 2014-03-31 17:51:38 +0100 | [diff] [blame] | 90 | return self.data_frame |
| 91 | |
Javi Merino | 952815a | 2014-03-31 18:08:32 +0100 | [diff] [blame] | 92 | if not self.data_csv: |
Javi Merino | c2ec568 | 2014-04-01 15:16:06 +0100 | [diff] [blame] | 93 | self.parse_into_csv() |
Javi Merino | f78ea5b | 2014-03-31 17:51:38 +0100 | [diff] [blame] | 94 | |
Javi Merino | f0f51ff | 2014-04-10 12:34:53 +0100 | [diff] [blame] | 95 | if self.data_csv is "": |
| 96 | return pd.DataFrame() |
| 97 | |
| 98 | unordered_df = pd.read_csv(StringIO(self.data_csv)) |
| 99 | self.data_frame = unordered_df.set_index("time") |
Javi Merino | 04f2749 | 2014-04-02 09:59:23 +0100 | [diff] [blame] | 100 | |
Javi Merino | f78ea5b | 2014-03-31 17:51:38 +0100 | [diff] [blame] | 101 | return self.data_frame |
Javi Merino | df8316a | 2014-03-31 18:39:42 +0100 | [diff] [blame] | 102 | |
Javi Merino | fb2e8fd | 2014-04-08 12:27:38 +0100 | [diff] [blame] | 103 | def set_plot_size(width, height): |
| 104 | """Set the plot size. |
| 105 | |
| 106 | This has to be called before calls to .plot() |
| 107 | """ |
| 108 | if height is None: |
| 109 | if width is None: |
| 110 | height = 6 |
| 111 | width = 10 |
| 112 | else: |
| 113 | height = width / GOLDEN_RATIO |
| 114 | else: |
| 115 | if width is None: |
| 116 | width = height * GOLDEN_RATIO |
| 117 | |
| 118 | plt.figure(figsize=(width, height)) |
| 119 | |
Javi Merino | 05983ef | 2014-04-08 12:54:20 +0100 | [diff] [blame] | 120 | def default_plot_settings(title=""): |
| 121 | """Set xlabel and title of the plot |
| 122 | |
| 123 | This has to be called after calls to .plot() |
| 124 | """ |
| 125 | |
| 126 | plt.xlabel("Time") |
| 127 | if title: |
| 128 | plt.title(title) |
| 129 | |
Javi Merino | 7a7cd70 | 2014-04-14 15:41:15 +0100 | [diff] [blame] | 130 | def normalize_title(title, opt_title): |
| 131 | """ |
| 132 | Return a string with that contains the title and opt_title if it's not the empty string |
| 133 | |
| 134 | See test_normalize_title() for usage |
| 135 | """ |
| 136 | if opt_title is not "": |
| 137 | title = opt_title + " - " + title |
| 138 | |
| 139 | return title |
| 140 | |
Javi Merino | 0e83b61 | 2014-06-05 11:45:23 +0100 | [diff] [blame] | 141 | class Thermal(BaseThermal): |
| 142 | """Process the thermal framework data in a ftrace dump""" |
| 143 | def __init__(self, path=None): |
| 144 | super(Thermal, self).__init__( |
| 145 | basepath=path, |
| 146 | unique_word="thermal_zone=", |
| 147 | ) |
| 148 | |
Javi Merino | c68737a | 2014-06-10 15:21:59 +0100 | [diff] [blame^] | 149 | def plot_temperature(self, title="", width=None, height=None): |
| 150 | """Plot the temperature""" |
| 151 | dfr = self.get_data_frame() |
| 152 | title = normalize_title("Temperature", title) |
| 153 | |
| 154 | set_plot_size(width, height) |
| 155 | |
| 156 | (dfr["temp"] / 1000).plot() |
| 157 | |
| 158 | default_plot_settings(title=title) |
| 159 | plt.legend() |
| 160 | |
| 161 | |
Javi Merino | 1e69e2c | 2014-06-04 18:25:09 +0100 | [diff] [blame] | 162 | class ThermalGovernor(BaseThermal): |
Javi Merino | 5bd3d44 | 2014-04-08 12:55:13 +0100 | [diff] [blame] | 163 | """Process the power allocator data in a ftrace dump""" |
Javi Merino | 6846155 | 2014-04-08 11:40:09 +0100 | [diff] [blame] | 164 | def __init__(self, path=None): |
Javi Merino | 1e69e2c | 2014-06-04 18:25:09 +0100 | [diff] [blame] | 165 | super(ThermalGovernor, self).__init__( |
Javi Merino | 6846155 | 2014-04-08 11:40:09 +0100 | [diff] [blame] | 166 | basepath=path, |
| 167 | unique_word="Ptot_out", |
Javi Merino | c2ec568 | 2014-04-01 15:16:06 +0100 | [diff] [blame] | 168 | ) |
| 169 | |
| 170 | def write_thermal_csv(self): |
| 171 | """Write the csv info in thermal.csv""" |
| 172 | if not self.data_csv: |
| 173 | self.parse_into_csv() |
| 174 | |
| 175 | with open("thermal.csv", "w") as fout: |
| 176 | fout.write(self.data_csv) |
| 177 | |
Javi Merino | a3553e9 | 2014-04-08 15:57:08 +0100 | [diff] [blame] | 178 | def plot_temperature(self, title="", width=None, height=None): |
Javi Merino | df8316a | 2014-03-31 18:39:42 +0100 | [diff] [blame] | 179 | """Plot the temperature""" |
Javi Merino | 5bd3d44 | 2014-04-08 12:55:13 +0100 | [diff] [blame] | 180 | dfr = self.get_data_frame() |
Javi Merino | 9e18609 | 2014-04-08 15:41:41 +0100 | [diff] [blame] | 181 | control_temp_series = (dfr["currT"] + dfr["deltaT"]) / 1000 |
Javi Merino | 7a7cd70 | 2014-04-14 15:41:15 +0100 | [diff] [blame] | 182 | title = normalize_title("Temperature", title) |
Javi Merino | 9e18609 | 2014-04-08 15:41:41 +0100 | [diff] [blame] | 183 | |
| 184 | set_plot_size(width, height) |
| 185 | |
Javi Merino | 5bd3d44 | 2014-04-08 12:55:13 +0100 | [diff] [blame] | 186 | (dfr["currT"] / 1000).plot() |
Javi Merino | 9e18609 | 2014-04-08 15:41:41 +0100 | [diff] [blame] | 187 | control_temp_series.plot(color="y", linestyle="--", |
| 188 | label="control temperature") |
| 189 | |
Javi Merino | a3553e9 | 2014-04-08 15:57:08 +0100 | [diff] [blame] | 190 | default_plot_settings(title=title) |
Javi Merino | 9e18609 | 2014-04-08 15:41:41 +0100 | [diff] [blame] | 191 | plt.legend() |
Javi Merino | 749b26a | 2014-03-31 19:17:30 +0100 | [diff] [blame] | 192 | |
Javi Merino | f1dcb2d | 2014-04-02 16:52:11 +0100 | [diff] [blame] | 193 | def plot_multivalue(self, values, title, width, height): |
| 194 | """Plot multiple values of the DataFrame |
| 195 | |
| 196 | values is an array with the keys of the DataFrame to plot |
| 197 | """ |
Javi Merino | fb2e8fd | 2014-04-08 12:27:38 +0100 | [diff] [blame] | 198 | set_plot_size(width, height) |
Javi Merino | 5bd3d44 | 2014-04-08 12:55:13 +0100 | [diff] [blame] | 199 | dfr = self.get_data_frame() |
| 200 | dfr[values].plot() |
Javi Merino | 05983ef | 2014-04-08 12:54:20 +0100 | [diff] [blame] | 201 | default_plot_settings(title=title) |
Javi Merino | f1dcb2d | 2014-04-02 16:52:11 +0100 | [diff] [blame] | 202 | |
Javi Merino | c00feff | 2014-04-14 15:41:51 +0100 | [diff] [blame] | 203 | def plot_input_power(self, title="", width=None, height=None): |
Javi Merino | f1dcb2d | 2014-04-02 16:52:11 +0100 | [diff] [blame] | 204 | """Plot input power""" |
Javi Merino | e0ddf0d | 2014-05-07 18:40:12 +0100 | [diff] [blame] | 205 | dfr = self.get_data_frame() |
| 206 | in_cols = [s for s in dfr.columns |
| 207 | if re.match("P.*_in", s) and s != "Ptot_in"] |
| 208 | |
Javi Merino | c00feff | 2014-04-14 15:41:51 +0100 | [diff] [blame] | 209 | title = normalize_title("Input Power", title) |
Javi Merino | e0ddf0d | 2014-05-07 18:40:12 +0100 | [diff] [blame] | 210 | self.plot_multivalue(in_cols, title, width, height) |
Javi Merino | 9c01077 | 2014-04-02 16:54:41 +0100 | [diff] [blame] | 211 | |
Javi Merino | c00feff | 2014-04-14 15:41:51 +0100 | [diff] [blame] | 212 | def plot_output_power(self, title="", width=None, height=None): |
Javi Merino | 9c01077 | 2014-04-02 16:54:41 +0100 | [diff] [blame] | 213 | """Plot output power""" |
Javi Merino | e0ddf0d | 2014-05-07 18:40:12 +0100 | [diff] [blame] | 214 | dfr = self.get_data_frame() |
| 215 | out_cols = [s for s in dfr.columns |
| 216 | if re.match("P.*_out", s) and s != "Ptot_out"] |
| 217 | |
Javi Merino | c00feff | 2014-04-14 15:41:51 +0100 | [diff] [blame] | 218 | title = normalize_title("Output Power", title) |
Javi Merino | e0ddf0d | 2014-05-07 18:40:12 +0100 | [diff] [blame] | 219 | self.plot_multivalue(out_cols, |
Javi Merino | c00feff | 2014-04-14 15:41:51 +0100 | [diff] [blame] | 220 | title, width, height) |
Javi Merino | cd4a827 | 2014-04-14 15:50:01 +0100 | [diff] [blame] | 221 | |
Javi Merino | 9fc5485 | 2014-05-07 19:06:53 +0100 | [diff] [blame] | 222 | def plot_inout_power(self, title="", width=None, height=None): |
| 223 | """Make multiple plots showing input and output power for each actor""" |
| 224 | dfr = self.get_data_frame() |
| 225 | |
| 226 | actors = [] |
| 227 | for col in dfr.columns: |
| 228 | match = re.match("P(.*)_in", col) |
| 229 | if match and col != "Ptot_in": |
| 230 | actors.append(match.group(1)) |
| 231 | |
| 232 | for actor in actors: |
| 233 | cols = ["P" + actor + "_in", "P" + actor + "_out"] |
| 234 | this_title = normalize_title(actor, title) |
| 235 | dfr[cols].plot(title=this_title) |
| 236 | |
Javi Merino | cd4a827 | 2014-04-14 15:50:01 +0100 | [diff] [blame] | 237 | def summary_plots(self, **kwords): |
| 238 | self.plot_temperature(**kwords) |
| 239 | self.plot_input_power(**kwords) |
| 240 | self.plot_output_power(**kwords) |